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Role of apolipoprotein C2 in acute myeloid leukemia: clinical, functional and mechanistic study

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Role of apolipoprotein C2 in acute myeloid leukemia: clinical, functional and mechanistic study

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Role of Apolipoprotein C2 in Acute Myeloid Leukemia:
Clinical, Functional and Mechanistic Study

by
Tian Zhang

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(Medical Biology)
August 2020
Copyright 2020 Tian Zhang
ii

Dedication to my dearest ma-ma and ba-ba who raised me with
tremendous love and patience.
iii
Acknowledgements
It is a humbling experience to acknowledge those people who have helped along the journey of
my PhD. I am indebted to so many people for their encouragement and support.
First and foremost, I am very grateful to my advisor, Dr. Alachkar for her wonderful guidance,
persistent encouragement and tremendous support during my graduate study at USC. She is
such a smart and great PI I have ever met. Without her, I cannot really achieve this far and make
those accomplishments for my research. I also very appreciate the moments when I was tired as
a new mom, she always encouraged me and was open to share her valued experience as a mom.
I would also like to give my sincere appreciation to Dr. Enrique Cadenas and Dr. Keigo Machida
for their support and for serving on my committee over the past 3 years. Their insightful
suggestions, research perspectives, and knowledge assisted me to improve my project a lot.
I would like to use this opportunity to express my special thanks to my best lab members-- Pooja,
Sharon, John and Lucas. Thank you all for being there with me and making my days in lab happy
and easy. Also thank you all for your tremendous help on my research. Pooja, I appreciate your
expertise on mice work which saved me a lot of time and efforts to complete in vivo experiment.
I will always remember the days nights we spent together to complete the experiments and trouble
shoot a lot of difficulties. Sharon, I thank you for being the one who always support me and
understand me. You helped me with your expertise on statistical analysis which determined the
important direction for my research. Lucas, your positive attitudes always inspire me. And John I
iv
greatly appreciate your help and support. I also want to thank Lyn Jiawen Yang, who put a lot of
efforts to my project during her master period.
I also want to express my appreciation to Dr. Ite the director of PIBBS office for the chances,
encouragements, guidance given by her.
I want to thank my parents, my grandparents, my uncles and aunts for their unconditional love
and endless support making me stronger and stronger along the way.
Especially, I would like to thank my friend Moore (Mengmei) Zheng for helping me watch over my
baby in the past few weeks and in this COVID-19 special time. This saved me a lot of time and
energy so that I can focus on my dissertation working. My dissertation cannot be completed
without you.
Last but not the least, I want to thank my little daughter, you are my little angel and the inspiration
of my life. It’s not easy doing PhD while taking care of a baby, but your smiles and your laughter
are the best remedy for me. Also tremendous thanks to my husband who has been there with me
and experienced all the ups and downs with me through my PhD. I appreciate the time when we
shared happiness as well as hardships.
Overall, I want to thank all people who made my study possible. Without your continuous
involvement as well as your enthusiasm, generosity and kindness, my Ph.D journey would not
have been possible.
v
Table of Contents
Acknowledgements .......................................................................................................... iii
List of Tables .................................................................................................................. viii
List of Figures .................................................................................................................. ix
Abstract ........................................................................................................................... xi
Chapter 1 Introduction ................................................................................................. 1
1.1 Acute Myeloid Leukemia (AML) ......................................................................... 1
1.1.1 Definition, incidence, etiology, and classification ...................................................... 1
1.1.2 Clinical features and diagnosis ................................................................................. 8
1.1.3 Cytogenetic and molecular aberrations .................................................................. 10
1.2 Apolipoproteins C2 (APOC2) ........................................................................... 23
1.2.1 Overview of TG-rich lipoprotein metabolism ........................................................... 23
1.2.2 APOC2 .................................................................................................................... 25
1.2.3 Transcriptional control of APOC2 gene .................................................................. 27
1.2.4 APOC2 deregulation in disease .............................................................................. 27
1.3 CD36 ................................................................................................................ 29
1.3.1 CD36 expression and function ................................................................................ 29
1.3.2 CD36 roles in multiple cancers ............................................................................... 31
Chapter 2 The Clinical Characterization of APOC2 in AML ...................................... 33
2.1 Introduction ...................................................................................................... 33
2.2 Experimental procedure ................................................................................... 35
2.2.1 Study approval ........................................................................................................ 35
2.2.2 Patient datasets ...................................................................................................... 35
2.2.3 Patient samples ...................................................................................................... 35
2.2.4 Statistical analysis ................................................................................................... 36
2.3 Results ............................................................................................................. 37
2.3.1 APOC2 is upregulated in AML ................................................................................ 37
2.3.2 The subtypes of APOC2-upregulated AML ............................................................ 39
2.3.3 The clinical characteristics ...................................................................................... 41
2.3.4 APOC2 is associated with poor clinical outcomes .................................................. 43
2.3.5 APOC2 overexpression is associated with MLL rearrangements ........................... 45
2.3.6 APOC2 upregulation is associated with FLT3 mutations ........................................ 48
vi
2.3.7 APOC2 upregulation has significant association with t(15;17) translocation mutation
49
2.4 Discussion ....................................................................................................... 50
Chapter 3 The functional characterization of APOC2 in AML ................................... 52
3.1 Introduction ...................................................................................................... 52
3.2 Experimental procedure ................................................................................... 53
3.2.1 Study approval ........................................................................................................ 53
3.2.2 AML murine xenograft models ................................................................................ 53
3.2.3 Cell culture and transfection ................................................................................... 53
3.2.4 Plasmid constructs .................................................................................................. 54
3.2.5 Cell viability and colony-forming cell assays ........................................................... 55
3.2.6 Immunoblot analysis ............................................................................................... 55
3.2.7 RNA extraction, cDNA synthesis, and real-time PCR analysis ............................... 56
3.2.8 Lentiviral production ................................................................................................ 57
3.2.9 Flow cytometry ........................................................................................................ 57
3.2.10 Apoptosis assay .................................................................................................. 58
3.2.11 Statistical analysis ............................................................................................... 58
3.3 Results ............................................................................................................. 60
3.3.1 APOC2 ectopic expression promotes leukemia growth in AML cell lines ............... 60
3.3.2 APOC2 ectopic expression promotes leukemia growth in primary AML patient
samples .............................................................................................................................. 62
3.3.3 APOC2 knockdown inhibits leukemia cells progression in AML cells ..................... 64
3.3.4 APOC2 knockdown decrease the viability of AML primary blasts .......................... 68
3.3.5 APOC2 knockdown induces apoptotic cell death ................................................... 70
3.3.6 Conditional knockdown of APOC2 and CD36 decrease leukemia burden in murine
leukemia models ................................................................................................................. 72
3.4 Discussion ....................................................................................................... 79
Chapter 4 Mechanistic studies involving APOC2 upregulation in AML ..................... 80
4.1 Introduction ...................................................................................................... 80
4.2 Experimental procedures ................................................................................. 83
4.2.1 Study approval ........................................................................................................ 83
4.2.2 Patient datasets ...................................................................................................... 83
4.2.3 AML murine xenograft models ................................................................................ 83
4.2.4 Cell culture and transfection ................................................................................... 84
4.2.5 Plasmid constructs .................................................................................................. 84
4.2.6 Cell viability ............................................................................................................. 85
4.2.7 Immunoblot analysis ............................................................................................... 85
vii
4.2.8 Immunoprecipitation ................................................................................................ 86
4.2.9 Lentiviral production ................................................................................................ 87
4.2.10 Flow cytometry .................................................................................................... 87
4.2.11 Seahorse and cellular metabolic analysis ........................................................... 88
4.2.12 APOC2 Methylation Patient Data Analysis ......................................................... 88
4.2.13 APOC2 Methylation PCR Analysis ..................................................................... 89
4.2.14 Statistical analysis ............................................................................................... 89
4.3 Results ............................................................................................................. 91
4.3.1 APOC2 is hypomethylated in AML .......................................................................... 91
4.3.2 APOC2 is epigenetically regulated by MLL-rearrangement .................................... 95
4.3.3 APOC2 is hypomethylated in MLL-rearranged AML cells ...................................... 97
4.3.4 APOC2 colocalizes with CD36 ................................................................................ 99
4.3.5 APOC2 was co-immunoprecipitated with CD36 ................................................... 101
4.3.6 CD36 knockdown impedes the proliferation of leukemia cells .............................. 102
4.3.7 APOC2 functionally cooperates with CD36 to promote leukemia growth ............. 103
4.3.8 Both APOC2 and CD36 are necessary for pro-leukemic effects in AML cells. ..... 107
4.3.9 Targeting CD36 function by (sulfo-N-succinimidyl oleate) SSO ........................... 109
4.3.10 Targeting CD36 function by CD36 antibody inhibits the progression of AML cells
112
4.3.11 Targeting CD36 by CD36 antibody induces apoptosis and abrogates APOC2 pro-
leukemic effects ................................................................................................................ 114
4.3.12 APOC2 triggers downstream ERK signaling of CD36 ...................................... 117
4.3.13 CD36 depletion causes decreased level of p-ERK ........................................... 119
4.3.14 Simultaneous expression of APOC2 and CD36 triggers greater increase of ERK
phosphorylation and activation of LYN ............................................................................. 121
4.3.15 Depletion of APOC2 or CD36 abolished activation of ERK induced by OE CD36
or OE APOC2 ................................................................................................................... 123
4.3.16 APOC2 and CD36 overexpression affect the bioenergetic profile of AML cells 125
4.3.17 Conditional knockdown of APOC2 and CD36 decrease leukemia burden in
murine leukemia models ................................................................................................... 129
4.3.18 Anti-CD36 antibody treatment reduces leukemia progression and increases
overall survival of AML murine model. .............................................................................. 135
References ................................................................................................................... 141
viii
List of Tables
Table 1.1 The risk factors of AML etiology ............................................................................ 3
Table 1.2 French-American-British classification system of AML .......................................... 5
Table 1.3 WHO classification system .................................................................................... 6
Table 1.4 Surface and cytoplasmic markers for AML diagnosis by flow cytometry ............... 8
Table 2.1 clinical characteristics .......................................................................................... 42
Table 2.2 Multivariate survival analysis ............................................................................... 44
Table 2.3 Mutation characteristics ....................................................................................... 47
Table 3.1 Patient information ............................................................................................... 62
Table 4.1 APOC2 methylation CpG island in AML vs Normal ............................................. 92

ix
List of Figures
Figure 1.1 Chromosomal translocation mutations and their percentages in AML. ............. 11
Figure 1.2 Molecular mutation categories .......................................................................... 14
Figure 1.3 Somatic alterations frequency and interrelationships among various mutations.
.................................................................................................................................... 15
Figure 1.4 Lipid metabolism circuit ..................................................................................... 24
Figure 1.5 The structure of apoc2 ...................................................................................... 25
Figure 1.6 APOC2 involved functional complex ................................................................. 26
Figure 1.7 CD36 structure .................................................................................................. 29
Figure 2.1 APOC2 is upregulated in AML .......................................................................... 38
Figure 2.2 The subtypes of APOC2-upregulated AML ....................................................... 40
Figure 2.3 APOC2- associated clinical outcomes .............................................................. 43
Figure 2.4 APOC2 expression is enhanced in MLL-rearranged AML ................................ 46
Figure 2.5 APOC2 is upregulated in FLT3-mutated AML ................................................... 48
Figure 2.6 APOC2 upregulation is associated with t(15;17) translocation mutation. .......... 49
Figure 3.1 APOC2 overexpression promotes AML cell lines growth .................................. 61
Figure 3.2 APOC2 overepxression promotes AML patient samples growth ...................... 63
Figure 3.3 Transient knockdown of APOC2 inhibits proliferation of AML cell lines. ........... 65
Figure 3.4 Tetracycline-incucible knockdown of APOC2 inhibits cell growth. .................... 67
Figure 3.5 APOC2 knockdown inhibits cell growth in primary patient samples. ................. 69
Figure 3.6 APOC2 knockdown induces apoptosis. ............................................................ 71
Figure 3.7 Knockdown APOC2 mice showed less leukemia burden. ................................. 73
Figure 3.8 Knockdown APOC2 mice group showed less engraftment in peripheral blood. 76
Figure 3.9 Knockdown APOC2 effects on NSG mice. ........................................................ 78
Figure 4.1 APOC2 is hypomethylated in AML leukemia stem cells. ................................... 94
Figure 4.2 APOC2 is epigenetically regulated by MLL-rearrangement .............................. 96
x
Figure 4.3 APOC2 is hypomethylated in MLL-rearranged AML cells. ................................ 98
Figure 4.4 APOC2 colocalizes with CD36. ....................................................................... 100
Figure 4.5 APOC2 was co-immunoprecipitated with CD36. ............................................. 101
Figure 4.6 CD36 knockdown impedes the proliferation of AML cell lines. ........................ 102
Figure 4.7 APOC2 functionally cooperates with CD36 to promote cell growth. ............... 104
Figure 4.8 CD36 expression in LSC and its association with clinical outcomes. .............. 106
Figure 4.9 Both APOC2 and CD36 are necessary for AML growth. ................................. 108
Figure 4.10 Effects of targeting CD36 by SSO. ................................................................ 110
Figure 4.11 Effect of targeting CD36 by CD36 blocking antibody. ................................... 113
Figure 4.12 Targeting CD36 by antibody indduces apoptosis. ......................................... 115
Figure 4.13 The level changes of CD36 downstream target ERK. ................................... 118
Figure 4.14 Depletion of CD36 decreased the level of p-ERK. ........................................ 120
Figure 4.15 Simultaneous expression of APOC2 and CD36 causes greater increase in p-
ERK and activates LYN. ........................................................................................... 122
Figure 4.16 Depletion of APOC2 or CD36 abolished activation of ERK induced by OE
CD36 or OE APOC2. ................................................................................................ 124
Figure 4.17 APOC2 and CD36 overexpression affect the bioenergetic profile of AML cells
.................................................................................................................................. 126
Figure 4.18 Conditional knockdown of APOC2 and CD36 decrease leukemia burden .... 130
Figure 4.19 Other effects of APOC2 or CD36 knockdown in NSG mice. ......................... 134
Figure 4.20 Anti-CD36 antibody effects on NSG leukemia models. ................................. 136
Figure 4.21 Anti-CD36 antibody delays the prograssion of leukemia in mice model. ...... 138
xi
Abstract
Acute Myeloid Leukemia (AML) is a devastating hematologic malignancy that affects the
hematopoietic stem cells. The 5-year overall survival (OS) of patients with AML is less than 30%,
highlighting the urgent need to identify new therapeutic targets. We analyzed gene expression
datasets for genes that are differentially overexpressed in AML cells compared with healthy
hematopoietic cells. We found that APOC2 was consistently upregulated in AML across different
datasets. Apolipoprotein C2 (APOC2), is a small secreted apolipoprotein, and a member of the
apoCs that constitutes chylomicrons, very-low-density lipoproteins, and high-density lipoproteins.
APOC2 activates lipoprotein lipase and contributes to lipid metabolism. Thus, the need to find
new therapeutic targets is high. Here, we discovered that apolipoprotein C2 (APOC2) is
upregulated in AML, particularly in patients with mixed-lineage leukemia (MLL) rearrangements.
High APOC2 mRNA levels are associated with shorter OS (HR: 2.71; 95%CI: 1.12–6.57; p=0.027).
Here, we characterize the functional and mechanistic role of APOC2 in AML to establish the
rationale for this gene as a viable therapeutic target.
Lentiviral transduction gain and loss of function approaches in AML cell lines (THP-1, MOLM-13
and U937) demonstrated that overexpressed (OE) APOC2 promotes leukemia growth (17-50%,
p<0.01). While, the knockdown (KD) of APOC2 (shAPOC2) induces apoptotic cell death (35-50%,
p<0.05) compared with control (shCtrl) cells. Similar results were observed in patient blasts.
xii
We further identified the fatty acid translocase (FAT)/ CD36 as a potential partner acting with
APOC2 to promote leukemia growth. Confocal imaging showed co-localization of APOC2 and
CD36 on 293T cell membrane. In THP-1 and MOLM-13 cells, the KD of CD36 significantly
decreased cell viability (37-41%, p<0.02). While the OE of CD36 induced proliferation by 30-47%
(p<0.01). The combined expression of APOC2 and CD36 further enhanced proliferation
compared with the overexpression of either gene alone in both CD34+ cells and AML cell lines
(17-19%, p<0.05). Conditional KD of APOC2 or CD36 also decreased leukemia burden in murine
AML models. NOD-scid/Il2rg-/- mice (NSG) were engrafted with HL60 or MOLM-13 cells
expressing teton-inducible shRNAs. APOC2 or CD36 KD decreased leukemia engraftment in
peripheral blood, bone marrow (BM) and spleens measured by huCD45 staining and flow
cytometry.
Targeting the fatty acid translocation function of CD36 by an inhibitor (SSO: 50 or 100uM) or
blocking CD36 with a monoclonal antibody (CD36 mAb) induced apoptosis by 20-40% in THP-1
and MOLM-13 cells (p<0.05). CD36 mAb also abrogated APOC2-induced proliferation in AML
cells. In addition, CD36 mAb treatment reduced leukemia burden and prolonged OS of MOLM-13
engrafted mice. Mechanistically, western blots of phospho-ERK and total-ERK proteins in various
AML cell lines, demonstrated that APOC2-CD36 activates ERK pathway. Metabolically, seahorse
analyses showed that shAPOC2 and shCD36 cells exhibit a quiescent metabolic phenotype
xiii
compared with shCtrl cells; while APOC2 or CD36 OE cells have a higher oxidative
phosphorylation and glycolysis rates compared with Ctrl cells (p<0.05).

Altogether, this study establishes APOC2-CD36 signal axis as novel therapeutic target in AML
that warrant further development into the clinic.
1

Chapter 1 Introduction
1.1 Acute Myeloid Leukemia (AML)
1.1.1 Definition, incidence, etiology, and classification
AML is an aggressive hematological malignancy that affects myeloid lineage. Immature myeloid
precursors develop into abnormally differentiated but rapidly proliferating blood cells to gradually
replace normal hematopoietic blasts in bone marrow, peripheral blood and infiltrate other parts of
the body such as lymph nodes, spleen, liver and central nervous system[1, 2]. According to
Cancer statistics 2020, it has been estimated that nearly 19,940 (11,090 males and 8850 females)
people in the United States will be diagnosed with AML in 2020. Among all types of leukemia,
AML accounts for highest percentage of estimated deaths (48.4%) [Cancer Statistics, 2020].
AML occurs in patients of all ages but is more common in older adults[3]. Curative therapies are
generally applicable to only small portion of patients who are young and fit, and with certain
favorable molecular and cytogenetic prognostic factors. Older patients, however, exhibit poor
prognosis and worse clinical outcome[4]. Between 2013 and 2017, the age-adjusted rate of new
cases of AML was 4.3 per 100,000 men and women per year and the death rate was 2.8 per
100,000 men and women per year in United States. The 5-year overall survival rate of all patients
with AML is only 28.7%[5]. Even with current treatment, induction of intensive chemotherapy,
consolidation and allogeneic hematopoietic stem cell transplantation (alloHSCT), only 35–40%
2
among younger patients and 5–15% among older patients achieve 5 years survival, highlighting
the urgent need for new therapeutic targets[6].
The etiology of AML is still under investigation. Even though certain risk factors have been
reported to be associated with the development of AML, the etiology attributing AML to particular
risk factors only explains small portion of AML cases. The risk factors are divided into four different
categories as genetic disorders, physical and chemical exposures, radiation exposure, and
chemotherapy. More details are shown in table 1.1.

3
Table 1.1 The risk factors of AML etiology
Genetic disorders Down syndrome
Klinefelter syndrome
Patau syndrome
Ataxia telangiectasia
Shwachman syndrome
Kostman syndrome
Neurofibromatosis
Fanconi anemia
Li-Fraumeni syndrome
Physical and chemical exposures Benzene
Drugs such as pipobroman
Pesticides
Cigarette smoking
Embalming fluids
Herbicides
Radiation exposure Nontherapeutic, therapeutic radiation
Chemotherapy Alkylating agents
Topoisomerase-II inhibitors
Anthracyclines
Taxanes

4
Historically, AML was first classified into eight different subtypes (M0 through M7) according to
the French-American-British classification system in 1976 based on the morphological and
cytochemical characteristics of leukemic cells (Table 1.2). With the improved understanding of
AML etiology and advances in AML diagnosis and management, World Health Organization
(WHO) established a new classification system to distinguish among different types of AML. The
classification includes six major categories: AML with recurrent genetic abnormalities; AML with
myelodysplasia-related features; therapy-related AML; AML not otherwise specified; myeloid
sarcoma; and myeloid proliferation related to Down syndrome (Table 1.3) [7].

5

Table 1.2 French-American-British classification system of AML

FAB subtype Name
M0 Undifferentiated acute myeloblastic leukemia
M1 Acute myeloblastic leukemia with minimal maturation
M2 Acute myeloblastic leukemia with maturation
M3 Acute promyelocytic leukemia
M4 Acute myelomonocytic leukemia
M4eos Acute myelomonocytic leukemia with eosinophilia
M5 Acute monocytic leukemia
M6 Acute erythroid leukemia
M7 Acute megakaryocytic leukemia
6

Table 1.3 WHO classification system
Types Genetic Abnormalities
AML with recurrent
genetic abnormalities
• AML with t(8;21)(q22;q22); RUNX1-RUNX1T1
• AML with inv(16)(p13.1q22) or
t(16;16)(p13.1;q22); CBFB-MYH11
• APL with PML-RARA (Acute promyelocytic
leukemia with promyelocytic leukemia–retinoic acid
receptor alpha)
• AML with t(9;11)(p21.3;q23.3); MLLT3-KMT2A
• AML with t(6;9)(p23;q34.1); DEK-NUP214
• AML with inv(3)(q21.3q26.2) or
t(3;3)(q21.3;q26.2); GATA2, MECOM
• AML (megakaryoblastic) with
t(1;22)(p13.3;q13.3); RBM15-MKL1
• Provisional entity: AML with BCR-ABL1
• AML with mutated NPM1
• AML with biallelic mutations of CEBPA
• Provisional entity: AML with mutated RUNX1
AML with myelodysplasia-
related changes

Therapy-related myeloid
neoplasms

AML, not otherwise
specified (NOS)
• AML with minimal differentiation
• AML without maturation
• AML with maturation
• Acute myelomonocytic leukemia
• Acute monoblastic/monocytic leukemia
• Pure erythroid leukemia
• Acute megakaryoblastic leukemia
• Acute basophilic leukemia
• Acute panmyelosis with myelofibrosis
7

Myeloid sarcoma
Myeloid proliferations
related to Down
syndrome:
• Transient abnormal myelopoiesis (TAM)
• Myeloid leukemia associated with Down syndrome

8
1.1.2 Clinical features and diagnosis
Because of abnormally accumulated myeloblasts in the bone marrow and peripheral blood, most
of the patients have anemia, neutropenia and peripheral blood leukocytosis (excessive abnormal
white blood cells), thus resulting in fatigue, weakness, repeated infections, weight loss, fever and
abnormal hemostasis at diagnosis[8]. Lymphadenopathy and hepatosplenomegaly may
happen[9].
According to WHO criteria, blood or marrow myoblast count of ≥20% is required for the diagnosis
of AML. But this criteria doesn’t apply to t(15;17), t(8;21), inv(16) or t(16;16) AML in which the
cytogenetic abnormality is favorable diagnostic and irrespective of blast percentage[7]. To
diagnose the presence of AML, peripheral blood smear or aspiration marrow smear is examined
under microscope after May-Grünwald-Giemsa or Wright-Giemsa staining: at least 200
leukocytes should be counted in blood smear sample; at least 500 nucleated cells should be
counted in marrow smear sample[6]. Additionally, flow cytometry detecting AML specific markers
is conventionally used to differentiate AML from other leukemia and specify the subtype [10, 11].
The surface and cytoplasmic markers are shown in table 1.4 for AML diagnosis by flow cytometry.
Table 1.4 Surface and cytoplasmic markers for AML diagnosis by flow cytometry
Expression of cell-surface and
cytoplasmic markers of AML
Precursors† CD34, CD117, CD33, CD13, HLA-DR
Granulocytic markers‡ CD65, cytoplasmic MPO
Monocytic markers§ CD14, CD36, CD64
Megakaryocytic markers|| CD41 (glycoprotein IIb/IIIa), CD61 (glycoprotein IIIa)
Erythroid markers CD235a (glycophorin A), CD36
Adapted from [10]
9
As more than 50% of adult AML cases are detected with chromosome abnormalities[12],
cytogenetics analysis is a required part of the diagnosis for further determination of the
appropriate treatment and characterization of the disease risk and outcome [13]. Samples from
marrow or blood are typically used for chromosomal abnormality tests via routine cytogenetics or
fluorescent in situ hybridization [10]. Genetic mutations test for screening NPM1, CEBPA, RUNX1,
FLT3, TP53, and ASXL1 should be also included in AML diagnosis. Mutations in NPM1, CEBPA,
RUNX1 can defines the disease categories; mutations in FLT3 can be prognostic and affected by
the tyrosine kinase inhibition treatment; mutations in TP53 and ASXL1 can be associated with
poor prognosis [10, 14, 15].

10
1.1.3 Cytogenetic and molecular aberrations
AML is a heterogeneous disease in which a variety of cytogenetic and molecular alterations have
been identified. Specific chromosomal abnormalities have been established as particularly strong
prognostic markers for survival. Different chromosomal translocations and large chromosome
gains and losses can be detected in ~50% to 60% of newly diagnosed AML patients [16]. Among
different chromosomal translocation mutations (Figure 1.1), t(15;17) translocation and MLL
rearrangements are two of the typical translocation mutations in AML.

11
Figure 1.1 Chromosomal translocation mutations and their percentages in AML.
Adapted from paper [17]

4
Acute Myeloid Leukemia
— Chromosomal abnormality signatures
Other translocations
t(9;22)
der(11q23)
inv(16)
t(15;17)
t(8;21)
Martens JH, et al. FEBSLetter, 2010
10%
10%
10%
5~10%
5~10%
50~60%
Normal
Karyotype
12
Acute promyelocytic leukemia (APL) is a type of AML accounting for 5-10% AML cases. It is
characterized by the presence of PML-RARα fusion gene which results from t(15;17)(q22;q21)
chromosomal translocation[18]. The gene for retinoic acid receptor alpha (RARα) fuses with
promyelocytic leukemia (PML), generating PML-RARα fusion products[19], which are responsible
for the pathogenesis of APL and sensitive to all-trans retinoic acid (ATRA) [20]. PML-RARα fusion
protein sets differentiation blockage at the promyelocytic stage through inactivation of genes
associated with cell differentiation and apoptosis[19]. It was reported that PML-RARα requires
DNA methyltransferase 3A (DNMT3A) mutations to act as an oncogenic transcription factor in
APL initiation. The DNA methyltransferase activity of DNMT3A was demonstrated to be
indispensable to the enhanced self-renewal of PML-RARα-transformed hematopoietic
progenitors [21]. Over the past decades, the treatment of APL has been improved by utilizing
ATRA and arsenic trioxide (ATO), which are known to target PML-RARα fusion protein[22]. Nearly
80% of APL patients carrying PML-RARα achieve long-term remission[20].
Another chromosomal translocation involving Mixed Lineage Leukemia (MLL) gene at
chromosome 11q23 is reported in 5-10% of adult AML patients[23]. As a result of chromosomal
translocation, over 70 protein partners are found to be fused with the N terminus of MLL[24]. Even
though the diversity of fusion partners complicates the functions of this mutation, the majority of
the fused proteins are mainly responsible for the pathogenesis of MLL-rearranged leukemia
including acute lymphoblastic leukemia (ALL) and AML [25]. Notably, overexpression of MLL-AF9
in human HSPCs resulted in a distinct DNA methylation signature which characterizes the MLL-
13
AF9 AML[26], suggesting a close correlation between MLL fusion protein and aberrant DNA
methylation in leukemic transformation. A recent study has also observed that the Hoxa promoters
were aberrantly hypomethylated in MLL-EEN leukemia mouse model, and MLL-EEN accounted
for the upregulated expression of Hoxa cluster genes [27]. Importantly, the CXXC domain retained
in the MLL fusion proteins can recognize non-methylated CpG dinucleotides at Hoxa9 locus and
protect it from DNA methylation and repressive histone 3 lysine 9 tri-methylation (H3K9me3) mark,
which subsequently triggers an aberrant induction of Hoxa9 [28] [29].
But with the development of next generation sequencing technology, emerging information of
recurrent AML gene mutations have been discovered. Certain cytogenetic and molecular genetic
mutations have been implicated in the pathogenesis of AML, resulting in abnormal proliferation
and differentiation of myeloid blasts [30]. Genes that were significantly mutated in AML were
categorized into several functional groups: signaling and kinase pathway, epigenetic modifier,
Nucleophosmin, transcription factors, tumor suppressors, spliceosome complex, and cohesin
complex (Figure 1.2). The overall frequency for common mutations is described in the figure 1.3
below.

14

Figure 1.2 Molecular mutation categories
Genetic mutations are generally categorized into eight different groups: signaling genes, tumor
suppressor genes, DNA methylation genes, chromotin modification genes, cohensin complex
genes, spliceosome complex genes, nucleophosmin, and myeloid transcription factor fusion. And
the representative genes for each category are shown here respectively.

5
Acute Myeloid Leukemia
— Molecular mutation signatures
TP53, WT1
DNMT3A, TET2, IDH1/2
MLL fusions
SRSF2, SF3B1, U2AF1
NPM1
CEBPA, RUNX1, GATA2
FLT3, RAS, KIT
Signaling
genes
Myeloid
transcription
factor fusion
Nucleophosmin
Spliceosome
-complex
genes
Cohesin-
complex
genes
Chromatin-
modification
genes
DNA-
methylation
genes
Tumor-
suppressor
genes
15

Figure shows the frequency of somatic mutations in the entire cohort and the interrelationships
among the various mutations, as represented visually with the use of a Circos plot. The length of
the arc corresponds to the frequency of mutations in the first gene, and the width of the ribbon
corresponds to the percentage of patients who also had a mutation in the second gene. Pairwise
co-occurrence of mutations is denoted only once, beginning with the first gene in the clockwise
direction. Adapted from [31].

Figure 1.3 Somatic alterations frequency and interrelationships among various mutations.
16

1.1.3.1 Signaling and kinase pathway mutations
FMS-like tyrosine kinase 3 (FLT3)
FLT3 is a receptor tyrosine kinase that regulates multiple cellular processes as cell proliferation,
differentiation and apoptosis. This membrane-bound receptor contains four parts:
immunoglobulin-like extracellular ligand-binding domain, a transmembrane domain, a
juxtamembrane dimerization domain and intracellular kinase domain which is very conserved and
always interrupted by a kinase insert. Once FLT3 binds to its ligand, it transforms from monomeric
and unphosphorylated form to dimerized and phosphorylated form to trigger a series of
downstream phosphorylation reactions including MAP kinase, STAT and AKT/PI3 kinase
signaling pathways [32].
FLT3 activation plays an important role in regulating normal hematopoiesis and cellular growth
[33], [34]. FLT3- internal tandem duplications (FLT3-ITD) and tyrosine kinase domain mutations
(FLT3-TKD) are two major mutations in FLT3 gene. The two types of FLT3 mutations are identified
in nearly one-third of patients with AML resulting in autophosphorylation, constitutive receptor
activation and ligand-independent proliferation [32]. Several studies have reported FLT3-ITD
mutations were associated with leukocytosis and normal cytogenetics. Patients with FLT3-ITD
mutations had a significantly higher relapse rate and worse overall survival [35], [36]. Besides,
FLT3-TKD mutations have been reported in 7-10 % of pediatric patients with AML but not been
shown to be associated with high relapse rate [37],[38].
17
FLT3-ITD mutation has been considered as a driver mutation in AML based on several lines of
preclinical and clinical evidence [39], [40], [41]. Therefore, a number of tyrosine kinase inhibitors
(TKIs) have been developed to target FLT3-initiated oncogenic signal pathways. Indeed, the
combination of FLT3 inhibitors with the use of alloHSCT significantly improved the clinical
outcomes over the past decade in AML patients with FLT3-ITD mutations [42]. The first generation
of FLT3 inhibitors are multitargeted TKIs (eg, lestaurtinib, sunitinib, sorafenib, and midostaurin).
But for the lack of selectively targeting FLT3, the first-generation inhibitors showed limited
antileukemic activity with increased toxicity [39]. Only the use of Midostaurin was well tolerated
and showed antileukemic activity to a certain extent in patients with relapsed/refractory FLT3-
mutated AML [43]. In 2017, the US Food and Drug Administration approved the use of Midostaurin
in combination with standard cytarabine and daunorubicin induction and cytarabine consolidation
therapy to treat adult patients with newly diagnosed FLT3-mutated AML based on the results on
the RATIFY clinical trial [44]. More efforts were put to develop the next-generation TKIs (eg,
gilteritinib, crenolanib, and quizartinib) for the lack of selectivity of multitargeted TKIs for FLT3-
ITD. The next-generation TKIs have higher specificity and efficiency than the first generation TKIs
[45]. Recently, it is encouraging to see that gliteritinib, a second generation FLT3 inhibitor, showed
consistent FLT3 inhibition and a favorable safety profile in patients with relapsed or refractory
AML, which got the approval of the first FLT3-targeting therapy as a monotherapy in this patient
population in the USA [46]. Although great improvement for FLT3-mutated treatment was
achieved by use of FLT3 inhibitors, the resistance to those inhibitors becomes another challenge.
18
RAS
RAS genes encodes a group of proteins which are the central of many signaling networks in many
tissue linages [47]. RAS genes are mutated in about 10–15% AML cases, and recurrent AML
mutations rely on Ras signaling for their leukemogenesis effects (PTPN11, NF1, KIT and FLT3-
ITD) [48]. Upon ligand binding to growth factor receptors, Ras guanine nucleotide exchange
factors are recruited to activate RAS proteins by exchange of guanosine diphosphate (GDP) for
guanosine triphosphate (GTP). RAS genes encode 4 different homologous proteins. They are H-
Ras, N-Ras, K-Ras4a and K-Ras4b [49]. In mouse models, some studies have reported that N-
Ras and K-Ras promote the leukemogenesis and maintain self-renewal of AML cells in vivo [50],
[51], [52], [53]. Moreover, aberrant activation of the mitogen-activated protein kinase (MAPK) and
phosphatidylinositol-3-kinase (PI3K) pathways downstream of RAS has been revealed to induce
malignant transformation of AML [47], [54]. Despite that RAS targeting drugs have been
undergoing development for several decade, very little progress have been made in targeting
RAS, and only recently some promising compounds are being clinical tested in solid cancer [55],
[56]. Therefore, targeting RAS in AML still have a long way to go.
KIT
KIT is a member of type III tyrosine kinase family and is a 145-KDa transmembrane glycoprotein.
Binding to KIT ligand, KIT activates downstream signaling pathways involved in cell proliferation,
differentiation and survival [57]. KIT mutations are likely to be identified only in AML with core-
19
binding factor (CBF) translocations and are associated with poor prognosis, although this hasn’t
been consistently observed [58].
1.1.3.2 Mutations in epigenetic modification
Post-translational modification of histones and DNA methylation are the two major mechanisms
of epigenetics modification. DNA methylation occurs ubiquitously and is observed to silence gene
expression. In cancer, aberrant methylation of tumor suppressor genes is associated with
tumorigenesis. Methyltransferases for adding methyl group to DNA and methylcytosine
dioxygenase for removal of methyl group from DNA are involved in epigenetics regulation
processes. Mutations in epigenetic regulators are found in more than 50% AML cases and DNA
methylation is frequently altered in AML.
DNA methyltransferase 3A (DNMT3A)
DNMT3A mutations are observed in nearly 20% of AML patients, and the R882 mutation is the
most frequent in AML patients with DNMT3A mutations [59]. It has been shown that R882
missense mutation prevents methyltransferase activity and DNA binding resulting in aberrant
HSC function like blocking differentiation and promoting self-renewal [60], [61]. It has also been
proposed that DNMT3A mutation arises in pre-leukemic HSCs first and then develops into AML
with secondary mutations like FLT3-ITD, NPM1 and IDH1 mutations [59], [62]. The mechanisms
that DNMT3A mutations drive AML still remain unclear. And the prognostic importance of
DNMT2A mutations still need to be further determined.
Ten-eleven translocation 2 (TET2)
20
TET2 is also frequently mutated in AML as well as other hematological malignancies including
chronic myelomonocytic leukemia, MDS/ myeloproliferative neoplasms, T or B-cell lymphoma [63],
[64], [65], [66]. The loss-of-function mutations of TET2 account for 17% of AML cases [67]. Similar
to DNMT3A, TET2 mutations confer pro-leukemic ability to HSC and triggers leukemia
progression after acquiring more genetic lesions [62].
Isocitrate dehydrogenase 1/2 (IDH1/IDH2)
IDH1/2 are metabolic enzymes in the Krebs cycle, catalyzing the oxidative decarboxylation of
isocitrate to a-ketoglutarate (a-KG). The very first mutation of IDH1 was found in AML samples in
2009. The overall prevalence of IDH1/2 mutations is 15% in AML patients [31]. Some studies
have directly and indirectly shown that TET2 and IDH share the same pathway to drive
leukemogenesis. Mutations in IDH1, IDH2 and TET2 appear to be mutually exclusive. And mutant
IDH enzymes catalyze a-KG to D-2-hydroxyglutarate (D-2-HG) to cause the inhibition of TET2
activity and promote leukemia development [68], [69]; [70].
1.1.3.3 Mutations in Nucleophosmin
NPM1
Along with FLT3 and DNMT3A, NPM1 is one of the most commonly mutated genes in AML,
accounting for 20-30% AML cases. NPM1 gene encodes the nuclear chaperone protein NPM,
which rapidly shuttles between the nucleus and cytoplasm, but mainly resides in nucleoli in
physiological condition [71]. It gets involved in a variety of cellular processes as the transport of
pre-ribosomal particles, ribosome biogenesis, maintenance of genomic stability, DNA replication
21
and cell cycle. Mutations in the NPM1 gene are always heterozygous, and appear mainly in exon
12, with a few exceptions reported in exon 11 and exon 9. Prognosis is much better for the AML
patients with NPM1 mutation but without FLT3-ITD mutation [72], [73]. However, prognosis is
poor for AML patients with NPM1 mutation as well as DNMT3A or FLT3-ITD mutations [74]. The
exact mechanisms driving leukemia are still ongoing bur haven’t yet elucidated.
1.1.3.4 Mutations in transcription factors and master regulators
Mutations in transcription factors and master regulators (RUNX1, CEBPA, GATA2) are found in
around 20-25% adult patients with AML. RUNX1 is an important transcription factor, that
contributes to HSC generation, HSC differentiation and homeostasis. RUNX1 mutations usually
contain various missense and frameshift mutations that disrupt the maintenance of HSC leading
to HSC exhaustion [75]. CEBPA is a critical hematopoietic transcription factor participating
lineage-specific myeloid differentiation. According to the WHO AML classification, only AML with
biallelic CEBPA mutations confirmed as a unique pathologic entity and are associated with
favorable prognosis [76]. GATA2 gene encodes a zin-finger transcription factor which is important
for myeloid hematopoiesis. The prevalence of mutated GATA2 is nearly 5% of all AML patients
[77]. To date, there is no targeted therapy against those transcription factors to treat AML patients.
1.1.3.5 RNA splicing factor mutations
RNA splicing factor mutations are identified in about 10% patients with AML, even though the
mutations also exist in MDS and myeloproliferative neoplasms. The mutations are associated with
old age, decreased survival, poor rates of response to standard treatment and less proliferative
22
disease. Those mutations promote malignancy through splicing genes of epigenetic regulation,
transcription and genome integrity incorrectly [78].

23
1.2 Apolipoproteins C2 (APOC2)
1.2.1 Overview of TG-rich lipoprotein metabolism
Triglycerides (TG) are the essential source of fatty acids for the energy production and storage of
human body. TG come from either dietary (exogenous) or hepatic (endogenous) sources
following lipolysis. Absorbed by intestine, primary TG are carried by TG-rich lipoproteins (TRL)
chylomicrons and delivered to peripheral tissues. Endogenously, TG synthesized by liver are
packaged into very low-density lipoproteins (VLDL) and transported to different tissues (Figure
1.4) [79].
Lipoprotein lipase (LPL) is a critical enzyme in TRL metabolism to hydrolyze plasma TG and
release free fatty acids for subsequent oxidation or storage [80]. In order to meet the consumption
rate of different tissues, LPL is tightly regulated by several positive and negative factors including
few apolipoproteins (APO) as APOC1, APOC2, APOC3, APOA5 and APOE [81], [82], [83] [84],
[85]. APOs usually function as lipid carriers for its transportation by forming lipoprotein complexes,
and act as ligands for cell membrane receptors [86], coactivators of enzymes, and binding
partners of LPL [87], [88]. In terms of LPL activity, both APOC1 and APOC3 have been reported
to inhibit LPL activity by competing with LPL for binding to lipid [89]. APOE also has been shown
to inhibit LPL-mediated lipolysis of TRL emulsions [90]. APOC2 and APOA5 are co-activators of
LPL activation.
24

Figure 1.4 Lipid metabolism circuit
TG are the essential source of fatty acids for the energy production and storage. In triglycerides
rich lipoprotein metabolism, APOC2 is required for the hydrolysis of triglycerides and release of
free fatty acids. TG generally come from either dietary (exogenous) or hepatic (endogenous)
sources following lipolysis. Dietary lipids are absorbed in the small intestine, TG and cholesterol
were packaged into chylomicron, which contains APOC2. Once in circulation, chylomicron is
hydrolyzed by lipoprotein lipase through binding to APOC2 and release free fatty acids.
chylomicron remnants are removed from circulation by the liver. For the endogenous pathway,
liver generates VLDL to plasma carrying TG. VLDL undergoes lipolysis by LPL binding to APOC2
and generates free fatty acids for peripheral tissues. Then VLDL is converted to LDL particles that
are taken up by the liver or peripheral tissues.

Liver
Intestine
9
APOC2
Chylomicron
T
T
T
C
C
Peripheral tissues
LPL
LPL
APOC2
Dietary fat
Free
fatty
acids
APOC2 involved lipid metabolism circuit
VLDL
LDL
Free
fatty
acids
Exogenous sources Endogenous sources
25
1.2.2 APOC2
APOC2 is a small secreted protein circulating in blood as components of chylomicrons, VLDL,
and high-density lipoproteins (HDL) (Figure 1.5). APOC2 is expressed mainly in the liver, and
then secreted into the plasma where it binds lipids and lipoprotein lipase. APOC2, as the obligate
co-activator of LPL, also participates in hydrolysis of triglycerides presented in chylomicrons,
VLDL, and HDL, thus facilitating energy delivery and storage(Figure 1.6) [79].

Figure 1.5 The structure of apoc2
APOC2 is a 10KD small protein which contains the domains binding to LPL and lipids.
26

8
Apolipoprotein C2 (APOC2)
APOC2
T
T
T
T
T
T
T
T
T
C
C
C
C
T
T
T
C
Triglyceride
Cholesterol
‣
It is component of chylomicron, VLDL, LDL and HDL.

‣
It’s the cofactor of lipoprotein lipase (LPL) to
hydrolyze triglycerides.

‣
APOC2 is a 9-KD secreted protein.

‣
It’s mainly expressed in liver and secreted in plasma.
LPL
Figure 1.6 APOC2 involved functional complex
APOC2 is a cofactor of LPL and a component of chylomicrons, VLDL, LDL and HDL.
27
1.2.3 Transcriptional control of APOC2 gene
The APOC2 protein is encoded by the APOC2 gene. The APOC2 gene clusters with other
apolipoprotein genes on chromosome 19 (q13.32), a known translocation hotspot in AML and a
gene-rich region that includes the AKT2, TGFB1, and MLL2 genes [91]. APOC2 is known to be
mainly expressed in the liver, but other tissues and organs (intestines, macrophages, adipose
tissue, brain skin and so on) also produce APOC2 protein to a less extent. The transcription of
APOC2 gene is regulated in a tissue-specific manner. In liver, APOC2 transcription is regulated
by farnesoid X receptor (FXR) and retinoid X receptor (RXR), which originally regulate genes
involved in bile acid synthesis and transport [92]. By the stimulation of bile acids, FXR/RXR
heterodimers bind to FXR response elements, which reside in hepatic control region (HCR) 1 and
2, and activate APOC2 expression [93]. In the macrophages, APOC2 gene is regulated by liver
X receptor (LXR) to enhance the delivery of lipids and energy to these highly metabolic myeloid
cells, thereby indicating APOC2 may play a role in those cells. It has also been shown that two
macrophage-specific multi-enhancer elements (ME.1 and ME.2) are critical for triggering the
activity of APOC2 promoter by LXR and RXR [94]. In intestine, it has been reported that APOC2
upregulation is associated with the failure of CD36 downregulation in mice [95]. But more studies
are needed to well understand the mechanism of APOC2 transcription in the intestine.
1.2.4 APOC2 deregulation in disease
Similar to LPL deficiency, deficiency of APOC2 has been reported to cause severe
hypertriglyceridemia and contribute to cardiovascular diseases. Interestingly, enhanced
28
expression of APOC2 in transgenic mice also induces hypertriglyceridemia, indicating APOC2
may have other unknown functions in lipid metabolism [96].
A recent study has revealed APOC2 is required for LPL-mediated hematopoietic stem progenitor
cell maintenance through the release of essential fatty acid- docosahexaenoic acid (DHA). This
study uncovered the unique function of APOC2 in hematopoiesis other than hydrolysis of TG [97].
Furthermore, besides LPL, CD36 is identified as another interaction partner of APOC2 to initiate
its downstream MAPK pathway for macrophage inflammatory responses [98].
APOC2 hasn’t been identified functions in most of the cancers. To date, one study has reported
that high APOC2 level in serum is associated with significantly shorter survival after resection in
pancreatic cancer patients(p=0.009). By adding the recombinant APOC2 in a dose-dependent
manner, both the growth and invasion of pancreatic cancer cell lines increased[99].
29
1.3 CD36
1.3.1 CD36 expression and function
CD36, an 88 kDa transmembrane glycoprotein which is also known as fatty acids (FA) translocase,
belongs to type B scavenger receptor family and is expressed on various cell types including
dendritic cells (DCs), platelets, microvascular endothelial cells (MVECs), mononuclear
phagocytes, adipocytes, hepatocytes, myocytes and podocytes [100]. In phagocyte cells, CD36
recognizes apoptotic cells, some pathogens, and modified LDL, thus causing inflammatory
responses and atherothrombotic disease. For MVECs, CD36 acts as a negative regulator of
angiogenesis by interacting with thrombospondin-1(TSP-1) and related proteins. Upon binding to
interact with the plasma membrane. The
extracellular domain is heavily glycosylat-
ed, accounting for the observed molecular
weight that is 30 to 40,000 daltons greater
than the weight predicted from the cDNA.
Studies of recombinant proteins expressed
in insect cells suggest that 9 of the 10 as-
paragine residues in the extracellular do-
main are glycosylated and that glycosyla-
tion is necessary for correct trafficking to
the plasma membrane (103). Both of the
intracellular domains contain paired cys-
teine residues that are lipid acylated and
thus probably tightly associated with the
inner leaflet of the plasma membrane (104)
(Fig. 2). CD36 can be ubiquitinated on
lysines 469 and 472 of the C-terminal do-
main (105), and this can target it to lyso-
somes, thus regulating its abundance. Inter-
estingly, CD36 ubiquitination was stimulat-
ed by increasing fatty acid concentrations
and inhibited by insulin, suggesting poten-
tial physiologic regulation of CD36 activity
by this pathway (105).
The extracellular domain mediates lig-
and recognition and contains independent
binding sites for TSR peptides
(106, 107) and oxidized phos-
pholipids (108, 109); the struc-
tural basis for fatty acid binding
remains largely unknown (5,
60). The mechanisms by which
a receptor with minimal intra-
cellular presence, no intrinsic
kinase or phosphatase activity,
no known intracellular scaffold-
ing domain(s), and no direct
link to GTPases activates multi-
ple signaling pathways remain
poorly understood but are under
intense study. A common theme
in CD36 signal transduction is
activation of Src family kinases
(110) and MAPKs. Antibodies
to CD36 coprecipitate specific
Src kinases and upstream
MAPK kinases (MAPKKs)
from lysates of different cell
types, and incubation of cells with CD36
ligands, such as oxLDL, increases the
amount of activated (phosphorylated) Src
kinases in the precipitates (52, 54). These
studies suggest that CD36 associates with
and participates in assembly of a dynamic
signaling complex essential to downstream
functions. It is highly likely that the C-ter-
minal cytoplasmic domain of CD36 directs
these associations. Point mutations of spe-
cific tyrosine or cysteine residues (Y
463
or
C
464
) in this domain (53) result in loss of
response to ligands, and a recombinant
protein containing this cytoplasmic do-
main precipitated a multiprotein complex
from monocytes that contained Lyn, a
MAPKK, and several as-yet-unidentified
proteins (52). Because CD36 resides in
cholesterol-rich, detergent-insoluble lipid
raft domains and copurifies with caveolae
from some tissues (111–114), it is possible
that CD36 signaling relates to its localiza-
tion in these membrane regions in which
signaling molecules, such as Src, accumu-
late. It is also possible that residence in
these domains facilitates lipid transport
through a docking mechanism and aid
from associated membrane and cytoplas-
mic proteins. CD36 is phosphorylated on
an extracellular threonine residue (115),
which influences binding of several lig-
ands (115, 116) and may effect internaliza-
tion and signaling.
It is also likely that CD36 may effect
signal transduction, in part, by interacting
with other membrane receptors, such as
integrins, tetraspanins (117), and TLRs.
The latter was elegantly demonstrated in
studies showing cooperation between
CD36 and TLR2 or TLR6 in macrophage
recognition and response to bacteria and
bacterial cell wall components, such as
Staphylococcus-derived lipoteichoic acid
(LTA) and diacylated lipoproteins (18,
118, 119). In some studies, however, some
components of the proinflammatory re-
sponse and bacteria uptake were shown to
be dependent on CD36-JNK signaling
(120, 121) and did not require TLR-medi-
ated activation of NF- B. TLRs do not ap-
pear to be required for CD36-dependent
uptake of oxLDL (52) or apoptotic cells.
Several CD36 functions require integrins,
and both 2
(28, 57) and 3
(117) inte-
grins coimmunoprecipitated with CD36.
Internalization of apoptotic cells and
photoreceptor outer segments requires in-
tegrins– v
3
in macrophages (22) and
v
5
in dendritic cells (24) and retinal
pigment epithelia (122). Microglial re-
sponses to A require 2
integrins, and the
spreading of brain tumor cells on throm-
bospondin-1 seems controlled by a func-
tional interaction between 1
integrins and
CD36 (123).
In summary, CD36-mediated signaling
pathways are conserved, defined by certain
common themes, and involved in many
critical cellular processes, but still relative-
ly poorly understood. Figure 1 outlines our
current model. Careful dissection of path-
ways in the context of specific cells and
ligands may yield novel insights for drug
development of multiple disorders.
REVIEW
www.SCIENCESIGNALING.org 26 May 2009 Vol 2 Issue 72 re3 5
TSR binding
TSR peptide
Glycosylation site
Oxidized lipid binding
Bioactive or oxidized lipids
Palmitoylation
C3
C7
Y463
C464
C466
C322
C243
T92
C272
S--S
S--S S--S
C313
C333
C311
Fig. 2. Topology and domains of CD36. This ditopic transmembrane receptor
resides in lipid raft membrane domains (shown shaded) and may interact with
other cell surface receptors, such as integrins, tetraspanins, and TLRs (not
shown). Ligand recognition may be modulated by phosphorylation of CD36 at
Thr (92) (T). The extracellular domain contains three disulfide bridges (Cys
243
-
Cys
311
, Cys
272
-Cys
333
, and Cys
313
-Cys
322
), multiple glycosylation sites, and at
least two separate ligand binding domains, one for proteins with throm-
bospondin repeat (TSR) domains and one for oxidized lipids. The N- and C-
terminal tails contain paired palmitoylated cysteine residues. Tyr
463
and Cys
464
in the C-terminal tail are important for ligand binding and for interaction with
downstream signaling molecules.
on September 17, 2018 http://stke.sciencemag.org/ Downloaded from
Figure 1.7 CD36 structure
Topology and domains of CD36. This ditopic
transmembrane receptor resides in lipid raft
membrane domains (shown shaded) and may
interact with other cell surface receptors, such as
integrins, tetraspanins, and TLRs (not shown).
Ligand recognition may be modulated by
phosphorylation of CD36 at Thr (92) (T). The
extracellular domain contains three disulfide
bridges (Cys
243
- Cys
311
, Cys
272
-Cys
333
, and
Cys
313
-Cys
322
), multiple glycosylation sites, and
at least two separate ligand binding domains, one
for proteins with throm- bospondin repeat (TSR)
domains and one for oxidized lipids. The N- and C-
terminal tails contain paired palmitoylated cysteine
residues. Tyr
463
and Cys
464
in the C-terminal tail
are important for ligand binding and for interaction
with downstream signaling
30
CD36, long-chain fatty acids are transported into cells for lipid utilization and energy
storage(Figure 1.7) [101].

31
1.3.2 CD36 roles in multiple cancers
Besides the important roles of CD36 in multiple physiological processes, CD36 is also largely
investigated for its tumorigenic property in oral carcinoma, liver cancer, breast cancer, and blood
cancer. Tumor cells are expected to exhibit higher energy potential than normal cells to meet the
requirements of their rapid proliferation and development. As a fatty acids translocase, CD36
facilitates the transportation of fatty acids, thus contributing to tumor growth [102].
A recent study has shown that oleic acid (OA) promoted cervical cancer carcinogenesis by
enhancing the CD36 expression and activating its downstream Src/ERK signaling pathway. In the
xenograft mice model, the group taking high OA diet had larger tumor volume and higher weight
compared with the group taking normal diet. But CD36 inhibition abrogated the pro-tumor effects
[103]. These findings reflect the potential of CD36 to be a therapeutic target of cervical cancer.
However, stimulated by TSP-1 on the surface of MVECs, CD36 pro-angiogenic response
switches to pro-apoptotic response, leading to inhibition of angiogenesis and initiation of
apoptosis [104]. Therefore, the roles of CD36 in cancer is dependent of the binding ligands and
localization.
In glioblastoma, CD36 is highly expressed in tumorigenic cancer stem cell. With exposure to
oxidized phospholipids, the ligands of CD36, cancer stem cell selectively uses CD36 to promote
its growth and maintenance [105].
In human oral carcinomas, a subpopulation of cells expressing high levels of CD36 and lipid
metabolism genes revealed to initiate metastasis. The presence of CD36 positive cells is clinically
32
associated with a poor prognosis for multiple types of carcinomas and restraining CD36
expression inhibits metastasis [106]. Moreover, metastasis induces by CD36 has been reported
to be involve in the lipid metabolism of cancer cells [107].
In the progression of gastric cancer (GC), the upregulation of CD36 is associated with poor
prognosis of patients according to TCGA database. Uptaken by CD36, palmitate acid triggers the
phosphorylation of AKT, facilitates the nuclear localization of beta-catenin through inactivation of
GSK3b, and thus promotes the metastasis of GC [108].
In ovarian cancer (OvCa), CD36 is highly expressed in the co-cultured primary human omental
adipocytes and facilitates the transportation of fatty acids. The knockdown or inhibition of CD36
prevents adipocyte-induced lipid accumulation and development of OvCa [109].
For Chemotherapy-resistant human AML, the cytarabine (AraC)-resistant preexisting and
persisting cells showed high level of oxidative phosphorylation and upregulated CD36 expression,
indicating the significance of targeting CD36 to potentiate AraC anti-leukemic effects [110]. A
similar study also revealed that CD36 characterized a subpopulation of leukemic stem cell (LSCs)
to use adipose tissue to evade chemotherapy in AML [111].
To support the survival of acute monocytic leukemia (AMoL) cells, bone marrow adipocytes play
important role to provide an optimal environment for the maintenance of AMoL cells. It has been
shown that bone marrow adipocytes can upregulate CD36 and AMPK genes in AMoL cells,
contributing to increased fatty acids oxidation and survival of AMoL cells [112].
33
Chapter 2 The Clinical Characterization of APOC2 in AML

2.1 Introduction

AML is a known for its clinical diversity and genetical heterogeneity. In early decades, certain
recurrent chromosomal aberrations were identified and well established for diagnosis and
prognosis. It has been reported that early 50% of adult patients carry chromosomal abnormalities
[12]. t (15; 17), t (8; 21), inv (16) and 11q23/MLL are four most common rearrangements in AML
[17] with frequencies between 3 and 10%. For the other 50% patients with normal karyotype, a
number of gene mutations and deregulated expression of genes have been identified [48].
Clinically, some of these gene mutations have identified as important prognostic and predictive
markers and targeting those mutations are being developed as novel treatments for AML.
Therefore, characterizing gene mutations as well as the deregulation of genes is important to
further provide an insight into the mechanisms of leukemogenesis and discovery potential targets
for AML.
To achieve this goal, we analyzed gene expression datasets (GSE7186[113], GSE13159[114],
GSE1159[115], GSE13164[114]) for genes that are differentially overexpressed in AML
compared to healthy donor cells. We found that APOC2 was consistently expressed at a
significantly higher level in AML than in control samples. No study has shown the role of APOC
in AML. Here we speculated that APOC2 upregulation is probably involved in AML
leukemogenesis. In this chapter, I first investigated the expression of APOC2 in patients with AML
34
and different subtypes of AML. Then the association of APOC2 upregulation with clinical outcome
was analyzed. To further establish the clinical relevance of APOC2 upregulation, we analyzed its
expression pattern according to cytogenetic and mutational status of patients with AML.
In this chapter, I statistically characterized APOC2 upregulation and its deregulation in AML to
further provide us knowledge for AML leukemogenesis and discovery of potential targets.

35
2.2 Experimental procedure

2.2.1 Study approval
The use of human materials was approved by the Institutional Review Board of the University of
Southern California (USC) in accordance with the Helsinki Declaration. All animal protocols were
approved by the Institution for Animal Care and Use Committee (IACUC) of USC.
2.2.2 Patient datasets
Molecular data and clinical outcomes were available in 173 patients with AML from The Cancer
Genome Atlas (TCGA) from cBioPortal[116, 117]. We dichotomized patients in the TCGA data
set into high (Z ≥ 1) and low (Z < 1) mRNA expression groups based on their APOC2 mRNA
expression Z-score (RNA Seq V2 RSEM). All the patients were diagnosed and have received
treatment according to the National Comprehensive Cancer Network (NCCN) guidelines between
November 2001 and March 2010. Additional patient data from the GSE7186[113],
GSE13159[114], GSE1159[115], GSE13164[114], and GSE17855[118] datasets were
downloaded from the Gene Expression Omnibus (GEO) database.
2.2.3 Patient samples
Blood samples were obtained from patients with AML at the time of diagnosis from the Norris
Comprehensive Cancer Center at USC. All samples were collected after obtaining written
informed consent. The use of human materials was approved by the Institutional Review Boards
of USC in accordance with the Helsinki Declaration.
36

2.2.4 Statistical analysis
All experiments were independently repeated at least three times. Data were represented as the
mean ± standard error of the mean (SEM). Statistical significance was calculated using the
Student’s t-test, Mann-Whitney test, one-way analysis of variance (ANOVA), two-way ANOVA in
GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA, USA). The statistical test was
indicated in the figure legend for each analysis.
Survival analysis was conducted in STATA 12.0 SE using the Cox proportional hazards model to
assess the association between APOC2 expression and overall and event-free survival in patients
with AML after adjusting for other factors, such as sex, cytogenetic status, and genetic mutations.
The associations between the APOC2 expression group and the molecular and mutational status
were analyzed using both Student’s t-test and Fisher’s exact test. A p-value less than 0.05 was
considered statistically significant for all tests. P value was adjusted according for multiple testing
in the methylation analysis.

37
2.3 Results
2.3.1 APOC2 is upregulated in AML
By analyzing gene expression datasets for genes that are differentially overexpressed in AML
compared with that in healthy donor cells, we found that APOC2 was consistently expressed at a
significantly higher level in samples from patients with AML than in control samples. In the
GSE13159 data set, APOC2 mRNA was significantly overexpressed in 542 AML patient samples
compared with 74 healthy peripheral blood mononuclear cells (PBMC) samples (2.9-fold, p <
0.0001) (Figure 2.1a). In the GSE13164 data set, APOC2 mRNA was significantly higher in 257
AML samples compared with 58 healthy PBMC samples (1.7-fold, p < 0.0001) (Figure 2.1b).
Consistently, APOC2 mRNA was upregulated in 285 AML samples compared with eight control
samples in the GSE1159 data set (6.0-fold, p < 0.0001) (Figure 2.1c). In the GSE7186 data set,
APOC2 exhibited a higher mRNA level in 23 AML patient samples compared with six normal bone
marrow (BM) samples (32.0-fold, p = 0.0003) (Figure 2.1d).

38

Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
a) The relative expression of APOC2 in: 542 AML cases compared with 74 healthy donors
in the GSE13159 data set; b) 257 AML cases compared with 58 healthy donors in the
GSE13164 data set; c) 285 AML cases compared with eight healthy donors in the GSE1159
data set; d) and 23 AML cases compared with six healthy donors in the GSE7186 data set
(compared by Mann-Whitney tests).

a b

c

d
Figure 2.1 APOC2 is upregulated in AML
39
2.3.2 The subtypes of APOC2-upregulated AML
To better understand the Next, we assessed APOC2 expression according to the French-
American-British (FAB) classification of AML and observed higher levels of APOC2 in the M3 and
M5 FAB subtypes compared with other subtypes (Figure 2.2, one-way ANOVA, p < 0.0001).

40

(a)
(b)
Supplemental Figures:
Supplementary Figure 1

FAB 0 FAB 1 FAB 2 FAB 3 FAB 4 FAB 5 FAB 6 FAB 7
-5
0
5
10
TCGA FAB SUBTYPE
Log2 median-centered intensity
****
****
Figure S1. A-B) Relative APOC2 expression according to the French-American-British (FAB) classification of
AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001). C) Relative APOC2 expression in patients
with MLL-rearranged AML compared with patients without MLL-rearranged AML in GSE 13164, TCGA and
GSE1159. D) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML compared
with patients without FLT3-WT AML in TCGA and GSE1159. E) Relative APOC2 expression in patients with
t(15;17) AML compared with patients without t(15;17) AML in TCGA and GSE1159. The difference between
groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3 Mutation
n=178 n=106
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3-ITD
FLT3-TKD
FLT3-ITD/TKD
n=178 n=73 n=28 n=5
*
**
ns
-2
0
2
4
6
Log2 median-centered intensity
GSE13164
n=240 n=17
****
-5
0
5
10
Log2 median-centered intensity
GSE1159
Non MLL-Rearrangement AML
MLL-Rearrangement AML
n=217 n=17
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
0
5
10
15
Log2 median-centered intensity
TCGA
FLT3-WT
FLT3-ITD
FLT3 Point
Mutation
n=104 n=35 n=12
*
*
-5
0
5
10
15
Log2 median-centered intensity
TCGA
No t(15:17)
t(15:17)
****
n=135 n=16
0
5
10
15
Log2 median-centered intensity
TCGA
***
n=143 n=8
Supplemental Figures:
Supplementary Figure 1

FAB 0 FAB 1 FAB 2 FAB 3 FAB 4 FAB 5 FAB 6
-4
-2
0
2
4
GSE1159 FAB SUBTYPE
Log2 median-centered intensity
****
****
(D)
Figure S1. A-B) Relative APOC2 expression according to the French-American-British (FAB) classification of
AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001). C) Relative APOC2 expression in patients
with MLL-rearranged AML compared with patients without MLL-rearranged AML in GSE 13164, TCGA and
GSE1159. D) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML compared
with patients without FLT3-WT AML in TCGA and GSE1159. E) Relative APOC2 expression in patients with
t(15;17) AML compared with patients without t(15;17) AML in TCGA and GSE1159. The difference between
groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3 Mutation
n=178 n=106
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3-ITD
FLT3-TKD
FLT3-ITD/TKD
n=178 n=73 n=28 n=5
*
**
ns
-2
0
2
4
6
Log2 median-centered intensity
GSE13164
n=240 n=17
****
-5
0
5
10
Log2 median-centered intensity
GSE1159
Non MLL-Rearrangement AML
MLL-Rearrangement AML
n=217 n=17
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
0
5
10
15
Log2 median-centered intensity
TCGA
FLT3-WT
FLT3-ITD
FLT3 Point
Mutation
n=104 n=35 n=12
*
*
-5
0
5
10
15
Log2 median-centered intensity
TCGA
No t(15:17)
t(15:17)
****
n=135 n=16
0
5
10
15
Log2 median-centered intensity
TCGA
***
n=143 n=8
a-b) Relative APOC2 expression according to the French-American-British (FAB) classification
of AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001).
Figure 2.2 The subtypes of APOC2-upregulated AML
41
2.3.3 The clinical characteristics
We dichotomized patients in the TCGA data set into high (Z ≥ 1) and low (Z < 1) mRNA expression
groups based on their APOC2 mRNA expression Z-score (RNA Seq V2 RSEM). Patients with
high APOC2 expression had a significantly higher percentage of bone marrow blasts (median:
89.5% vs. 72%, p = 0.0099) and had a lower percentage of peripheral blood blasts (PB median:
40% vs. 0%, p = 0.0033; Table 2.1) than patients with low APOC2. Five out of eight patients in
the APOC2 high mRNA expression group were reported to have no PB blasts compared to 17
out of 165 patients in the low APOC2 group (p = 0.0009 by Fisher’s exact test).

42

Table 2.1 clinical characteristics

Table S2. Clinical characteristics

(APOC2 Z>1) (APOC2 Z<1)
43
2.3.4 APOC2 is associated with poor clinical outcomes
For survival analysis, after excluding t(15;17) patients and adjusting for the factors previously
described, we observed that patients with high APOC2 mRNA expression (Z ≥ 1) had significantly
shorter overall survival (OS) than patients with low APOC2 mRNA expression (median OS: 6 vs.
17.4 months, p = 0.0006; Figure 2.3).

Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Non MLL-Rearrangement AML
MLL-Rearrangement AML
Patients in the TCGA data set dichotomized into high (Z≥1) or low (Z<1) groups according to
their APOC2 mRNA expression Z-score (RNA Seq V2 RSEM). Patients with high APOC2 levels
had significantly shorter OS than patients with low APOC2 expression (median OS 6 vs 17.4
months, P=0.0006).
Figure 2.3 APOC2- associated clinical outcomes
44
Multivariate survival analysis using the Cox proportional hazards model showed that high
APOC2 expression (Z ≥ 1) was significantly associated with decreased overall survival
(n=153 patients, excluding patients with FAB M3 classification and 4 patients without
cytogenetic risk information; HR: 2.51; 95% CI: 1.03 – 6.07; p-value: 0.042) after adjusting
for age, transplant status, cytogenetic risk, and FLT3 and p53 mutation status (Table 2.2).

Table 2.2 Multivariate survival analysis
Multivariate cox proportional hazards model analyzing of the effect of high APOC2 (Z >1)
expression on overall survival in patients with AML (TCGA DATA: n=153 patients, excluding
patients WITH FAB M3 CLASSIFICATION AND FOUR patients without cytogenetic risk
information).

HAZARD
RATIO
95% CI P-VALUE
AGE 1.01 1.00 1.03 0.089
TRANSPLANT
STATUS
0.395 0.24 0.64 <0.001
CYTOGENETIC RISK 2.23 1.47 3.37 <0.001
FLT3 1.63 1.04 2.55 0.035
TP53 2.13 1.06 4.28 0.034
APOC2 (Z > 1) 2.51 1.03 6.07 0.042

45
2.3.5 APOC2 overexpression is associated with MLL rearrangements
Because AML is a heterogeneous disease with distinct cytogenetic and molecular subtypes,
it is crucial to determine how APOC2 expression levels vary according to cytogenetic and
mutational status across patients. Our analysis of AML datasets showed that APOC2 is
significantly upregulated in t(11q23)/MLL-rearranged AML. APOC2 mRNA levels were
higher in 38 patients with MLL rearrangements compared with 504 patients without MLL
rearrangements in the GSE13159 data set (Figure 2.4 a, 9.0-fold, p < 0.0001). APOC2
mRNA levels also were higher in 47 patients with MLL rearrangements compared with 190
patients without MLL rearrangements in the GSE17855 data set (Figure 2.4 b, 6.6-fold, p <
0.0001). Similar findings were observed in three other data sets (Figure 2.4 c-e, GSE13164,
5.4-fold, p < 0.0001; TCGA, 9.2-fold, p = 0.0007; GSE1159, 5.1-fold, p =0.0006).

46

a-e) The relative expression of APOC2 comparison between patients with MLL-rearranged AML
compared with patients without MLL-rearranged AML in GSE13159, GSE17855, GSE 13159,
GSE 17855, GSE 13164, TCGA and GSE1159. The difference between groups was analyzed
by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Non MLL-Rearrangement AML
MLL-Rearrangement AML
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Non MLL-Rearrangement AML
MLL-Rearrangement AML
Supplemental Figures:
Supplementary Figure 1

Figure S1. A-B) Relative APOC2 expression according to the French-American-British (FAB) classification of
AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001). C) Relative APOC2 expression in patients
with MLL-rearranged AML compared with patients without MLL-rearranged AML in GSE 13164, TCGA and
GSE1159. D) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML compared
with patients without FLT3-WT AML in TCGA and GSE1159. E) Relative APOC2 expression in patients with
t(15;17) AML compared with patients without t(15;17) AML in TCGA and GSE1159. The difference between
groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3 Mutation
n=178 n=106
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3-ITD
FLT3-TKD
FLT3-ITD/TKD
n=178 n=73 n=28 n=5
*
**
ns
-2
0
2
4
6
Log2 median-centered intensity
GSE13164
n=240 n=17
****
-5
0
5
10
Log2 median-centered intensity
GSE1159
Non MLL-Rearrangement AML
MLL-Rearrangement AML
n=217 n=17
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
0
5
10
15
Log2 median-centered intensity
TCGA
FLT3-WT
FLT3-ITD
FLT3 Point
Mutation
n=104 n=35 n=12
*
*
-5
0
5
10
15
Log2 median-centered intensity
TCGA
No t(15:17)
t(15:17)
****
n=135 n=16
0
5
10
15
Log2 median-centered intensity
TCGA
***
n=143 n=8
(a)
(b)
(c) (d) (e)
Figure 2.4 APOC2 expression is enhanced in MLL-rearranged AML
47
When we dichotomized patients in the TCGA data set into high (Z≥1) and low (Z<1) expression
groups according to APOC2 mRNA expression Z-scores (RNASeq V2 RSEM), we observed that
high APOC2 expression (Z ≥ 1) was significantly associated with MLL rearrangements (Table 2.3,
Fisher’s exact test, p = 0.003).
Table 2.3 Mutation characteristics
Genetic
Aberration
Patients
with
APOC2
Z<1
(n=165)
Patients
with
APOC2
Z>1 (n=8)
Fisher’s
Exact p-
value

Patients
with
wildtype
Gene
Patients
with
mutant
Gene
Mann-
Whitney
U’s t-
test
Mutated patients N
(%)
Median APOC2 (log2-
median centered
mRNA)
APL (M3) 14 (8.48%) 2 (25%) 0.165 5.21 7.93 0.0001
MLL-
rearrangements
(Histo)
5 (3.09%) 3 (37.5%) 0.003 5.35 9.54 0.0014
FLT3-mut 47 (28.5%) 2 (25%) >0.999 4.35 6.93 0.0045
TP53-mut 14 (8.48%) 0 >0.999 5.85 1.21 0.0040
DNMT3A-mut 41 (24.8%) 2 (25%) >0.999 5.28 6.81 0.1962
CEBPA-mut 12 (7.27%) 1 (12.5%) 0.472 5.36 7.34 0.2031
NRAS-mut 12 (7.27%) 0 >0.999 5.50 5.48 0.7103
TET2-mut 15 (9.09%) 0 >0.999 5.62 2.95 0.0860
IDH1-mut 16 (9.70%) 0 >0.999 5.88 1.98 0.0065
IDH2-mut 17 (10.3%) 0 >0.999 5.88 0.75 0.0004
RUNX1-mut 16 (9.70%) 0 >0.999 5.97 0.30 <0.0001
NPM1-mut 45 (27.3%) 3 (37.5%) 0.687 4.24 7.41 <0.0001
WT1-mut 10 (6.06%) 0 >0.999 5.56 4.97 0.5696

48

2.3.6 APOC2 upregulation is associated with FLT3 mutations
Patients with the FLT3 mutations exhibited higher APOC2 mRNA expression than patients with
wild-type FLT3 (FLT3-WT) (Figure 2.5 a, TCGA data; FLT3-ITD vs FLT3-WT 6.0-fold, p = 0.013
and FLT3 point-mutation vs. FLT3-WT, 14.0-fold, p=0.035). Similar observation was found in the
GSE1159 dataset (Figure 2.5 b-c). However, the frequency of FLT3 mutations in patients with
high APOC2 (Z ≥ 1) was not significantly different than that in patients with low APOC2 (Z<1) (25%
vs 28.5%, Table 2.3).

a-c) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML
compared with patients without FLT3-WT AML in TCGA and GSE1159. The difference
between groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; **
P<0.01; * P<0.05).
Supplemental Figures:
Supplementary Figure 1

Figure S1. A-B) Relative APOC2 expression according to the French-American-British (FAB) classification of
AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001). C) Relative APOC2 expression in patients
with MLL-rearranged AML compared with patients without MLL-rearranged AML in GSE 13164, TCGA and
GSE1159. D) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML compared
with patients without FLT3-WT AML in TCGA and GSE1159. E) Relative APOC2 expression in patients with
t(15;17) AML compared with patients without t(15;17) AML in TCGA and GSE1159. The difference between
groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3 Mutation
n=178 n=106
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3-ITD
FLT3-TKD
FLT3-ITD/TKD
n=178 n=73 n=28 n=5
*
**
ns
-2
0
2
4
6
Log2 median-centered intensity
GSE13164
n=240 n=17
****
-5
0
5
10
Log2 median-centered intensity
GSE1159
Non MLL-Rearrangement AML
MLL-Rearrangement AML
n=217 n=17
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
0
5
10
15
Log2 median-centered intensity
TCGA
FLT3-WT
FLT3-ITD
FLT3 Point
Mutation
n=104 n=35 n=12
*
*
-5
0
5
10
15
Log2 median-centered intensity
TCGA
No t(15:17)
t(15:17)
****
n=135 n=16
0
5
10
15
Log2 median-centered intensity
TCGA
***
n=143 n=8
Supplemental Figures:
Supplementary Figure 1

Figure S1. A-B) Relative APOC2 expression according to the French-American-British (FAB) classification of
AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001). C) Relative APOC2 expression in patients
with MLL-rearranged AML compared with patients without MLL-rearranged AML in GSE 13164, TCGA and
GSE1159. D) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML compared
with patients without FLT3-WT AML in TCGA and GSE1159. E) Relative APOC2 expression in patients with
t(15;17) AML compared with patients without t(15;17) AML in TCGA and GSE1159. The difference between
groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3 Mutation
n=178 n=106
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3-ITD
FLT3-TKD
FLT3-ITD/TKD
n=178 n=73 n=28 n=5
*
**
ns
-2
0
2
4
6
Log2 median-centered intensity
GSE13164
n=240 n=17
****
-5
0
5
10
Log2 median-centered intensity
GSE1159
Non MLL-Rearrangement AML
MLL-Rearrangement AML
n=217 n=17
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
0
5
10
15
Log2 median-centered intensity
TCGA
FLT3-WT
FLT3-ITD
FLT3 Point
Mutation
n=104 n=35 n=12
*
*
-5
0
5
10
15
Log2 median-centered intensity
TCGA
No t(15:17)
t(15:17)
****
n=135 n=16
0
5
10
15
Log2 median-centered intensity
TCGA
***
n=143 n=8
Supplemental Figures:
Supplementary Figure 1

Figure S1. A-B) Relative APOC2 expression according to the French-American-British (FAB) classification of
AML in TCGA and GSE1159 datasets (one-way ANOVA, P<0.0001). C) Relative APOC2 expression in patients
with MLL-rearranged AML compared with patients without MLL-rearranged AML in GSE 13164, TCGA and
GSE1159. D) Relative APOC2 expression in patients with FLT3-ITD and FLT3 point mutations AML compared
with patients without FLT3-WT AML in TCGA and GSE1159. E) Relative APOC2 expression in patients with
t(15;17) AML compared with patients without t(15;17) AML in TCGA and GSE1159. The difference between
groups was analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3 Mutation
n=178 n=106
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
FLT3-WT
FLT3-ITD
FLT3-TKD
FLT3-ITD/TKD
n=178 n=73 n=28 n=5
*
**
ns
-2
0
2
4
6
Log2 median-centered intensity
GSE13164
n=240 n=17
****
-5
0
5
10
Log2 median-centered intensity
GSE1159
Non MLL-Rearrangement AML
MLL-Rearrangement AML
n=217 n=17
***
-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
0
5
10
15
Log2 median-centered intensity
TCGA
FLT3-WT
FLT3-ITD
FLT3 Point
Mutation
n=104 n=35 n=12
*
*
-5
0
5
10
15
Log2 median-centered intensity
TCGA
No t(15:17)
t(15:17)
****
n=135 n=16
0
5
10
15
Log2 median-centered intensity
TCGA
***
n=143 n=8
(a)
(b)
(c)
Figure 2.5 APOC2 is upregulated in FLT3-mutated AML
49
2.3.7 APOC2 upregulation has significant association with t(15;17) translocation
mutation
In addition, APOC2 levels were higher in patients with t(15;17) compared with patients without
t(15;17) (Figure 2.6 a-b, GSE 13159 2.0-fold, p <0.0001; GSE1159, 2.7-fold, p=0.004;). There
was no significant association between high APOC2 (Z ≥ 1) and mutations in IDH1, IDH2, RUNX1,
DNMT3A, or NPM1 (Fisher’s exact test, Table 2.3).

-5
0
5
10
Log2 median-centered intensity
GSE1159
No t(15:17)
t(15:17)
**
n=216 n=18
a-b) Relative APOC2 expression in patients with t(15;17) AML compared with patients
without t(15;17) AML in GSE 13159 and GSE1159. The difference between groups was
analyzed by Mann- Whitney test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
-2
0
2
4
6
Log2 median-centered intensity
GSE13159
No t(15:17)
t(15:17)
****
n=505 n=37
(a) (b)
Figure 2.6 APOC2 upregulation is associated with t(15;17) translocation mutation.
50
2.4 Discussion
The link between lipid metabolism and cancer is well established, yet the lipid metabolism effector
APOC2 in AML has not been studied previously. In normal tissues APOC2 is mainly expressed
in the liver and secreted into the plasma; it is also expressed at relatively lower levels by the
intestine, macrophages, adipose tissue, brain and so on. Whether APOC2 plasma levels are also
higher in patients with AML remained to be determined. In this chapter, we identified APOC2 as
a gene that is consistently upregulated in AML in several data sets and that is primarily
upregulated in type M3 and M5 leukemia. Meanwhile, APOC2 upregulation is associated with
poor clinical outcome. The association is still significant after adjustment of age, transplant status,
cytogenetic risk, and FLT3 and p53 mutation status (p=0.042), The analyses suggest that APOC2
upregulation is likely to be involved in the leukemogenesis of AML, yet its oncogenic potential
needs to be further verified.
Because AML is a heterogeneous disease composed of various of cytogenetic aberrations and
genetic mutations like MLL- rearrangements, FLT3 mutations, and t(15;17) translocation
mutations. Clinical characterization of APOC2 mRNA levels in AML populations with different
mutations showed significant association with MLL-rearrangements, FLT3-ITD mutations and
t(15;17) translocation mutations. MLL-rearrangements and FLT3-ITD mutations are associated
with poor clinical outcome in AML. The association with MLL-rearrangement is particularly
interesting considering that APOC2 is localized in a genetic loci on Chr19 p13.3 in close proximity
to the genetic loci that is involved in MLL-rearrangements t(11,19) (q23,p13.3). Because APOC2
51
is also upregulated in other MLL-rearrangements, a trans rather than cis transcriptional activation
is likely responsible for the observed upregulation of this gene in AML. It has been reported that
MLL maintains the expression of its target genes by protecting them from methylation. Whether
increased level of APOC2 in AML is regulated by MLL will be discussed later. Furthermore,
APOC2 gene is transcriptionally regulated by the LXR and STAT1 in macrophage. The
involvement of LXR and STAT1 in cancer progression is well known.
52
Chapter 3 The functional characterization of APOC2 in AML

3.1 Introduction
APOC2, as a small secreted protein, is known to play an important role in lipid metabolism. It
binds to lipids and lipoprotein lipase and participates in hydrolysis of VLDL and HDL, thus
facilitating energy delivery and storage. APOC2 is primarily expressed in liver and macrophage.
Especially in macrophage, APOC2 functions to enhance the delivery of lipids and energy to these
highly metabolic myeloid cells. With the deficiency of APOC2, it’s possible to develop severe
hypertriglyceridemia and cardiovascular disease [119] [120].
APOC2 hasn’t been identified to function in almost cancers. To date, there is only one study
reporting that high APOC2 level in serum is associated with significantly shorter survival after
resection in pancreatic cancer patients(p=0.009). By adding the recombinant APOC2 in a dose-
dependent manner, both the growth and invasion of pancreatic cancer cell lines increased[99].
In this chapter, I reported the upregulation of APOC2 in different AML datasets and the association
of enhanced APOC2 mRNA level with poor clinical outcome. I have also shown that APOC2 is
elevated in MLL- rearrangements, patients with FLT3 mutations, and patients with t(15;17)
translocation. These initial observations suggest that APOC2 has the potential to drive and/or
maintain the progression of AML. In this chapter, I examined the cell proliferation when
overexpressing and knocking down APOC2 in AML cell lines, primary AML blasts and AML
xenograft murine models. I also detected the cell apoptosis in AML cells stably expressing APOC2
shRNA to study the functional phenotypes of APOC2 in AML.
53
3.2 Experimental procedure
3.2.1 Study approval
The use of human materials was approved by the Institutional Review Board of the University of
Southern California (USC) in accordance with the Helsinki Declaration. All animal protocols were
approved by the Institution for Animal Care and Use Committee (IACUC) of USC.
3.2.2 AML murine xenograft models
NOD-scid/Il2rg
-/-
(NSG) mice were purchased from The Jackson Laboratory (Bar Harbor, ME,
USA) and kept in pathogen-free conditions. To generate AML engraftment, HL-60 and MOLM-13
knockdown APOC2(shAPOC2) cells as well as control cells (shCtrl) (2 × 10
6
per mouse) were
injected intravenously (through the tail vein) into 4–6-week-old male and female NSG mice. For
shRNA expression, mice were received doxycycline via oral gavage or Doxycycline Grain Based
Rodent Diet (Thermo Fisher Scientific, 14-727-450). Engraftments were monitored by
bioluminescence imaging once per week. Once mice reached the endpoint when signs of disease
burdens appeared, the blood and bone marrow were collected for fluorescence-activated cell
sorting (FACS) analysis. Tumor progression was monitored by bioluminescence imaging and flow
cytometry.
3.2.3 Cell culture and transfection
AML cell lines THP-1, MV4-11, and KG-1 were obtained from ATCC (Manassas, VA, USA).
MOLM-13, U937 and KG-1A cells were kindly provided by Dr. Wendy Stock’s Laboratory. All AML
54
cell lines were authenticated at the University of Arizona Cell Authentication Core and tested for
mycoplasma contamination in our lab using PCR based method (SouthernBiotech, Birmingham,
AL). All cell lines were mycoplasma-free. AML cell lines were cultured in RPMI 1640 medium
supplemented with 10% fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA) and 1%
antibiotics (Invitrogen). Primary samples were cultured in RPMI 1640 supplemented with 10%
FBS and StemSpan™ CC100, which contains a combination of both early- and late-acting
recombinant human (rh) cytokines (Flt3L, SCF, IL-3 and IL-6). HEK293T cells were cultured in
Dulbecco’s modified Eagle’s medium (DMEM; Invitrogen) supplemented with 10% FBS and 1%
antibiotics. Transfection was performed with Calcium Phosphate Transfection Kits (Clontech,
Mountain View, CA, USA), according to the manufacturer’s instruction.
3.2.4 Plasmid constructs
The PLVX-APOC2-AcGFP-N1 plasmid was constructed by cloning the APOC2 cDNA from U937
into the XhoI/BamH1 sites of the PLVX-AvGFP-N1 (Clontech). pLKO.1 - TRC cloning vector was
a gift from David Root (Addgene plasmid # 10878 ; http://n2t.net/addgene:10878 ;
RRID:Addgene_10878)[121]. Tet-pLKO-puro was a gift from Dmitri Wiederschain (Addgene
plasmid # 21915; http://n2t.net/addgene:21915 ; RRID:Addgene_21915)[122]. Small hairpin
RNAs (shRNAs) of APOC2 targeting TGCTGAAGGGAGAGGAGTAAC and
AGTTACTGGGAGTCAGCAAAG were inserted into both the pLKO.1-TRC and Tet-pLKO-puro
vectors. All constructs were confirmed by sequencing (Genewiz, Cambridge, MA, USA).
55

3.2.5 Cell viability and colony-forming cell assays
Trypan blue assay was used to count the cells either manually or using the Countess II FL
automatic cell counter (Life Technologies, Carlsbad, CA, USA) to determine cell viability. The
alamarBlue Cell Viability Reagent (ThermoFisher, Waltham, MA, USA) also was used to confirm
cell viability. Cells were washed and replaced with fresh medium. For each sample, 100 µl of
homogenous cells were subsequently incubated with 10 µl of alarmaBlue dye for 1–4 h at 37°C.
The BioTek Synergy H1 Hybrid Multi-Mode Microplate Read Machine (BioTek Instruments, Inc.,
Winooski, VT, USA) was used to detect fluorescence. All the counting experiments were
independently repeated at least three times. Experimenters were blind to conditions during the
counting procedures.
Colony-forming cell (CFC) assays were conducted by plating 5 × 10
4
primary blasts in 0.9%
MethoCult (StemCell Technologies, Vancouver, Canada) supplemented with StemSpan CC100.
Cultures were incubated at 37°C in a humidified atmosphere of 5% CO2 in air for 10–14 days.
Colony-forming units were counted by experimenter’s blind to the condition. All experiments were
performed in duplicate and repeated at least three times.

3.2.6 Immunoblot analysis
56
To conduct immunoblotting, cells were washed with phosphate buffered saline (PBS) and lysed
in Pierce IP Lysis Buffer (ThermoFisher) supplemented with a complete protease inhibitor cocktail
(Pierce; ThermoFisher). Cell lysates were microcentrifuged for 10 min at 10,000 × g at 4°C, and
the supernatants were collected. Cell lysates were measured using the Pierce 660-nm Protein
Assay Reagent (ThermoFisher) using the NanoDrop One (Thermo Scientific). Lysates then were
resolved by SDS-PAGE and transferred to a PVDF membrane (Bio-Rad, Hercules, CA, USA).
Membranes were blocked with 5% non-fat milk or bovine serum albumin for 1 h, and probed with
the following antibodies: anti-human APOC2 (Invitrogen, PA1-27196, 1:2,000) anti-Actin (Cell
Signaling Technology, 3700S, 1:2,000), and anti-GAPDH (Santa Cruz BioTechnology, Dallas, TX,
USA; SC-32233, 1:2,000). Horseradish peroxidase (HRP)-conjugated goat secondary antibodies
also were used (Invitrogen, 1:3,000). Immunodetection was achieved using the Pierce ECL
Western Blotting Substrate Reagent (ThermoFisher) and ChemiDoc Touch machine (Bio-Rad).
Western blot band density was evaluated using ImageJ analysis. For the same batch of samples,
the same blot was stripped and probed repeatedly to get the full set of antibody detections. Each
western blot was repeated three times independently.
3.2.7 RNA extraction, cDNA synthesis, and real-time PCR analysis
Total RNA was isolated with the RNeasy Mini Kit (Qiagen, Germantown, MD, USA). A total of 1
µg of total RNA was used for cDNA synthesis using the SuperScript® IV First-Strand Synthesis
System (Thermo Fisher). Quantitative real-time PCRs were carried out using the Applied
57
Biosystems PowerUp SYBR Green Master Mix (Thermo Fisher). Samples were obtained and
analyzed using the Applied Biosystem 7900HT Fast Real-Time PCR System (Thermo Fisher).
The gene expression levels were normalized to Actin. The primer sequences of APOC2 used for
qPCR were 5’-CTATAAATCCTCTCTGTGCCCG-3’ (forward) and 5’-
GGACCTCAAATCCCAATACCAG-3’ (reverse). The primer sequences of CD36 used for qPCR
were 5’- GCCAGGTATTGCAGTTCTTTTC-3’ (forward) and 5’- TGTCTGGGTTTTCAACTGGAG-
3’(reverse).
3.2.8 Lentiviral production
To produce lentivirus, HEK293T cells were transfected with PLVX or PLKO.1 plasmids together
with packaging plasmids psPAX and pMD2.G using Calcium Phosphate Transfection Kits
(Clontech). Viral particles were collected 72 h after transfection, filtered by a 0.45-µm sterile filter
and concentrated in PEG reagent at 4°C overnight. The concentrated viral particles then were
centrifuged at 2,000 × g for 30 min. Viral pellets were resuspended in complete cell culture
medium and stored in -80°C.
3.2.9 Flow cytometry
Cells were harvested from peripheral blood and bone marrow for immunophenotype analysis.
After washing with PBS, cells were stained on ice with various antibodies diluted in PBS for 30
min. Subsequently, cells were washed with PBS and resuspended in PBS for flow cytometry
58
analysis. The PE-Cy5.5 anti-human CD45 (eBioscience, 25-0459-41) was used for flow cytometry
analysis.
3.2.10 Apoptosis assay
The apoptosis assay was conducted using the eBioscience Annexin V Apoptosis Detection Kit
APC (Thermo Fisher Scientific, 88-8007-72). Cells were harvested after starvation
synchronization and were then washed once with PBS and binding buffer. Cells were
resuspended in binding buffer at a concentration of 5 × 10
6
cells/ml. Cells were incubated with
APC-conjugated Annexin V at a concentration of 100 μl of the cell suspension for 10–15 min at
room temperature. Cells then were washed again with binding buffer. Cells then were incubated
with 5 μl of propidium iodide staining solution on ice for 5–10 min and analyzed by flow cytometry.
3.2.11 Statistical analysis
All experiments were independently repeated at least three times. Data were represented as the
mean ± standard error of the mean (SEM). Statistical significance was calculated using the
Student’s t-test, Mann-Whitney test, one-way analysis of variance (ANOVA), two-way ANOVA in
GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA, USA). The statistical test was
indicated in the figure legend for each analysis.
Survival analysis was conducted in STATA 12.0 SE using the Cox proportional hazards model to
assess the association between APOC2 expression and overall and event-free survival in patients
with AML after adjusting for other factors, such as sex, cytogenetic status, and genetic mutations.
59
The associations between the APOC2 expression group and the molecular and mutational status
were analyzed using both Student’s t-test and Fisher’s exact test. A p-value less than 0.05 was
considered statistically significant for all tests. P value was adjusted according for multiple testing
in the methylation analysis.

60
3.3 Results
3.3.1 APOC2 ectopic expression promotes leukemia growth in AML cell lines
To investigate the functional role of APOC2 in leukemic cells, we first assessed the level of
APOC2 mRNA in a panel of AML cells by qPCR (Figure 3.1 a). We selected cell lines with low or
medium levels of APOC2 expression to conduct gain-of-function studies. We established an
ectopic lentiviral expression system to generate stable cells with APOC2 overexpression (OE
APOC2). In three different AML cell lines (MOLM-13, THP-1, and U937), APOC2 overexpression
caused slight, but statistically significant, increases in cell proliferation compared to controls (OE
Ctrl) four and five days after puromycin selection (Figure 3.1 b, MOLM-13, 33–74%, p < 0.0001;
THP-1, 17–34%, p = 0.002; U937, 33–50%, p = 0.003). Overexpression of APOC2 was verified
by western blot (WB; Figure 3.1 c).

61

U937
THP-1
NB4
MV4-11
MOLM-13
KG-1A
KG-1
Kasumi-1
0.00
0.01
0.02
0.03
0.04
0.05
0.20
0.25
Relative mRNA
APOC2 mRNA level
a) qPCR analysis of APOC2 mRNA levels in different AML cell lines.b) Cell proliferation
assays in MOLM-13 cells, THP-1 cells, and U937 cells transduced with control or APOC2
overexpression lentiviral particles (compared by two-way Anova). c) Western blot analysis of
APOC2 overexpression in AML cell lines. (**** p < 0.0001; *** p < 0.001; ** p < 0.01; * p <
0.05).

Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
(a)
(b)
(c)
Figure 3.1 APOC2 overexpression promotes AML cell lines growth
62
3.3.2 APOC2 ectopic expression promotes leukemia growth in primary AML patient
samples
In primary blasts from patients with AML, overexpression of APOC2 significantly increased cell
growth in six out of eight primary blast samples (Figure 3.2 a, means: #1: 4.87 × 10
4
vs. 33.03 ×
10
4
, p = 0.0005; #3: 1.54 × 10
4
vs. 4.78 × 10
4
, p = 0.001; #4: 19.73 × 10
4
vs. 37.07 × 10
4
, p =
0.003; #5: 17.90 × 10
4
vs. 47.83 × 10
4
, p < 0.0001; #7: 9.56 × 10
4
vs. 16.47 × 10
4
, p = 0.0008;
#8: 18 × 10
4
vs. 24 × 10
4
, p = 0.021). AML blast colony forming cell (CFC) assays showed that
APOC2 overexpression promoted colony forming ability compared with controls in three out of
five patient samples (Figure 3.2 b, means: #1: 6.67 vs 28.33, p = 0.0004; #3: 4.00 vs. 12.00, p =
0.0034; #5: 42.00 vs. 122.30, p = 0.0008). Overexpressed APOC2 protein levels were detected
in both cell lysates and cell culture supernatant (Figure 3.2 c). Patient sample information is listed
in Table 3.1.

Table S5. Patient information

Patient ID Sample Type FLT3 Mutation
Patient#1 Diagnosis NA
Patient#2 Diagnosis NA
Patient#3 Diagnosis NA
Patient#4 Diagnosis ITD
Patient#5 Relapse ITD
Patient#6 Relapse ITD
Patient#7 Diagnosis WT
Patient#8 Diagnosis WT

Table 3.1 Patient information
63

0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
#7
#8
0
#4
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
(I) (J)
(K)
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Non MLL-Rearrangement AML
MLL-Rearrangement AML
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
MLL-Rearrangement
NoMLL-Rearrangement
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
(I) (J)
(K)
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Non MLL-Rearrangement AML
MLL-Rearrangement AML
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
MLL-Rearrangement
NoMLL-Rearrangement
a) Viability assays for the growth of AML patient primary blasts transduced with
either APOC2 or control lentiviral particles (compared by unpaired t-tests). b)
Colony formation assays in AML patient primary blasts transduced with either
APOC2 or a control vector (compared by unpaired t-tests). c) Western blot
analysis of APOC2 overexpression in primary patient samples. (**** p < 0.0001;
*** p < 0.001; ** p < 0.01; * p < 0.05).

(a) (b)
(c)
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
(I) (J)
(K)
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Non MLL-Rearrangement AML
MLL-Rearrangement AML
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
MLL-Rearrangement
NoMLL-Rearrangement
Figure 3.2 APOC2 overepxression promotes AML patient samples growth
64
3.3.3 APOC2 knockdown inhibits leukemia cells progression in AML cells
Next, we assessed the effect of APOC2 knockdown on leukemia cells using shRNA lentiviral
plasmids. APOC2-shRNA infected AML cell lines (MOLM-13, KG-1, and THP-1) exhibited
significant reductions in proliferation compared with their respective controls, which were
transduced with scramble sequence (Figure 3.3 a-d, MOLM-13, 58%, p = 0.0036; THP-1, 33%,
p = 0.014). mRNA level of APOC2 was detected by qPCR (Figure 3.3 e).

65

0 1 2 3 4
0.0
5.0×10
5
1.0×10
6
1.5×10
6
2.0×10
6
2.5×10
6
cell count /ml
MOLM-13
shCtrl
shAPOC2
**
***
Days
a-d) Cell proliferation assay of a) MOLM-13 cells. b) KG-1 cells transiently infected with two
APOC2-shRNAs and control shRNA. Cell proliferation assay of c) MOLM-13 cells and d)
THP-1 cells transiently infected with APOC2-shRNA and control shRNA. The differences
between groups were analyzed by two-way Anova. (**** P<0.0001; *** P<0.001; ** P<0.01; *
P<0.05). e) The qPCR results of APOC2 knockdown in MOLM-13 cell lines. The difference
between groups was analyzed by Unpaired T test (**** P<0.0001; *** P<0.001; ** P<0.01; *
P<0.05).
0 1 2 3 4
0
1×10
6
2×10
6
3×10
6
cell count /ml
THP-1
shCtrl
shAPOC2
*
**
Days
Figure 4 APOC2 knockdown inhibits AML cell survival in vitro.
MOLM-13
KG-1
MV4-11
(A) (B)
(C) (D)
0.0
0.5
1.0
1.5
shCtrl
shAPOC2-1
shAPOC2-2
*** ***
(E)
Cell Number/x10
6
shCtrl
shAPOC2
AML Patient Blast
0
1
2
3
***
Cell Number/x10
6
1 2 3 4 5
5
10
15
Days
Relative cell proliferation fold
**
****
**
****
1 2 3 4 5
2
4
6
Days
Relative cell proliferation fold
shCtrl
shAPOC2-1
shAPOC2-2
****
****
**
****
0
20
40
60
80
100
Patient Blast
CFU number
shCtrl
shAPOC2
**
0.0
0.5
1.0
1.5
Relative mRNA
shCtrl
shAPOC2-1
shAPOC2-2
*** ***
MOLM-13 KD qPCR
(F)
0.0
0.5
1.0
1.5
Relative mRNA
shCtrl
shAPOC2
*
(G)
Patient Blast KD qPCR
Fig 4 A-C: Effects of APOC2 knockdown on cell proliferation
in MOLM13, KG1 and MV4-11. Fig 4D: The qPCR results of
APOC2 knockdown in MOLM-13 cell lines.
Fig 4E: Knockdown of APOC2 in primary blasts with AML
decreased cell viability. Fig 4F: Knockdown of APOC2
decreased the colony formation ability of primary blasts with
AML. Fig 4G: The qPCR results of APOC2 knockdown in
patient blasts. The difference between groups was analyzed
by Student’s T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
Figure 4 APOC2 knockdown inhibits AML cell survival in vitro.
MOLM-13
KG-1
MV4-11
(A)
(B)
(C) (D)
0.0
0.5
1.0
1.5
shCtrl
shAPOC2-1
shAPOC2-2
*** ***
(E)
Cell Number/x10
6
shCtrl
shAPOC2
AML Patient Blast
0
1
2
3
***
Cell Number/x10
6
1 2 3 4 5
5
10
15
Days
Relative cell proliferation fold
**
****
**
****
1 2 3 4 5
2
4
6
Days
Relative cell proliferation fold
shCtrl
shAPOC2-1
shAPOC2-2
****
****
**
****
0
20
40
60
80
100
Patient Blast
CFU number
shCtrl
shAPOC2
**
0.0
0.5
1.0
1.5
Relative mRNA
shCtrl
shAPOC2-1
shAPOC2-2
*** ***
MOLM-13 KD qPCR
(F)
0.0
0.5
1.0
1.5
Relative mRNA
shCtrl
shAPOC2
*
(G)
Patient Blast KD qPCR
Fig 4 A-C: Effects of APOC2 knockdown on cell proliferation
in MOLM13, KG1 and MV4-11. Fig 4D: The qPCR results of
APOC2 knockdown in MOLM-13 cell lines.
Fig 4E: Knockdown of APOC2 in primary blasts with AML
decreased cell viability. Fig 4F: Knockdown of APOC2
decreased the colony formation ability of primary blasts with
AML. Fig 4G: The qPCR results of APOC2 knockdown in
patient blasts. The difference between groups was analyzed
by Student’s T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
Figure 4 APOC2 knockdown inhibits AML cell survival in vitro.
MOLM-13
KG-1
MV4-11
(A) (B)
(C) (D)
0.0
0.5
1.0
1.5
shCtrl
shAPOC2-1
shAPOC2-2
*** ***
(E)
Cell Number/x10
6
shCtrl
shAPOC2
AML Patient Blast
0
1
2
3
***
Cell Number/x10
6
1 2 3 4 5
5
10
15
Days
Relative cell proliferation fold
**
****
**
****
1 2 3 4 5
2
4
6
Days
Relative cell proliferation fold
shCtrl
shAPOC2-1
shAPOC2-2
****
****
**
****
0
20
40
60
80
100
Patient Blast
CFU number
shCtrl
shAPOC2
**
0.0
0.5
1.0
1.5
Relative mRNA
shCtrl
shAPOC2-1
shAPOC2-2
*** ***
MOLM-13 KD qPCR
(F)
0.0
0.5
1.0
1.5
Relative mRNA
shCtrl
shAPOC2
*
(G)
Patient Blast KD qPCR
Fig 4 A-C: Effects of APOC2 knockdown on cell proliferation
in MOLM13, KG1 and MV4-11. Fig 4D: The qPCR results of
APOC2 knockdown in MOLM-13 cell lines.
Fig 4E: Knockdown of APOC2 in primary blasts with AML
decreased cell viability. Fig 4F: Knockdown of APOC2
decreased the colony formation ability of primary blasts with
AML. Fig 4G: The qPCR results of APOC2 knockdown in
patient blasts. The difference between groups was analyzed
by Student’s T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).
(c) (d) (e)
(a) (b)
Figure 3.3 Transient knockdown of APOC2 inhibits proliferation of AML cell lines.
66
Because the viability of the shAPOC2 cells was significantly reduced over time, we were unable
to generate stable cells with APOC2 knockdown after puromycin selection. We therefore
engineered a tetracycline-on (tet-on) lentiviral plasmid for the inducible expression of shRNA in
which the APOC2 gene was targeted by two different shRNAs. Consistently, in three cell lines
(MOLM-13, THP-1, and HL60), both shRNAs against APOC2 inhibited cell proliferation compared
with the scramble control group, which further validates that the observed effect is unlikely to be
due to off-target knockdowns (Figure 3.4 a-c). The knockdown of APOC2 mRNA levels was
confirmed by qPCR.

67

day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
Cell proliferation assays in a) MOLM-13 cells, b) THP-1 cells, and c) HL60 cells infected
with two different tet-on APOC2-shRNAs or control shRNA. The knockdown efficiency of
APOC2 was measured by qPCR (compared by two-way Anova).
(a)
(b)
(c)
Figure 3.4 Tetracycline-incucible knockdown of APOC2 inhibits cell growth.
68
3.3.4 APOC2 knockdown decrease the viability of AML primary blasts
The knockdown of APOC2 also inhibited cell proliferation in AML primary blasts (Figure 3.5 a,
means: #2:2.7 × 10
6
vs. 1.07 × 10
6
, p = 0.0001; #3: 2.74 × 10
6
vs. 1.98 × 10
6
, p = 0.0026; #8: 2.26
× 10
6
vs. 1.69 × 10
6
, p = 0.0007). CFC assays that were performed in primary blasts obtained
from three different patients with AML showed that the knockdown of APOC2 significantly
decreased the number of colonies (Figure 3.5 b, means: #2: 83.5 vs. 29.5, p = 0.02; #3:100.0 vs.
56.5, p = 0.006; #8: 45.0 vs. 23.0, p = 0.004). The efficiency of the APOC2 knockdown was
measured by qPCR (Figure 3.5 c).

69

a) Cell viability assay results for the knockdown of APOC2 in primary blasts from
patients with AML. b) Colony formation assay results for the knockdown of APOC2 in
primary blasts with AML. c) Measurement of APOC2 knockdown in patient blasts by
qPCR.
#2
#5
#8
0
1
2
3
Cell Number/x10
6
AML
Patient Blast
shCtrl
shAPOC2
***
**
***
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
THP-1
shCtrl
shAPOC2
***
* ns
ns
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
MOLM-13
shCtrl
shAPOC2
**
**
ns ns
Figure 2
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
shCtrl
shAPOC2
qPCR
(G)
MOLM-13
shCtrl
MOLM-13
shAPOC2
(H)
THP-1
shCtrl
THP-1
shAPOC2
PI
Annexin V-APC
Annexin V-APC
PI
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
#2
#5
#8
0
1
2
3
Cell Number/x10
6
AML
Patient Blast
shCtrl
shAPOC2
***
**
***
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
THP-1
shCtrl
shAPOC2
***
* ns
ns
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
MOLM-13
shCtrl
shAPOC2
**
**
ns ns
Figure 2
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
shCtrl
shAPOC2
qPCR
(G)
MOLM-13
shCtrl
MOLM-13
shAPOC2
(H)
THP-1
shCtrl
THP-1
shAPOC2
PI
Annexin V-APC
Annexin V-APC
PI
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
#2
#5
#8
0
1
2
3
Cell Number/x10
6
AML
Patient Blast
shCtrl
shAPOC2
***
**
***
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
THP-1
shCtrl
shAPOC2
***
* ns
ns
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
MOLM-13
shCtrl
shAPOC2
**
**
ns ns
Figure 2
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
shCtrl
shAPOC2
0.0
0.5
1.0
1.5
Relative mRNA
*
(G)
Patient Blast KD qPCR
qPCR
(G)
MOLM-13
shCtrl
MOLM-13
shAPOC2
(H)
THP-1
shCtrl
THP-1
shAPOC2
PI
Annexin V-APC
Annexin V-APC
PI
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
(a) (b)
(c)
Figure 3.5 APOC2 knockdown inhibits cell growth in primary patient samples.
70
3.3.5 APOC2 knockdown induces apoptotic cell death
Moreover, Annexin V and PI staining analysis by flow cytometry showed that the APOC2
knockdown in MOLM-13 and THP-1 cells increased the population of late apoptotic cells on post-
lentiviral transduction day 9 and day 4, respectively, compared with the respective controls
(Figure 3.6 a-c, MOLM-13: shCtrl vs. shAPOC2, live cells, 75.71% vs. 53.06%, p = 0.008; late
apoptotic cells, 19% vs. 37.24%, p = 0.007; THP-1: shCtrl vs. shAPOC2, live cells, 86.35% vs.
63.3%, p = 0.003; THP-1 apoptotic cells, 5.59% vs. 19.55%, p = 0.0387).

71

a-b) Annexin V and PI staining levels were measured by flow cytometry to assess cell
apoptosis in MOLM-13 and THP-1 cells infected with APOC2 shRNA or control shRNA.
c) The quantification of early and late apoptotic cell population changes The differences
between the groups were analyzed using Unpaired t-tests (**** p < 0.0001; *** p < 0.001;
** p < 0.01; * p < 0.05).

#2
#5
#8
0
1
2
3
Cell Number/x10
6
AML
Patient Blast
shCtrl
shAPOC2
***
**
***
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
THP-1
shCtrl
shAPOC2
***
* ns
ns
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
MOLM-13
shCtrl
shAPOC2
**
**
ns ns
Figure 2
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
shCtrl
shAPOC2
qPCR
MOLM-13
shCtrl
MOLM-13
shAPOC2
THP-1
shCtrl
THP-1
shAPOC2
PI
Annexin V-APC
Annexin V-APC
PI
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
#2
#5
#8
0
1
2
3
Cell Number/x10
6
AML
Patient Blast
shCtrl
shAPOC2
***
**
***
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
THP-1
shCtrl
shAPOC2
***
* ns
ns
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
MOLM-13
shCtrl
shAPOC2
**
**
ns ns
Figure 2
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
shCtrl
shAPOC2
qPCR
MOLM-13
shCtrl
MOLM-13
shAPOC2
THP-1
shCtrl
THP-1
shAPOC2
PI
Annexin V-APC
Annexin V-APC
PI
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
#2
#5
#8
0
1
2
3
Cell Number/x10
6
AML
Patient Blast
shCtrl
shAPOC2
***
**
***
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
THP-1
shctrl
shapoc2-1
shapoc2-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
HL60
Cell Number
/x10
4
shctrl
shapoc2-1
shapoc2-2
*
****
****
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
#2
#3
#8
0
20
40
60
80
100
120
CFU number
Patient Blast
shCtrl
shAPOC2
*
*
**
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
THP-1
shCtrl
shAPOC2
***
* ns
ns
Live cells
Late apoptotic cells
Early apoptotic cells
Necrotic cells
0
20
40
60
80
100
Population Percentage
MOLM-13
shCtrl
shAPOC2
**
**
ns ns
Figure 2
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.1
0.2
0.3
0.4
THP-1
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.00
0.01
0.02
0.03
0.04
MOLM13
Relative mRNA
***
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0000
0.0005
0.0010
0.0015
0.0020
Relative mRNA
HL60
***
***
shCtrl
shAPOC2
qPCR
MOLM-13
shCtrl
MOLM-13
shAPOC2
THP-1
shCtrl
THP-1
shAPOC2
PI
Annexin V-APC
Annexin V-APC
PI
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM-13
shctrl
shapoc2-1
shapoc2-2
****
****
****
(a)
(b)
(c)
Figure 3.6 APOC2 knockdown induces apoptosis.
72
3.3.6 Conditional knockdown of APOC2 and CD36 decrease leukemia burden in
murine leukemia models
To examine the effect of targeting APOC2 in murine models of AML, luciferase-positive HL60
cells (HL60
luci+
) with either tet-on-inducible APOC2 shRNAs or tet-on-inducible scramble
sequences were intravenously injected into NSG mice to generate human AML xenografts (n = 7
in shCtrl group, n = 8 in shAPOC2 group). Three days later, mice were treated once every other
day with doxycycline via oral gavage. Mice were monitored and imaged on week four and five
post-transplant. Mice were sacrificed on day 36 when signs of disease burden appeared. We
found a lower percentage of leukemic cell engraftments in the shAPOC2 group compared with
the shCtrl group. Mice in the shCtrl group exhibited a stronger bioluminescent signal compared
with mice in the shAPOC2 group (Figure 3.7 a).

73

a) Bioluminescent imaging of NOD-scid/Il2rg
-/-
(NSG) mice intravenously injected with
HL60 shCtrl or shAPOC2 luciferase cells.
shCtrl shAPOC2
-50
0
50
100
150
Engraftment (%)
Peripheral Blood
***
shCtrl shAPOC2
hCD45
Forward Side Scatter
shCtrl shAPOC2
Blank
(A)
(B)
Bone Marrow
Peripheral
Blood
Spleen
shCtrl shAPOC2 shCD36
0
20
40
60
80
Bone Marrow
Engraftment (%)
****
*
shCtrl shAPOC2 shCD36
0
5
10
15
20
Peripheral Blood
Engraftment (%)
**
***
shCtrl shAPOC2 shCD36
0
5
10
15
20
Engraftment (%)
Spleen
**
**
hCD45
SSC
(C)
shCtrl
shCD36 shAPOC2
Figure 6
Figure 3.7 Knockdown APOC2 mice showed less leukemia burden.
74

Furthermore, the shAPOC2 group exhibited significantly less leukemic burden in peripheral blood
compared with the shCtrl group (Figure 3.8 a-b, CD45
+
cells: 73.6% vs. 11.8%, p = 0.0003). The
engraftment of HL60 cells in mice was quantified in Figure 3.8 c.

75

hCD45
hCD45
Supplementary Figure 8
shCtrl shAPOC2 Figure S8. A) FACS blots showing hCD45 positive engraftment in peripheral blood of HL60
shCtrl group (n=7). B): FACS blots showing hCD45 positive engraftment in peripheral blood of
HL60 shAPOC2 group (n=8).

(a)
(b)
76

shCtrl shAPOC2
-50
0
50
100
150
Engraftment (%)
Peripheral Blood
***
shCtrl shAPOC2
hCD45
Forward Side Scatter
shCtrl shAPOC2
Blank
Bone Marrow
Peripheral
Blood
Spleen
shCtrl shAPOC2 shCD36
0
20
40
60
80
Bone Marrow
Engraftment (%)
****
*
shCtrl shAPOC2 shCD36
0
5
10
15
20
Peripheral Blood
Engraftment (%)
**
***
shCtrl shAPOC2 shCD36
0
5
10
15
20
Engraftment (%)
Spleen
**
**
hCD45
SSC
shCtrl
shCD36 shAPOC2
Figure 6
(c)
a) Flow cytometry results showing hCD45 positive engraftment in peripheral blood of HL60
shCtrl group (n=7). b) Flow cytometry results showing hCD45 positive engraftment in
peripheral blood of HL60 shAPOC2 group (n=8). c) Quantification of engraftment of HL60 cells
in the peripheral blood. The differences between the groups were analyzed using unpaired t-
tests (**** p < 0.0001; *** p < 0.001; ** p < 0.01; * p < 0.05).

Figure 3.8 Knockdown APOC2 mice group showed less engraftment in peripheral blood.
77

Minimal engraftment of HL60 was observed in the spleens and bone marrow of mice in both
groups (Figure 3.9 a). Six out of seven mice in the shCtrl group exhibited more than three
secondary tumors, located on the back, lower abdomen, and legs. In contrast, only one out of
eight mice in the shAPOC2 group exhibited secondary tumors (Figure 3.9 b).

78

shCtrl
shAPOC2
0
2
4
6
8
Spleen
Engraftment (%)
ns
shCtrl
shAPOC2
0
2
4
6
Bone Marrow
Engraftment (%)
ns
hCD45
hCD45
Supplementary Figure 9
shCtrl shAPOC2
Spleen Bone Marrow Figure S9. A-B) Representative FACS blots showing hCD45 positive population in bone marrow,
and spleen of HL60 shCtrl, and HL60 shAPOC2.Quantitative information of engraftment in spleen
and bone marrow was shown in right bar graphs. C) Images of tumors collected from the necks,
lower abdomens, and legs of engrafted mice.

shCtrl shAPOC2

shCtrl
shAPOC2
0
2
4
6
8
Spleen
Engraftment (%)
ns
shCtrl
shAPOC2
0
2
4
6
Bone Marrow
Engraftment (%)
ns
hCD45
hCD45
Supplementary Figure 9
shCtrl shAPOC2
Spleen Bone Marrow Figure S9. A-B) Representative FACS blots showing hCD45 positive population in bone marrow,
and spleen of HL60 shCtrl, and HL60 shAPOC2.Quantitative information of engraftment in spleen
and bone marrow was shown in right bar graphs. C) Images of tumors collected from the necks,
lower abdomens, and legs of engrafted mice.

shCtrl shAPOC2
a) Representative flow cytometry results showing hCD45 positive population in bone marrow,
and spleen of HL60 shCtrl, and HL60 shAPOC2.Quantitative information of engraftment in
spleen and bone marrow was shown in right bar graphs. b) Images of tumors collected from
the necks, lower abdomens, and legs of engrafted mice.
(a)
(b)
Figure 3.9 Knockdown APOC2 effects on NSG mice.
79
3.4 Discussion
The role of APOC2 in lipid metabolism has been intensively investigated, but its role in AML hasn’t
been revealed yet. To define whether APOC2 upregulation is necessary for the maintenance
or/and proliferation of AML, we conducted gain- and loss- of function assays.
In three AML cell lines (MOLM-13, THP-1, and U937) with low or medium expression of APOC2,
forced ectopic expression of APOC2 slightly but significantly increase the cell growth. Similarly,
in the primary patient samples, overexpression of APOC2 increase the viability of cells. The
effects of loss of function of APOC2 were also tested by constructing tetracycline-inducible system
to conditionally express APOC2 shRNA. We observed that knockdown APOC2 abrogates the
proliferative ability and triggers apoptosis in both AML cell lines and primary patient samples. The
knockdown effect was confirmed in murine model. Considering APOC2 is consistently
upregulated in AML population, we speculated that APOC2 protects cells from apoptosis leading
to reduced cell death. But it’s still unclear what pro-leukemic mechanism and which pathway
APOC2 is involved in.

80
Chapter 4 Mechanistic studies involving APOC2 upregulation in AML

4.1 Introduction

In previous chapters, we have reported the clinical relevance and functional phenotypes of
APOC2 upregulation in AML. And we found that APOC2 confers pro-leukemic ability to AML cells
as overexpression of APOC2 promotes cell growth and knockdown of APOC2 induces apoptotic
cell death. But it’s unclear that how APOC2 is consistently upregulated in AML and the mechanism
by which APOC2 upregulation contributes to leukemogenesis.
AML is characterized by aberrant DNA methylation landscapes. Especially, in patients with 11q23
abnormalities, the genome-wide DNA methylation analysis showed significant
hypomethylation[26, 123]. It was shown that a MLL fusion protein- MLL-EEN protects Hoxa
promoters from methylation and maintain the expression of Hoxa gene. The oncogenic MLL
fusion protein- MLL-AF4 can also reverse DNA methylation in certain CpGs[124]. All those studies
suggest MLL is involved in the mechanism of methylation regulation.
Our previous clinical analysis already revealed the significant association between APOC2
upregulation and MLL-rearrangements, suggesting that APOC2 expression is likely to be
regulated by DNA methylation and MLL-rearrangement may impact methylation patterns of
APOC2 gene. To test this idea, I first analyzed the methylation status in patients with high level
of APOC2 versus low level of APOC2. Then I tested whether the methylation level of APOC2
gene is affected by MLL-rearrangement mutation.
81
Previously, it has been found that APOC2 forms amyloid fibrils under lipid free condition[125] and
fibrillar APOC2 interacts with CD36 to trigger its downstream ERK signaling pathway in
macrophage for the development of atherosclerosis [98]. To test whether the action of APOC2 is
similar in AML, I detected the interaction between APOC2 and CD36 first.
CD36 is a multifunctional receptor presented on macrophages, platelets, skeletal muscle, and
adipocytes. This transmembrane glycoprotein is also known as fatty acids translocase. But for
the past decade, CD36 has more emerging roles in different cancers. Remarkably, in
chemotherapy-resistant AML, the AraC-resistant cells showed enhanced level of CD36
expression and high level of oxidative phosphorylation, implicating the significance of targeting
CD36 to potentiate AraC anti-leukemic effects[110]. A similar study also reported that CD36
characterized a subpopulation of leukemic stem cell (LSCs) using use adipose tissue and evading
chemotherapy in AML[111]. All those studies unveil the potential important functions of CD36 in
AML.
Here we hypothesized that APOC2 interact with CD36 to trigger its downstream signaling pathway
and thus resulting in leukemia growth.
To determine the mechanism that APOC2 upregulation contributes to pathogenesis of AML, I
conducted multiple functional assays to demonstrate whether the phenotype associated with
CD36 ectopic expression or loss of function is consistent with that of APOC2 upregulation and
knockdown. Then I checked the effects of simultaneous overexpressing APOC2 and CD36 on
proliferation of AML cells or knocking down APOC2 and CD36 on the proliferation of OE APOC2
82
and CD36 stable AML cells. Since there are available inhibitor and blocking antibody of CD36, I
used them to treat AML cells and tested whether CD36 is involved in the pro-leukemic effects
caused by APOC2.
I also conducted immunoblotting in different cells to detect p-ERK, ERK, P-LYN and LYN protein
levels, the downstream target of CD36. Given the roles of APOC2 and CD36 in lipid metabolism
and transport, we speculated that modulating their expression in AML cells would impact cells
bioenergetic profile. Live-cell metabolic measurements were performed by Seahorse XF showed
that OE APOC2 or OE CD36 THP-1 and MOLM-13 cells. Last but not the least, I verified the in
vitro results in murine mice model.
This chapter will demonstrate the mechanism of APOC2 upregulation contributing to leukemia
development via interaction with CD36.

83
4.2 Experimental procedures
4.2.1 Study approval
The use of human materials was approved by the Institutional Review Board of the University of
Southern California (USC) in accordance with the Helsinki Declaration. All animal protocols were
approved by the Institution for Animal Care and Use Committee (IACUC) of USC.
4.2.2 Patient datasets
All the patients were diagnosed and have received treatment according to the National
Comprehensive Cancer Network (NCCN) guidelines between November 2001 and March 2010.
Patient data from GSE63409[126] and GSE30377 [127] datasets were downloaded from the
Gene Expression Omnibus (GEO) database.
4.2.3 AML murine xenograft models
To generate AML engraftment, MOLM-13 knockdown APOC2(shAPOC2) cells, knockdown
CD36(shCD36) and control cells (shCtrl) (2 × 10
6
per mouse) were injected intravenously (through
the tail vein) into 4–6-week-old male and female NSG mice. For shRNA expression, mice were
received doxycycline via oral gavage or Doxycycline Grain Based Rodent Diet (Thermo Fisher
Scientific, 14-727-450). Once mice reached the endpoint when signs of disease burdens
appeared, the blood and bone marrow were collected for flow cytometry analysis.
To conduct CD36Ab treatment in vivo, MOLM-13 cells (2 × 10
6
per mouse) were first engrafted in
mice. Starting from day 7, mice were injected intravenously with 100 μl of PBS containing either
84
5 μg of a monoclonal CD36Ab FA6.152 or 5 μg of the corresponding IgG every 3 days for 5 doses.
Experiments were ended at day 21.
4.2.4 Cell culture and transfection
All AML cell lines were authenticated at the University of Arizona Cell Authentication Core and
tested for mycoplasma contamination in our lab using PCR based method (SouthernBiotech,
Birmingham, AL). All cell lines were mycoplasma-free. AML cell lines were cultured in RPMI 1640
medium supplemented with 10% fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA) and
1% antibiotics (Invitrogen). HEK293T cells were cultured in Dulbecco’s modified Eagle’s medium
(DMEM; Invitrogen) supplemented with 10% FBS and 1% antibiotics. Transfection was performed
with Calcium Phosphate Transfection Kits (Clontech, Mountain View, CA, USA), according to the
manufacturers instruction.
To conduct the CD36Ab treatment assay, THP-1 and MOLM-13 cells were treated with either 20
μg/ml of a monoclonal CD36Ab FA6.152 (Abcam, Cambridge, MA, USA) or a corresponding
mouse monoclonal IgG (Invitrogen) for the first 30 min. Cells were then released in RPMI
supplemented with 10% FBS in a final concentration of 2 μg/ml CD36Ab.
To conduct the Sulfo-N-succinimidyl Oleate sodium (SSO) treatment assay, SSO (SML2148;
Sigma, Bedford, MA, USA) was freshly dissolved in DMSO at a concentration of 100 mM and
then immediately applied to the cells at final concentrations of 50 μM and 100 μM.
4.2.5 Plasmid constructs
85
shRNAs of CD36 targeting CCGACGTTAATCTGAAAGGAA and
AGAACCTATTGATGGATTAAA also were inserted into those two plasmids to create lentiviral
knockdown CD36 plasmids. mCherry-CD36-C10 was a gift from Michael Davidson (Addgene
plasmid # 55011 ; http://n2t.net/addgene:55011 ; RRID:Addgene_55011). The pCDH-EF1-
CD36-FHC plasmid was constructed by cloning CD36 cDNA from THP-1 into EcoRI/NotI sites of
PCDH-EF1-FHC. pCDH-EF1-FHC was a gift from Richard Wood (Addgene plasmid # 64874 ;
http://n2t.net/addgene:64874 ; RRID:Addgene_64874). All constructs were confirmed by
sequencing (Genewiz, Cambridge, MA, USA).
4.2.6 Cell viability
Trypan blue assay was used to count the cells either manually or using the Countess II FL
automatic cell counter (Life Technologies, Carlsbad, CA, USA) to determine cell viability. The
alamarBlue Cell Viability Reagent (ThermoFisher, Waltham, MA, USA) also was used to confirm
cell viability. Cells were washed and replaced with fresh medium. For each sample, 100 µl of
homogenous cells were subsequently incubated with 10 µl of alarmaBlue dye for 1–4 h at 37°C.
The BioTek Synergy H1 Hybrid Multi-Mode Microplate Read Machine (BioTek Instruments, Inc.,
Winooski, VT, USA) was used to detect fluorescence. All the counting experiments were
independently repeated at least three times. Experimenters were blind to conditions during the
counting procedures.
4.2.7 Immunoblot analysis
86
To conduct immunoblotting, cells were washed with phosphate buffered saline (PBS) and lysed
in Pierce IP Lysis Buffer (ThermoFisher) supplemented with a complete protease inhibitor cocktail
(Pierce; ThermoFisher). Cell lysates were microcentrifuged for 10 min at 10,000 × g at 4°C, and
the supernatants were collected. Cell lysates were measured using the Pierce 660-nm Protein
Assay Reagent (ThermoFisher) using the NanoDrop One (Thermo Scientific). Lysates then were
resolved by SDS-PAGE and transferred to a PVDF membrane (Bio-Rad, Hercules, CA, USA).
Membranes were blocked with 5% non-fat milk or bovine serum albumin for 1 h, and probed with
the following antibodies: anti-human APOC2 (Invitrogen, PA1-27196, 1:2,000), anti-phospho-
P42/44 (Cell Signaling Technology, Danvers, MA, USA; 9101S, 1:1,000), anti-total-P42/44 (Cell
Signaling Technology, 9102S, 1:1,000), anti-Actin (Cell Signaling Technology, 3700S, 1:2,000),
and anti-GAPDH (Santa Cruz BioTechnology, Dallas, TX, USA; SC-32233, 1:2,000). Horseradish
peroxidase (HRP)-conjugated goat secondary antibodies also were used (Invitrogen, 1:3,000).
Immunodetection was achieved using the Pierce ECL Western Blotting Substrate Reagent
(ThermoFisher) and ChemiDoc Touch machine (Bio-Rad). Western blot band density was
evaluated using ImageJ analysis. For the same batch of samples, the same blot was stripped and
probed repeatedly to get the full set of antibody detections. Each western blot was repeated three
times independently.
4.2.8 Immunoprecipitation
87
Cells were washed with ice-cold PBS, lysed in Pierce IP Lysis Buffer (ThermoFisher)
supplemented with a complete protease inhibitor cocktail (Pierce; ThermoFisher). After one-hour
incubation, cell lysates were centrifuged for 10 min at 10,000 × g at 4°C, and the supernatants
were collected. Cell lysates were measured using the Pierce 660-nm Protein Assay Reagent
(ThermoFisher) using the NanoDrop One (Thermo Scientific). Cell lysates were rotated at 4 °C
for at least 30 min. Cell lysates were used for IP with the indicated antibodies. Generally, 1–4 μg
commercial antibody was added to 300ug cell lysates, which was then incubated at 4 °C for 3-4
h. After addition of protein A/G agarose beads, incubation was continued for overnight.
Immunoprecipitates were extensively washed with IP lysis buffer for 3-5 times and then eluted
with SDS–PAGE loading buffer by boiling for 5 min.
4.2.9 Lentiviral production
To produce lentivirus, HEK293T cells were transfected with PLVX or PLKO.1 plasmids together
with packaging plasmids psPAX and pMD2.G using Calcium Phosphate Transfection Kits
(Clontech). Viral particles were collected 72 h after transfection, filtered by a 0.45-µm sterile filter
and concentrated in PEG reagent at 4°C overnight. The concentrated viral particles then were
centrifuged at 2,000 × g for 30 min. Viral pellets were resuspended in complete cell culture
medium and stored in -80°C.
4.2.10 Flow cytometry
88
Cells were harvested from peripheral blood and bone marrow for immunophenotype analysis.
After washing with PBS, cells were stained on ice with various antibodies diluted in PBS for 30
min. Subsequently, cells were washed with PBS and resuspended in PBS for flow cytometry
analysis. The PE-Cy5.5 anti-human CD45 (eBioscience, 25-0459-41) was used for flow cytometry
analysis.
4.2.11 Seahorse and cellular metabolic analysis
Oxygen consumption rate (OCR: pmol/min/Norm. Unit) and extracellular acidification (ECAR)
(mpH/min/Norm. Unit) were determined in MOLM-13 and THP-1 cells using the Agilent Seahorse
XF platform and Seahorse XF Real-Time ATP Rate Assay Kit. On the day of assay, 20,000 of
overexpression cells were seeded in each well of Poly-D-Lysine (10μg/ml, Sigma, P6407) coated
96-well Agilent Seahorse XF Cell Culture Microplate. The plate was centrifuged at 200g without
brake for 1min. Oligomycin and Rotenone+antimycin A were dissolved and diluted in assay
medium and loaded in sensor cartridge in final concentration of 1.5μM and 0.5μM respectively.
4.2.12 APOC2 Methylation Patient Data Analysis
We downloaded publicly available Illumina 450K methylation array data from obtained normal
hematopoietic stem cells (HSCs) (N = 5) and leukemia CD34
+
CD38
-
cells (LSCs) (N = 15)
(GSE63409)[126]. We analyzed the methylation data to identify APOC2 methylation pattern
differences between healthy individuals and individuals with AML.

89
4.2.13 APOC2 Methylation PCR Analysis
5-Azacytidine was purchased from Sigma-Aldrich (A2385). Cell lines were treated with 5-Aza at
0nM, 250nM, 500nM, 750nM once every day for 72h. DNA samples from 5-Aza treated cells were
bisulfite converted using the Zymo EZ DNA Methylation kit for 12 hours using 500ng of DNA as
input according to manufacturer protocol. 500ng of Human Methylated DNA Standard and Human
Non-Methylated DNA Standard was also bisulfite converted as a control. Methylation specific
PCR (MSP) was performed with a primer pair designed to detect methylation in the APOC2
promoter using bisulfite converted DNA as a template. Primers were designed using the
MethPrimer online tool[128]. Bio-Rad Precision Melt Supermix was used to amplify methylated
APOC2 promoter. Left Primer 5’ -TTCGTTTATTAAGGTTTGGTTTTTC- 3’ Right Primer 5’ -
CGCTATATTACCCAAACTAATCTCG- 3’.
4.2.14 Statistical analysis
All experiments were independently repeated at least three times. Data were represented as the
mean ± standard error of the mean (SEM). Statistical significance was calculated using the
Student’s t-test, Mann-Whitney test, one-way analysis of variance (ANOVA), two-way ANOVA in
GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA, USA). The statistical test was
indicated in the figure legend for each analysis.
Survival analysis was conducted in STATA 12.0 SE using the Cox proportional hazards model to
assess the association between APOC2 expression and overall and event-free survival in patients
with AML after adjusting for other factors, such as sex, cytogenetic status, and genetic mutations.
90
The associations between the APOC2 expression group and the molecular and mutational status
were analyzed using both Student’s t-test and Fisher’s exact test. A p-value less than 0.05 was
considered statistically significant for all tests. P value was adjusted according for multiple testing
in the methylation analysis.

91
4.3 Results
4.3.1 APOC2 is hypomethylated in AML
To address whether APOC2 upregulation in AML is mediated by epigenetic mechanisms, we
compared APOC2 methylation pattern between patients with AML and healthy controls[126]. We
identified CpG sites within the APOC2 gene that were differentially methylated in AML leukemia
stem cells (LSC, CD34
+
CD38
-
cells) relative to hematopoietic stem cells (HSC) (Table 4.1). The
CpG sites corresponding to methylation probes cg25746394, cg01958934 cg09555818, and
cg13119609 showed significantly less methylation in LSCs compared with the same loci in HSCs
(Figure 4.1, cg25746394, p = 0.0035; cg01958934, p = 0.0117; cg09555818, p = 0.0030;
cg13119609, p = 0.0030).

92

Table 4.1 APOC2 methylation CpG island in AML vs Normal
Composite
Element
REF
CGI_Coordinate P value Mean of
Normal
HSC
Mean of
CD34+
AML
Adjusted P
Value
cg20090143 CGI:chr19:44954956-
44955826
0.549644 0.7395 0.7908 >0.999999
cg25746394 CGI:chr19:44954956-
44955826
0.000005 0.7549 0.357 0.000092
cg01958934 CGI:chr19:44954956-
44955826
0.000088 0.8279 0.4873 0.001588
cg09555818 CGI:chr19:44954956-
44955826
0.000003 0.7855 0.3802 0.000062
cg13119609 CGI:chr19:44954956-
44955826
0.000004 0.7862 0.3811 0.000063
cg27436184 CGI:chr19:44954956-
44955826
0.391552 0.8308 0.7572 >0.999999
cg10169327 CGI:chr19:44954956-
44955826
0.026528 0.7933 0.6023 0.477506
cg14723423 CGI:chr19:44954956-
44955826
0.67109 0.8082 0.8447 >0.999999
cg22164781 CGI:chr19:44954956-
44955826
0.806455 0.8336 0.8126 >0.999999
cg02912790 CGI:chr19:44954956-
44955826
0.84144 0.6801 0.663 >0.999999
cg04347059 CGI:chr19:44954956-
44955826
0.355592 0.9151 0.8358 >0.999999
93
cg04401876 CGI:chr19:44954956-
44955826
0.37956 0.8343 0.7589 >0.999999
cg04766076 CGI:chr19:44954956-
44955826
0.679093 0.8606 0.8251 >0.999999
cg06736138 CGI:chr19:44954956-
44955826
0.963978 0.8452 0.849 >0.999999
cg08656316 CGI:chr19:44954956-
44955826
0.7208 0.8275 0.8582 >0.999999
cg17769836 CGI:chr19:44954956-
44955826
0.447983 0.8438 0.7786 >0.999999
cg25017250 CGI:chr19:44954956-
44955826
0.327566 0.7625 0.6784 >0.999999
cg27353824 CGI:chr19:44954956-
44955826
0.569767 0.802 0.7532 >0.999999

94

Figure1
(A)
(B)
(C)
(D)
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
(I)
(H)
(J)
(K)
(G)
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
(E)
(F)
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0 50 100 150
0
50
100
Overall Survival without PML-RARA
Months
Percent survival
Z<1
Z>1
p=0.0006
0
5
10
15
APOC2 expression
TCGA
Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
APOC2 methylation beta value comparisons between normal HSC and CD34
+
CD38
-
cells (LSCs) from patients with AML probed by cg25746394, cg01958934,
cg09555818, and cg13119609 (unpaired t-tests adjusted P values: cg25746394,
p=0.0035; cg01958934, p=0.0117; cg09555818, p=0.003; cg13119609, p=0.003).
Figure 4.1 APOC2 is hypomethylated in AML leukemia stem cells.
95
4.3.2 APOC2 is epigenetically regulated by MLL-rearrangement
APOC2 upregulation in the MLL rearrangement AML was not limited to rearrangements that
involved chromosome 19. Given MLL as a methyltransferase positively regulates gene
expression[25], all these suggested a potential mechanism of epigenetic regulation of APOC2
expression in the MLL-rearrangement AML. To address this, we compared the methylation
patterns of APOC2 between patients with MLL-rearrangements and those without in the TCGA
dataset. We found that patients with MLL-rearrangements had significantly lower APOC2
methylation β values compared with patients without MLL-rearrangements (Figure 4.2 a, 2.0-fold,
p= 0.0038). In TCGA data, APOC2 expression level is significantly higher in hypomethylation
group compared with hypermethylation group (Figure 4.2 b, p<0.0001).

96

a) APOC2 methylation beta value comparison between patients with and without
MLL–rearranged AML (unpaired t-test, p=0.0035). b) Expression of APOC2 in AML
patients with APOC2 hypomethylation (β ≤ 0.2) and hypermethylation (β > 0.8).

Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Non MLL-Rearrangement AML
MLL-Rearrangement AML
(a) (b)
0 50 100 150
0
50
100
Overall Survival
Months
Percent survival
Z<1
Z>1
p=0.0006
Figure 1
Day1 Day2 Day3 Day4 Day5
0
100
200
300
400
500
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
THP-1
Cell Number
/x10
4
OE Ctrl
OE APOC2
****
***
Day1 Day2 Day3 Day4 Day5
5
10
15
20
25
Relative cell proliferation fold
U937
OE Ctrl
OE APOC2
**
****
7071
5010
6308
USC001
2427
5694
5957
0
20
40
60
Cell Number
/x10
4
***
*
***
***
**
**
#1
#2
#3
#5
#6
0
50
100
150
CFU number
OE Ctrl
OE APOC2
***
ns
**
***
ns
(I) (J)
(K)
THP-1 MOLM-13
OE Ctrl + - + - + -
OE APOC2 - + - + - +
U937
APOC2
GAPDH
n=504 n=38
-2
0
2
4
6
Log2 median-centered intensity
****
GSE13159
n=190 n=47
0
2
4
6
8
Log2 median-centered intensity
GSE17855
****
cg25746394
cg01958934
cg09555818
cg13119609
0.0
0.2
0.4
0.6
0.8
1.0
Probe
Beta-Value
APOC2 Methylation
Normal HSC
CD34
+
CD38
-
AML
*
*
**
**
0
5
10
15
APOC2 expression
TCGA Hypomethylation
Hypermethylation
****
n=40 n=12
0.0
0.2
0.4
0.6
0.8
1.0
Methylation
beta value
APOC2 Methylation
**
n=11 n=183
-2
0
2
4
6
Log2 median-centered intensity
GSE 13159
PBMC
AML
n=74 n=542
****
-2
0
2
4
6
Log2 median-centered intensity
GSE 13164
PBMC
AML
n=58 n=257
****
-5
0
5
10
Log2 median-centered intensity
GSE 1159
Control
AML
n=8 n=285
****
-4
-2
0
2
4
6
8
Log2 median-centered intensity
GSE 7186
BM
AML
n=6 n=23
***
Non MLL-Rearrangement AML
MLL-Rearrangement AML
MLL-rearrangement Non MLL
0.0
0.2
0.4
0.6
0.8
1.0
APOC2 methylation level in MLL groups
Methylation
beta value
MLL-rearrangement
Non MLL
**
MLL-Rearrangement
NoMLL-Rearrangement
Figure 4.2 APOC2 is epigenetically regulated by MLL-rearrangement
97
4.3.3 APOC2 is hypomethylated in MLL-rearranged AML cells
To further establish the epigenetic regulation of APOC2 expression, we treated four AML cell lines,
MV4-11 and MOLM-13 (with MLL-rearrangements), and U937 and NB4 (without MLL-
rearrangements) with increasing concentrations of the hypomethylating agent 5-azacytidine (5-
Aza). APOC2 mRNA expression significantly increased in U937 and NB4 but not in MV4-11 and
MOLM-13 (Figure 4.3 a-c). Methylation specific PCR (MSP) was performed to detect methylation
level in the APOC2 promoter. Amplified bands for NB4 and U937 cells were stronger than bands
for MOLM-13 and MV4-11 cells, indicating higher methylation level of APOC2 promoter in NB4
and U937 cells. In accordance with the mRNA expression level, NB4 and U937 showed
decreased methylation by increasing 5-Aza concentration (Figure 4.3 d). This further established
that the presence of MLL-rearrangements protects CpG clusters from methylation within the
APOC2 gene.

98

0nm
250nm
500nm
750nm
0nm
250nm
500nm
750nm
0.0
0.2
0.4
0.5
1.0
1.5
2.0
5-AZA treatment
Relative mRNA
Cell lines with MLL rearrangements
MOLM13
MV4-11
MOLM-13
MV4-11
NB4
U937
0.000
0.005
0.010
0.015
0.5
1.0
1.5
2.0
Relative mRNA
0nm
0nm
250nm
500nm
750nm
0nm
250nm
500nm
750nm
0.00
0.02
0.04
0.06
5-AZA treatment
Relative mRNA
Cell lines without MLL earrangements
NB4
U937
AML cell lines MOLM-13 and MV4-11 and NB4 and U937 were treated with 5-Aza at 0, 250,
500, and 750nm concentrations every day for three days, cells were collected. a) qPCR analysis
of APOC2 mRNA levels in MOLM-13, MV4-11, NB4 and U937 at base levels.b-c) APOC2
mRNA level changes post 5-Aza treatment. d) APOC2 promoter demethylation in 5-Aza treated
cell lines detected by methylation specific primers (MSP). 0% is the unmethylated control and
100% is fully methylated control. The differences between groups were analyzed by Unpaired
T test. (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

(a)
(b)
(c)
(d)
Figure 4.3 APOC2 is hypomethylated in MLL-rearranged AML cells.
99
4.3.4 APOC2 colocalizes with CD36
Fibrillar APOC2 previously was found to both interact with CD36 and trigger downstream
pathways in atherosclerosis[98]. To test whether the action of APOC2 is similar in AML, we first
performed immunofluorescence microscopy to identify co-localizations of APOC2 and CD36 in
HEK 293T cells. Both the confocal pictures and quantitative data showed mCherry-CD36
colocalized with APOC2-GFP but not empty-GFP (Figure 4.4 a-d, yellow area/mCherry area, 2.4-
fold, p = 0.0053; yellow area/GFP area, 2.2-fold, p = 0.005), indicating that APOC2 and CD36 are
colocalized.

100

a-b) Confocal microscopy showing the colocalization of CD36 and APOC2. 293T cells were
co-transfected with mCherry-CD36 and empty-GFP or mCherry-CD36 and APOC2-GFP
plasmids; and imaged 48 hours later by confocal microscopy. c-d) Quantitative analyses of
colocalization area conducted by ImageJ. Pictures were taken from ten different fields for
each slide (duplicate slides were used for each condition) and combined results of two
different experiments were reported. The difference between groups was analyzed by
unpaired T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
(a) (b)
(c) (d)
Figure 4.4 APOC2 colocalizes with CD36.
101
4.3.5 APOC2 was co-immunoprecipitated with CD36

To further confirm the physical interaction between APOC2 and CD36, co-immunoprecipitation
was conducted. flag-CD36 and APOC2 were forced expressed simultaneously in 293T cells and
flag antibody was used to pulled down the binding partners of CD36. The Western blot was probed
by APOC2 antibody and showed that APOC2 was co-immunoprecipitated with CD36 (Figure 4.5
a).

OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
a) Immunoprecipitation demonstrating the interaction between flag-CD36 and APOC2.
293T cells were co-transfected with flag-CD36 and APOC2 plasmids; flag antibody was
used to pull down CD36; APOC2 antibody was used to detect APOC2 in IP lysates as well
as input in WB.

Figure 4.5 APOC2 was co-immunoprecipitated with CD36.
102
4.3.6 CD36 knockdown impedes the proliferation of leukemia cells
Then, we examined the effect of CD36 gain or loss of function in AML cells by utilizing the
tetracycline-on lentiviral system for inducible expression of CD36 shRNAs (shCD36) and lentiviral
system for CD36 overexpression (OE CD36). Similar to the effect of APOC2 knockdown, CD36
knockdown inhibited cell proliferation in both THP-1 and MOLM-13 cells (Figure 4.6 a-b THP-1,
37.4%, p = 0.0096; MOLM-13, 40.8% , p= 0.0175).

a-b Effects of tetracycline-controlled CD36 knockdown on cell proliferation in
THP-1 and MOLM-13 cells.
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
(a)
(b)
Figure 4.6 CD36 knockdown impedes the proliferation of AML cell lines.
103
4.3.7 APOC2 functionally cooperates with CD36 to promote leukemia growth
To determine whether CD36 cooperates with APOC2 to enhance cell proliferation, we conducted
ectopic expression for either APOC2, or CD36, alone or combined (OE APOC2+CD36) in THP-1
and MOLM-13 cells. We found that OE APOC2+CD36 cells have significantly greater increase in
proliferation compared with OE APOC2 or OE CD36 cells (Figure 4.7 a-b). We also transduced
CD34
+
cord blood cells with empty vector, APOC2, CD36 or the combined lentiviral particles.
Assessment of cell count showed significant increase in the number of viable cell in CD34
+
cells
transduced with both APOC2 and CD36 compared with OE Ctrl cells and cells transduced with
either APOC2 or CD36 lentiviral particles alone at day 7 post-transduction. OE APOC2 or OE
CD36 resulted in only slight increase in cell proliferation (Figure 4.7 c, 30% increase, p = 0.0012).
Overexpression was confirmed by WB (Figure 4.7 d).

104

a-b) Effects of ectopic expression of APOC2, CD36 and both on cell proliferation in THP-
1 and MOLM-13 cells. c) Viability of CD45+ cells ectopically expressing empty vector,
APOC2, CD36 and both on day 3 and day 7. d) The expression level of APOC2 and
CD36 was detected by Western Blot.
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
(a) (b)
(c)
(d)
Figure 4.7 APOC2 functionally cooperates with CD36 to promote cell growth.
105
To assess whether CD36 expression is specific to the leukemia stem cell fraction, we used the
GSE30377 dataset to compare CD36 mRNA levels in AML cells from 23 patients that were sorted
into the following populations: CD34
+
CD38
-
, CD34
+
CD38
+
, CD34
-
CD38
-
, and CD34
-
CD38
+
. CD36
mRNA levels were not significantly different among the groups (Figure 4.8 a). Because high
APOC2 level was associated with poor overall survival, we asked whether high CD36 level is also
associated with clinical outcome. When patients were dichotomized based on CD36 median
expression, high CD36 expression patients have shorter but not statistically significant overall
survival (P=0.114); however when patients in the TCGA data were dichotomized based on their
APOC2 and/or CD36 mRNA expression Z-score into high (Z-score ≥2) and low (Z-Score <2),
patients with high APOC2 and/or CD36 levels had significantly shorter OS than patients with low
APOC2 and low CD36 expression (Figure 4.8 b, median OS 9.2 vs 21.5 months, P=0.017). To
confirm the functional association between APOC2 and CD36, shAPOC2 or shCD36 cells were
transduced with CD36 or APOC2 overexpression viral particles, respectively.

106

a) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and CD34-
/CD38- groups. b) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-
score ≥2) and low (Z-Score <2). Patients with high APOC2+CD36 levels had
significantly shorter OS. than patients with low APOC2+CD36 expression (median
OS 9.2 vs 21.5 months, P=0.017)

C D 3 4 + /C D 3 8 -
C D 3 4 + /C D 3 8 +
C D 3 4 -/C D 3 8 +
C D 3 4 -/C D 3 8 -
-6
-4
-2
0
2
4
G S E 3 0 3 7 7
C D 3 6 L o g 2 m R N A le v e l
(m e d ia n tra n s fo rm e d )
0 50 100 150
0
50
100
Months
Percent survival
TCGA Survival Outcome of High CD36 + High APOC2
CD36+APOC2(Z>=2)
CD36+APOC2(Z<2 0.0170 p=
Supplementary Figure 5
Figure S5: A) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and
CD34-/CD38- groups. B) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-score ≥2)
and low (Z-Score <2). Patients with high APOC2+CD36 levels had significantly shorter OS.
than patients with low APOC2+CD36 expression (median OS 9.2 vs 21.5 months, P=0.017)

48h
PI
Annexin V-
APC
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
**
**
***
***
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Supplementary Figure 6
Figure S6: A) Quantification of apoptosis populations in MOLM-13 cells for 24h B) Annexin V and PI
staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO treatment at 48h timepoint. C)
Quantification of apoptosis populations in THP-1 cells for 48h timepoints. D) Quantification of apoptosis
populations in MOLM-13 cells 48h timepoint. The difference between groups was analyzed by unpaired
T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

C D 3 4 + /C D 3 8 -
C D 3 4 + /C D 3 8 +
C D 3 4 -/C D 3 8 +
C D 3 4 -/C D 3 8 -
-6
-4
-2
0
2
4
G S E 3 0 3 7 7
C D 3 6 L o g 2 m R N A le v e l
(m e d ia n tra n s fo rm e d )
0 50 100 150
0
50
100
Months
Percent survival
TCGA Survival Outcome of High CD36 + High APOC2
CD36+APOC2(Z>=2)
CD36+APOC2(Z<2 0.0170 p=
Supplementary Figure 5
Figure S5: A) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and
CD34-/CD38- groups. B) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-score ≥2)
and low (Z-Score <2). Patients with high APOC2+CD36 levels had significantly shorter OS.
than patients with low APOC2+CD36 expression (median OS 9.2 vs 21.5 months, P=0.017)

48h
PI
Annexin V-
APC
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
**
**
***
***
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Supplementary Figure 6
Figure S6: A) Quantification of apoptosis populations in MOLM-13 cells for 24h B) Annexin V and PI
staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO treatment at 48h timepoint. C)
Quantification of apoptosis populations in THP-1 cells for 48h timepoints. D) Quantification of apoptosis
populations in MOLM-13 cells 48h timepoint. The difference between groups was analyzed by unpaired
T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

(a)
(b)
Figure 4.8 CD36 expression in LSC and its association with clinical outcomes.
107

4.3.8 Both APOC2 and CD36 are necessary for pro-leukemic effects in AML cells.
Knockdown of APOC2 or CD36 abolished the enhanced proliferation induced by ectopic
expression of the partner protein CD36 and APOC2, respectively. Overexpression and
knockdown of APOC2 and CD36 were confirmed by qPCR (Figure 4.9 a-b, MOLM-13 KD
APOC2/OE Ctrl vs KD APOC2/OE CD36, ns; MOLM-13 KD CD36/OE Ctrl vs KD CD36/OE
APOC2, ns). This suggests that both APOC2 and CD36 are required for the enhanced
proliferation and the presence of either protein is not sufficient to rescue the effect of depleting
the other.

108

a-b) Effects of knocking down APOC2 and CD36 on the proliferation of OE APOC2
and CD36 stable cells, respectively. mRNA levels of APOC2 and CD36 were
confirmed by qPCR. The difference between groups was analyzed by unpaired T test
(**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
OE CTRL
OE APOC2
0.00
0.05
0.10
0.15
0.20
0.25
Colocalization Percentage
**
Yellow area/
mCherry area
Figure 3
shCtrl
shCD36-1
shCD36-2
0.0
0.1
0.2
0.3
0.4
0.5
MOLM13
Relative mRNA
***
****
shCtrl
shCD36-1
shCD36-2
0.00
0.01
0.02
0.03
0.04
0.05
THP-1
Relative mRNA
****
****
CD36
APOC2
GAPDH
EV
APOC2
CD36
APOC2+
CD36
OE Ctrl + CD36
OE APOC2 + CD36
OE CTRL
OE APOC2
0.00
0.01
0.02
0.03
0.04
0.05
Colocalization Percentage
**
Yellow area/
GFP Area
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
MOLM-13
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
Day1 Day2 Day3 Day4 Day5
0
50
100
150
200
250
Cell Number
/x10
4
THP-1
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
****
****
****
IP: Flag(mouse)
CD36-flag
APOC2
CD36-flag
+ APOC2
IgG
CD36-flag
APOC2
CD36-flag
+ APOC2
Input
CD36
APOC2
GAPDH
80KD
25KD
37KD
day1 day2 day3 day4 day5
0
50
100
150
200
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
***
ns
day1 day2 day3 day4 day5
0
50
100
150
200
250
MOLM-13
Cell Number
/x10
4
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
**
ns
Day3
Day7
0.0
0.5
1.0
1.5
2.0
Relative cell proliferation fold
CD34+ Cells
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
ns
ns
ns
**
KD Ctrl/OE Ctrl
KD Ctrl/OE CD36
KD APOC2/OE Ctrl
KD APOC2/OE CD36
0
1
2
3
4
5
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
KD Ctrl/OE Ctrl
KD Ctrl/OE APOC2
KD CD36/OE Ctrl
KD CD36/OE APOC2
0.0
0.1
0.2
0.3
0.4
0.5
2
4
6
Relative mRNA
MOLM-13
APOC2
CD36
APOC2
CD36
day1 day2 day3 day4 day5
0
50
100
150
200
Cell Number
/x10
4
THP-1
shctrl
shcd36-1
shcd36-2
****
****
****
day1 day2 day3 day4 day5
0
100
200
300
Cell Number
/x10
4
MOLM13
shctrl
shcd36-1
shcd36-2
****
****
(a)
(b)
Figure 4.9 Both APOC2 and CD36 are necessary for AML growth.
109
4.3.9 Targeting CD36 function by (sulfo-N-succinimidyl oleate) SSO
While CD36 has multiple functions by interacting with several ligands, CD36 is a fatty acids
translocase facilitating the uptake of fatty acids. We therefore treated AML cells with SSO, the
irreversible inhibitor of CD36 for fatty acids translocation [PMID: 12479588], to assess whether
blocking fatty acids transportation causes a similar effect to that of CD36 knockdown. SSO at 50
µM and 100 µM concentrations induced apoptosis 24 h post-treatment, and the proportion of living
cells decreased significantly in treated cells (Figure 4.10 a-b, THP-1 cells: early apoptosis: 10.2%
vs. 38.6% for DMSO vs. 50 μM SSO, respectively, p = 0.027; 10.2% vs. 36.2% for DMSO vs. 100
μM SSO, respectively, p = 0.029; Figure 4.10 c, MOLM-13 cells: 6.6% vs. 18% for DMSO vs. 50
μM SSO, respectively, p = 0.05; 6.6% vs. 17.8% for DMSO vs. 100 μM SSO, respectively, p =
0.023). This apoptotic effect was transient, however, and disappeared 48 h post-treatment
(Figure 4.10 d-f).

110

Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*

C D 3 4 + /C D 3 8 -
C D 3 4 + /C D 3 8 +
C D 3 4 -/C D 3 8 +
C D 3 4 -/C D 3 8 -
-6
-4
-2
0
2
4
G S E 3 0 3 7 7
C D 3 6 L o g 2 m R N A le v e l
(m e d ia n tra n s fo rm e d )
0 50 100 150
0
50
100
Months
Percent survival
TCGA Survival Outcome of High CD36 + High APOC2
CD36+APOC2(Z>=2)
CD36+APOC2(Z<2 0.0170 p=
Supplementary Figure 5
Figure S5: A) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and
CD34-/CD38- groups. B) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-score ≥2)
and low (Z-Score <2). Patients with high APOC2+CD36 levels had significantly shorter OS.
than patients with low APOC2+CD36 expression (median OS 9.2 vs 21.5 months, P=0.017)

48h
PI
Annexin V-
APC
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
**
**
***
***
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Supplementary Figure 6
Figure S6: A) Quantification of apoptosis populations in MOLM-13 cells for 24h B) Annexin V and PI
staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO treatment at 48h timepoint. C)
Quantification of apoptosis populations in THP-1 cells for 48h timepoints. D) Quantification of apoptosis
populations in MOLM-13 cells 48h timepoint. The difference between groups was analyzed by unpaired
T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

(a)
(b) (c)
a) Results of the Annexin V and PI staining apoptosis assays in THP-1 cells 24 hours
after treatment with either 50 uM or 100 uM of sulfo-N-succinimidyl oleate sodium (SSO).
b) Quantification of apoptosis populations in THP-1 cells 24h after SSO treatment. c)
Quantification of apoptosis populations in MOLM-13 cells for 24h The difference
between groups was analyzed by unpaired T test (**** P<0.0001; *** P<0.001; ** P<0.01;
* P<0.05).

Figure 4.10 Effects of targeting CD36 by SSO.
111

d)Annexin V and PI staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO
treatment at 48h timepoint. e) Quantification of apoptosis populations in THP-1 cells for 48h
timepoints. f) Quantification of apoptosis populations in MOLM-13 cells 48h timepoint. The
difference between groups was analyzed by unpaired T test (**** P<0.0001; *** P<0.001; **
P<0.01; * P<0.05).

c

C D 3 4 + /C D 3 8 -
C D 3 4 + /C D 3 8 +
C D 3 4 -/C D 3 8 +
C D 3 4 -/C D 3 8 -
-6
-4
-2
0
2
4
G S E 3 0 3 7 7
C D 3 6 L o g 2 m R N A le v e l
(m e d ia n tra n s fo rm e d )
0 50 100 150
0
50
100
Months
Percent survival
TCGA Survival Outcome of High CD36 + High APOC2
CD36+APOC2(Z>=2)
CD36+APOC2(Z<2 0.0170 p=
Supplementary Figure 5
Figure S5: A) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and
CD34-/CD38- groups. B) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-score ≥2)
and low (Z-Score <2). Patients with high APOC2+CD36 levels had significantly shorter OS.
than patients with low APOC2+CD36 expression (median OS 9.2 vs 21.5 months, P=0.017)

48h
PI
Annexin V-
APC
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
**
**
***
***
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Supplementary Figure 6
Figure S6: A) Quantification of apoptosis populations in MOLM-13 cells for 24h B) Annexin V and PI
staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO treatment at 48h timepoint. C)
Quantification of apoptosis populations in THP-1 cells for 48h timepoints. D) Quantification of apoptosis
populations in MOLM-13 cells 48h timepoint. The difference between groups was analyzed by unpaired
T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

C D 3 4 + /C D 3 8 -
C D 3 4 + /C D 3 8 +
C D 3 4 -/C D 3 8 +
C D 3 4 -/C D 3 8 -
-6
-4
-2
0
2
4
G S E 3 0 3 7 7
C D 3 6 L o g 2 m R N A le v e l
(m e d ia n tra n s fo rm e d )
0 50 100 150
0
50
100
Months
Percent survival
TCGA Survival Outcome of High CD36 + High APOC2
CD36+APOC2(Z>=2)
CD36+APOC2(Z<2 0.0170 p=
Supplementary Figure 5
Figure S5: A) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and
CD34-/CD38- groups. B) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-score ≥2)
and low (Z-Score <2). Patients with high APOC2+CD36 levels had significantly shorter OS.
than patients with low APOC2+CD36 expression (median OS 9.2 vs 21.5 months, P=0.017)

48h
PI
Annexin V-
APC
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
**
**
***
***
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Supplementary Figure 6
Figure S6: A) Quantification of apoptosis populations in MOLM-13 cells for 24h B) Annexin V and PI
staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO treatment at 48h timepoint. C)
Quantification of apoptosis populations in THP-1 cells for 48h timepoints. D) Quantification of apoptosis
populations in MOLM-13 cells 48h timepoint. The difference between groups was analyzed by unpaired
T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

C D 3 4 + /C D 3 8 -
C D 3 4 + /C D 3 8 +
C D 3 4 -/C D 3 8 +
C D 3 4 -/C D 3 8 -
-6
-4
-2
0
2
4
G S E 3 0 3 7 7
C D 3 6 L o g 2 m R N A le v e l
(m e d ia n tra n s fo rm e d )
0 50 100 150
0
50
100
Months
Percent survival
TCGA Survival Outcome of High CD36 + High APOC2
CD36+APOC2(Z>=2)
CD36+APOC2(Z<2 0.0170 p=
Supplementary Figure 5
Figure S5: A) CD36 mRNA levels in CD34+/CD38-, CD34+/CD38+, CD34-/CD38+ and
CD34-/CD38- groups. B) Patients in the TCGA data were dichotomized based on their
APOC2 and CD36 mRNA expression Z-score (RNA Seq V2 RSEM) into high (Z-score ≥2)
and low (Z-Score <2). Patients with high APOC2+CD36 levels had significantly shorter OS.
than patients with low APOC2+CD36 expression (median OS 9.2 vs 21.5 months, P=0.017)

48h
PI
Annexin V-
APC
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
**
**
***
***
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
MOLM-13 48h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
ns
ns
Supplementary Figure 6
Figure S6: A) Quantification of apoptosis populations in MOLM-13 cells for 24h B) Annexin V and PI
staining apoptosis assay in THP-1 cells after 50uM and 100uM SSO treatment at 48h timepoint. C)
Quantification of apoptosis populations in THP-1 cells for 48h timepoints. D) Quantification of apoptosis
populations in MOLM-13 cells 48h timepoint. The difference between groups was analyzed by unpaired
T test (**** P<0.0001; *** P<0.001; ** P<0.01; * P<0.05).

(d)
(e)
(f)
112
4.3.10 Targeting CD36 function by CD36 antibody inhibits the progression of AML
cells
THP-1 and MOLM-13 cells both express relatively high levels of CD36. We therefore treated THP-
1 and MOLM-13 cells ectopically expressing APOC2 or their respective controls with CD36-
blocking antibody (2 μg/ml). Both groups of cells exhibited a significant decrease in cell
proliferation four days post-incubation with the CD36-blocking antibody (Figure 4.11 a, THP-1:
OE Ctrl, 47.96%, p < 0.0001; OE APOC2, 56.54%, p < 0.0001; Figure 4.11 b, MOLM-13: OE Ctrl,
42.35%, p = 0.0011; OE APOC2, 57.68%, p < 0.0001). These data suggest that treatment with
the CD36-blocking antibody abrogated the enhanced proliferation effects observed with APOC2
overexpression.

113

a-b) The effects of CD36-blocking antibody on cell proliferation in THP-1 and
MOLM13 OE Ctrl and OE APOC2 cells.
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
(a)
(b)
Figure 4.11 Effect of targeting CD36 by CD36 blocking antibody.
114
4.3.11 Targeting CD36 by CD36 antibody induces apoptosis and abrogates APOC2
pro-leukemic effects
Furthermore, CD36-blocking antibody induced significant apoptosis in both control cells and in
cells overexpressing APOC2 (Figure 4.12 a-b, IgG vs. CD36Ab: THP-1, Annexin V
+
cells, OE
Ctrl: 12.93% vs. 27.44%, p = 0.0265; OE APOC2: 11.89% vs. 37.35%, p = 0.0379;d-e MOLM-13,
OE Ctrl: 11.01% vs. 30.21%, p = 0.041; OE APOC2: 9.67% vs. 44.77%, p = 0.0294). Cells in the
OE APOC2 groups exhibited a higher percentage of Annexin V than cells in the OE Ctrl groups
when treated with CD36 antibody (p = 0.0318 for THP-1). Cells treated with the CD36 blocking
antibody also exhibited a reduction in BODIPY staining, indicating less cellular uptake of fatty
acids (Figure 4.12 c-f)

115

Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
(a) (b)
(c)
a) The effects of CD36 blocking antibody on apoptosis 24 h post-treatment in THP-1
OE Ctrl and OE APOC2 cells. b) The quantification of Annexin V
+
cell populations
among THP-1 OE Ctrl and OE APOC2 cells treated with IgG or CD36Ab. c) A
comparison of BODIPY staining between THP-1 OE Ctrl and OE APOC2 cells
treated with IgG or CD36Ab. The differences between the groups were analyzed
using unpaired t-tests (**** p < 0.0001, * p < 0.05).

Figure 4.12 Targeting CD36 by antibody indduces apoptosis.
116

d) The effects of CD36 blocking antibody on apoptosis 24 h post-treatment in MOLM-13 OE
Ctrl and OE APOC2 cells. e) The quantification of Annexin V
+
cell populations among MOLM-
13 OE Ctrl and OE APOC2 cells treated with IgG or CD36Ab. f) A comparison of BODIPY
staining between MOLM-13 OE Ctrl and OE APOC2 cells treated with IgG or CD36Ab. The
differences between the groups were analyzed using unpaired t-tests (**** p < 0.0001, * p <
0.05).

Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
Live cells
Early apoptotic cells
Late apoptotic cells
Necrotic cells
0
20
40
60
80
100
THP-1 24h Treatment
Percentage
DMSO
50uM SSO
100uM SSO
***
***
***
**
Figure 4
DMSO 50uM SSO 100uM SSO
24h
PI
Annexin V-APC
0 1 2 3 4
0
50
100
150
200
THP-1 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
PI
CD36 Ab
IgG
OE CTRL
OE APOC2
Annexin V-APC
Annexin V-APC
OE CTRL OE APOC2
IgG
CD36 Ab
PI
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
20
40
60
Annexin V+ Cells Percentage
MOLM-13
*
*
0 1 2 3 4
0
50
100
150
200
250
MOLM-13 OE cells CD36 Ab proliferation
Days
Cell Number
/x10
4
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
****
****
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
5000
10000
15000
20000
25000
GFP-Median
MOLM-13
Bodipy
OECtrlIgG
OEAPOC2IgG
OECtrlCD36Ab
OEAPOC2CD36Ab
OE Ctrl IgG
OE APOC2 IgG
OE Ctrl CD36Ab
OE APOC2 CD36Ab
0
10000
20000
30000
40000
GFP-Median
THP-1
OE Ctrl IgG
OE Ctrl CD36Ab
OE APOC2 IgG
OE APOC2 CD36Ab
0
10
20
30
40
Annexin V+ Cells Percentage
THP-1
*
*
*
(d)
(e)
(f)
117
4.3.12 APOC2 triggers downstream ERK signaling of CD36
To address whether APOC2 triggers signaling pathways downstream of CD36, we assessed the
effect of APOC2 gain-of-function and loss-of-function on ERK phosphorylation. We found that OE
APOC2 cells (both THP-1 and MOLM-13) exhibited higher levels of phospho-ERK (p-ERK)
compared with their respective control cells while total-ERK did not change (Figure 4.13 a , p-
ERK/total-ERK ratio change, THP-1 OE APOC2, 43.34% increase, p = 0.0343; MOLM13 OE
APOC2, 67.30% decrease, p = 0.0001). Conversely, p-ERK levels decreased when endogenous
expression of APOC2 was knocked down by two different APOC2 shRNAs (Figure 4.13 b, THP-
1 p-ERK/total-ERK ratio change, shAPOC2-1, 47.56% decrease, p <0.0001; shAPOC2-2, 81.50%
decrease, p = 0.0008; MOLM13 p-ERK/total-ERK ratio change, shAPOC2-1, 47.65% decrease,
p =0.0002; shAPOC2-2, 51.39% decrease, p = 0.0063). Similarly, in HL60, the knockdown of
APOC2 resulted in a significant decrease in p-ERK protein levels (Figure 4.13 c, p-ERK/total-
ERK ratio change, shAPOC2-1, 62.25% decrease, p = 0.0025; p-ERK/total-ERK ratio change,
shAPOC2-2, 72.00% decrease, p = 0.0017).

118

a) The levels of phospho-ERK (p-ERK) and total-ERK proteins detected by western blot (WB)
in THP-1 and MOLM-13 cells ectopically expressing APOC2 compared with empty vector
control cells. GAPDH was used as an internal control (quantification of three independent
repeats). b) The levels of p-ERK and total-ERK proteins detected by WB in THP-1 and
MOLM-13 APOC2 knockdown and scramble control cells. GAPDH was used as an internal
control (quantification of three independent repeats). c) The levels of p-ERK and total-ERK
proteins detected by WB in HL60 APOC2 knockdown and scramble control cells. The right
panel reports the p-ERK/total-ERK ratio in the control and knockdown APOC2 cells
(quantification of four independent repeats).
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
(a)
(b)
(c)
Figure 4.13 The level changes of CD36 downstream target ERK.
119
4.3.13 CD36 depletion causes decreased level of p-ERK
A significant decrease in p-ERK protein levels also was observed when CD36 was depleted by
two different CD36 shRNAs (Figure 4.14 a, THP-1: p-ERK/total-ERK ratio change, shCD36-1,
66.27% decrease, p = 0.0001; shCD36-2, 87.32% decrease, p < 0.0001; MOLM13: p-ERK/total-
ERK ratio change, shCD36-1, 32.56% decrease, p = 0.0007; shCD36-2, 46.90% decrease, p =
0.001). Consistently, treatment with the CD36 blocking antibody caused a decrease in p-ERK in
OE Ctrl compared with IgG treatment (p-ERK/total-ERK ratio change 22.58%, p=0.036) and
abrogated the enhanced level of p-ERK in OE APOC2 cells (Figure 4.14 b).

120

a) The levels of p-ERK and total-ERK proteins detected by WB in THP-1 and MOLM-13
CD36 knockdown and scramble control cells. GAPDH was used as an internal control
(quantification of three independent repeats). b) The levels of p-ERK and total-ERK
proteins detected by WB in MOLM-13 OE Ctrl and OE APOC2 cells treated with IgG or
CD36Ab. GAPDH was used as an internal control (quantification of two independent
repeats). The differences between the groups were analyzed using unpaired t-tests and
one-way ANOVA (**** p < 0.0001, * p < 0.05).
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
(a)
(b)
Figure 4.14 Depletion of CD36 decreased the level of p-ERK.
121

4.3.14 Simultaneous expression of APOC2 and CD36 triggers greater increase of
ERK phosphorylation and activation of LYN

Furthermore, the simultaneous overexpression of APOC2 and CD36 triggered greater increase
of ERK phosphorylation in both THP-1 and MOLM-13 cells (Figure 4.15 a, MOLM13: p-ERK/total-
ERK ratio change, OE APOC2, 1.5-fold increase; OE CD36, 1.6-fold increase; OE both, 3.0-fold
increase, p=0.0032; THP-1, p-ERK/total-ERK ratio change, OE APOC2, 2.0-fold increase; OE
CD36, 2.5-fold increase; OE both, 3.7-fold increase, p=0.0485). Overexpression of APOC2, CD36,
or both activates the CD36 downstream target LYN by increasing the p-LYN level (Figure
4.1517957188 b, MOLM13: p-LYN/total-LYN ratio change, OE APOC2, 1.5-fold increase; OE
CD36, 1.4-fold increase; OE both, 1.7-fold increase, p = 0.0032; THP-1, p-LYN/total-LYN ratio
change, OE APOC2, 1.6-fold increase; OE CD36, 1.8-fold increase; OE both, 2.0-fold increase,
p=0.0197).

122

a） The levels of p-ERK and total-ERK proteins detected by WB in THP-1 and MOLM-13
OE Ctrl, OE APOC2, OE CD36 and OE APOC2+CD36 cells. Actin was used as an internal
control (quantification of two independent repeats). b) The levels of p-LYN and total-LYN
proteins detected by WB in MOLM-13 and THP-1 OE Ctrl, OE APOC2, OE CD36 and OE
APOC2+CD36 cells. GAPDH was used as an internal control (quantification of two
independent repeats).

OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
(a)
(b)
Figure 4.15 Simultaneous expression of APOC2 and CD36 causes greater increase
in p-ERK and activates LYN.
123
4.3.15 Depletion of APOC2 or CD36 abolished activation of ERK induced by OE
CD36 or OE APOC2
Knockdown of APOC2 or CD36 abolished activation of ERK induced by OE CD36 or OE APOC2
respectively and even caused more reduce in p-ERK level compared with control (Figure 4.16 a-
b, p-ERK/total-ERK ratio change, shCtrl/OE CD36, 2.6-fold increase; shAPOC2/OE Ctrl, 49.38%
decrease; shAPOC2/OE CD36, 66.22% decrease, p = 0.0061; shCtrl/OE APOC2,1.5-fold
increase, shCD36/OE Ctrl, 45.63% decrease; shCD36/OE APOC2, 43.29% decrease, p =
0.0052 ).

124

OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic
Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
(a)
(b)
a-b) The levels of p-ERK and total total-ERK proteins detected by WB in CD36 OE
MOLM-13 cells transduced with shAPOC2 tet-on viral particles and in APOC2 OE cells
transduced with shCD36 tet-on viral particles (quantification of two independent repeats)

Figure 4.16 Depletion of APOC2 or CD36 abolished activation of ERK induced by
OE CD36 or OE APOC2.
125

4.3.16 APOC2 and CD36 overexpression affect the bioenergetic profile of AML cells
Given the roles of APOC2 and CD36 in lipid metabolism and transport, we speculated that
modulating their expression in AML cells would impact cells bioenergetic profile. Live-cell
metabolic measurements were performed by Seahorse XF showed that OE APOC2 or OE CD36
THP-1 and MOLM-13 cells exhibit higher energetic metabolic phenotype compared with OE Ctrl
cells (Figure 4.17 a). An increase in mitochondrial respiration rates assessed by the oxygen
consumption rates (OCR) was observed in OE APOC2 and OE CD36 at their basal conditions
(Figure 4.17 b-c). Similarly, extracellular acidification rates (ECAR) were also increased in OE
APOC2 and OE CD36 cells compared with OE Ctrl cells (Figure 4.17 c) under stressed conditions.

126

a) Cell energy phenotype of PLVX-Ctrl, PLVX-APOC2 and PCDH- Ctrl and PCDH-
CD36 in THP-1 and cells. Baseline Phenotype is indicated by an open marker.
Stressed Phenotype is indicated by a filled marker.

OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK

Supplementary Figure 7
Figure S7: A) Cell energy phenotype of PLVX- Ctrl vs OE APOC2 and PCDH-Ctrl vs OE CD36 MOLM-
13 cells. Baseline Phenotype is indicated by an open marker. Stressed Phenotype is indicated by a
filled marker. B-C) OCR, respiration (bar plot), ECAR and glycolysis (bar plot) of OE Ctrl, OE APOC2
and OE CD36 MOLM-13 determined by Seahorse XF cell analysis.

THP-1
MOLM-13 (a)
Figure 4.17 APOC2 and CD36 overexpression affect the bioenergetic profile
of AML cells
127

b-c) OCR, respiration of PLVX-Ctrl, PLVX-APOC2 and PCDH- Ctrl and PCDH- CD36 THP-
1 and MOLM-13 cells determined by Seahorse XF cell analysis. The differences between
the groups were analyzed using unpaired t-tests and one-way ANOVA (**** p < 0.0001, * p
< 0.05).
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1 MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic
Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK

Supplementary Figure 7
Figure S7: A) Cell energy phenotype of PLVX- Ctrl vs OE APOC2 and PCDH-Ctrl vs OE CD36 MOLM-
13 cells. Baseline Phenotype is indicated by an open marker. Stressed Phenotype is indicated by a
filled marker. B-C) OCR, respiration (bar plot), ECAR and glycolysis (bar plot) of OE Ctrl, OE APOC2
and OE CD36 MOLM-13 determined by Seahorse XF cell analysis.

Supplementary Figure 7
Figure S7: A) Cell energy phenotype of PLVX- Ctrl vs OE APOC2 and PCDH-Ctrl vs OE CD36 MOLM-
13 cells. Baseline Phenotype is indicated by an open marker. Stressed Phenotype is indicated by a
filled marker. B-C) OCR, respiration (bar plot), ECAR and glycolysis (bar plot) of OE Ctrl, OE APOC2
and OE CD36 MOLM-13 determined by Seahorse XF cell analysis.

(b)
(c)
128

OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic
Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13
THP-1
p-LYN
Total-LYN
GAPDH
OE CTRL
OE APOC2
OE CTRL
OE APOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
THP-1 MOLM-13
*
***
Figure 5
OE CTRL
OE APOC2
OE CTRL
OE APOC2
GAPDH
APOC2
p-ERK
ERK
THP-1 MOLM-13
MOLM-13
shCtrl
shCD36-1
shCD36-2
GAPDH
p-ERK
ERK
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
HL60
**
**
GAPDH
p-ERK
ERK
OE CTRL
OE APOC2
OE CTRL
OE APOC2
MOLM-13
IgG
MOLM-13
CD36Ab
THP-1
shCtrl
shCD36-1
shCD36-2
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
OE Ctrl
OE APOC2
OE CD36
OE APOC2
+CD36
MOLM-13 THP-1
p-ERK
ERK
Actin
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0
2
4
6
p-ERK/total-ERK ratio
OE Ctrl
OE APOC2
OE CD36
OE APOC2+CD36
MOLM-13 THP-1
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
shCtrl
shAPOC2-1
shAPOC2-2
MOLM-13
shCtrl
shAPOC2-1
shAPOC2-2
GAPDH
p-ERK
ERK
THP-1
shCtrl
shAPOC2-1
shAPOC2-2
p-ERK
ERK
HL60
GAPDH
shCtrl
shAPOC2-1
shAPOC2-2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
****
***
shCtrl
shAPOC2-1
shAPOC2-2
THP-1 MOLM-13
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
****
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
***
**
THP-1
MOLM-13
shCtrl
shCD36-1
shCD36-2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0.0 10.0 20.0 30.0
Aerobic Energetic
Glycolytic
Quiescent
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
5
10
15
20
25
30
35
40
45
50
55
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
0 10 20 30 40 50 60
0
10
20
30
40
50
60
70
80
90
THP-1 OCR
Time (minutes)
OCR (pmol/min/Norm. Unit)
THP-1 PCDH-Ctrl
THP-1 PCDH-CD36
0 10 20 30 40 50 60
0
10
20
30
THP-1 ECAR
Time (minutes)
ECAR (mpH/min/Norm. Unit)
THP-1 PLVX-Ctrl
THP-1 PLVX-APOC2
PLVX-Ctrl
PLVX-APOC2
0.0
20.0
40.0
60.0
80.0
100.0
0.0 10.0 20.0 30.0 40.0
Aerobic
Energetic
Glycolytic Quiescent
PCDH-Ctrl
PCDH-
CD36
Mitochondrial Respiration
OCR (pmol/min)
ECAR (mpH/min) Glycolysis
0
10
20
30
40
50
OCR (pmol/min/Norm. Unit)
THP-1
OCR
** **
Baseline
Stressed
PCDH-Ctrl
PCDH-CD36
0
20
40
60
80
100
OCR (pmol/min/Norm. Unit)
THP-1
OCR
***
**
Baseline
Stressed
0
10
20
30
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
****
****
Baseline
Stressed
0
10
20
30
40
ECAR (pmol/min/Norm. Unit)
THP-1
ECAR
***
***
Baseline
Stressed
0
10
20
30
40
OCR (pmol/min/Norm. Unit)
MOLM-13
OCR
PLVX-Ctrl
PLVX-APOC
Baseline
Stressed
*
*
OE CTRL
OE APOC2
OE CD36
OE A/C
OE CTRL
OE APOC2
OE CD36
OE A/C
0.0
0.5
1.0
1.5
2.0
2.5
p-lyn/total-lyn ratio
WB Intensity
MOLM-13
THP-1
OE Ctrl
OE APOC2
OE Ctrl
OE APOC2
0.0
0.5
1.0
1.5
p-ERK/total-ERK ratio
MOLM-13
IgG α-CD36
ns
*
**
p-ERK
ERK
MOLM-13
shCtrl
OE Ctrl
OE CD36
shAPOC2
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
shCtrl/OE Ctrl
shCtrl/OECD36
shAPOC2/OECtrl
shAPOC2/OECD36
0
1
2
3
p-ERK/total-ERK ratio
MOLM-13
shCtrl/OECtrl
shCtrl/OEAPOC2
shCD36/OECtrl
shCD36/OEAPOC2
0.0
0.5
1.0
1.5
2.0
p-ERK/total-ERK ratio
MOLM-13
MOLM-13
shCtrl
OE Ctrl
OE APOC2
shCD36
+
+
-
+
+
-
-
-
+
+
-
-
+
+
-
-
p-ERK
ERK

Supplementary Figure 7
Figure S7: A) Cell energy phenotype of PLVX- Ctrl vs OE APOC2 and PCDH-Ctrl vs OE CD36 MOLM-
13 cells. Baseline Phenotype is indicated by an open marker. Stressed Phenotype is indicated by a
filled marker. B-C) OCR, respiration (bar plot), ECAR and glycolysis (bar plot) of OE Ctrl, OE APOC2
and OE CD36 MOLM-13 determined by Seahorse XF cell analysis.

Supplementary Figure 7
Figure S7: A) Cell energy phenotype of PLVX- Ctrl vs OE APOC2 and PCDH-Ctrl vs OE CD36 MOLM-
13 cells. Baseline Phenotype is indicated by an open marker. Stressed Phenotype is indicated by a
filled marker. B-C) OCR, respiration (bar plot), ECAR and glycolysis (bar plot) of OE Ctrl, OE APOC2
and OE CD36 MOLM-13 determined by Seahorse XF cell analysis.

(d)
(e)
d-e) OCR, respiration of PLVX-Ctrl, PLVX-APOC2 and PCDH- Ctrl and PCDH- CD36 THP-
1 and MOLM-13 cells determined by Seahorse XF cell analysis. The differences between
the groups were analyzed using unpaired t-tests and one-way ANOVA (**** p < 0.0001, * p
< 0.05).
129
4.3.17 Conditional knockdown of APOC2 and CD36 decrease leukemia burden in
murine leukemia models
We also validated the effect of targeting APOC2 and CD36 in the MOLM-13 engrafted murine
model, in which MOLM-13 cells stably expressing tet-on-inducible APOC2 shRNA, CD36 shRNA,
or scramble sequences were intravenously injected into NSG mice to generate human AML
xenografts (n = 4 per group) and treated with doxycycline grain based rodent diet continuously.
Mice were sacrificed on day 25. Mice from the shAPOC2 and shCD36 groups exhibited
significantly less leukemia engraftment in the bone marrow, peripheral blood, and spleen
compared with the shCtrl group (Figure 4.18 a, % bone marrow engraftment means, 60.8 vs. 8.9
vs. 23.5 for shCtrl vs. shAPOC2 vs. shCD36, p < 0.0001 and p = 0.0368; % peripheral blood
engraftment means, 11.2 vs. 3.9 vs. 1.2, p = 0.0073 and p = 0.0003; % spleen engraftment means,
14.4 vs. 5.4 vs. 3.8, p = 0.0044 and p = 0.0021), indicating that the knockdowns of APOC2 and
CD36 reduced the leukemia burden in vivo (Figure 4.18 b-d).

130

a) Representative FACS showing hCD45-positive engraftment in the bone marrow,
peripheral blood, and spleen of MOLM-13 shCtrl, MOLM-13 shAPOC2, and MOLM-13
shCD36 luciferase cells of NGS mice. Quantification of engraftment of MOLM-13 cells in
the bone marrow, peripheral blood and spleen. The differences between the groups were
analyzed using unpaired t-tests (**** p < 0.0001; *** p < 0.001; ** p < 0.01; * p < 0.05).

shCtrl shAPOC2
-50
0
50
100
150
Engraftment (%)
Peripheral Blood
***
shCtrl shAPOC2
hCD45
Forward Side Scatter
shCtrl shAPOC2 Blank
(A)
(B)
Bone Marrow
Peripheral
Blood
Spleen
shCtrl shAPOC2 shCD36
0
20
40
60
80
Bone Marrow
Engraftment (%)
****
*
shCtrl shAPOC2 shCD36
0
5
10
15
20
Peripheral Blood
Engraftment (%)
**
***
shCtrl shAPOC2 shCD36
0
5
10
15
20
Engraftment (%)
Spleen
**
**
hCD45
SSC
shCtrl shCD36 shAPOC2
Figure 6
(a)
Figure 4.18 Conditional knockdown of APOC2 and CD36 decrease leukemia burden
131

shCtrl
shAPOC2
shCD36
Supplementary Figure 10
MOLM-13 engraftment- Bone Marrow
hCD45
SSC
Figure S10: FACS blots showing hCD45 positive population in bone marrow of MOLM-13 shCtrl,
shAPOC2, and shCD36 cells.

(b)
132

shCtrl
shAPOC2 shCD36
MOLM-13 engraftment- Peripheral Blood
hCD45
SSC
Supplementary Figure 11
Figure S11: FACS blots showing hCD45 positive population in peripheral blood of MOLM-13
shCtrl, shAPOC2, and shCD36 cells.

(c)
133

shCtrl shAPOC2 shCD36
Supplementary Figure 12
MOLM-13 engraftment- Spleen
hCD45
SSC
Figure S12: FACS blots showing hCD45 positive population in peripheral blood of MOLM-13
shCtrl, shAPOC2, and shCD36 cells.

(d)
134
There was no significant difference in the weights of the livers and spleens between the groups
engrafted with tet-on shAPOC2, shCD36 and scramble MOLM13 cells (Figure 4.19 a-d).

Blank
shCtrl
shAPOC2
shCD36
0.00
0.05
0.10
0.15
Spleen
Weight (g)
ns
ns
Blank
shCtrl
shAPOC2
shCD36
0.0
0.5
1.0
1.5
2.0
2.5
Weight (g)
Liver
ns ns
Blank shCtrl shAPOC2 shCD36 Group A Group B
0
500
1000
1500
2000
Liver
mg
Figure S13. A-B) Weights of spleens and livers collected from mice engrafted with MOLM-13
shCtrl, MOLM-13 shAPOC2, and MOLM-13 shCD36 luciferase cells. C) Spleens collected from
mice engrafted with MOLM-13 shCtrl, MOLM-13 shAPOC2, and MOLM-13 shCD36 luciferase
cells. D) Weights and sizes of livers collected from mice engrafted with MOLM-13 and treated
with IgG and CD36 antibody.
Supplementary Figure 13
(a)
(b) (c)
(d)
a-b) Weights of spleens and livers collected from mice engrafted with MOLM-13 shCtrl,
MOLM-13 shAPOC2, and MOLM-13 shCD36 luciferase cells. c) Spleens collected from mice
engrafted with MOLM-13 shCtrl, MOLM-13 shAPOC2, and MOLM-13 shCD36 luciferase
cells. d) Weights and sizes of livers collected from mice engrafted with MOLM-13 and treated
with IgG and CD36 antibody.

Figure 4.19 Other effects of APOC2 or CD36 knockdown in NSG mice.
135
4.3.18 Anti-CD36 antibody treatment reduces leukemia progression and increases
overall survival of AML murine model.
APOC2 cooperates with CD36 to activate ERK signaling pathway leading to enhanced leukemia
growth. In order to test the role of CD36 in vivo and verify the potential of targeting APOC2-CD36
signal pathway for AML treatment, CD36 blocking antibody was used to treat MOLM-13 engrafted
NSG mice. Seven days after injection of MOLM-13 cells into NSG mice, mice were treated with
CD36 blocking antibody or IgG control every other two days for five doses (n=4 per group). Mice
were sacrificed on day 21. CD36 antibody treatment group had less leukemia burden in bone
marrow, peripheral blood and spleen (Figure 4.20 a, % peripheral blood engraftment means,
20.27 vs. 8.98 for IgG vs. CD36 antibody, p=0.373; % bone marrow engraftment means, 53.08
vs. 40.70 for IgG vs. CD36 antibody, p=0.0011; % spleen engraftment means, 12.05 vs. 2.70 for
IgG vs. CD36 antibody, p<0.0001 ). The spleens in CD36 antibody treatment group were smaller
and weighed less than the ones in IgG group (Figure 4.20 b, spleen weight means, 161.5 mg vs.
69.15 mg, p<0.0001).

136

a) NSG mice were engrafted with MOLM-13 cells for seven days and then treated with CD36
antibody or IgG control. Representative flow cytometry results showing the engraftment of
bone marrow, peripheral blood and spleen, quantification of engraftment in bone marrow,
peripheral blood and spleen. b) Spleens collected from mice engrafted with MOLM-13 and
treated with IgG and CD36 antibody. Comparison of spleen weight between IgG group and
CD36 antibody group.

Figure 7
IgG Ctrl
α-CD36
Blank
hCD45
IgG Ctrl
SSC
Peripheral Blood Bone Marrow Spleen
IgG Ctrl
α-CD36
Spleen
Liver
IgG Ctrl
α-CD36
IgG CD36Ab
0
10
20
30
40
Peripheral Blood Engraftment
Engraftment (%)
*
IgG CD36Ab
0
20
40
60
Bone Marrow Engraftment
Engraftment (%)
**
IgG CD36Ab
0
5
10
15
Spleen Engraftment
Engraftment (%)
****
IgG
CD36Ab
0
5
10
15
20
25
Relative Ki67+ Staining Area
Spleen
****
IgG
CD36Ab
0
2
4
6
8
Relative Ki67+ Staining Area
Liver
****
IgG
CD36Ab
0
5
10
15
20
25
Relative CD45+ Staining Area
Spleen
****
IgG
CD36Ab
0
5
10
15
20
Relative CD45+ Staining Area
Liver
****
Ki67 CD45
IgG CD36Ab
0
50
100
150
200
Spleen
mg
****
0 20 40 60
0
50
100
Days elapsed
Percent survival
Survival
IgG Ctrl
CD36Ab
*
p=0.0202
α-CD36
Figure 7
IgG Ctrl
α-CD36
Blank
hCD45
IgG Ctrl
SSC
Peripheral Blood Bone Marrow Spleen
IgG Ctrl
α-CD36
Spleen
Liver
IgG Ctrl
α-CD36
IgG CD36Ab
0
10
20
30
40
Peripheral Blood Engraftment
Engraftment (%)
*
IgG CD36Ab
0
20
40
60
Bone Marrow Engraftment
Engraftment (%)
**
IgG CD36Ab
0
5
10
15
Spleen Engraftment
Engraftment (%)
****
IgG
CD36Ab
0
5
10
15
20
25
Relative Ki67+ Staining Area
Spleen
****
IgG
CD36Ab
0
2
4
6
8
Relative Ki67+ Staining Area
Liver
****
IgG
CD36Ab
0
5
10
15
20
25
Relative CD45+ Staining Area
Spleen
****
IgG
CD36Ab
0
5
10
15
20
Relative CD45+ Staining Area
Liver
****
Ki67 CD45
IgG CD36Ab
0
50
100
150
200
Spleen
mg
****
0 20 40 60
0
50
100
Days elapsed
Percent survival
Survival
IgG Ctrl
CD36Ab
*
p=0.0202
α-CD36
(a)
(b)
Figure 4.20 Anti-CD36 antibody effects on NSG leukemia models.
137
Additionally, to determine whether blocking CD36 potentially delays leukemia progression,
engrafted NSG mice were treated with IgG and CD36 blocking antibody the same as above for
survival analysis (n=7 per group). With CD36 antibody treatment, mice engrafted with MOLM-13
cells survived significantly longer than IgG group (Figure 4.21 a, p= 0.0202). Consistently, Ki67
staining and CD45 staining of spleens and livers presented a lower percentage of infiltrated blasts
compared with tissues obtained from the IgG treated group (Figure 4.21 b-c, spleen Ki67 staining,
4.35-fold, p<0.0001; liver Ki67 staining, 3.67-fold, p<0.0001; spleen CD45 staining, 4.38-fold,
p<0.0001; liver CD45 staining, 7.64-fold, p<0.0001).
138

a) Survival data from mice engrafted with MOLM-13 and treated with IgG and CD36 antibody.
b) Histology staining of Ki67 antibody on spleen, liver, sternum sections from mice engrafted
with MOLM-13 and treated with IgG and CD36 antibody. Quantification analysis and
representative staining of tissue sections obtained from the different organs. c) Histology
staining of CD45 antibody on spleen, liver sections from mice engrafted with MOLM-13 and
treated with IgG and CD36 antibody. Quantification analysis and representative staining of
tissue sections obtained from the different organs. The differences between the groups were
analyzed using unpaired t-tests (**** p < 0.0001; *** p < 0.001; ** p < 0.01; * p < 0.05).

Figure 7
IgG Ctrl
α-CD36
Blank
hCD45
IgG Ctrl
SSC
Peripheral Blood Bone Marrow Spleen
IgG Ctrl
α-CD36
Spleen
Liver
IgG Ctrl
α-CD36
IgG CD36Ab
0
10
20
30
40
Peripheral Blood Engraftment
Engraftment (%)
*
IgG CD36Ab
0
20
40
60
Bone Marrow Engraftment
Engraftment (%)
**
IgG CD36Ab
0
5
10
15
Spleen Engraftment
Engraftment (%)
****
IgG
CD36Ab
0
5
10
15
20
25
Relative Ki67+ Staining Area
Spleen
****
IgG
CD36Ab
0
2
4
6
8
Relative Ki67+ Staining Area
Liver
****
IgG
CD36Ab
0
5
10
15
20
25
Relative CD45+ Staining Area
Spleen
****
IgG
CD36Ab
0
5
10
15
20
Relative CD45+ Staining Area
Liver
****
Ki67 CD45
IgG CD36Ab
0
50
100
150
200
Spleen
mg
****
0 20 40 60
0
50
100
Days elapsed
Percent survival
Survival
IgG Ctrl
CD36Ab
*
p=0.0202
α-CD36
(a)
(b) (c)
Figure 4.21 Anti-CD36 antibody delays the prograssion of leukemia in mice model.
139
Discussion
In this chapter, I identified APOC2 cooperates with CD36 through physical interaction to promote
leukemia growth. Interestingly, targeting CD36 function by blocking antibody but not SSO induces
apoptosis and abrogates APOC2 pro-leukemic effects. Then I found APOC2-CD36 activates the
CD36 downstream ERK signaling pathway and enhances metabolic activity of leukemic cells. In
mice models, conditional knockdown of APOC2 and CD36 decrease leukemia burden in murine
leukemia models. Anti-CD36 antibody treatment reduces leukemia progression and increases
overall survival of AML murine model.
APOC2 overexpression activates the CD36-ERK pathways, which mechanistically explain the
observed phenotype[129]. While little is known about the role of APOC2 in cancer, the role of its
partner CD36 is more established. As a receptor, CD36 has been reported to recognize different
ligands, including phospholipids, lipoproteins, long-chain fatty acids, and amyloid fibrils[101]. In
response to ligands, CD36 recruits and activates its downstream non-receptor tyrosine kinases,
MAPK kinases. CD36 has been shown to confer chemotherapy resistance and metastasis
initiation potential in cancer cells[106]. In chronic myeloid leukemia (CML), the fatty acids
transporter CD36 is associated with leukemia stem cells that evade chemotherapy by residing in
the niche of adipose tissue[110, 111]. Furthermore, in chronic lymphoblastic leukemia (CLL) cells,
STAT3 was shown to activate CD36 by binding to its promoter, facilitating fatty-acid uptake[130].
In addition, AraC-resistant cells exhibit increased fatty-acid oxidation, upregulated CD36
expression, and high oxidative phosphorylation (OXPHOS); targeting mitochondrial metabolism
140
via the CD36-FAO-OXPHOS axis enhanced the anti-leukemic effects of AraC[110]. Our study
establishes the link between a novel target in AML, APOC2, and the fatty acids transporter, CD36,
and establishes ERK as a potential signaling pathway resulting from the interaction of APOC2
and CD36. Our study shows that targeting the APOC2-CD36-ERK pathway with either CD36
antibodies or SSO leads to anti-leukemia effects. The use of these treatments at high
concentrations and their short half-life limit their potential activity and suggests a need for more
effective drugs to modulate the APOC2-CD36 axis.

In summary, our clinical association analysis combined with preclinical functional and mechanistic
studies has uncovered a novel role of APOC2 upregulation in AML. APOC2 is upregulated in AML
and is associated with poor clinical outcomes. Furthermore, APOC2 promotes leukemia growth
via the CD36-ERK signaling pathway. Our study indicates that the APOC2-CD36 signaling axis
may be an actionable therapeutic target in AML.

141
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Abstract (if available)

Abstract Acute Myeloid Leukemia (AML) is a devastating hematologic malignancy that affects the hematopoietic stem cells. The 5-year overall survival (OS) of patients with AML is less than 30%, highlighting the urgent need to identify new therapeutic targets. We analyzed gene expression datasets for genes that are differentially overexpressed in AML cells compared with healthy hematopoietic cells. We found that APOC2 was consistently upregulated in AML across different datasets. Apolipoprotein C2 (APOC2), is a small secreted apolipoprotein, and a member of the apoCs that constitutes chylomicrons, very-low-density lipoproteins, and high-density lipoproteins. APOC2 activates lipoprotein lipase and contributes to lipid metabolism. Thus, the need to find new therapeutic targets is high. Here, we discovered that apolipoprotein C2 (APOC2) is upregulated in AML, particularly in patients with mixed-lineage leukemia (MLL) rearrangements. High APOC2 mRNA levels are associated with shorter OS (HR: 2.71

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Asset Metadata

Creator Zhang, Tian (author)

Core Title Role of apolipoprotein C2 in acute myeloid leukemia: clinical, functional and mechanistic study

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Medical Biology

Publication Date 08/01/2020

Defense Date 05/04/2020

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag AML,APOC2,apolipoproteins,CD36,leukemia,OAI-PMH Harvest

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Machida, Keigo (committee chair), Alachkar, Houda (committee member), Cadenas, Enrique (committee member)

Creator Email tianaiai@hotmail.com,tianaiai69@hotmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-356494

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Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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