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Clinical, functional and therapeutic analysis of CD99 in acute myeloid leukemia
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Clinical, functional and therapeutic analysis of CD99 in acute myeloid leukemia
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i
Clinical, Functional and Therapeutic Analysis of CD99 in Acute Myeloid Leukemia
by
Vijaya Pooja Vaikari
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
(Clinical and Experimental Therapeutics)
May 2020
Copyright 2020 Vijaya Pooja Vaikari
ii
Dedication
With immense gratitude, I dedicate my thesis
To Dr.K.J.R Murthy, for inspiring me to be a scientist
To my grandmother, you’re the strongest person I know
To my parents, Bindu and Vijay, for believing in me and always being there for me
To my sister, Kiran, for all the courage, inspiration and being my role model
To my in-laws, for all their support and positivity
To my dear friend Santosh Reddy, for never letting me quit
To my family in LA, Anupam, Navjot, Peddi and Nevil, you’ll made this journey memorable
To my husband, Sanmeet, for your love, for always being there and your unwavering faith in me,
it got me here
iii
Acknowledgments
First and most of all, I would like to thank my advisor, Dr.Houda Alachkar for teaching and
supporting me at every step of my PhD. I was fortunate to have an advisor who inspired
me to be better and motivated me through all the challenges. I extremely grateful to you.
I would like to thank my committee members, Dr. J. Andrew MacKay and Dr. Paul
Beringer for their time and advice regarding my research.
I am also very grateful to Dr. Mojtaba Akthari for providing us with all the clinical samples
and being a source of inspiration. Your kind words have always encouraged me.
I would like to acknowledge Dr. MacKay for his support and collaboration. I am very
grateful that I got to work on a project with his graduate student Mincheol Park. It was a
great learning experience and working with Mincheol has helped advance my project.
I was very fortunate to have lab mates who constantly supported me and helped me
throughout my PhD. Tian Zhang, thank you teaching my cloning and helping me with my
experiments. Sharon Wu for performing statistical analysis for my project. Lucas Gutierrez
and John Beckford for donating blood for my project and being so happy and motivating
me. You all have given me immense strength and I will forever be grateful to have friends
like you all. I would also like to acknowledge Yang Du for contributing to this project.
I am also thankful to my friends Anupam, Santosh, Navjot, Nevil and Sneha for their
support and for always being there.
Most importantly, I am grateful to my parents, my sister, my in laws and my dear husband
for constantly motivating me and bringing me till the finish line. Thank you.
iv
Table Of Contents
Dedication ii
Acknowledgments iii
List of Tables vi
List of Figures vii
Abstract ix
Chapter 1: Background 1
1.1 Acute Myeloid Leukemia 1
1.1.1 Definition 1
1.1.2 Incidence 1
1.1.3 Risk factors 3
1.1.4 Clinical Manifestations and Diagnosis 4
1.1.5 Classification 5
1.1.6 Risk Stratification and prognosis 11
1.1.7 Genomic landscape 13
1.1.8 Current therapy 16
1.1.9 Targeted therapy for AML 18
1.2. CD99 24
1.2.1 CD99 gene and expression 24
1.2.2 CD99 function in normal physiology 26
1.2.3. Role in cancer: Clinical significance 28
1.2.4. Role in cancer: Function and Mechanism 30
Chapter 2: Clinical characterization of CD99 in AML 33
2.1. Introduction 33
2.2 Experimental procedure 34
2.3 Results 36
2.3.1 CD99 is upregulated in patients with AML. 36
2.3.2 CD99 expression level according to patient’s clinical characteristics 39
2.3.3 CD99 association with AML mutations 44
2.3.4 CD99 overexpression is associated with better clinical outcome 47
2.3.5 Characterization and association of CD99 transcripts in AML clinical setting 52
2.4. Discussion 58
v
Chapter 3 : Functional and Mechanistic Characterization of CD99 in
AML 61
3.1 Introduction 61
3.2 Experimental procedures 62
3.3 Results 70
3.3.1 Characterization of CD99 expression in vitro 70
3.3.2 Effect of CD99 knockdown in vitro 73
3.3.3 Effect of CD99 overexpression in vitro 75
3.3.4 Ectopic expression of CD99-L enhances ROS levels, DNA damage and induces cell apoptosis 81
3.3.5 Ectopic expression of CD99-L isoform induces myeloid differentiation and reduces cell migration 84
3.3.6 Overexpression of CD99-L isoform delayed leukemia engraftment in THP-1 murine model 87
3.3.7 Overexpression of CD99-L isoform delayed leukemia engraftment in MOLM-13 murine model 89
3.3.8 Overexpression of CD99 L isoform delayed leukemia engraftment in primary leukemia model. 92
3.3.9 CD99 monoclonal antibody induces anti-leukemic effect 94
3.3.10 CD99 modulates ERK and SRC signaling pathways in AML cells 98
3.4 Discussion 101
Chapter 4 : Development of a therapeutic CD99 scFv nanoworm 105
4.1 Introduction 105
4.2 Experimental procedures 107
4.3 Results 111
4.3.1 a-CD99-A192 binds specifically to CD99 surface protein in vitro 111
4.3.2 Cytotoxic activity of a-CD99-A192 in AML cells 113
4.3.3 a-CD99-A192 induces apoptosis in AML cells 115
4.3.4 Antileukemic activity of a-CD99-A192 in primary AML cells 117
4.3.6 Antileukemia activity of a-CD99-A192 in AML xenograft model 119
4.4. Discussion 121
Chapter 5 : Concluding Remarks 124
References: 129
vi
List of Tables
Table 1.1 WHO classification of AML 7
Table 1.2 The association of the genetic abnormality with prognosis 16
Table 1.3 Patient outcome with new therapeutics 22
Table 2.1 CD99 association with clinical characteristics 40
Table 2.2 CD99 association with clinical characteristics 42
Table 2.3 Fischer exact analysis for association of CD99 expression with 46
Table 2.4 Multivariable analysis of high CD99 expression 51
Table 2.5 CD99 transcript Ensembl IDs and their description 53
Table 3.1 Primer match list for CD99 primer set 1 and set 2 for all CD99 transcripts 71
Table 3.2 Patients details 78
vii
List of Figures
Figure 1-1: Incidence of AML in US (Shallis et al., 2019). ..................................................... 1
Figure 1-2: UK incidence of AML by sex and age (Khwaja et al., 2016) ............................. 3
Figure 1-3 FAB classification of AML (modified from (Bennett et al., 1976)). .................... 6
Figure 1-4: Stratification according to the ELN recommendations ..................................... 12
Figure 1-5: Functional category of genes commonly mutated in AML .............................. 14
Figure 1-6: Recently approved drugs for AML (Winer and Stone, 2019) .......................... 19
Figure 1-7:Treatment of AML with new therapeutics (DiNardo and Wei, 2020) .............. 22
Figure 1-8:Structural characterization of CD99 gene and isoforms (Pasello et al., 2018)
....................................................................................................................................................... 25
Figure 1-9: Effect of knocking down CD99 in Ewing sarcoma (Manara et al., 2018). .... 31
Figure 1-10: Effect of knocking down CD99 in Ewing sarcoma .......................................... 32
Figure 2-1:CD99 is overexpressed in AML ............................................................................ 37
Figure 2-2: CD99 expression in CD34+ subpopulation ....................................................... 38
Figure 2-3: CD99 is overexpressed in AML ........................................................................... 43
Figure 2-4:CD99 association with mutation status ............................................................... 45
Figure 2-5:CD99 association with patient survival in the TCGA data set ......................... 48
Figure 2-6:CD99 association with patient survival in the GSE425 and GSE12417 data
set ................................................................................................................................................. 50
Figure 2-7: Characterization of CD99 transcript expression in AML .................................. 54
Figure 2-8: Association of CD99 transcripts with clinical characteristics .......................... 57
Figure 3-1: CD99 isoform expression in AML blasts and cell lines in vitro. ...................... 72
Figure 3-2: Effect of CD99 knockdown on cell viability ........................................................ 74
viii
Figure 3-3: Effect of CD99-L and S overexpression on viability of AML cells .................. 76
Figure 3-4: Effect of CD99-L and S overexpression on viability of AML cells ................. 79
Figure 3-5: Long term culture assay for THP-1 cells ............................................................ 80
Figure 3-6: Ectopic expression of CD99 long isoform enhances ROS levels, DNA
damage and induces cell apoptosis ........................................................................................ 83
Figure 3-7: Ectopic expression of CD99-L isoform induces myeloid differentiation and
reduces cell migration ................................................................................................................ 86
Figure 3-8: Overexpression of CD99-L isoform delayed leukemia engraftment in THP-1
murine model .............................................................................................................................. 88
Figure 3-9: Overexpression of CD99-L isoform delayed leukemia engraftment in MOLM-
13 murine model ......................................................................................................................... 91
Figure 3-10: Overexpression of CD99-L isoform delayed leukemia engraftment in
primary leukemia model. ........................................................................................................... 93
Figure 3-11: CD99 monoclonal antibody induces differentiation and reduces cell
migration and colony formation in AML cells ......................................................................... 97
Figure 3-12: Effect of CD99 on ERK and SRC signaling pathways in AML cells. ......... 100
Figure 4-1: a-CD99-A192 binds specifically to surface CD99 .......................................... 112
Figure 4-2: Cytotoxic effect of a-CD99-A192. ..................................................................... 114
Figure 4-3: a-CD99-A192 induces cell apoptosis ............................................................... 116
Figure 4-4: Anti-leukemic effect of a-CD99-A192 in primary cells ................................... 118
Figure 4-5: Antileukemia activity of a-CD99-A192 in AML xenograft model .................. 120
ix
Abstract
Acute Myeloid Leukemia (AML) is a heterogeneous, hematological malignancy of the
hematopoietic stem cells that results from a block in the differentiation with uncontrolled
proliferation of leukemic blasts. The outcome of patients with AML remains dismal due to
the high relapse rate(Lowenberg, 2008). In order to address this need, we analyzed
various Oncomine data sets for gene expression data of normal hematopoietic vs AML
cells and found CD99 to be significantly upregulated in AML. CD99 (E2, MIC2) is a human
32-kD transmembrane sialo-glycoprotein expressed on many hematopoietic and non-
hematopoietic cells. In hematopoietic stem cells, CD99 is differentially expressed based
on distinct maturation stages: initially, CD99 expression is high in multipotent CD34
+
cells
in the bone marrow but the expression declines as these cells differentiate into mature
blood cells. CD99 is highly expressed in Ewing's Sarcoma (EWS) and gliomas and is
associated with poor prognosis. Contrary to these studies, in non-small cell lung
carcinoma and osteosarcoma, higher CD99 expression was associated with better
prognosis and acts as an onco-suppressor.
We analyzed CD99 expression across various AML datasets and found that CD99 was
significantly higher in patients with AML compared with healthy donor samples.
Additionally, high CD99 was associated with better outcome in cytogenetically abnormal
AML. In a panel of AML cell lines, CD99 surface levels were higher than that of healthy
cord blood cells. CD99 gene encodes two isoforms with distinct expression and functional
profiles in both normal and malignant tissues. We analyzed CD99 RNAseq data of AML
patients for protein coding transcripts and found that the those encoding for the long and
short isoform are the main transcripts expressed in AML. Based on this we used lentivirus
x
mediated overexpression of CD99 long and short isoforms to determine its functional
relevance in AML. We found that CD99 long isoform (CD99-L) initially induces an
increase in cell proliferation as well as it induces higher levels of reactive oxygen species
(ROS), DNA damage, apoptosis and subsequent decrease in cell viability compared with
AML cells transduced with empty vector or CD99-S isoform. In several leukemia murine
models including mice engrafted with primary blasts, the CD99-L overexpression
significantly delayed disease progression and resulted in lower leukemia engraftment in
the bone marrow and peripheral blood compared with mice engrafted with leukemic cells
overexpressing empty vector or CD99-S isoform. Mechanistically, CD99-L resulted in
transient induction followed by a dramatic decrease of both ERK and SRC
phosphorylation.
Furthermore, commercially available CD99 monoclonal antibody reduced cell viability,
colony formation, cell migration as well as induced cell differentiation and apoptosis in
leukemia cell lines and primary blasts. Based on this we then developed and evaluated
the efficacy of α-CD99-A192 nanoworms as a therapy for AML. In vitro analyses showed
promising anti-leukemic activity of α-CD99-A192 by reducing cell proliferation and
inducing cell apoptosis. Furthermore, α-CD99-A192 had an excellent in vivo efficacy and
significantly increased survival of mice in MOLM-13 xenograft model.
Overall, this study established the clinical role of CD99, the functional and mechanistic
role of CD99 through in vitro and in vivo analyses and developed and validated a
therapeutic approach to target CD99 for AML.
1
Chapter 1: Background
1.1 Acute Myeloid Leukemia
1.1.1 Definition
Acute Myeloid Leukemia (AML) is a heterogeneous, hematological malignancy of the
hematopoietic stem cells that results from a block in the differentiation and uncontrolled
proliferation of leukemic blasts(Kouchkovsky and Abdul-Hay, 2016). It is the most
aggressive and common acute leukemia in adults(Yamamoto and Goodman, 2008). In
AML, there is an increased burden of immature myeloid cells that accumulate in the bone
marrow and blood and prevent the normal functioning of the hematopoietic system.
1.1.2 Incidence
In this United States, the incidence of AML is higher than other leukemias (Figure 1-
1)(Shallis et al., 2019).
Figure 1-1: Incidence of AML in US (Shallis et al., 2019).
2
According to Surveillance, Epidemiology, and End Results (SEER), in 2016 the age-
adjusted incidence of AML is 4.3 per 100,000 person-years (N. Howlader, 2020). In AML
(excluding acute promyelocytic leukemia), the age-specific occurrence rises steadily from
around 40 to 50 years of age and more suddenly from around 60 to 64 years of age, with
a median age of diagnosis of 70 years (Bennett et al., 1976; Juliusson et al., 2009). The
annual age-standardized incidence rate of AML among individuals >18 years of age
ranges from 30 to 40 per million(2015; Derolf et al., 2009). AML is characterized by a
slight male predominance with the male to female ratio normally ranging from 1.1 to 1.3,
rising to around 1.8 at 80–84 years of age(Dores et al., 2012)(Figure 1-2).
AML incidence is also skewed based on ethnicity(@NCICancerStats, 2020). Caucasians
have the highest incidence rate and Pacific Islanders/Alaskan natives have the lowest
incidence rates (Deschler and Lubbert, 2006). There is also lower age-standardized
occurrence of AML in Asia than in western countries(Juliusson et al., 2012). The
incidence of AML is almost half in Japan and China than in US and Europe(Matsuo and
Ito, 2009; Wang et al., 2012).
3
Figure 1-2: UK incidence of AML by sex and age (Khwaja et al., 2016)
1.1.3 Risk factors
In majority of the cases, AML appears as a de novo malignancy in otherwise healthy
people. The risk for AML significantly increases with the exposure to DNA damaging
agents, chemotherapy, radiation therapy or immunosuppressive therapy given for a pre-
existing condition. This results in development of AML called Therapy related AML (t-
AML) (Offman et al., 2004; Sill et al., 2011; Smith et al., 2003). Alkylating agents and
topoisomerase inhibitors are also linked to the development of AML(Bueso-Ramos et al.,
2015). Additionally, relatives of young patients with AML were found to be at increased
risk of AML/MDS, suggesting that germline genes may contribute to disease
development. The increased risk of all hematologic malignancies among relatives of
patients with AML suggests that genes for malignancy in general and/or other
4
environmental factors may be shared(Goldin et al., 2012). Certain conditions like Down
syndrome(Xavier and Taub, 2010), Fanconi anaemia(Alter, 2014), Diamond–Blackfan
anaemia(Simkins et al., 2017), and severe congenital neutropenia also predispose
patients to AML. There is also an increased risk of AML in patients with an autoimmune
disease(Ramadan et al., 2012).
1.1.4 Clinical Manifestations and Diagnosis
Clinical Manifestation of AML include accumulation of immature blasts in the bone marrow
and peripheral blood. Patients present with symptoms related to the bone marrow failure
which include fatigue, anorexia and weight loss along with leukocytosis(Rollig and
Ehninger, 2015). Lymphadenopathy (swollen or enlarged lymph nodes) and
hepatosplenomegaly can occur. Patients also present with anemia or
thrombocytopenia(Khwaja et al., 2016). If left untreated, it could lead to infection or
bleeding leading to death due to the aggressive nature of the disease. Spontaneous cell
lysis can occur in some cases of AML with very high leukemia burden, giving rise to
hyperkalaemia, hypocalcemia, hyperphosphatasemia, hyperuricemia, and increased
plasma levels of lactose dehydrogenase(Ejaz et al., 2015). Such symptoms are often
exacerbated with the initiation of treatment(Belay et al., 2017).
A patient is likely diagnosed with AML if there are 20% or more blasts in the peripheral
blood or bone marrow(Arber et al., 2016). Additionally diagnosis is also confirmed if at
least two of the following markers are detected in and/or on myeloblasts:
myeloperoxidase, CD13, CD33, CDw65 and CD117, with myeloperoxidase having the
highest specificity for the myeloid lineage(Plesa et al., 2020). The presence of or α-
5
naphthylacetate is also an indication of AML(Fergedal et al., 1998). Lymphoid antigens
are present in about ∼25% of the patients. Infiltration of the bone marrow with blasts is
frequently detectable at low magnification by its increased uniformity and cellularity. Auer
rods in the cytoplasm of the blasts are indicative of AML(Khwaja et al., 2016).
Immunophenotypic characterization of whole-blood and bone marrow aspirates from
patients are used to identify the morphological characteristics of the disease to classify
the AML to better understand the treatment and disease course. Cytogenetic analysis is
also required part of the diagnosis as well to further determine the appropriate treatment,
characterize the disease risk and predict clinical outcome(Estey, 2013; Grimwade and
Mrozek, 2011). Morphological, and cytogenetic classification is further discussed in the
next section.
1.1.5 Classification
1.1.5.1 French–American–British classification
The first classification of AML was presented in 1976 by the French–American–British
classification system in which AML is categorized into eight subtypes (M0 to M7) based
on the morphological characteristics of the leukemic cells under the microscope using
staining. Subtypes M0 through M5 are all immature forms of white blood cells. M6 subtype
starts in immature red blood cells and M7 subtype originates from in immature forms of
precursor platelets(Figure 1-3)(Bennett et al., 1976).
6
Figure 1-3 FAB classification of AML (modified from (Bennett et al., 1976)).
7
1.1.5.2 World Health Organization (WHO) classification
In 2001, World Health Organization (WHO) introduced a new classification system that
takes into account advances made in diagnosis and treatment of AML which was then
further revised in 2008(Vardiman et al., 2009) and then in 2016(Arber et al., 2016) as
seen in Table 1.1.
Table 1.1 WHO classification of AML
Acute myeloid leukemia 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
• 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)
• AML (megakaryoblastic) with t(1;22)(p13.3;q13.3)
• AML with mutated NPM1
• AML with mutated CEBPA
• AML with mutated RUNX1 (Provision entity)
AML with myelodysplasia-related changes
Therapy -related AML
Acute myeloid leukemia, not otherwise specified
Myeloid sarcoma
Myeloid proliferations related to down syndrome
8
This classification is based on immunophenotype, morphology and clinical presentation
into the following categories :
1. AML with recurrent genetic abnormalities
This account for almost 20-30% of all AML cases. In this the AML variants consist of
genetic abnormalities of prognostic significance. Within this category, there are nine
subtypes which are defined based on structural or molecular abnormalities.
• AML with t(8;21)(q22;q22); RUNX1-RUNX1T1: The balanced translocation
t(8;21)(q22;q22), RUNX1-RUNX1T1 (previously AML1-ETO). This accounts for
almost 7% of adults with newly diagnosed AML(Grimwade et al., 2010). It is one of
the three cytogenetic abnormalities in AML which, if found, results in the diagnosis
of AML regardless of the bone marrow blast count(Campo et al., 2011).
• AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 : This
abnormality in chromosome 16 is seen in around 5% of newly diagnosed patients.
This frequently occurs in younger patients and is associated with a more favorable
outcome (excluding cases with c-KIT mutation)(Grimwade et al., 2010).
• APL with PML-RARA: Acute promyelocytic leukemia with PML-RARA is defined by
presence of promyelocytes with the PML-RARA fusion gene which links the retinoic
acid receptor alpha (RARA) gene on chromosome 17 with the promyelocytic
leukemia (PML) gene on chromosome 15 in the bone marrow. This accounts for
almost 13% of new AML cases and if treated appropriately results in a favorable
prognosis(Daver et al., 2015; Larson et al., 1984).
9
• AML with t(9;11)(p21.3;q23.3); MLLT3-KMT2A : This results from rearrangements
of 11q and occurs in almost 6% of adult cases. The t(9;11) translocation occurs in
about 1% percent of adults. Patients within this subtype tend to have an
intermediate prognosis(Kühn et al., 2014).
• AML with t(6;9)(p23;q34.1); DEK-NUP214 : This occurs in about 1% of adult cases
and presents with variable morphology(Sandahl et al., 2014). There is also a high
incidence of FLT3 ITD mutations(Song et al., 2014). This subtype is associated with
a poor prognosis.
• AML with inv(3)(q21.3q26.2) or t(3;3)(q21.3;q26.2): The inv(3) and t(3;3) account
for nearly 1% of newly diagnosed AML cases. This is often seen in de novo AML.
This subtype is associated with a poor prognosis(Pintado et al., 1985).
• AML (megakaryoblastic) with t(1;22)(p13.3;q13.3): This occurs rarely. Patients
present with anemia, hepatosplenomegaly, thrombocytopenia, and a relatively high
white blood cell (WBC) count(Chan et al., 1992).
• AML with BCR-ABL1: This occurs frequently in mixed-phenotype AML (38 %). This
subtype is associated with a poor prognosis(Atfy et al., 2011).
• AML with NPM1 mutation: Mutations in the nucleophosmin gene (NPM1) is a
subtype of recurrent genetic mutations in AML. This mutation confers a favorable
prognosis but when it occurs along with mutations in FLT3 confers a poor
prognosis(Arber et al., 2016).
• AML with CEBPA mutation: Biallelic mutations in CEBPA confers a favorable
prognosis but when it occurs along with mutations in FLT3 confers a poor
prognosis(Pabst et al., 2009).
10
• AML with RUNX1 mutation (Provision entity): Mutations in RUNX1 occurs in about
10-30% of AML. This mutation is associated with a worse overall survival
outcome(Arber et al., 2016)
2. AML with MDS-Related Features
AML with myelodysplasia-related features is defined by cases that is developed from
previous myelodysplastic syndrome or its related abnormalities, or multilineage dysplasia.
Patients with AML with a previous record of MDS or its related cytogenetic abnormalities
have a poor prognosis with conventional therapy(Weinberg et al., 2009).
3. Therapy -related AML
Patients in this subtype have essentially developed AML due to prior exposure to
cytotoxic therapy and is a consequence of mutations developed due to the therapy
resulting in AML. The outcome of these patients is worse compared to de novo
AML.(Abdel-Wahab and Levine, 2013).
4. AML not otherwise specified
This subtype includes patients who do not meet the criteria for other categories. This
subgroup is further classified based on the FAB classification(Walter et al., 2013) as seen
in Figure 1-4.
5. Myeloid sarcoma
Patients in this group have extramedullary mass consisting of myeloid blasts. Rather than
a subtype this is considered as a clinical presentation of AML. The presence of myeloid
sarcoma in AML is considered a poor prognosis(Avni and Koren-Michowitz, 2011).
11
6. Myeloid proliferations related to down syndrome
Down syndrome (DS) is one of the most important leukemia pre-disposing syndromes. In
children with DS, the risk of developing AML is almost 150-fold higher. Almost 2% of the
children with DS develop AML with 70% of them being acute megakaryoblastic
leukemia(FAB-M7)(Tomizawa and Kolb, 2017). These conditions develop before the age
of five in children. Trisomy 21 contributes to the somatic mutations in GATA1 which is an
important factor to AML pathogenesis(Cantor, 2015).
1.1.6 Risk Stratification and prognosis
Various factors are taken into consideration to determine the treatment and prognosis of
the patient. Patient-associated factors like age and performance status predict the course
of treatment, whereas disease-associated factors like genetic changes, prior MDS or
cytotoxic therapy predicts the resistance to current therapy. Clinical factors like increased
age (>60 years) are associated with poor complete remission (CR) and decreased overall
survival (OS)(Kantarjian et al., 2006). Therapy-related AML as well AML related with a
prior hematological disorder also carry a significantly worse prognosis due to increase
resistance to therapy(Hulegardh et al., 2015).
Most importantly, cytogenetics aberrations account for the strongest prognostic factor in
determining the survival outcome and remission. Three molecular markers (NPM1 and
CEBPA mutations and FLT3 internal tandem duplications) are currently being used in the
determination of treatment of the patients as reflected by the European LeukemiaNet
(ELN) recommendations updated in 2017(Döhner et al., 2017) (Figure 1-5). This
prognostic system stratify patients based on both their cytogenetic and molecular status
12
into 3 risk groups: favorable, intermediate and adverse (Figure 1.3). For instance, patients
t(15;17), t(8;21), or inv(16) all present a favorable prognosis, with a 3-year OS of 66%
and 33% in patients younger and older (>60 years), respectively. Patients with normal
cytogenetics (CN-AML) are within the intermediate prognostic risk(Dohner et al., 2010).
On the contrary, cytogenetic aberrations which include more than 3 chromosomal
abnormalities are associated with significantly poor prognosis and in the higher risk
group(Mrozek et al., 2012). Genetic mutations further help stratify the risks associated
with the prognosis and are included in the initial diagnostic workup. Nonetheless, the
ability to predict resistance to therapy is still a limitation in the clinical setting.
Figure 1-4: Stratification according to the ELN recommendations
(Döhner et al., 2017).
13
1.1.7 Genomic landscape
On the molecular genomics level, AML is a heterogeneous disease, with multiple somatic
driver mutations and coexisting competing clones. A detailed understanding of the
molecular landscape of AML helps better understand AML pathogenesis and develop
new therapeutic strategies. The cancer genome atlas analyzed genomic data from 200
patients with AML and have identified gene that are significantly mutated in AML(Ley et
al., 2013). Genes mutations found were categorized into nine groups known to play an
important role in AML pathogenesis: nucleophosmin (NPM1) (27%), cohesin-complex
genes (13%), DNA-methylation–related genes (44%), chromatin-modifying genes (30%),
myeloid transcription-factor genes (22%), signaling genes (59%), tumor-suppressor
genes (16%), and spliceosome-complex genes (14%) (Figure 1-4) (Döhner et al., 2015).
Out of the 200 samples , 199 samples had at least one mutation in one of these nine
categories. Among these patients, FLT3 gene was mutated in 56 patients and mutations
in kinases, phosphatases, or RAS family proteins were present in 62 samples. Further
analysis revealed high incidence of co-occurrence of mutations in FLT3,
DNMT3A, and NPM1.
14
Figure 1-5: Functional category of genes commonly mutated in AML
(Döhner et al., 2015)
Genomic analysis further helped understand AML pathogenesis. It was earlier believed
that a mutation in a gene encoding a signaling protein may be a required for disease
initiation(Kelly and Gilliland, 2003), but more recent genomic studies have shown that
only 59% of the patients had a mutation in this class of proteins. Additionally, mutations
in NPM1, DNMT3A, CEPBA, IDH1/2, and RUNX1 were found to be mutually exclusive
of transcription factor genes indicating the role of these genes in leukemogenesis(Ley et
15
al., 2013). It was also found that mutations within proteins of the spliceosome, signaling
proteins, cohesins, and histone-modifying proteins were mutually exclusive indicating that
one of these gene mutations was enough for leukemogenesis. An important aspect is
also the presence of mutations in epigenetic regulator likes ASXL1, DNMT3A, TET2, and
IDH2 preleukemic stem cells indicating the role of these mutations in disease
pathogenesis(Corces-Zimmerman et al., 2014; Kronke et al., 2013; Shlush et al., 2014).
More recently, analysis of gene mutation and its association with drug sensitivity gave a
deeper insight into therapeutic strategies. For instance, mutations in TP53 or AXL1
resulted in a broad pattern of drug resistance. Mutation in NRAS and KRAS also largely
contributed towards drug resistance. Mutations in IDH1 increased drug resistance but
mutations in IDH2 increase sensitivity. Furthermore, mutations in several slpicosmal
components lead to increase sensitivity towards drugs. More interestingly, increased
sensitivity towards ibrutinib (BTK and TEC family kinase) was seen in mutations of NPM1,
FLT3 and DNMT3A. Co-mutation of BCL6 corepressor (BCOR) with RUNX1 resulted in
increased sensitivity to JAK inhibitors(Tyner et al., 2018). Based on this, the association
between mutations and gene expression lead to a better understanding of treatment
options for AML. The association of the genetic abnormality with the patient clinical
outcome is listed in table 1.2.
16
Table 1.2 The association of the genetic abnormality with prognosis
(adapted from (Aziz et al., 2017)
Mutation Prognosis
FLT3 ITD Unfavorable (Daver et al., 2019)
FLT3 TKD Uncertain (Daver et al., 2019)
NPM1 Favorable (Liu et al., 2014)
DNMT3A Unfavorable (Ley et al., 2010)
WT1 Uncertain (Rampal and Figueroa, 2016)
KIT Unfavorable (Ayatollahi et al., 2017)
TP53 Unfavorable (Rucker et al., 2012)
CEBPA Favorable (Li et al., 2015b)
IDH1/IDH2 Unfavorable (Ok et al., 2019)
JAK2 Uncertain (Vicente et al., 2007)
MLL-PTD Unfavorable (Choi et al., 2018)
RUNX1 Unfavorable (Sood et al., 2017)
ASXL1 Unfavorable (Pratcorona et al., 2012)
TET2 Unfavorable (Wang et al., 2019)
1.1.8 Current therapy
The standard of care therapy for AML has changed very minimally for the past several
decades. The treatment is divided into two phases of chemotherapy: Induction therapy
and consolidation therapy. The purpose of the induction therapy is to achieve remission
by reducing leukemia burden. The intensity of the treatment is often dependent on the
age and health of the patient. It consists of 7 days of continuous infusion cytarabine with
3 days of anthracycline referred as ‘7+3’ therapy. Patients with a favorable or intermediate
risk are often given this treatment regimen(Estey, 2014). Additionally, patients are also
administered either daunorubicin(Gong et al., 2015) or idarubicin(Li et al., 2015c).
Following induction therapy, bone marrow biopsy is performed to determine the leukemic
burden in the patients. A patient is considered to be in remission if the blasts are less than
5%. If remission is not achieved, another round of induction therapy is administered.
17
Around 60–80% of patients with de novo AML achieve complete remission through
induction therapy(Buchner et al., 2012).
Consolidation therapy is administered once the patient is in remission. Its purpose is to
destroy the remaining leukemic blasts and to prevent disease relapse. This includes
chemotherapy (high-dose cytarabine (ara-C)) and allogeneic hematopoietic stem cell
transplant (allo-HSCT). For patients with a favorable outcome, chemotherapy is the first
line consolidation option. For patients with intermediate, poor risk, CN-AML or high FLT3-
ITD allelic ratio, allo-HSCT significantly increases relapse free survival and overall
survival(Cornelissen et al., 2007; Li et al., 2015a; Schetelig et al., 2015; Yanada et al.,
2005).
AML was almost incurable before 1960s. Following that, there was a considerable
improvement the survival of patients <60 due to better chemotherapy, HSCT transplant
and supportive care. Albeit, the survival of older patients hasn’t improved much(Burnett
et al., 2011). The difference in response to therapy based on age is mainly due to the
ability of younger patients to tolerate intensive treatment options as well as the occurrence
of poor risk factors with age(Lazarevic et al., 2014). Furthermore, older patients are
excluded from most clinical trials for various therapies based on the inclusion criteria.
Remission was achieved in nearly 70% of the patients between age of 19-40 years. The
improved outcome in older patients is only due to prolonged survival with adequate care
without achieving remission(Shah et al., 2013). The relapse rates range from
18
approximately 30% to 35% in younger patients with favorable risk factors, to 70% to 80%
in older patients with adverse risk factors.
When patient survival was compared between Europe, Sweden and US, significant
difference in cure was observed between patients less that 40 years surviving 15% higher
in Sweden than Europe. Interestingly, 4% of the patients between the age of 71-80 years
are cured in Sweden whereas none were cured in the Europe for this age
group(Andersson et al., 2010; Shah et al., 2013). Additionally, women tended to respond
better to treatment than men. In the US, non-Hispanic white people had better prognosis
than other ethnic groups with the difference becoming more prominent in younger
patients(Juliusson et al., 2006).
There is still a limitation in completely understanding AML survival outcome based on
ethnicity/demographic or population due to lack of information as well as a difference in
management of the disease and different socio-ecomin status.
1.1.9 Targeted therapy for AML
Over the past few years, several clinical trials have led to new drugs being approved
between 2017-2018 (Winer and Stone, 2019) (Figure 1-6).
19
Figure 1-6: Recently approved drugs for AML (Winer and Stone, 2019)
New breakthrough in targeted therapies have led to new guidelines with emphasis on
molecular studies leading to these drugs being administered along with chemotherapy in
some cases. Since mutations in FLT3 have a high frequency, there is an increase in the
development of tyrosine kinase inhibitors. Currently, the targeted
therapy drug midostaurin (Rydapt) is administered to adult patients with newly diagnosed
FLT3-positive AML in combination with standard cytarabine and daunorubicin induction
and cytarabine consolidation. Recently, Gilteritinib was approved for treatment of adult
patients who have relapsed or refractory AML (Lee et al., 2017b; Stone et al., 2005).
Treatment with midostaurin for FLT3-ITD patients increased the overall survival from 25.6
20
months to 74.7 controlled clinical trial. Currently the 4-year survival of patients is
51.%(Stone et al., 2017).
With the finding that epigenetic mutations are frequent in AML and are reversible, this has
led to the development of new epigenetic therapies(Abdel-Wahab and Levine, 2013;
Dawson et al., 2012). Patients who are 75 years or who have comorbidities that preclude
the use of intensive induction chemotherapy along with IDH1 or IDH2 mutation are being
treated with Ivosidenib or Enasidenib respectively. In patients where Ivosidenib treatment
resulted in clearance of IDH1 mutation resulted in longer duration of remission (11.1
months) than those without clearance (6.5 months)(DiNardo et al., 2018). In phase 1/11
trial treatment with Enasidenib the overall response rate in relapsed/refractory older
patients with IDH2 mutation was 40.3% with 19% achieving complete remission(Pollyea
et al., 2019).
Azacitidine (5-Aza) and decitabine are hypomethylating agents currently used in the
clinical setting for mutations in DNMT3A(Fenaux et al., 2010; Issa et al., 2004).
For patients with therapy related AML, CPX-351 (Vyxeos) is administered. This improved
survival to 9.56 months as from 5.95 months(Lancet et al., 2018). For older patients (>75
years) or those who have comorbidities that preclude use of intensive induction
chemotherapy Glasdegib (a small-molecule Hedgehog inhibitor) or Venetoclax (B-cell
lymphoma-2 (BCL-2) inhibitor) is administered. This improved median overall survival to
8.8 months as compared to 4.9 months with low-dose cytarabine (LDAC). In older patients
with NPM1 mutation combination of Venetoclax and LDAC resulted in a good response
with CR/Cri rates of 89%(Richard-Carpentier and DiNardo, 2019).
21
CD33 is an antigen expressed on the blasts of most cases of AML. In 2017, gemtuzumab
ozogamicin (Mylotarg) was approved for the treatment of newly diagnosed CD33 positive
AML along with daunorubicin and cytarabine. Mylotarg along with daunorubicin and
cytarabine improved the event free survival to 13.6 months from 8.8 months as compared
with daunorubicin and cytarabine treatment(Jen et al., 2018).
There are also several other monoclonal antibodies currently under investigation in
clinical trials. SGN-33A is under investigation against CD33(Stein et al., 2018), CSL362
and SL-401 antibodies are being investigated against CD123(Frankel et al., 2017; Lee et
al., 2015). Clinical trials are also underway for bispecific antibody targeting CD3 and
CD33(Harrington et al., 2015; Krupka et al., 2016). The overall treatment summary with
the new targeted therapies and outcomes are summarized in figure 1.7 and table
respectively.
22
Figure 1-7:Treatment of AML with new therapeutics (DiNardo and Wei, 2020)
Table 1.3 Patient outcome with new therapeutics
Drug Indication Age Survival
Rydapt
/midostaurin + IC
(Stone et al., 2017)
FLT3
MUT
AML 18-59 51.4% at 4 y
CPX-351 (Lancet et al.,
2018)
tAML, AML MRC 60-75 Median, 9.6 vs. 5.95
months of 7+3 regimen
Mylotarg/GO
(Jen et al., 2018)
Newly diagnosed
adults with
CD33
+
AML with IC
50-70 Median, 4.3 vs 3.6 months
of best supportive care
glasdegib +
LDAC (Cortes et al.,
2019)
>75 years or unfit for
IC
63-92
Median, 8.8 vs 4.9 months
with low-dose cytarabine
(LDAC)
venetoclax +
HMA (DiNardo et al.,
2019)
New AML ≥75 y or
unfit
65-86
Median, 17.5 mo
Venclexta/venetoclax +
LDAC (Wei et al., 2019)
New AML ≥75 y or
unfit
63-90
Median, 10.1 mo
23
Despite these advances in therapies, the overall survival is still not significantly improved
and there is a need to further identify novel therapeutic targets. For instance, only half the
patients treated with midostaurin achieve 4-year survival. Since AML is a vastly
heterogenous disease with several chromosomal aberrations and genetic mutations
which could potentially de-regulate various other genes that promote leukemogenesis,
identifying genes deregulated in AML will provide a new insight into targeted therapy as
well as combination therapies. Gene expression profiling provides essential information
regarding new gene targets and their clinical and functional correlation in AML. For this
reason, our aim was to identify a novel therapeutic target for AML, characterize its
functional and mechanistic role in AML and then develop it as a therapeutic strategy for
AML.
24
1.2. CD99
1.2.1 CD99 gene and expression
CD99 is a transmembrane protein that is encoded by the MIC2 gene(Goodfellow et al.,
1988) located in the pseudo-autosomal region (PAR) of both the X (Xp22.33-Xpter) and
Y (Yp11-Ypter) chromosomes in humans(Aubrit et al., 1989; Banting et al., 1989; Ellis et
al., 1994). CD99 is highly O-glycosylated(Aubrit et al., 1989) and together with CD99
antigen-like 2 (CD99L2) and Xga constitutes a family of molecules that demonstrate no
homology to any other known molecules(Aubrit et al., 1989; Ellis et al., 1994).
The CD99 gene encodes two distinct proteins as consequence of alternative splicing of
the cytoplasmic region resulting in : a wild-type full-length CD99 long isoform (CD99 L)
with 185 amino acids (molecular weight of 32 kDa) and a truncated short isoform (CD99
S) with 161 amino acids (molecular weight of 28 kDa)(Hahn et al., 1997). The CD99 S
transcript contains an 18-bp insertion between exons 8 and 9 on the gene leading to an
in-frame stop codon resulting in truncated polypeptide (Figure 1-8).
25
Figure 1-8:Structural characterization of CD99 gene and isoforms (Pasello et al., 2018)
.
Though the x-ray structure of CD99 has not been elucidated, it was shown the CD99 has
a hairpin structure fixed by two flexible loops and does not have any regular secondary
structures(Kim et al., 2004). Furthermore, CD99 forms integral membrane protein with a
100 amino acid extracellular domain, a transmembrane domain and a cytoplasmic C-
terminal domain of 38 amino acids. The extracellular and transmembrane domains are
the same in both the isoforms, but the cytoplasmic domain of the long and short isoform
vary. CD99 L isoform contains two putative phosphorylation sites, a serine at amino acid
residue 168 (S168) and a threonine at amino acid residue 181 (T181). It is speculated
that this difference in phosphorylation site could result in varied signaling cascades for
these isoforms(Scotlandi et al., 2007). CD99 L and S isoforms are known to form homo
and hetero-dimers on cell surfaces, a process which begins in the Golgi apparatus
following which the dimers are exported to cell surface(Scotlandi et al., 2007).
26
CD99 expression is mostly high in pancreatic islet cells(Martens et al., 2018), cortical
thymocytes (Bernard et al., 1997), granulosa cells of the ovary, and Sertoli cells of the
testis(Gordon et al., 1998). In addition, CD99 is expressed at high levels in all leukocyte
lineages as well as CD34
+
cells of the bone marrow with the highest expression in the
most immature lymphocytes and granulocytes(Dworzak et al., 1994). In hematopoietic
stem cells, CD99 is differentially expressed based on distinct maturation stages: initially,
CD99 expression is high in multipotent CD34
+
cells in the bone marrow but the expression
declines as these cells differentiate into mature blood cells(Dworzak et al., 1994).
1.2.2 CD99 function in normal physiology
In normal physiology, although the function of CD99 is not fully understood, it has been
implicated in several biological processes. CD99 is involved in the rosette formation of T
cells, wherein pre-incubation of T cells with CD99 mAb resulted in rosette inhibition. In
this manner CD99 plays a role in T cell adhesion (Bernard et al., 1988). Stimulating CD99
also plays a role in adhesion by increasing the binding T cells and activated peripheral
blood lymphocytes to the vascular endothelial cells(Bernard et al., 2000). Furthermore,
CD99 mAb specifically induces homotypic aggregation of corticothymocytes (CD4
+
CD8
+
)
cells and this ability was restricted only to immature T cells and not mature T cells or
peripheral B cells(Bernard et al., 1995).
CD99 also plays an important role in cell apoptosis and differentiation. CD99 mAb
treatment of thymocytes induced exposure of phosphatidylserine to the outer surface
resulting in cell apoptosis. This event occurred mainly in the well-delineated
subpopulation (double positive, intermediate surface of CD3-TCR,CD69+ cells) of
27
thymocytes and had no effect on mature thymocytes also indicating the role of CD99 in
thymocyte positive selection and cell differentiation(Bernard et al., 1997).
CD99 is also essential for the diapedesis of leukocytes. CD99 is expressed on leukocytes
as well as on endothelial cells. The homotypic interaction of CD99 between the two cells
types leads to cell migration (Dufour et al., 2008). CD99 on the endothelial cell activates
protein kinase A which then activates membrane trafficking from the lateral border
recycling compartment to sites of transendothelial migration, enabling the movement of
leukocytes across the endothelium(Watson et al., 2015).
CD99 is also known to regulate intracellular protein trafficking. CD99 regulates the
transport of MHC class 1 to the plasma membrane and is associated with the post-Golgi
trafficking machinery(Sohn et al., 2001). Furthermore, engagement of CD99 resulted in
upregulation of TCR and MCH class 1 and 11 in thymocytes by activation of cytoskeletal
components leading to increased mobility of specific antigens to cell surface(Choi et al.,
1998).
The function of CD99 isoforms has been evaluated very minimally and potentially have
opposing functions. It was previously shown that peripheral T cells have high CD99 long
isoform expression whereas double-positive thymocytes express both the long and short
isoforms. When co-expressed, the isoforms form covalent heterodimers located in the
glycosphingolipidic rafts and induce sphingomyelin degradation leading to cell apoptosis.
Localization of both the isoforms was found to be necessary for the induction of
apoptosis(Alberti et al., 2002). Additionally, the long isoform is known to be involved in
cell aggregation by increase LFA-1 expression. On the other hand, the short isoform
28
downregulates LFA-1 expression and thus, the two isoforms could have an opposing role
on cell adhesion(Hahn et al., 1997).
1.2.3. Role in cancer: Clinical significance
Clinical significance of CD99 expression has been evaluated in several malignancies with
opposing roles. In some malignancies, CD99 expression is down-regulated. For instance,
in pulmonary neuroendocrine tumors decrease of the CD99 expression was observed
from better to poorly differentiated tumors, and the loss of CD99 correlated with
occurrence of nodal metastases(Pelosi et al., 2006). In gastric adenocarcinomas, low
CD99 expression was associated with poor survival outcome and unfavorable
clinicopathologic variables(Lee et al., 2007). In gallbladder carcinoma, CD99 expression
was downregulated in advanced-stage (II, III, IV) compared with early-stage
carcinoma(Choi et al., 2004). Furthermore, loss of CD99 expression was associated with
poor survival in pancreatic endocrine tumors(Goto et al., 2004). In non-small cell lung
carcinoma, CD99 is differentially expressed in the tumor stroma and a higher CD99
expression was associated to a better outcome in these patients(Edlund et al., 2012).
CD99 has also been extensively studied in osteosarcoma, where CD99 was found to be
down-regulated in clinical samples and functions as an onco-suppressor(Manara et al.,
2006).
On the contrary, CD99 was found to be highly expressed on the cell surface of Ewing's
sarcoma (EWS) tumors(Desai and Jambhekar, 2010), gliomas (Seol et al., 2012) and
was also shown to be expressed in many other mesenchymal, hematopoietic and
epithelial cancers(Czapiewski et al., 2015). High CD99 expression along with and the
29
occurrence of an EWS gene-rearrangement with FLI1, or ERG are the hallmarks of
Ewing sarcoma(Vural et al., 2011). High CD99 expression is also frequently used to
distinguish Ewing sarcoma from other types of small round-cell tumors of childhood, small
round-cell osteosarcoma, and Ewing-like round cell tumors, a group of uncommon
malignancies morphologically similar to Ewing sarcoma but exhibiting a different type of
genetic mutations and presenting with lower levels of CD99 expression(Ambros et al.,
1991; Antonescu et al., 2017; Fellinger et al., 1991; Llombart-Bosch et al., 2009; Machado
et al., 2016).
CD99 is also known to be upregulated in cancers of the nervous system. CD99 is highly
expressed in ependymomas, astrocytoma and in gliomas, where its expression level is
used to distinguish tumor grades. For instance, nonependymal tumors do not show
membrane staining for CD99, whereas ependymomas show strong expression of CD99
in membranous pattern with intracytoplasmic or intercellular dots. This helps
distinguishing ependymomas from the other central nervous system tumors that
histologically mimic ependymoma(Choi et al., 2001). In gliomas, CD99 expression was
almost 5-fold higher than in normal brain. More importantly, expression of CD99
correlated directly with advancing grade of glial tumors(Persson et al., 2007).
Furthermore, CD99 expression was restricted to the cytoplasm or membrane in malignant
astrocytoma, in contrast to non-neoplastic brain tissue or non-infiltrative pilocytic
astrocytoma(Urias et al., 2014).
Similar findings were observed in hematopoietic malignancies. CD99 expression was
found to be a suggestive detection marker to assess minimal residual disease (MRD) in
T-lineage acute lymphoblastic leukemia (T-ALL)(Dworzak et al., 2004). Additionally,
30
CD99 was significantly overexpressed in early B cell lymphoblastic lymphomas(Dworzak
et al., 1999) and in AML(Angelini et al., 2015; Chung et al., 2017; Zhang et al., 2000).
CD99 immuno-reactivity was previously reported in 43% of AML cases but rarely in
myeloproliferative disorders, myelodysplastic syndromes, remission and normal bone
marrow samples(Zhang et al., 2000).
1.2.4. Role in cancer: Function and Mechanism
CD99 is highly deregulated in a large number of cancers and has a dual role. Its function
has mainly been studied in Ewing sarcoma where it presents as an oncogene and in
osteosarcoma where it serves as an onco-suppressor. The exact mechanism behind the
its dual role in cancer is yet to be elucidated. Some studies suggest that the contradictory
role of CD99 in cancer could be owing to the isoforms of CD99. Several studies have
shown that the long and short isoforms of CD99 can positively or negatively regulate
cellular adhesion, apoptosis, migration, and metastasis.
In Ewing sarcoma, cells deprived of CD99 but still presenting EWS-FLI1 showed
considerable inhibition of cell proliferation, migration, and invasiveness and increased cell
differentiation(Rocchi et al., 2010). Mechanistically, high constitutive CD99 expression in
Ewing sarcoma inhibited potassium-channel modulatory factor (KCMF1) which was
inversely related to migration capacity of the cell. Ectopic expression of KCMF1
significantly reduced migration(Kreppel et al., 2006). More importantly, CD99 is known
regulate ERK1/2 and Notch pathway in Ewing sarcoma (Figure 1-9). Loss of CD99
induced prolong phosphorylation of ERK1/2 which drives the cell toward terminal
differentiation. Alternatively, loss of CD99 was also shown to activate miR34a which in
31
turn inhibits Notch and NF-kB pathway leading to reduced cell proliferation and increased
cell differentiation(Ventura et al., 2015). Furthermore, in EWS, inhibition of CD99 with
anti-CD99 antibody resulted in apoptosis and enhanced sensitivity to chemotherapeutic
agents(Sohn et al., 1998).
Figure 1-9: Effect of knocking down CD99 in Ewing sarcoma (Manara et al., 2018).
More recently, the role of CD99 isoforms in osteosarcoma has been reported. Forced
expression of CD99 L isoform was shown to upregulate caveolin-1 which functions as an
allosteric inhibitor of Src kinase and reduced the level of c-Src autophosphorylation which
resulted in decrease cell proliferation and migration via inhibition of ROCK2 activity in
osteosarcoma cells. Forced expression of CD99 S isoform indeed had the opposite
effect(Scotlandi et al., 2007; Zucchini et al., 2014) (Figure 1-10).
32
Furthermore, in breast cancer cells it was shown that the ectopic expression of CD99 S
isoform contributed to invasiveness of the disease by upregulating SRC kinase which
resulted MMP9 upregulation in a ERK1/2, JNK and AP1 dependent pathway(Byun et al.,
2006) (Figure 1-10).
Figure 1-10: Effect of knocking down CD99 in Ewing sarcoma
(Manara et al., 2018)
33
Chapter 2: Clinical characterization of CD99 in AML
2.1. Introduction
The role of CD99 is highly controversial in cancer. In several malignancies like Ewing
sarcoma, gliomas and lymphomas, CD99 overexpression is associated with
aggressiveness of the disease. On the contrary, low CD99 expression was associated
with poor outcome in gastric adenocarcinoma, gallbladder and pancreatic carcinomas. In
hematological malignancies, CD99 is highly expressed in T-ALL, B cell lymphomas and
myelodysplastic syndrome. Importantly, in AML, high CD99 expression was associated
with leukemic stem cell population. There is growing evidence that CD99 plays a role in
cancers and particularly in leukemia, but there is still very little known about the clinical
relevance of CD99 in AML as well as the distribution of CD99 isoforms in AML.
In this chapter, we aim to characterize the clinical implication of CD99 expression and its
isoform in AML by analyzing its association to clinical and molecular characteristics in
AML across various patient datasets. Mainly, we analyzed CD99 expression in AML vs
normal. CD99 association with patient characteristics like age, sex, WBC and platelet
counts as well as relevant mutations was determined. Further, we looked at the
association of CD99 expression with patient survival after grouping them based on
various characteristics relevant to AML. More importantly, we analyzed CD99 isoform
expression in AML and its association with survival.
34
2.2 Experimental procedure
2.2.1 Patient Samples
Diagnostic or relapse blood was obtained from AML patients treated at the Norris
Comprehensive Cancer Center at USC 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.
2.2.2 Patient Datasets
CD99 mRNA expression of patients from the GSE7186(Andersson et al., 2007),
GSE13159(Haferlach et al., 2010), GSE1159(Valk et al., 2004), GSE15434(2018b),
GSE3077(Barnes et al., 2005), GSE425(2018a; Bullinger et al., 2004),
GSE12417(Metzeler et al., 2008) and GSE17855(Balgobind et al., 2011; Sandahl et al.,
2014) datasets were downloaded from the GEO database.
For the TCGA dataset analysis, 186 patients with previously untreated AML were
studied, all of whom had been diagnosed and received treatment according to the
National Comprehensive Cancer Network (NCCN) guidelines between November 2001
and March 2010 was downloaded from oncomine. The GSE3077 dataset had microarray
data for CD34 and CD38 population in 23 patients with AML.
CD99 isoform analysis was performed using the GSE106291 dataset that consisted of
246 patients with AML, all of whom had received intensive induction treatment. The age
range of patients were between 18-84 years with a median age of 58 years. M3 patients
were excluded from this analysis. CD99 transcript counts were extracted from this data
set annotated with GRCh38 release-96 build using Salmon (v0.9.1)(Patro et al., 2017).
35
Counts were normalized (TMM) using edgeR (Robinson et al., 2010)and log2 transformed
counts per million were extracted.
2.2.3 Statistical analysis
For gene expression analysis, patients were divided into two quartiles based on CD99
median expression. To investigate the associations between CD99 expression levels
and the clinical and molecular characteristics, Student’s t-test and univariate analysis
were used in the hypothesis testing for categorical and continuous variables,
respectively. The Mantel-Cox log- rank test was used to estimate the association
between CD99 expression and EFS and OS of the patients. Univariate and
multivariable analysis were performed using STATA3. The statistical cutoff value was
adjusted to p-value ≤0.05. All other analyses were performed using the GraphPad
Prism software packages.
36
2.3 Results
2.3.1 CD99 is upregulated in patients with AML.
In an effort to identify target genes that were differentially overexpressed in AML, we
compared gene expression profiles between normal and AML from various datasets
(GSE13159, GSE13164, GSE7186, GSE1159, GSE995, and TCGA Leukemia) available
on Oncomine. We found that CD99 was significantly upregulated in AML compared with
normal cells in five of the data sets with available measurements of CD99 RNA expression
levels (median ranking among upregulated measured genes 155, p= 0.013; TCGA data
sets did not have CD99 levels in normal cells). Other genes among the top ten genes
found in this analysis were FLT3 (median ranking 102, p<0.001) and WT1 (median
ranking 120, p<0.001); both of which are known to play an important role in AML. CD99
was significantly higher (3.5-fold; p=0.0072; Figure 2-1A) in 23 AML patients compared
with 6 normal bone marrow samples from the GSE7186 dataset. Consistently, CD99 was
significantly over-expressed (2-fold; p<0.0001) in blasts of 542 patients with AML
compared with peripheral blood mononuclear cells (PBMCs) from 74 healthy donors from
the GSE13159 dataset (Figure 2-1B). In the GSE1159 dataset, CD99 median expression
was significantly upregulated (1.8-fold; p=0.003) in blasts from 285 patients with AML
compared with that in healthy donor cells (Figure 2-1C). Additionally, in the GSE13164
dataset there was an increase in CD99 expression (2.3-fold; p<0.001) in blasts obtained
from 257 patients compared with that in PBMCs obtained from 58 healthy donors (Figure
2-1D). In the GSE995 dataset, there was an increase (3-fold; p=0.28) in CD99 expression
in blasts from nine patients compared with that in cells from six healthy donor samples
(Figure 2-1E).
37
Figure 2-1:CD99 is overexpressed in AML
CD99 was overexpressed in patients with AML as compared with healthy donor samples
across various data sets (A-E).
We also analyzed CD99 expression in cells obtained from 23 patients with AML
(GSE3077 dataset) and sorted according to their CD34 and CD38 expression levels. We
found that CD99 expression was significantly higher (1.34-fold; p<0.001) in the
A)
GSE7186
B)
C)
GSE1159
GSE13164
GSE13159
D)
E) GSE995
F)
A)
GSE7186
B)
C)
GSE1159
GSE13164
GSE13159
D)
E) GSE995
F)
38
CD34+CD38+ and CD34+CD38- subpopulation compared with CD34-CD38- and CD34-
CD38+; suggesting a possible role of CD99 in the leukemia stem cells (Figure 2-2).
Figure 2-2: CD99 expression in CD34+ subpopulation
CD99 expression was significantly higher in stem cell like population (CD34+ cells)
analyzed from 23 AML samples.
A)
GSE7186
B)
C)
GSE1159
GSE13164
GSE13159
D)
E) GSE995
F)
39
2.3.2 CD99 expression level according to patient’s clinical characteristics
To determine the association of CD99 with patient clinical characteristics, patients were
dichotomized based on CD99 median CD99 expression into CD99 high and CD99 low.
Patients with low CD99 expression had a significantly lower percentage of bone marrow
(BM) blasts (median, 66.2 vs 72.5, p=0.024), peripheral blood (PB) blasts (median, 23.7
vs 50.7, p<0.0001) and white blood cell (WBC) count (median, 27.7 vs 45.8, p=00.009)
(Table 2.1). Median age was 57.8 and 52.1 in the CD99 high and low groups, respectively
(Table 2.1).
40
Table 2.1 CD99 association with clinical characteristics
41
According to the National Comprehensive Cancer Network (NCCN) AML classification,
AML is classified into favorable, intermediate and poor risk groups based on patients
molecular and cytogenetic characteristics. CD99 expression was significantly higher in
the favorable risk group than that in the intermediate and poor-risk group (1.2-fold; p<
0.01, 1.2-fold; p<0.0001 respectively) (Figure 2-3A). This was also confirmed through
Fischer exact test (Table 2.2). We also assessed CD99 expression according to the
French-American-British (FAB) classification of AML(Table 2.2). We found that patients
with M5 AML had significantly lower CD99 expression compared to M1, M2, M3 and M4
groups. (Figure 2-3B). Furthermore, we analyzed CD99 expression according to leukemia
cytogenetics. We found no significant statistical differences in CD99 expression in
patients with complex karyotype, Inv (16), t (15; 17), t(8,21), del (7q) / 7q- and trismony 8
compared with patients with normal karyotype (Figure 2-3C).
42
Table 2.2 CD99 association with clinical characteristics
43
Figure 2-3: CD99 is overexpressed in AML
CD99 expression was significantly higher in patients with favorable risk status as
compared with intermediate and poor risk status (A). CD99 expression was
significantly lower in patients with M5 AML as compared to other FAB groups (B).
No significant difference in CD99 expression was observed among patients with
various karyotypes (C).
A) B)
C)
44
2.3.3 CD99 association with AML mutations
Next, we wanted to determine the association of high CD99 expression with mutations in
AML. In the TCGA dataset, we found that CD99 expression was significantly higher in
patients with FLT3-ITD (N=37) compared with patients with FLT3 point mutations (N=16)
and FLT3 wild-type (N=133) (1.3-fold; p=0.0028; Figure 2-4A). Similarly, based on CD99
median expression, we also found a significant association between high CD99
expression and the presence of FLT3-ITD mutation analyzed by Fisher Exact (P=0.04;
Table 2.3). This association was further confirmed in two additional datasets: GSE17855
(childhood AML) and GSE15434 (patients with cytogenetically normal karyotype). We
found CD99 expression was significantly higher in patients with FLT3-ITD compared with
patients with FLT3 wild-type (FLT3-WT) (1.3-fold; p<0.005 Figure 3-4B and 1.4-fold;
p<0.001 Figure 2-4C respectively).
Furthermore, CD99 expression was significantly lower (1.9-fold; p<0.001) in patients
carrying TP53 mutations (N=15) compared with patients carrying TP53 wild-type gene
(N=171) (Figure 2-4D; Fisher Exact P=0.0006, Table 2.3).
No associations were observed between CD99 expression and mutations in IDH1, IDH2,
RUNX1, DNMT3A, NMP1, TET2, NRAS, CEBPA and WT1 genes (Figure 2-4E and Table
2.3).
45
Figure 2-4:CD99 association with mutation status
CD99 expression was found to be significantly higher in patients with FLT3 ITD mutation
as compared with FLT3 WT gene (A-C). CD99 expression was significantly lower in
patients with p53 mutation as compared with WT gene (D). No associations were
observed between CD99 expression and other mutations in AML (E).
A) B)
C)
FLT3 WT FLT3 ITD
0
2
4
6
8
CD99 Expression
(Log2)
GSE17855
*
(N=189) (N=48)
FLT3 WT FLT3 ITD
6
8
10
12
14
CD99 Expression
(Log2)
GSE15434
(N=161) (N=90)
****
D)
TCGA
E)
46
Table 2.3 Fischer exact analysis for association of CD99 expression with
mutations in AML
CD99Low CD99High pvalue(WTvsMutated) FischerExact Test
FLT3-ITD,no.(%) p=0.002 P=0.0402
Present 37(30) 12(25.2) 24(47.5)
Absent 149(70) 81(74.7) 69(70.3)
IDH1,no.(%) p=0.08 P=1
Mutated 17(9.0) 8(8.4) 9(9.6)
Wildtype 169(91.0) 85(91.5) 84(90.3)
IDH2,no.(%) p=0.11 P=0.3
Mutated 17(9.5) 6(6.3) 11(12.7)
Wildtype 169(91.5) 87(93.6) 82(87.2)
RUNX1,no.(%) p=0.50 P=1
Mutated 17(8.5) 8(8.4) 9(10.4)
Wildtype 169(91.5) 85(91.5) 84(89.5)
TET2,no.(%) p=0.98 P=0.6
Mutated 17(9.0) 10(10.6) 7(7.4)
Wildtype 169(91) 83(89.4) 86(92.5)
NRAS,no.(%) p=0.2 P=0.7
Mutated 14(7.9) 8(8.4) 6(6.3)
Wildtype 172(91.4) 85(91.5) 87(93.6)
CEBPA,no.(%) p=0.1 P=0.08
Mutated 13(9.0) 3(10.6) 10(7.4)
Wildtype 173(91) 90(89.4) 83(92.5)
WT1,no.(%) p=0.92 P=0.5
Mutated 11(9.0) 4(10.6) 7(7.4)
Wildtype 175(91) 89(89.4) 86(92.5)
DNMT3A,no.(%) p=0.9 P=0.31
Mutated 49(26.0) 28(29.7) 21(22.3)
Wildtype 137(73.9) 65(70.2) 72(77.65)
NMP1,no.(%) p=0.24 P=0.4
Mutated 50(26.0) 28(29.7) 22(22.3)
Wildtype 136(73.9) 65(70.2) 71(77.65)
TP53
Mutated 15 14(93) 1(6.6) p=0.001 P=0.0006
Wildtype 171 79(46.2) 92(53.8)
47
2.3.4 CD99 overexpression is associated with better clinical outcome
To determine the association of CD99 expression with patient clinical outcome, patients
were dichotomized into low and high CD99 groups based on CD99 median expression.
For this analysis with patients with t(15;17) were excluded from the analysis, as these
patients have a better outcome and are treated with All-Trans-Retinoic Acid (ATRA).
Based on the Kaplan Meier survival analysis we found that the survival of the CD99 high
group were significantly longer than those of the CD99 low patients (median: 27 vs 11.2
months; p=0.0026; Figure 2-5A). Next, we stratified patients based on their cytogenetics
aberrations into cytogenetically normal (CN) and cytogenetically abnormal (CA) groups
and found within CA-AML patients, the CD99 high group survived significantly longer than
that of the CD99 low patients (median: 32.3 vs 11 months; p=0.02; Figure 2-5B). On the
contrary, there was no significant difference between the two groups in CN-AML patients
(p=0.22 Figure 2-5C). Additionally, we also analyzed the expression of CD99 between
CN-AML and CA-AML and found no significant difference (p=0.33, Figure 2-5C). When
we analyzed the event-free survival, we found no significant difference in the CD99 high
group and CD99 low patients (median: 15.6 vs 13.3 months; p=0.13; Figure 2-5D-F).
48
Figure 2-5:CD99 association with patient survival in the TCGA data set
High CD99 expression was associated with better overall survival in all patients and in
CA-AML patients (A-B). CD99 was not associated with overall survival in CN-AML
patients (C). CD99 was not associated with event free survival in all the patients, CA-AML
or CN-AML patients (D-F).
A. Patient survival based on CD99 median
expression
C. CN-AML patient survival based on CD99 median
expression
B. CA-AML patient survival based on CD99 median
expression
D. Patient event free survival based on CD99 median
expression
E. CA-AML patient event free survival based on CD99
median expression
F. CN-AML patient event free survival based on CD99
median expression
49
To further confirm this association, we analyzed CD99 association with the survival of
patients in the GSE425 data-set consisting of 71 patients with CA-AML. Consistently, we
found that patients in the CD99 high group had a significantly longer overall survival
compared with CD99 low (p=0.04, Figure 2-6A). There was no association of CD99
expression with survival when we included CN-AML patients or analyzed them separately
(Figure 2-6B-C). In accordance with these results, when we analyzed survival of
GSE12417 dataset which includes only CN-AML patients, no significant difference was
observed between high and low CD99 expression group (N=163) (Figure 2-6D).
In a multivariable analysis, CD99 high expression association with overall survival was
not significant when adjusted by age, cytogenetic risk, transplant status, DNMT3A
mutation status, and TP53 mutation status (p=0.364; Table 2.4).
50
Figure 2-6:CD99 association with patient survival in the GSE425 and GSE12417 data
set
High CD99 expression was associated with better overall survival CA-AML patients from
the GSE425 dataset (A).CD99 was not associated with overall survival in all CA-AML and
CN-AML combined or only CN-AML patients from the GSE425 dataset (B-C). CD99 was
not associated with overall survival of CN-AML patients from the GSE12417 dataset (D).
Patient survival based on CD99 median expression
CN-AML Patient survival based on CD99 median
expression
CA-AML Patient survival based on CD99 median
expression
A)
C)
B)
D) CN-AML Patient survival based on CD99 median
expression
51
Table 2.4 Multivariable analysis of high CD99 expression
association with overall survival
Multivariant Analysis
OS (categorical
CD99)
Parameter p-value Hazard Ratio (95% Conf. Interval)
Age 0.033 1.016617 (1.001304, 1.032165)
Intermediate Risk 0.001 3.135137 (1.601362, 6.137954)
Poor Risk 0.000 4.704015 (2.109915, 10.48751)
Transplant status 0.000 0.4344322 (.2781283, .6785766)
DNMT3A 0.108 1.396372 (.9291901, 2.098445)
TP53 0.057 1.955111 (.9791412, 3.903891)
CD99 0.364 0.839078 (.5746331, 1.22522)
Supplementary Table 2
52
2.3.5 Characterization and association of CD99 transcripts in AML clinical setting
CD99 gene is known to have several transcripts, with long and short isoform being the
predominantly studied proteins. To determine the expression of various CD99 protein
coding transcripts in patients with AML we analyzed RNAseq data from the GSE106291
dataset with 246 patients with AML. ENST00000381192.10 (CD99-L) and
ENST00000611428.5 (CD99-S) were the top expressed transcripts (Figure 2-7A). The
combined expression of ENST00000482405.7 and ENST00000611428.5 both of which
encode for CD99-S isoform was significantly higher than the level of
ENST00000381192.10 (CD99-L) (p=0.0073) (Figure 2-7B). Transcript Ensembl IDs and
their description are listed in (Table 2.5). The transcript expression of
ENST00000381192.10 positively correlated with ENST00000482405.7 (Figure 2-7C)
and ENST00000611428.5 (Figure 2-7D).
53
Table 2.5 CD99 transcript Ensembl IDs and their description
Name Transcript ID bp Protein Biotype Isoform CCDS Uniprot
CD99-205 ENST00000381192.10 1129 185aa Protein coding Long Isoform CCDS14119 P14209
CD99-210 ENST00000611428.5 1243 160aa Protein coding Short Isoform CCDS75947 P14209
CD99-208 ENST00000482405.7 842 160aa Protein coding Short Isoform CCDS75947 P14209
CD99-212 ENST00000624481.4 1089 184aa Protein coding CCDS83452 A0A096LP69
CD99-204 ENST00000381187.8 892 169aa Protein coding CCDS48071 P14209
CD99-203 ENST00000381184.6 918 177aa Protein coding - A8MQT7
CD99-202 ENST00000381180.9 533 76aa Protein coding - A6NJT9
CD99-211 ENST00000623253.4 573 160aa Nonsense mediated
decay
CCDS75947 P14209
CD99-201 ENST00000381177.7 756 22aa Nonsense mediated
decay
- A6NGF6
CD99-206 ENST00000449611.6 604 No protein Processed transcript - -
CD99-207 ENST00000482293.6 466 No protein Processed transcript - -
CD99-214 ENST00000646103.1 1278 No protein Retained intron - -
CD99-209 ENST00000497752.7 815 No protein Retained intron - -
CD99-215 ENST00000647297.1 583 No protein Retained intron - -
CD99-213 ENST00000645950.1 497 No protein Retained intron - -
54
Figure 2-7: Characterization of CD99 transcript expression in AML
CD99-L and CD99-S were the top expressed CD99 transcripts in AML(A). CD99 S was
significantly higher than CD99 L isoform (B). CD99 L positively correlated with both
transcripts of CS99 S (C-D)
Long Transcript Short Transcript
-20
-10
0
10
20
Long and Short CD99 Transcript
**
CD99 Expression
N=246 N=246
-10 -5 5 10
-10
-5
5
10
ENST00000381192.10
ENST00000482405.7
ENST00000381192.10
vs.
ENST00000482405.7
Spearman r
r 0.5109
95% confidence interval 0.4091 to 0.6002
P value
P (two-tailed) <0.0001
P value summary ****
Exact or approximate P value? Approximate
Significant? (alpha = 0.05) Yes
Number of XY Pairs 246
-10 -5 5 10
-10
-5
5
10
ENST00000381192.10
ENST00000611428.5
ENST00000381192.10
vs.
ENST00000611428.5
Pearson r
r 0.2143
95% confidence interval 0.09164 to 0.3305
R squared 0.04591
P value
P (two-tailed) 0.0007
P value summary ***
Significant? (alpha = 0.05) Yes
Number of XY Pairs 246
A)
C)
B)
D)
ENST00000381192.10
ENST00000482405.7
ENST00000611428.5
ENST00000381187.8
ENST00000381184.6
ENST00000624481.4
ENST00000381180.9
-10
-5
0
5
10
CD99 Isoform Expression (N=246)
TMM Normalized
log2 transformed cpms
55
Next, we wanted to determine the association of each CD99 transcript with FLT3-ITD
mutation. ENST00000381187.8 and ENST00000624481.4 were significantly higher in
patients with FLT3-ITD mutation compared with FLT3-WT patients (p=0.001 and p=0.002;
Figure 3-8 A). ENST00000611428.5 (CD99-S) was not significantly associated with
FLT3-ITD after adjusting for multiple hypotheses testing (p=0.049).Furthermore, we
analyzed the association of various CD99 transcript’s upregulation with overall survival in
246 patients with AML using CD99 median cut-off for each transcript. Interestingly, High
ENST00000381192.10 (CD99-L) exhibited a trend of association with better overall
survival (median OS: 908 vs 445 days; p=0.06). No difference in survival between high
and low CD99 expression was observed for the other transcripts (Figure 2-8 B).
56
FLT3-WT
(N=197)
FLT3-ITD
(N=49)
-10
-5
0
5
10
CD99 Expression
ENST00000381187.8
***
FLT3-WT
(N=197)
FLT3-ITD
(N=49)
-10
-5
0
5
10
ENST00000611428.5
CD99 Expression
*
FLT3-WT
(N=197)
FLT3-ITD
(N=49)
-10
-5
0
5
10
CD99 Expression
ENST00000624481.4
**
FLT3-WT
(N=197)
FLT3-ITD
(N=49)
-8
-6
-4
-2
0
2
4
CD99 Expression
ENST00000381184.6
FLT3-WT
(N=197)
FLT3-ITD
(N=49)
-10
-5
0
5
10
CD99 Expression
ENST00000381192.10
FLT3-WT
(N=197)
FLT3-ITD
(N=49)
-10
-5
0
5
10
CD99 Expression
ENST00000482405.7
A)
57
Figure 2-8: Association of CD99 transcripts with clinical characteristics
Association of CD99 transcripts with FLT3-ITD mutations (A). Association of CD99
transcripts with patient overall survival (B).
0 1000 2000 3000
0
50
100
ENST00000381192.10
Overall Survival
Days
Percent survival
CD99 Low (N=123)
CD99 High (N=123)
p=0.06
0 1000 2000 3000
0
50
100
ENST00000611428.5
Percent survival
CD99 Low (N=123)
CD99 High (N=123)
Days
p=0.3
0 1000 2000 3000
0
50
100
ENST00000482405.7
Days
Percent survival
CD99 Low (N=123)
CD99 High (N=123)
p=0.18
0 1000 2000 3000
0
50
100
ENST00000381187.8
Days
Percent survival
CD99 Low (N=123)
CD99 High (N=123)
p=0.3
0 1000 2000 3000
0
50
100
ENST00000624481.4
Days
Percent survival
CD99 Low (N=123)
CD99 High (N=123)
p=0.19
0 1000 2000 3000
0
50
100
ENST00000381184.6
Days
Percent survival
CD99 Low (N=123)
CD99 High (N=123)
p=0.68
B)
58
2.4. Discussion
In this chapter we studied the expression of CD99 in AML and determined its clinical
significance. We found that CD99 is overexpressed in AML and particularly in CD34
positive AML cells which mainly represent leukemic stem cell population (LSC). It was
also recently shown that CD99
+
cells expressed an antigenic profile similar to lymphoid-
primed multipotent progenitors (LMPPs; CD34
+
CD38
−
CD90
−
CD45RA
+
), the
immunophenotype that enriches LSCs in the majority of human AML(Chung et al.,
2017). Since LSCs play an important role disease initiation, progression and therapy
resistance, identifying new LSC markers could potentially aid in developing new
therapeutic targets. In Ewing sarcoma, CD99 was shown to inhibit neural differentiation
and contribute to oncogenesis. Phenotypic studies have suggested that the level of CD99
expression among mPB CD34
+
cells appeared to be related to their differentiation ability
and a high level of CD99 expression among mPB CD34
+
cells was associated with
characteristics of early stages of hematopoietic differentiation: CD38
-
, CD90
+
, CD105
+
,
CD133
+
, ABCG2
+
and high ALDH activity. Most immature and granulocyte-macrophage
clonogenic progenitors appear to be present in the CD34
+
/CD99
high
subset. On the
contrary, most erythroid progenitors (erythroid burst-forming units [BFU-Es]) appear to be
present in the CD34
+
/CD99
low
subset. Based on this we speculate that CD99 expression
could regulate myeloid differentiation but the exact mechanism of this is yet to be
determined.
Because AML is a heterogeneous disease, it is essential to identify patients who are likely
to have high CD99 expression and thus may benefit from treatments aimed to target this
gene. Our analysis revealed an association between CD99 overexpression and particular
59
mutations and cytogenetic aberrations. The association between CD99 upregulation and
the presence of FLT3-ITD is particularly interesting. This finding is also consistent with
the previous observation from Angelini et al, showing that CD123/CD99/CD25(+) cells
≥11.7% in CD34+ cell fraction could predict FLT3-ITD mutations with high specificity and
sensitivity(Angelini et al., 2015). Patients with FLT3-ITD mutation have a significantly
worse outcome than patients with FLT3-WT. Based on this we speculate within the FLT3-
ITD positive patient population, CD99 may serve as an enhanced therapeutic target or
can be used as a combination therapy.
Despite its upregulation in AML, high CD99 expression was associated with better
outcome. Patients with high CD99 expression survived significantly longer than patients
with low CD99. Yet, this association was not significant in multivariate analysis in the
TCGA data, this is likely due to the that this effect is driven by other molecular and
cytogenetic factors possibly due to its upregulation in patients with favorable risk subsets
(inv16, t(8,21)); or the reverse association with TP53 mutations. Furthermore, patients
with high CD99 expression also had higher peripheral blasts and bone marrow blasts as
compared to patients with low CD99 expression but patients the median age of patients
was lower in patients with high CD99 expression as compared to low CD99 expression.
Since older patients tend to have poor outcome this could also contribute to the poor
overall survival in the CD99 low group.
Considering the increased interest in CD99 as a therapeutic target in AML, we sought to
investigate the clinical association of CD99 isoforms. RNAseq analysis of AML patient
samples revealed that transcripts coding for CD99-L and S isoforms are both expressed
in AML. High ENST00000381192.10 (CD99 L) also demonstrated a trend of association
60
with better overall. Further analysis to associate isoform expression with clinical
characteristic will provide a better insight into the role of the isoforms in AML. This is the
first report to study the association of CD99 isoforms with patient clinical characteristics.
In this study though we successfully characterized various CD99 isoform expression in
patients, the study is limited due to the lack of information with respect to the clinical and
various other molecular characteristics required to determine the association with the
isoforms.
CD99 association with patient clinical data provide us with a rational to further investigate
the role of CD99 and more particularly its isoforms in in vitro and in in vivo analyses in the
third chapter.
61
Chapter 3 : Functional and Mechanistic Characterization of
CD99 in AML
3.1 Introduction
CD99 is known to a function as a tumor suppressor gene in certain malignancies as well
as an oncogene. In several malignancies CD99 is overexpressed and is associated with
CD99 is highly expressed in Ewing's sarcoma (EWS)(Ambros et al., 1991), gliomas(Seol
et al., 2012), T-lineage acute lymphoblastic leukemia (T-ALL)(Dworzak et al., 2004), early
B cell lymphoblastic lymphomas(Dworzak et al., 1999), and gliomas. In these
malignancies CD99 is associated with increased cell migration, invasion, and
aggressiveness of the disease(Guerzoni et al., 2015a; Seol et al., 2012). Silencing CD99
or targeting it with a monoclonal antibody resulted in beneficial anti-cancer activity(Feo et
al., 2019; Seol et al., 2012; Ventura et al., 2015). On the other hand, CD99 is expressed
at low levels in osteosarcoma(Manara et al., 2006), Hodgkin’s lymphomas(Kim et al.,
2000), pancreatic tumors(Goto et al., 2004) and gastric carcinomas(Jung et al., 2002).
Here, decreased CD99 expression was shown to increase aggressiveness of the disease
and overexpressing it resulted in reduced cell migration, proliferation and increased cell
differentiation(Lee et al., 2007; Manara et al., 2006; Scotlandi et al., 2007; Zucchini et al.,
2014). Since CD99 gene encodes for separate isoform, it is speculated that the isoforms
contribute to its dual role in cancer. Very little is known about the role of CD99 isoform in
AML. For this purpose, we used gain and loss of function of CD99 long and short isoform
to identify the functional and mechanistic role of these isoforms in AML. This effect was
evaluated in primary blasts and AML cell lines. We also analyzed the effect of
overexpressing CD99 long and short isoform on leukemia engraftment in vivo.
62
Importantly, we analyzed the therapeutic benefit of targeting CD99 with a monoclonal
antibody.
3.2 Experimental procedures
3.2.1 Cell lines and primary blasts
THP-1, MV4-11, KG-1, and Kasumi-1 were purchased from ATCC. MOLM 13, U937,
KG-1A and NB4 cells were kindly provided by Dr. Wendy Stocks’s lab. All AML cell
lines were authenticated at the University of Arizona Cell Authentication Core. AML cell
lines were grown in Roswell Park Memorial Institute 1640 (RPMI 1640) medium
(Thermo Fisher, MA, USA) supplemented with 10% fetal bovine serum (FBS) and
100U/mL penicillin (Thermo Fisher, MA, USA).
Peripheral blood mononuclear cells (PBMCs) and mononuclear cells were isolated by
density gradient centrifugation using Ficoll-Paque method. Briefly, blood was diluted with
equal volumes of PBS and layered over Ficoll-Paque at 1:3 ratio and centrifuged at 200-
300 Xg for 30 minutes with breaks off. Following this, the buffy coat is collected and
washed thoroughly to collect PBMCs. Primary cells were grown in RPMI plus 20%FBS
and cytokine cocktails CC100 (Flt3L, SCF, IL-3 and IL-6).
HEK 293T cells were grown in DMEM medium supplemented with 10% calf serum.
3.2.2 Plasmids
The PLVX-CD99 L-AcGFP-C1 and PLVX-CD99 S- AcGFP -C1 was constructed by
cloning the CD99 cDNA from U937 into the Apa1 and Xho1 sites of the PLVX-Zsgreen-
C1 (Clontech, CA, USA). Primers used to generate PLVX-CD99 L-Zsgreen-C1 are as
63
follows: Forward: CGCTCTGGGCGCACC, Reverse: AACAAATTGAAGGGC. Primers
used to generate PLVX-CD99 S-Zsgreen-C1 are as follows: Forward:
CGCTCTGGGCGCACC, Reverse: TCAGCCATCATTTTC. For the PLVX- AcGFP -C1,
the GFP is fused with CD99 on the N-Terminal. For CD99 shRNA plasmid PLKO.1
backbone was used. The PLKO.1 CD99 sh RNA plasmid was generated by using the
following target sequence: CCATCTCTAGCTTCATTGCTT. Primers used to generate
this are as follows:
Forwad:CCGGCCATCTCTAGCTTCATTGCTTCTCGAGAAGCAATGAAGCTAGAGATG
GTTTTTG, Reverse:
AATTCAAAAACCATCTCTAGCTTCATTGCTTCTCGAGAAGCAATGAAGCTAGAGATG
G.
3.2.3 Transient transfection and viral induction
Transient knockdown using RNA interference, THP-1 and MV4-11 cells were
transfected with 10 nmol (10uL) of CD99-siRNA or off target-siRNA control per reaction
using 200 ul of electroporation buffer in an electroporator. For lentivirus infection, 293T
cells were transfected along with CD99-L, CD99-S or empty vector (EV) PLVX plasmids
and, psPAX and MD2.G packing plasmids using Calcium Phosphate Transfection Kits
according to manufacturer’s instructions (Clontech, CA, USA). Virus was collected 72
hours after transfection, filtered and concentrated using PEG reagent at 1:4 dilution,
pelleted 24-48 hours later and resuspended in RPMI supplemented with 10% FBS and
1% Antibiotics. To transduce AML cells, 1X10
5
suspension cells/well were seeded in
96 well plate and infected with 100uL virus and expanded after puromycin selection 72-
64
96 hours post infection. Two separate batches of lentiviral infection were performed for
THP-1, U937, and MOLM-13 cells. For the CD99-shRNA experiments, CD99-shRNA
plasmid was added to cells for 96 hours and cells were used for various assays.
3.2.4 Viability and colonogenic assays
1X10
5
cells/mL in a 96-well plate were treated with anti-CD99 mAb clone H036-1.1
(Thermofisher). 48-hours later, alamar blue assay was performed per the
manufacturer’s protocol (Invitrogen). For CD99 overexpression viability assay, stable
cells expressing CD99 L, CD99-S or EV cells from two separate viral transductions
were seeded at 1X10
5
cell/mL. The number of live cells was counted at 24, 48 and 72-
hours using trypan blue. The experiment was performed in duplicates for each set of
transduced cells. For primary blasts overexpression, viability was determined 96 hours
after infection with CD99 L, CD99-S or EV lentiviral particles using trypan blue.
Methylcellulose clonogenic assays were carried out by plating 5×10
4
primary blasts in
MethoCult (StemCell Technologies) in duplicate wells as per the manufacturer protocol
and colonies were counted 14 days later.
3.2.5 Migration Assay
Migration assay was performed using the modified Boyden chambers (cat.no:3436,
Corning, New York, USA) that consisted of Transwell-coated matrigel membrane filter
inserts with 8 µm pores in 24-well tissue culture plates. 1X10
5
cells in duplicates of THP-
1, MOLM-13 and isolated healthy PBMCs were re-suspended in 100ul RPMI media
containing 10% FBS and treated with 5µg/mL of mAbCD99 or PBS for 30mins on ice.
The cells were then seeded in the insert wells and 600 ul of RPMI media containing
65
10% FBS and SDF-1a were added to the lower chamber and incubated for 4 hours at
37°C. The experiment was performed twice. Following this, cells migrated towards
SDF-1a were analyzed by capturing multiple images of the lower chamber for each
well and analyzing them using ImageJ software. Similarly, for the overexpression
experiment, THP-1, MOLM-13 and U937 cells stably overexpressing CD99 L, CD99 S
or EV cells were seeded in duplicates and migration was analyzed.
3.2.6 Western blots
Protein was isolated from cells using the Pierce-Protease lysis buffer (cat.no:8788,
Thermo Fisher, MA, USA) which was supplemented with a protease inhibitor mix (cat.no:
A32959, Thermo Fisher, MA, USA). BCA protein assay reagent (Pierce) was used to
measure protein concentrations. 10-30 µg of total protein lysates was loaded to each lane
of SDS-PAGE gels. Transfer was performed using the Trans-blot (BioRad) semi-dry
transfer system. Membranes were blocked with 5% non-fat milk or BSA for 1 hours and
probed with indicated antibodies. Horseradish peroxidase (HRP)-conjugated secondary
antibodies (Santa Cruz Biotechnology) were used for detection. Anti-CD99 antibody used
was 013 (Thermofisher, MA5-12287), Anti- H2Axɣ (Santacruz, sc-517348), MDM2
(SantaCruz, sc-965), SRC (Cell Signaling, cat.no. 2123), P-SRC (Cell Signaling,
cat.no.6943), ERK (Cell Signaling, cat.no.9102), P-ERK (Cell Signaling, cat.no.9101 ),
Actin (Cell Signaling, cat.no.3700 ). All primary antibodies were incubated at 1:1000
dilution overnight. Anti-CD99 antibody was used at 1:500 dilution at room temperature
overnight. Following day, unbound primary antibody was washed away and stained with
secondary antibody at 1:5000 dilution for 1 hour are room temperature. Immunodetection
66
was achieved with the ECL super signal reagent and detected by a Bio-Rad ECL
machine.
3.2.7 RNA extraction and RNA expression quantification
Total RNA was extracted using TriZOL reagent (Invitrogen, CA, USA) according to
manufacturer’s instructions. cDNA was synthesized using SuperScript III reagents
(Invitrogen, CA, USA) according to the manufacturer’s protocol. Quantitative real-time
RT-PCR (qRT-PCR) was performed using commercially available TaqMan gene
expression assay primers and probes. The expression levels were normalized to B2M for
microRNA expression.
qPCR analysis for isoform analysis was performed using SYBR green assay. For CD99
isoform analysis, the following primers were used forward (CD99 L and CD99 S):
GTGATCCCCGGGATTGTG; CD99 L reverse: CTATTTCTCTAAAAGAGTACG; CD99 S
reverse: CCTAGGTCTTCAGCCATC.
3.2.8 Wright-geimsa assay
For wright-geimsa assay, THP-1 cells treated with 2.5µg/mL of mAbCD99 for 3 days
were washed and fixed onto a glass slides using a cytospin. Cells were then stained
with quick stain wright-geimsa stain for 1 min and imaged. Images were quantified
using imageJ.
67
3.2.9 BrdU staining assay
The APC BrdU Flow kit was used (act no. 552598, BD Biosciences, San Jose, USA)
and assay was performed according to manufacturer’s protocol. For the assay, all the
cells were synchronized by overnight starvation. Following this BrdU was added to the
cells for 12 hours and the assay was performed as per the manufacturer’s protocol.
3.2.10 Flow analysis
Cell surface expression of PE conjugated anti-CD99 (cat.no:12-0997-42, eBiosceince,
CA, USA), and APC conjugated anti-CD11b (cat.no:A18613) was performed by
incubating cells with 2.5uL of antibody on ice for 15 mis and washing away unbound
antibodies. Apoptosis assay was performed using the Annexin V and PI APC kit
according to the manufactures protocol (Invitrogen, Cat no:88-8007-72). For in vivo
experiments, cell-surface expression of human CD45 (huCD45: cat.no:25-0459-41,
eBioscience, CA, USA) were measured by staining mouse peripheral blood, bone
marrow and spleen cells for 30 mins on ice. Unbound anti-huCD45 washed away and
measured via flow cytometry. Mean florescence intensity (MFI) was used to quantify
data. Flow cytometry was performed on the LSRII BD Fortessa X20 flow cytometer and
processed using FloJo software (BD, Franklin Lakes, NJ, USA).
3.2.11 Aggregation assay
Cells overexpressing CD99-L or CD99-S (or EV) were seeded at a concentration of 1X10
5
cells /mL for 6 hours and images of cell aggregates were taken using a fluorescent
microscope.
68
3.2.12 ROS assay
ROS assay was performed using Cell ROX deep red reagent (Invitrogen, Cat
no.C10422) according to the manufacturer’s protocol and measured using flow
cytometry.
3.2.13 In vivo studies
For the xenograft experiments, 4- to 6-week-old NOD-scid /Il2rg
-/-
(NSG) mice were used.
For the THP-1 xenograft model, 2.5X10
6
THP-1 cells were injected via tail vein injection.
2 separate experiments were conducted, and results were summarized together. For the
first experiment mice were implanted with empty vector (n=3) and CD99 L (n=3). For the
second experiment mice were implanted with empty vector (n=3), CD99 L (n=3) and
CD99 S (n=3). For both the experiments, mice were sacrificed once the control mice were
sick (day 30-32 post injection). For the MOLM-13 experiment, mice were implanted with
2.5X10
6
cells of empty vector (n=6), CD99 L (n=6) or CD99 S (n=3) and were sacrificed
only when sick (day 19 post injection). For the primary cell experiment, cells were
transduced with CD99 L (or EV) for 96 hours. Prior to engraftment 4- to 6-week-old NOD-
scid /Il2rg
-/-
(NSG) mice were irradiated using the X-ray irradiator at a dose of 250 cGy
and 24 hours later, 1X10^6 cells were engrafted via tail vein in empty vector (n=3) and
CD99 L(n=3) mice. Mice were sacrificed four months after engraftment. For all the in vivo
experiments, bone marrow, peripheral blood, liver and spleen tissues were stained for
CD45 to confirm engraftment and analyzed using Flow cytometry.
69
3.2.14 Statistical Analysis
Student t test was used to determine the significance in means between two groups for
viability, apoptosis, and engraftment analysis. Mice survival analysis was performed by
the Kaplan Meier survival analysis based on Log-rank (Mantel Cox). For all analysis,
p < 0.05 was considered significant. All the data is presented as mean ± standard error
(SE).
70
3.3 Results
3.3.1 Characterization of CD99 expression in vitro
To examine the role of CD99 in AML in vitro, we assessed CD99 expression by flow
cytometry in nine AML cell lines (KG-1, KG-1A, MOLM13, MV4-11, Kasumi-1, THP-1,
NB4, U937, UOC-M1); we found higher CD99 surface expression in AML cell lines as
compared with healthy cord blood cells (Figure 3-1A). Western-blots revealed 28 and
32KDa bands corresponding to CD99-L and CD99-S isoforms in KG-1A, U937, and
Kasumi-1 cells, but only the lower band was recognized in THP-1, MOLM-13, CD34+
cells and two healthy donors PBMC lysates (Figure 3-1B).
Likewise, qPCR analysis showed that CD99 transcripts were upregulated in AML blast
samples (N=9) and AML cell lines (KG-1a, U937, THP-1, and MOLM-13) compared with
healthy donor PBMCs (N=3) and CD34+ cells. Transcript ENST00000482405.7 is higher
in CD34+ cells than in AML cell lines (Figure 3-1C). Since CD99 is known to have several
isoforms, qPCR primers used for this analysis and their specificity to various isoforms are
listed in Table 3.1.
71
Table 3.1 Primer match list for CD99 primer set 1 and set 2 for all CD99 transcripts
Transcript ID AA Primer
Forward-1
Primer
Reverse-1
Primer
Forward-2
Primer
Reverse-2
ENST00000381192.10 205 185 Y Y N N
ENST00000381187.8 204 169 Y Y N N
ENST00000381184.6 203 177 Y N N N
ENST00000482405.7 208 160 Y N Y Y
ENST00000611428.5 210 160 Y Y N N
ENST00000624481.4 212 184 Y Y N N
ENST00000381180.9 202 76 N N
72
Figure 3-1: CD99 isoform expression in AML blasts and cell lines in vitro.
CD99 surface expression in AML cells lines vs cord blood cells analyzed via flow
cytometry (A). CD99 protein expression in CD34+ cells, healthy donor PBMCS and AML
cell lines (B). CD99 isoform expression in CD34+ cells, healthy donor PBMCS, primary
blasts and AML cell lines analyzed through isoform qPCR
CD34+
Healthy Donor
Primary AML Blasts
AML Cell Lines
10
-3
10
-2
10
-1
10
0
CD99 isoform expression
(Normalized to Actin)
Primer Set 2
CD34+
Healthy Donor
Primary AML Blasts
AML Cell Lines
10
-6
10
-5
10
-4
10
-3
10
-2
CD99 isoform expression
(Normalized to Actin)
Primer Set 1
THP-1
U937
MOLM-13
CD99
Actin
A)
C)
B)
D)
73
3.3.2 Effect of CD99 knockdown in vitro
To study the effect of CD99 knock-down on cell viability, cells were transduced with
lentiviral-CD99-shRNA. Interestingly, this led to a significant decrease in primary AML
blasts viability (N=4; Figure 3-2A) and in AML cell lines (THP-1, MOLM-13, and U937)
(40-60%, P<0.05; Figure.3-2B). Knockdown was confirmed by qPCR in the AML cell lines
and primary blast (AML 4) (Figure 3-2C) and through western-blot in THP-1 and U937
cells (Figure 3-2D ). This was further confirmed in THP-1 and MV4-11 cells which were
transiently transfected by electroporation with CD99-siRNA resulting in ~35-50%
decrease in cell viability when compared with negative-control-siRNA (p=0.001 and
p=0.001 respectively; Figure 3-2E). Knockdown was confirmed through qPCR analysis of
CD99 and western blot analysis (Figure 3-2 F and G respectively).
74
Figure 3-2: Effect of CD99 knockdown on cell viability
Knockdown of CD99 through lentiviral-CD99-shRNA led to decrease in cell viability in
AML blasts and cell lines (A-D). Knockdown of CD99 through electroporation with CD99-
siRNA led to decrease in cell viability in cell lines (E-G)
EV
shCD99
CD99
Actin
THP-1
U937
AML 4
AML 9
AML 10
AML 11
0.0
0.5
1.0
1.5
Relative Fluorescence
Normalized to EV
EV
shCD99
**** *** *
THP-1 MOLM-13 U937
0.0
0.5
1.0
1.5
CD99 Expression
Normalized to EV
EV
shCD99
**
*
****
A)
E)
B)
D)
C)
F)
G)
MV4-11 THP-1
0
50
100
150
Viability
Relative to control
siControl
SiCD99
** ***
75
3.3.3 Effect of CD99 overexpression in vitro
Next, we established a gain-of-function approach to study CD99-L and CD99-S isoforms
functions. We generated stable cells to overexpress CD99-L and CD99-S by performing
lentiviral transduction in THP-1, U937 and MOLM-13 cells expressing variable
endogenous levels of CD99 isoforms. Overexpression was confirmed via flow cytometry
and western blot (Figure 3-3 A and B). Notably, CD99-L transduced cells had significantly
increased cell proliferation at 72-hrs compared with their respective empty vector (EV)-
controls and CD99-S transduced cells, respectively, counted by trypan-blue in THP-1
(1.78-fold, p<0.001; 1.61-fold, p<0.01), U937 (1.47-fold, p<0.001; 2.59-fold, p<0.0001)
and MOLM-13 cells (2-fold, p<0.0001; 1.45-fold, p<0.0001; Figure 3-3C). This was also
confirmed by alamar-blue assay (Figure 3-3D) suggestive of enhanced metabolic activity.
We further assessed cell proliferation using BrdU assay in THP-1 cell line. THP-1 cells
overexpressing CD99-L displayed a higher percentage of BrdU staining compared with
EV cells (1.6 -fold; p=0.006; Figure 3-3E) suggestive of increased DNA synthesis in these
cells.
76
Figure 3-3: Effect of CD99-L and S overexpression on viability of AML cells
CD99-L and S stable cells were generated using lenti viral transduction. Overexpression
was confirmed using western blot and flow cytometry. Viability was analyzed using trypan
blue, alamar blue assay and BrdU staining in AML cell lines (A-E)
Empty Vector
CD99 Long OE
CD99 Short OE
THP-1 U937 MOLM-13
CD99
U937 THP-1
EV CD99 L CD99 S
0.0
0.5
1.0
1.5
2.0
Relative Fluorescence
Normalized to EV
U937
****
****
EV CD99 L CD99 S
0.0
0.5
1.0
1.5
2.0
Relative Fluorescence
Normalized to EV
MOLM-13
****
*
EV CD99 L CD99 S
0.0
0.5
1.0
1.5
2.0
Relative Fluorescence
Normalized to EV
THP-1
****
**
THP-1 EV THP-1 CD99 L
A)
E)
B)
D)
C)
77
We also ectopically overexpressed CD99-L using lentiviral transduction in AML blasts
(n=7, Table 3.2). Overexpression of CD99-L was confirmed using western-blot and
fluorescence microscopy for GFP (Figure 3-4A and B respectively ). Higher cell number
was observed in lenti-CD99 blasts compared with lenti-EV transduced blasts 96-hrs after
viral transduction (2.8-fold; p<0.0001, Figure 3-4C). To determine the effect of CD99 on
colony formation, 24-hrs after lentiviral transduction, 5X10
5
primary blasts were seeded
in MethoCult in duplicates, and colonies were counted on day-14. An increase in the
number of colonies was observed in 3/6 patient samples overexpressing CD99 compared
with their respective controls; AML-3 (1.5-fold, p=0.02), AML-4 (1.5-fold, p=0.02) and
AML-5 (3-fold, p=0.001) (Figure 3-4D).
Furthermore, we ectopically expressed CD99-L and CD99-S in three additional AML
blasts (Figure 3-4E). Cell viability was measured 96-hrs after transduction using trypan
blue and alamar blue. A significant increase in the number of live cells was observed in
cells transduced with CD99-L compared with lenti-EV (1.51-fold; p<0.0001) and CD99-S
transduced blasts (1.3-fold; p<0.0001) (Figure 3-4F). An increase in the number of
colonies was observed in 1/3 patient samples overexpressing CD99-L isoform compared
with their respective controls; AML-10 (2-fold, p=0.04) (Figure 3-4G).
In CD34+ cells, we observed no significant change in the number of viable cells between
cells transduced with CD99-L, -S isoform or EV (Figure 3-4H) at 96-hrs post-transduction.
Transducing cells with lentiviral-CD99-shRNA resulted in slight decrease in cell viability
(Figure 3-4I).
78
Table 3.2 Patients details
Patient ID AML Status sample FLT3 Mutation
AML 1 Diagnosis NA
AML 2 Diagnosis NA
AML 3 Diagnosis NA
AML 4 Diagnosis ITD
AML 5 Relapse ITD
AML 6 Diagnosis WT
AML 7 Diagnosis WT
AML 8 Relapse ITD
AML 9 Diagnosis NA
AML 10 Diagnosis NA
AML 10 Diagnosis NA
79
Figure 3-4: Effect of CD99-L and S overexpression on viability of AML cells
Primary blasts were transfected with CD99-L and S isoforms. Overexpression was
confirmed via western blots and fluorescent microscopy. Viability was measured using
trypan blue assay and colony formation assay was performed using methocult.
AML2 AML 3 AML 1
CD99 OE - + - + - +
CD99
GAPDH
EV CD99 L
AML 1
AML 2
AML 3
AML 4
AML 5
AML 7
0
10
20
30
40
100
120
140
No. of Colonies
Relative to EV
EV
CD99 L OE
* *
*
EV CD99 L CD99 S
A)
C)
B)
D)
F)
E)
G)
CD99 S OE
CD99 L OE
EV
shCD99
EV
H)
I)
80
Conversely, long-term culture of CD99-L transduced cells showed a subsequent
decrease in cell viability, and cells could not be maintained in culture for more than 4-6
weeks. To validate this, we performed long term culture assay in THP-1 cells for 10 days
starting roughly 2 weeks post viral transduction. Proliferation of CD99-L cells started to
decline by day 5 of initial serum stimulation compared with EV and CD99-S cells, even
when cell density and nutrients were accounted for (Figure 3-5).
Figure 3-5: Long term culture assay for THP-1 cells
Trypan blue assay was performed in CD99-L and S OE cells starting D1 to D10 using
trypan blue assay.
81
3.3.4 Ectopic expression of CD99-L enhances ROS levels, DNA damage and
induces cell apoptosis
Because the initial enhanced proliferation of CD99-L cells was serum induced and
reversed with further expansion in vitro, we speculated that the serum induced cell growth
would stimulate higher production of ROS in these cells. Indeed, THP-1 cells transduced
with CD99-L exhibit 2.5 and 1.6-fold increase in ROS levels compared with CD99-S and
EV cells, respectively measured via flow cytometry (Figure 3-6A) and quantified for MFI
(Figure 3-6B). Because of their higher ROS levels, we asked whether DNA damage is
increased in these cells. Western-blot analysis showed that CD99-L cells exhibit higher
level of the DNA damage marker H2Axɣ compared with CD99-S and EV cells (Figure 3-
6 C). Consistently, apoptosis was also significantly enhanced in CD99-L transduced cells
measured by annexin-V measurements in THP-1 cells in (CD99-L vs EV: 3.48-fold,
p=0.001; CD99-L vs CD99-S: 6.32-fold, p=0.0027), U937 cells (CD99-L vs EV: 3.26-fold,
p=0.07; CD99-L vs CD99-S: 3.67-fold, p=0.10), and MOLM-13 cells (CD99-L vs EV: 4.88-
fold, p=0.0032; CD99-L vs CD99-S: 4.2-fold, p=0.0042), when measured 24 hours after
cells were seeded 0.5X10
6
cells/mL. Representative annexin V stain (Figure 3-6D) and
quantified annexin v % (Figure 3-6E). The enhanced apoptosis was also confirmed by the
increase of cleaved caspase-3 (Figure 3-6F).
82
A)
B) EV
CD99-L
CD99-S
C)
83
Figure 3-6: Ectopic expression of CD99 long isoform enhances ROS levels, DNA
damage and induces cell apoptosis
ROS assay was performed in THP-1 cells overexpressing CD99-L and S isoforms and
analyzed via flow cytometry (A-B). DNA damage was analyzed by blotting for H2Axɣ (C).
Apoptosis was measured using annexin V assay through flow cytometry analysis and
blotting for cleaved- caspase 3 (D-F).
D)
E)
F)
84
3.3.5 Ectopic expression of CD99-L isoform induces myeloid differentiation and
reduces cell migration
Previous studies have demonstrated that CD99 homotypic interaction in CD99 expressing
cells (Bernard et al., 1995; Byun et al., 2006; Cerisano et al., 2004) play a role in trans-
endothelial migration of monocytes (Schenkel et al., 2002). Thus, we asked which isoform
is responsible for cell homotypic interaction and whether they affect cell migration and
myeloid differentiation differently. When cells were seeded at 1X10
5
cells/mL per well in
a 6-well plate and images for cell aggregation were taken six hours later, THP-1 stable
cells displayed higher cell aggregation capacity compared with empty vector and CD99-
S cells, (representative image for THP-1 cells, Figure 3-7A).
To determine the effect of CD99 overexpression on cell migration, THP-1, U937, and
MOLM-13 cells (1X10^
5
cells) stably overexpressing CD99-L, -S or EV were seeded in a
transwell chamber for 4-hrs and migration towards SDF-1a was analyzed. Our results
show that CD99-L overexpression resulted in decrease cell migration compared with EV
cells and CD99-S cells in THP-1(CD99-L vs EV: 70% decrease, p<0.0001; CD99-L vs
CD99-S: 66% decrease, p<0.0001), U937 (CD99-L vs EV: 80% decrease, p<0.0001;
CD99-L vs CD99-S: 83% decrease, p<0.0001) and MOLM-13 cells (CD99-L vs EV: 80%
decrease, p<0.0001; CD99-L vs CD99-S: 60% decrease, p=0.0032) (Figure 3-7B).
Representative images for migration assay (Figure 3-7C).
Consistently, CD99-L expressing cells showed an increase in CD11b expression
measured by flow cytometry 24 hours after cells were seeded in THP-1 (CD99-L vs EV:
2.055-fold, p=0.0027; CD99-L vs CD99-S: 1.63-fold, p=0.043), U937 (CD99-L vs EV:
85
1.56-fold, p=0.01; CD99-L vs CD99-S: 1.29-fold, p=0.11) and MOLM-13 (CD99-L vs EV:
1.89- fold, p<0.0001; CD99-L vs CD99-S: 1.68-fold, p<0.079) (Figure 3-7D).
A)
THP-1:EV THP-1:CD99 L THP-1:CD99 S
B)
MOLM-13
EV
CD99 L
CD99 S
U937 THP-1
C)
86
Figure 3-7: Ectopic expression of CD99-L isoform induces myeloid differentiation and
reduces cell migration
Aggregation assay was performed by seeding THP-1 cells and imaging for cell
aggregates 6 hours later (A). Migration assay was performed using trans well plates and
quantifying cells that migrated towards SDF-1a (B). Cell differentiation was measured by
flow cytometry analysis of CD11b (C).
Empty Vector
CD99 Long OE
CD99 Short OE
D)
87
3.3.6 Overexpression of CD99-L isoform delayed leukemia engraftment in THP-1
murine model
Next, we investigated the effect of ectopic expression of CD99 isoforms in murine
leukemia models. THP-1 cells stably overexpressing CD99-L (n=6) or CD99-S (n=3) or
EV (n=6) were injected into NOD-scid /Il2rg
-/-
(NSG) mice. Mice were sacrificed on day
30-32 post implantation. Liver, spleen, bone marrow and peripheral blood were collected.
Notably, mice engrafted with CD99-L cells had smaller spleens compared with EV mice
(0.04 vs 0.07 g; p=0.010) and CD99-S mice (0.04 vs 0.068 g; p=0.0003) (Figure 3-8A
and B). hCD45 flow analysis revealed that CD99-L mice had significantly less bone
marrow engraftment compared with the EV mice (7.29% vs 19.47 %; p=0.02), and CD99-
S mice (7.29% vs 18.9 %; p=0.04) (Figure 3-8C). Similarly, CD99-L mice had significantly
less peripheral blood engraftment compared with the EV mice (14.73% vs 84.52 %;
p=0.0002), and CD99-S mice (14.73% vs 83.3 %; p=0.006; Figure 3-8D).
88
Figure 3-8: Overexpression of CD99-L isoform delayed leukemia engraftment in THP-1
murine model
Spleen weight and images of blank, EV, CD99-L and CD99-S mice at the time of sacrifice
(A-B). Bone marrow and peripheral blood engraftment of THP-1 cells in EV, CD99-L and
CD99-S mice determined by quantitative analysis of CD45+ cells through flow cytometry
(C-D).
A) B)
D) C)
Blank
EV
CD99L
CD99S
89
3.3.7 Overexpression of CD99-L isoform delayed leukemia engraftment in MOLM-
13 murine model
In the MOLM-13 murine model, mice were engrafted with CD99-L, CD99-S and EV mice
(n=6 for EV and CD99-L, and n=3 for CD99-S) and sacrificed on day 19 post cell
transplantation. Mice engrafted with CD99-L cells had significantly smaller spleens
compared with the EV mice (0.048 vs 0.11g; p=0.004) and CD99-S mice (0.048 vs 0.10g;
p=0.026) (Figure 3-9A-B). Flow cytometry analysis of hCD45 for engraftment revealed
that CD99-L mice had significantly less engraftment compared with the EV mice in the
bone marrow (25.38 vs 59.57%, p=0.003; Figure 3-9 C), peripheral blood (15.03 vs
50.5%, p=0.0051; Figure 3-9 D). H&E staining of the liver, spleen, and sternum showed
that EV and CD99-S tissues presented a higher percentage of infiltrated blasts compared
with the CD99-L mice (Figure 3-9E). We also performed additional pathology analysis
using immunostaining for CD45 and Ki67 on collected tissues: spleen (Figure 3-9F), liver
(Figure 3-9G) and sternum (Figure 3-11H). We found an increased CD45 (CD99-L vs EV,
p=0.004; CD99-L vs CD99-S, p=0.13) and Ki67 (CD99-L vs EV, p=0.0002; CD99-L vs
CD99-S, p=0.17) staining in EV tissues and CD99-S tissues compared with CD99-L
tissues, confirming a decrease in leukemia engraftment in mice with CD99-L cells (Figure
3-9I and J).
90
Blank
EV
CD99L
CD99S
A)
B)
D)
C)
91
Figure 3-9: Overexpression of CD99-L isoform delayed leukemia engraftment in MOLM-
13 murine model
Spleen weight and images of blank, EV, CD99-L and CD99-S mice at the time of sacrifice
(A-B). Bone marrow and peripheral blood engraftment of MOLM-13 cells in EV, CD99-L
and CD99-S mice determined by quantitative analysis of CD45+ cells through flow
cytometry (C-D). Representative H&E staining images of Liver, spleen and sternum (E).
Representative images of immunostaining for CD45 and Ki67 on collected tissues of
spleen, liver and sternum (F-H). Quantitative analysis of Ki67 and CD45 cells in the liver
tissues of mice engrafted with MOLM-13 EV, CD99-L and CD99-S cells quantified using
ImageJ (I-J).
H&E
EV
CD99 L
Liver
Spleen
CD99 S
Sternum
Spleen
EV
CD99 L
CD45
Ki67
CD99 S
CD45 Ki67
Liver
Sternum
CD45 Ki67
E)
F) G)
H)
I) J)
92
3.3.8 Overexpression of CD99 L isoform delayed leukemia engraftment in primary
leukemia model.
To validate these findings in primary blasts murine model, we engrafted primary AML
samples (AML-4) transduced with CD99-L (n=3) or EV (n=3) in sublethally irradiated
mice. Mice were sacrificed four months post-engraftment. CD99-L isoform resulted in
significant decrease in spleen weight (0.03 vs 0.05 g; p=0.04; Figure 3-10 A-B). Flow
cytometry analysis of hCD45 revealed that CD99-L mice had less engraftment though not
significant compared with the EV mice in the bone marrow (1.52 vs 4.76%, p=0.01; Figure
3-10 C), and a significant decrease in hCD45 + cells in peripheral blood (7.5 vs 26.9 %,
p=0.005; Figure 3-10 D).
93
Figure 3-10: Overexpression of CD99-L isoform delayed leukemia engraftment in
primary leukemia model.
Primary AML cells overexpressing EV (N=3) or CD99-L (N=3) were engrafted in mice. N-
O) Spleen weight and images of EV and CD99-L mice at the time of sacrifice (four-month
post-transplantation). P-Q) Bone marrow and peripheral blood engraftment of primary
AML cells in EV and CD99-L mice determined by quantitative analysis of CD45+ cells by
flow cytometry.
Blank
EV
CD99L
A)
B)
D)
C)
94
3.3.9 CD99 monoclonal antibody induces anti-leukemic effect
AML patient blasts (n=7) incubated with monoclonal CD99 antibody (CD99mAB: 20
µg/mL) showed a significant decrease in cell viability 48-hrs later (0.5±0.02-fold;
p<0.0001, Figure 4-11A). To determine the effect of CD99 antibody on their ability to form
colonies, long-term colony formation assay was performed. In cells treated with
CD99mAb, a decrease in colony formation was observed in 3/6 patient samples; AML-2
(0.5-fold, p=0.02), AML-6 (0.65-fold, p=0.03) and AML-7 (0.36-fold, p=0.01) (Figure 3-
11B).
CD99mAB treatment (5 µg/ml) of THP-1 and MOLM-13 cells resulted in a 50% decrease
in cell viability at 48 hours (p<0.0001, p<0.001 respectively). There was no effect on
healthy donor PBMCs (Figure 3-11C). Furthermore, the decrease in viability was
accompanied by an increase in Annexin-V apoptosis stain in THP-1 (7.35-fold, p=0.04;
Figure 3-11D and E). We also performed a migration assay to examine the effect of CD99
antibody (5 µg/mL) on THP-1 and MOLM-13 cells migration toward SDF1a using transwell
chambers. Four hours after treatment with the monoclonal antibody we found a 70%
decrease in cell migration in both THP-1 and MOLM-13 cells (p=0.01 and p=0.004
respectively; Figure 3-11 F and G). Similar to the effect of CD99 overexpression, CD99
mAB treatment of THP-1 cells triggered an increase in CD11b positive population of cells,
indicative of cell differentiation (2.79-fold, p=0.04; Figure 3-11 H). Consistently, wright-
giemsa stain revealed that CD99 monoclonal antibody (2.5 µg/ml) induced differentiation
with morphology resembling more mature cell fates (Figure 3-11 I).
95
B)
C)
A)
96
THP-1
MOLM-13
Control CD99 mAB
PBMC
Control CD99 mAB
Annexin V
PI
E) D)
G) F)
97
Figure 3-11: CD99 monoclonal antibody induces differentiation and reduces cell
migration and colony formation in AML cells
Treatment with mAbCD99 reduced Cell viability and colony formation in AML blasts and
AML cell lines. (A-C). Increased Apoptosis in THP-1 and MOLM-13 cells (D-E). Reduced
migration of THP-1 and MOLM-13 cells (F-G). Increase cell differentiation of THP-1 cells
(H-I).
THP-1
CD11b
CD99 mAB
Control
CD99 mAB Control
H)
I)
98
3.3.10 CD99 modulates ERK and SRC signaling pathways in AML cells
Because the initial enhanced proliferation of CD99-L expressing cells was serum
stimulated and transient, we speculated that growth factor induced signaling pathways
are affected by CD99. In EWS and Osteosarcoma, CD99 was found to modulate ERK
pathways(Guerzoni et al., 2015b; Manara et al., 2016). Thus, we examined the effect of
ectopic expression of CD99 isoforms on AKT and ERK kinase activity. We also assessed
changes in SRC signaling, previously shown to be affected by CD99(Chung et al., 2017;
Lee et al., 2017a). CD99-L induces transient upregulation of P-ERK, P-AKT and P-SRC
compared with CD99-S and EV expressing cells (Figure 3-12A and B) measured 72-hrs
post viral transduction. CD99 knockdown (against both S and L) decreased P-ERK but
increased P-AKT and P-SRC (THP-1 cells express mainly CD99-S isoform, Figure 3-
12C). In EWS, treatment with CD99-antibody induced cell death via rapid decrease of
MDM2 and activation of IGF-1R and ERK signaling(Guerzoni et al., 2015b; Manara et al.,
2016). Thus, we asked whether MDM2 is affected by CD99 expression. CD99-L cells
exhibit lower MDM2 protein levels compared with CD99-S and EV cells (Figure 3-12 D).
Also, MDM2 is reduced in cells treated with CD99mAb 2-9hrs post-treatment (Figure. 3-
12E), yet P-ERK was not changed (Figure 3-12E and F). Because MDM2 is known to
ubiquitinate IGF-1R, we speculated that CD99-induced reduction in MDM2 may
upregulate IGF-1R downstream target genes such as Cyclin D1(Warsito et al., 2012).
CCND1 mRNA levels in CD99-L cells were higher than that in CD99-S (1.75-fold; p=0.02)
or EV (2.8-fold; p<0.0001) (Figure 3-12G). CD99 knockdown also decreased CCND1
mRNA (p<0.0001, Figure 3-12H). We also examined P-ERK and P-SRC in stable cells
maintained in culture for >2 weeks (Figure 3-12I). Contrary to the early effect, we found
99
a dramatic decrease in P-SRC in CD99-L cells. Similarly, cells treated with anti-CD99mAb
showed a rapid increase in P-SRC observed within 1-2hrs followed by a decrease in P-
SRC observed 3-9hrs post-treatment (Figure 3-12J and K).
100
Figure 3-12: Effect of CD99 on ERK and SRC signaling pathways in AML cells.
Transient CD99-L overexpression increased P-ERK, P-AKT and P-SRC levels (A-B).
CD99 knockdown decreased P-ERK, but increased P-AKT and P-SRC (C). CD99 L
isoform cells and CD99 mAB exhibited lower levels of MDM2 (D-E). CCND1 mRNA levels
were increased in CD99-L cells and decreased in CD99 knockdown cells (G-H). CD99-L
stable cell had decreased P-ERK, and P-SRC levels (I). CD99 mAb treatment increased
P-SRC initially and then decreased in P-SRC (J-K)
B)
C)
H) G)
E) D)
I)
J)
K)
A)
F)
101
3.4 Discussion
CD99 is expressed as short and long isoforms that have differential expression pattern
depending on the tissue context. However, the different roles of the two isoforms in both
normal and malignant tissues is very limited. Investigating the role of the different isoforms
in preclinical studies is crucial to gain insight into the role of CD99 in AML.
We found higher surface CD99 expression in AML cells lines than in cord blood cells. We
also observed varying levels of CD99 isoform protein expression in heathy donor PBMCs
and AML cell lines. AML cell lines had higher CD99 protein expression as compared to
PBMCs, consistent with results from clinical data analysis. However, determining the
predominant isoform is challenging since western blot might be limited in its ability to
compare isoform levels by the antibodies used and the varying levels of epitope
recognition (antibody body used in this study recognizes the O13 epitope) particularly
because CD99 is highly glycosylated which may also affect the size of the band.
Though apoptosis and proliferation assays were conducted together, we found that
although there was an increase in proliferation confirmed by alamar blue, trypan blue and
Brdu assay, there was also an increase in apoptosis confirmed through increase in
Annexin-V staining and increase in cleaved caspase-3; suggesting that these cells are
more sensitive to serum stimulation and depletion. Based on this, we then performed a
long-term proliferation assay and found that there was an increase in proliferation of cells
up to day 5 followed by a decrease in cell proliferation observed till day 10 even when we
accounted for nutrients and cell density from the start. We speculated that these cells
would exhibit higher proliferative potential during the first 2 weeks of viral transduction
with repeated serum stimulation, then the larger number of dead cells start to accumulate,
102
and cells become unhealthy and difficult to maintain for long term. Additionally, apart from
an increase in cell apoptosis in CD99-L cells, these cells also had increased ROS levels,
cleaved caspase-3 and pH2AX that are associated with DNA damage. This phenotype is
consistent with oncogenic stress where there is an initial increase in proliferative activity
brought upon by arrest in cell proliferation(Michaloglou et al., 2005).
Based on this we speculated that growth factor induced signaling pathways are affected
by CD99. Both in Ewing Sarcoma and osteosarcoma, CD99 was found to modulate ERK
and SRC signaling pathways (Hahn et al., 2000; Zucchini et al., 2014). Based on this we
tested the effect of ectopic expression of CD99 isoforms on AKT and ERK kinase activity.
We found that initially, P-ERK, P-AKT and P-SRC levels were higher in cells expressing
CD99-L isoform compared with CD99-S and EV expressing cells which is consistent with
the increase in cell proliferation observed. On the other hand, we found a dramatic
decrease in both P-ERK and P-SRC in CD99-L expressing stable cells cultured for longer
time (2-4 weeks). This effect of CD99 L ectopic expression is also consistent with previous
studies showing that CD99-L upregulation increases caveolin resulting in reduced P-
SRC(Scotlandi et al., 2007).
Furthermore, our data suggest that the homotypic interaction of CD99-L isoform but not
the short isoform results in cell aggregation, which could potentially promote cell
apoptosis. This could result in the decreased P-ERK and P-SRC levels observed over
long term culture. This effect is also consistent with the previously published data where
CD99 ligation using a monoclonal antibody in MDA-MB-231 cells overexpressing CD99-
L isoform resulted in a 4-fold increase in cell aggregation(Byun et al., 2006). CD99 is also
known to cause homotypic aggregation of cortico-thymocytes(Bernard et al., 1995).
103
In Ewing Sarcoma, triggering with CD99 antibody induced cell death via rapid decrease
of MDM2 and activation of IGF-1R and RAS-Rac1 signaling(Manara et al., 2016).
Because of the effect we observed on P-ERK, we asked whether MDM2 levels is also
affected in cells ectopically expression CD99. We found that CD99 L isoform cells exhibit
lower levels of MDM2 compared with CD99 S and EV expressing cells. We also observed
a reduction in MDM2 in cells treated with CD99 mAB at 2-9 hours post antibody treatment,
yet P-ERK was not changed in these cells. Because MDM2 is known to ubiquitinate IGF-
1R, we speculated that CD99 induced reduction in MDM2 would upregulate IGF-1R
downstream target genes such as CyclinD1. We found upregulation of CCND1 mRNA
levels in CD99-L cells compared with CD99-S. On the other hand, CD99 knockdown
resulted in significant decrease in CCND1 mRNA levels which explains the observed
decrease in cell proliferation upon.
Overall, we speculate that the upregulation of AKT, ERK, SRC and CCND1 post CD99
viral transduction may explain the early increase in cell proliferation, and possibly
increase the CD99 homotypic interaction which could then result in increased cell
apoptosis as well as an increase in caveolin expression in turn downregulating P-SRC.
Consistently, in vivo data showed that overexpression of CD99-L isoform but not the S
isoform delayed disease progression and repressed bone marrow engraftment of THP-1,
MOLM-13, and primary leukemic blasts. Whether CD99 interaction with murine
microenvironment plays a role in inhibiting leukemia cells homing to the bone marrow is
unclear and warrant further investigation.
104
Importantly, targeting CD99 using mAB resulted in an increase in anti-leukemia activity in
vitro. In addition to validating some of the activity of the CD99 mAB in AML shown by
Chung(Chung et al., 2017), such as the effect on apoptosis and cell viability, our study
demonstrates other phenotypic effects of CD99 mAB treatment that resemble that of the
ectopic expression of CD99-L isoform, this includes the effect on cell migration, apoptosis,
and differentiation, suggesting an agonistic mechanism of function by which the antibody
works. This novel finding is critical to understanding the function of CD99 in AML.
Altogether, our study expands the knowledge needed for the preclinical development of
CD99 as a therapeutic target in AML.
Based on the findings of anti-leukemic activity of the monoclonal antibody against CD99,
our next goal was to further develop a therapeutic approach to target CD99.
105
Chapter 4 : Development of a therapeutic CD99
scFv nanoworm
4.1 Introduction
In chapter 3 we found that monoclonal antibody (MAb) against CD99 presented as a
successful therapeutic approach. MAbs have become a vital tool for targeted therapy in
various malignancies and have recently received a lot of clinical attention. A few MAbs
specific to CD99 have been generated by different groups in the past, none have made it
to clinical trials yet.
MAbs are limited due to high cumbersome development process and costs. An alternate
solution is the use of single-chain antibody fragments (scFv). scFvs are about 30 kDa
consisting of variable regions of heavy (VH) and light (VL) chains, joined by a flexible
peptide linker. They possess specificity equivalent to MAbs and more readily manipulated
through recombinant protein engineering. scFvs can be more reasonably produced in
Escherichia Coli(Skerra and Pluckthun, 1988) as compared to expensive production of
MAbs in mammalian systems(Hu et al., 2007). However, scFvs are challenging to purify
since they lack stability(Hayhurst and Harris, 1999).
To overcome these limitations, we have used anti-CD99 scFv fused with to an elastin-like
polypeptide (ELP), A192. ELPs are derived from human tropoelastin and are genetically
engineered protein polymers consisting of an amino acid sequence (VPGXG)n. “X”
represents a guest amino acid, and “n” indicates the number of the pentameric
repeats(Despanie et al., 2016). Crucially, ELPs undergo reversible phase separation
above a tunable transition temperature and can be purified without
106
chromatography(Christensen et al., 2009). In this chapter, we test the in vitro and in vivo
efficacy of a new nanoworm against CD99 as a potential therapy for AML.
107
4.2 Experimental procedures
4.2.1 Cloning of α-CD99-A192
α-CD99-A192 and α-FLT3 A192 were generated by Mincheol Park from Andrew Mackay
Lab. Briefly, the α-CD99 scFv gene was fused to the amino terminus of an ELP called
A192, in the pET-25b(+) vector, resulting in α-CD99-A192. Between the gene and A192,
a thrombin cleavage site, encoding for LVPRGS, was introduced.
The α-CD99 scFv DNA sequence used was :
ATGGCTGAAGTACAGTTAGTGGAATCAGGAGGTGGTTTAGTACGCCCAGGTGGTT
CTTTACGCCTTAGCTGTGCAGCTTCTGGCTTCACATTTAGTTCCTACGCAATGAGTT
GGGTCCGTCAAGCGCCGGGCAAAGGATTAGAGTGGGTGAGCGCAATTAGCGGTT
CAGGGGGTTCGACCTACTACGCAGACAGTGTCAAGGGTCGCTTTACAATTTCTCG
CGATAATTCTAAGAATACCTTGTATTTGCAAATGAACTCGCTTCGTGCGGAAGATAC
TGCAGTGTACTATTGTGCAAAAAGCCACAAACGCTTTGACTACTGGGGACAGGGAA
CCTTAGTGACGGTTTCACGCGGAGGCGGTGGATCTGGCGGCGGAGGGTCGGGG
GGAGGTGGCTCATCAGAATTGACACAGGACCCTGCCGTGTCAGTTGCCCTGGGG
CAAACCGTACGCATTACATGCCAGGGTGATTCACTTCGTTCTTACTATGCTTCCTG
GTACCAGCAAAAGCCAGGCCAAGCCCCCGTGCTGGTTATCTATGGGAAAAACAAC
CGCCCGTCGGGCATTCCAGACCGCTTTTCCGGTTCTTCTTCAGGTAATACGGCAA
GTCTGACCATTACTGGAGCACAAGCCGAGGACGAGGCAGACTACTATTGTAATTC
GAGTTTCCCTCGCACCAGTTCCGTAGTGTTTGGGGGCGGAACTAAATTGACAGTG
CTTGGA.
108
α-CD99 scFv were cloned into pET-25b(+) vector and the fusion protein was produced in
Clearcoli® BL21 (DE) Electrocompetent Cells (60810, Lucigen, WI, USA) using
electroporation.
4.2.2 α-CD99-A192 competitive binding study
For the binding study, MOLM-13, MV4-11 and U937 cells were incubated with either
rhodamine-labeled A192 or a-CD99-A192 (1, 10, and 25 µM) for 30 minutes on ice. Cells
were then washed to remove unbound a-CD99-A192. Bound rhodamine-labeled A192
and α-CD99-A192 were measured by assessing the shift in the mean fluorescence
intensity (MFI) by flow cytometry.
For the competitive binding study, MOLM-13 cells overexpressing CD99 receptors were
treated with 2.5 µg/ml or 5.0 µg/ml of αCD99 monoclonal antibody (mAb), or 5 µg/ml of
IgG for 30 minutes at 4 °C. Then the cells were washed with PBS two times, and then
they were treated with 1.8 µM of rhodamine-labeled α-CD99-A192 for 30 minutes at 4 °C.
MOLM-13 cells which were not treated with antibodies were treated with 1.2 µM of
rhodamine-labeled A192 as a control. After the binding, the cells were washed with PBS
two times and bound rhodamine-labeled A192 and α-CD99-A192 were measured by
assessing the shift in the mean fluorescence intensity (MFI) by flow cytometry. Data were
analyzed by normalizing MFI to unstained cells.
4.2.3 Viability assays
Cell viability was analyzed by incubating 0.5×10
5
cells with either A192 or a-CD99-
A192 treated at 1,10, 25 and 50 µM. Cells were treated for 30 minutes on ice and were
109
then seeded in a 12 well plate at a concentration of 5×10
5
/mL. The number of live cells
was counted using trypan blue (cat.no:15250-061, Life Technologies, Carlsbad, USA)
at 72 hours, and cell viability was determined by the ratio of the number of live cells in
treated samples to that in untreated cells. Experiments were performed three times. To
determine the IC50 for U937, MOLM-13, and MV4-11, cells were seeded in triplicates
in a 96 well plate at 5×10
5
cells/mL and treated with α-CD99-A192 (0.01, 0.1, 0.25, 0.5,
1, 10, 25, 50, and 100 µM). To measure the viability, 72 hours after seeding cells, 10
µl of alamar blue (cat no: DAL 1100, Invitrogen, Carlsbad, USA) was added per well,
and incubated for four hours at 37 °C, following which fluorescence was measured on
a synergy H1 microplate reader. The change in viability was calculated by normalizing
the fluorescence of treated cells to that of untreated cells. IC50 was calculated based
on non-linear regression.
4.2.4 Flow cytometry analysis
In vitro apoptosis assay was performed using the Annexin V and PI APC kit according
to the manufactures protocol (Invitrogen, Cat no:88-8007-72). The percentage of APC
+
cells were compared among groups. For in vivo experiments, cell-surface expression
of human CD45 (huCD45: cat.no:25-0459-41, eBioscience, CA, USA) were measured
to confirm engraftment. Mouse peripheral blood, bone marrow and spleen cells were
stained with PE-Cy7-A conjugated anti-huCD45 for 30 mins on ice. Unbound anti-
huCD45 washed away and measured via flow cytometry. Mean florescence intensity
(MFI) of PE-Cy7-A was used to quantify data. Flow cytometry was performed on the
110
LSRII BD Fortessa X20 flow cytometer and processed using FloJo software (BD,
Franklin Lakes, NJ, USA).
4.2.5 In vivo efficacy studies
Animal protocols were approved by the Institution for Animal Care and Use Committee of
the University of Southern California. For xenograft experiments, 2.5×10
6
MOLM-13 cells
were administered via tail vein injection into 4- to 6-week-old female NOD-scid /Il2rg
-/-
(NSG) mice purchased from Jackson Laboratory (Bar Harbor, ME). For α-CD99-A192
efficacy studies, engrafted mice were treated with 200 µL of 220 µM A192 (n=4) or α-
CD99-A192 (n=4) via tail vein on Day 7, 10, 13 and 16 post engraftments. Mice were
euthanized on Day 21. For α-FLT3-A192 efficacy studies, engrafted mice were treated
with 200 µL of 220 µM A192 (n=8) or α-CD99-A192 (n=8) via tail vein on Day 7, 10, 13
and 16 post engraftments. Mice were euthanized on Day 17. For both experiments’
spleen, bone marrow and blood were collected and stained for huCD45 and analyzed
using flow cytometry.
4.2.6 Statistical Analysis
Student t test was used to determine the significance in means between two groups for
viability, apoptosis, and engraftment analysis. Mice survival analysis was performed by
the Kaplan Meier survival analysis based on Log-rank (Mantel Cox). For all analysis,
p < 0.05 was considered significant. All the data is presented as mean ± standard
deviation (SD).
111
4.3 Results
4.3.1 a-CD99-A192 binds specifically to CD99 surface protein in vitro
The binding affinity of a-CD99-A192 was initially assessed to confirm the specificity of
a-CD99-A192 in CD99
+
AML cell lines MOLM-13, MV4-11, U937 and CD99
-
293T cells.
Flow cytometry analysis revealed that rhodamine labeled a-CD99-A192 bound
specifically to MOLM-13 as compared to A192 at 1uM (2.4-fold; p=0.04) and 10uM (3.1-
fold; p=0.01) (Fig 4-1A). In MV4-11 a-CD99-A192 bound specifically at 1uM (1.7-fold;
p=0.001) and 10uM (2.8-fold; p=0.02) (Fig 4-1B). Similarly, in U937 cells, a-CD99-A192
bound specifically at 1uM (1.5-fold; p=0.002) and 10uM (1.9-fold; p=0.0001) (Fig 4-1C).
a-CD99-A192 did not bind to CD99
-
293T (Fig 4-1D).
To further establish the binding specificity of a-CD99-A192 to CD99, we performed a
competitive binding assay and analyzed the binding via flow cytometry. MOLM-13 cells
pre-treated with either mAbCD99 or IgG were washed and then treated with rhodamine
labeled a-CD99-A192. After normalizing to untreated cells, we found that cells
pretreated with 2.5 and 5 µg/mL mAbCD99 had significantly lower in binding to a-
CD99-A192 as compared to cells treated with a-CD99-A192 alone (~35%, p=0.03 and
~60%, p=0.001 respectively). Pre-treatment with IgG did not affect the binding of a-
CD99-A192 to surface CD99. No binding was observed in MOLM-13 cells treated with
rhodamine labeled A192 (Fig 4-1).
112
Figure 4-1: a-CD99-A192 binds specifically to surface CD99
a-CD99-A192 binding to surface CD99 in MOLM-13, MV4-11 and U937 cells through
flow cytometry analysis. No binding was observed in CD99
-ve
293T cells. (A-D). Binding
of a-CD99-A192 to surface CD99 reduced in cells pre-treated with CD99 mAb (E).
A
E
B
C
D
113
4.3.2 Cytotoxic activity of a-CD99-A192 in AML cells
To determine the antileukemia activity of a-CD99-A192, MOLM-13, MV4-11 and U937
cells were treated with a-CD99-A192 at 1, 10, 25 and 50 µM, or the same concentrations
of A192. Trypan blue assay was performed to count viable cells. In cells treated with a-
CD99-A192 there was a significant decrease in the percentage of viable cells as
compared with A192 in MOLM-13 cells at 1 µM (p<0.0001, 30% decrease), 10 µM
(p<0.0001, 43% decrease), 25 µM (p<0.0001, 78% decrease) and 50 µM (p<0.0001, 82%
decrease) (Figure. 4-2A). in MV4-11 cells a-CD99-A192 significantly reduced cell viability
at 1 µM (p<0.0001, 30% decrease), 10 µM (p<0.0001, 46% decrease), 25 µM (p<0.0001,
80% decrease) and 50 µM (p<0.0001, 84% decrease) (Figure 4-2B). Similarly, in U937
cells a-CD99-A192 significantly reduced cell viability at 1 µM (p<0.0001, 30% decrease),
10 µM (p<0.0001, 41% decrease), 25 µM (p<0.0001, 75% decrease) and 50 µM
(p<0.0001, 83% decrease) (Figure 4-2C). IC50 values of a-CD99-A192 for MOLM-13,
MV4-11 and U937 cells were determined as 8.1 µM, 4.9 µM and 6.05 µM, respectively
(Figure 4-2D-F respectively).
114
Figure 4-2: Cytotoxic effect of a-CD99-A192.
a-CD99-A192 decrease cell viability in MOLM-13, MV4-11 and U937 cells measured via
trypan blue (A-C). IC50 of a-CD99-A192 measured via alamar blue in MOLM-13, MV4-
11 and U937 cells.
A
C
F
D
E
B
115
4.3.3 a-CD99-A192 induces apoptosis in AML cells
We also found that the decrease in cell viability was due to an enhanced apoptosis in α-
CD99-A192 treated cells. Annexin V staining revealed a significant increase at 72 hours
in MOLM-13 cells treated with a-CD99-A192 (1 µM: p=0.03,1.3-fold; 10 µM: p=0.01, 1.5-
fold; 25 µM: p=0.001, 1.6-fold and 50 µM: p=0.01, 1.6-fold; Figure 4-3A). In MV4-11 cells
treated with a-CD99-A192 showed higher levels of apoptosis compared with A192 treated
cells (1 µM: p=0.04,1.4-fold; 10 µM: p=0.005, 1.7-fold; 25 µM: p=0.007, 2-fold and 50 µM:
p=0.007, 2-fold; Figure 4-3B). Similarly, in U937 cells treated with a-CD99-A192 showed
higher levels of apoptosis compared with A192 treated cells (1 µM: p=0.04,1.48-fold; 10
µM: p=0.007, 1.7-fold; 25 µM: p=0.01, 2.3-fold and 50 µM: p=0.009, 2.3-fold; Figure 4-
3C).
116
Figure 4-3: a-CD99-A192 induces cell apoptosis
Annexin V assay confirmed increased cell apoptosis in MOLM-13, MV4-11 and U937
cells treated with a-CD99-A192
1 10 25 50
0
1
2
3
4
Conc (µM)
% Annexin V
+
U937
A192
α-CD99-A192
* **
*
**
1 10 25 50
0.0
0.5
1.0
1.5
2.0
2.5
Conc (µM)
% Annexin V
+
MOLM-13
A192
α-CD99-A192 *
*
**
*
1 10 25 50
0
1
2
3
Conc (µM)
% Annexin V
+
MV4-11
A192
α-CD99-A192
*
**
**
**
A
A192 a- CD99-A192
50 !M
1 !M 10 !M 25 !M 50 !M
56.4 4.04
36.2 3.4
42.3 7.73
46.1 3.89
35.2 10.4
51.1 2.91
16.8 11.2
69.9 2.16
15.2 11.5
70.8 2.47
57.3 7.13
33.3 2.26
54.1 7.55
37.5 0.89
44.9 8.24
46.5 0.42
28 8.28
63.2 0.53
27.8 8.71
63.1 0.39
68.8 3.2
24.2
3.87
55.9 4.15
38.3 1.6
47.9
4.61
46.6 0.86
29.9 4.54
65.7 0.68
26.8 4.43
68.2 0.59
B
C
Annexin V
+
PI
+
117
4.3.4 Antileukemic activity of a-CD99-A192 in primary AML cells
We further tested the effect of a-CD99-A192 in primary AML cells (USC001) obtained
from patient with AML. Rhodamine labelled a-CD99-A192 (20 µM) significantly bound to
surface CD99 protein compared with A192 (2.6-fold, p<0.001; Fig. 4-4A). Additionally, a-
CD99-A192 significantly reduced cell viability of AML primary cells (24 hours: p=0.002,
50% decrease; 48 hours µM: p<0.0001, 50% decrease; Fig. 4-4B). This was also
accompanied with a significant increase in cell apoptosis at 48 hours (p=0.002, 1.2-fold;
Fig. 4-4C).
118
Figure 4-4: Anti-leukemic effect of a-CD99-A192 in primary cells
a-CD99-A192 bound to surface CD99 in primary cells, decreased cell proliferation,
induced cell apoptosis (A-C)
A B
A192
a-CD99-A192
C
119
4.3.6 Antileukemia activity of a-CD99-A192 in AML xenograft model
Having demonstrated that a-CD99-A192 specifically binds to surface CD99 and are
effectively mediates cell apoptosis, we then sort to determine its therapeutic potential in
MOLM-13 xenografted nod scid mice. Interestingly, mice treated with a-CD99-A192 had
smaller spleens that weighed significantly less compared with the mice treated A192 (113
vs. 180 mg, p<0.001) (Figure 4-6A-B). huCD45 analysis for leukemia engraftment
revealed that mice treated with a-CD99-A192 had significantly less engraftment
compared with the A192 mice in the bone marrow (%huCD45: 29 vs. 53%, p<0.0001;
Figure 4-6 C-D), peripheral blood (%huCD45: 6 vs. 22%, p<0.001; Figure 4-6 E-F) and
the spleen (%huCD45: 5 vs. 13%, p<0.0001; Figure 4-6 G-H).The therapeutic effect of a-
CD99-A192 was further confirmed in MOLM-13 xenograft model via survival analysis.
Mice treated with a-CD99-A192 survived significantly longer than mice in the A192 group
(median survival: 37 vs. 28 Days, p<0.0001; Figure 4-6I).
120
Figure 4-5: Antileukemia activity of a-CD99-A192 in AML xenograft model
Mice engrafted with MOLM-13 cells and treated with a-CD99-A192 had reduced spleen
sizes (A-B), decrease % CD45+ cells in the bone marrow, peripheral blood and spleen
(C-H). Kaplan Meier survival analysis of mice treated with a-CD99-A192
A
Blank
A192
a-CD99-A192
B
C
D
a-CD99-A192
A192
F
E
a-CD99-A192 A192
G
H
A192 a-CD99-A192
I
121
4.4. Discussion
CD99 is upregulated in various diseases like Ewing sarcoma, ependymomas, T-lineage
acute lymphoblastic leukemia, gliomas and AML(Ambros et al., 1991; Buxton et al., 2009;
Choi et al., 2001; Chung et al., 2017; Kavalar et al., 2009; Vaikari et al., 2019; Zhang et
al., 2000). CD99 presents as a viable target for antibody-based therapies since it is a
surface marker. Indeed, the antitumor activity of targeting CD99 with monoclonal
antibodies was demonstrated in several preclinical cancer models. In these studies the
use of an antibody against CD99 has resulted in inhibition of cell migration and activation
of cell apoptosis(Cerisano et al., 2004; Seol et al., 2012; Sohn et al., 1998).
In Ewing sarcoma, CD99 mAb resulted in homotypic cell aggregation and caspase-
independent cell death. Furthermore, CD99 mAb potentiated the antitumor activity of
doxorubicin and vincristine in preclinical therapeutic studies for Ewing sarcoma and more
importantly the combination therapy was effective against chemo-resistant tumor
cells(Manara et al., 2016; Scotlandi et al., 2000). Apart from its therapeutic benefit, CD99
can also serves a diagnostic marker. In Ewing Sarcoma, CD99 is used along with EWR1
and FLI1 as a diagnostic biomarker(Louati et al., 2018). Although there is extensive
evidence backing the high potential of CD99 mAb in the clinical setting, no antibody
against CD99 has made it into clinical investigation as a therapeutic approach yet.
Challenges in antibody development including limitations related to their ineffective
clustering on target receptors as well as lack of therapeutic concentrations on target cells
hinder monoclonal antibodies from transitioning into clinical development. This study
presents the development and efficacy testing of a new antibody-based CD99
122
nanoparticle, which is composed of α-CD99 single-chain variable fragment (scFv) linked
to A192, an elastin-like polypeptide (ELP), derived from human tropoelastin.
Because ELPs phase separate above tunable transition temperature, a chromatography-
free, high purity fusion protein can be obtained without the need of any additional
purification tags which can hinder protein activity (Goel et al., 2000; Sabaty et al., 2013).
In addition, it has been discovered that scFv-ELP phase separation clustered target
receptors on the cell membrane after binding and enhanced the internalization of the
receptors, resulting in improved biological activity compared to a commercial monoclonal
antibody(Aluri et al., 2014). It is unknown whether CD99 transmembrane glycoproteins
get internalized upon binding, but if CD99 shows the similar mechanism to that of receptor
proteins that get internalized, we might expect an enhanced therapeutic effect of α-CD99-
A192 nanoworms compared to α-CD99 monoclonal antibodies. Such studies are the
focus of future research projects by our group.
Across various AML cell lines, α-CD99-A192 showed positive binding to CD99
+
cells but
not CD99
-
293T cells. The specificity of the binding was also demonstrated in a
competitive-binding assay of CD99 mAb in MOLM-13 cells. Furthermore, α-CD99-A192
significantly reduced cell viability and increased cell apoptosis in both AML cell lines and
primary AML cells. In the MOLM-13 xenograft model, treatment with α-CD99-A192
reduced leukemia burden and significantly improved survival of the mice. Altogether the
In vitro and in vivo testing of α-CD99-A192 established a strong activity of this compound
in preclinical models.
In conclusion, this study reports the development and evaluation of a new therapeutic
scFv nanoparticle directed against CD99. With CD99 serving a therapeutic target for
123
various malignancies, our study suggests α-CD99 scFv-ELP fusion protein can be a
candidate therapeutic agent for AML. α-CD99-A192 also has further scope in the clinical
setting than evaluated here. Apart from AML, we also speculate that this new scFv against
CD99 can be used in several other disease models, such as Ewing sarcoma and gliomas.
124
Chapter 5 : Concluding Remarks
Acute Myeloid Leukemia (AML) is a hematological malignancy of the hematopoietic stem
cells that results from clonal proliferation of immature myeloid cells. The outcome of
patients with acute myeloid leukemia (AML) remains dismal due to the high relapse
rate(Lowenberg, 2008). In order to address this need, in this study through gene
expression analysis we identified CD99 to be significantly upregulated in AML.
Across various datasets, CD99 expression was significantly higher in patients with AML
as compared with healthy donor PBMCs. More importantly, we found that CD99
expression was significantly higher in the leukemic stem cell like population CD34
+
CD38
+
and CD34
+
CD38
-
subpopulation compared with CD34
-
CD38
-
and CD34
-
CD38
+
. This is
accordance with previous reports(Bonardi et al., 2013; Han et al., 2015; Kikushige et al.,
2010) suggesting that CD99 could serve as a leukemic stem cell marker. It is known that
hematopoietic malignancy can only be initiated by leukemic stem cells expressing the
same markers as normal hematopoietic stem cells (CD34
+
CD38
−
)(Lapidot et al., 1994).
This population of cells possess the ability of self-renewal and proliferation making
markers on the leukemic stem cells pivotal in targeted therapies. This provided further
rationale to study the role of CD99 in AML.
Because AML is a heterogeneous disease, it is pivotal to identify patients who are likely
to have high CD99 expression and may benefit from therapies aimed to target this gene.
Clinical analysis of 186 patients from The Cancer Genome Atlas - acute myeloid leukemia
dataset revealed that, CD99 was overexpressed in patients with FLT3-ITD and was
downregulated in patients with TP53 mutations. The association between CD99
upregulation and the presence of FLT3-ITD is particularly interesting. FLT3-ITD is
125
mutated in almost 30% of patients with AML and patients with FLT3-ITD mutation have a
significantly worse outcome than patients with FLT3-WT. Based on this we speculate
within the FLT3-ITD positive patient population, CD99 may serve as an enhanced
therapeutic target or can be used as a combination therapy.
To understand the clinical relevance of CD99 upregulation in AML, we analyzed the
association of CD99 high and low expression based on CD99 median expression and
found that high CD99 expression was associated with better outcome. Yet, this
association was not significant in multivariate analysis and, this is likely due to the fact
this effect is driven by other molecular and cytogenetic factors possibly due to its
upregulation in patients with favorable risk subsets (inv16, t(8,21)); or the reverse
association with TP53 mutations. Furthermore, patients with high CD99 expression also
had higher peripheral blasts and bone marrow blasts as compared to patients with low
CD99 expression but patients the median age of patients was lower in patients with high
CD99 expression as compared to low CD99 expression. Since older patients tend to have
poor outcome this could also contribute to the poor overall survival in the CD99 low group.
To determine the functional relevance of CD99, we used gain and loss function approach.
Since CD99 gene encodes two isoforms with distinct expression and functional profiles
in both normal and malignant tissues we aimed to understand the role of these isoforms
in AML. Interestingly, we found that though the CD99 long isoform initially induces an
increase in cell proliferation, it also induces higher levels of reactive oxygen species
(ROS), DNA damage, apoptosis and subsequent decrease in cell viability. In several in
vivo murine models, the CD99-L isoform delayed leukemia progression and resulted in
126
lower AML engraftment in the bone marrow. Mechanistically, CD99-L isoform initially
induced ERK and SRC phosphorylation followed by a dramatic decrease of both. Our
data suggest that the homotypic interaction of CD99-L isoform but not the short isoform
results in cell aggregation, which could potentially promote cell apoptosis. This is
consistent with the previous studies where ligation of CD99 using a monoclonal antibody
resulted in a 4-fold increase in cell aggregation(Byun et al., 2006). CD99 is also known to
cause homotypic aggregation of cortico-thymocytes(Bernard et al., 1995). Increase in cell
aggregation could result in the decreased P-ERK and P-SRC levels observed over long
term culture.
Mechanistically, previous studies have reported that triggering of CD99 with monoclonal
antibody induces cell death via rapid decrease of MDM2 and activation of IGF-1R and
RAS-Rac1 signaling(Manara et al., 2016). We found that CD99 L isoform cells exhibit
lower levels of MDM2 compared with CD99 S and EV expressing cells. We also observed
a reduction in MDM2 in cells treated with CD99 mAB at 2-9 hours post antibody treatment,
yet P-ERK was not changed in these cells. Because MDM2 is known to ubiquitinate IGF-
1R, we speculated that CD99 induced reduction in MDM2 would upregulate IGF-1R
downstream target genes such as CyclinD1. We found upregulation of CCND1 mRNA
levels in CD99-L cells compared with CD99-S. On the other hand, CD99 knockdown
resulted in significant decrease in CCND1 mRNA levels which explains the observed
decrease in cell proliferation upon. Previous reports have stated that the CD99
monoclonal antibody acts as an agonist and reported similar phenotypes to those
observed in this study. The similarity between the CD99 long isoform expression and the
monoclonal antibody associated phenotypes suggestive that the antibodies acts as an
127
agonist. Since CD99 is known to form homodimers, whether overexpressing CD99 long
isoform or treatment with monoclonal antibody induces similar signaling cascades are yet
to be determined and warrant for further analysis.
Overall, we speculate that the upregulation of AKT, ERK, SRC and CCND1 post CD99
viral transduction may explain the early increase in cell proliferation, and possibly
increase the CD99 homotypic interaction which could then result in increased cell
apoptosis as well as an increase in caveolin expression in turn downregulating P-SRC.
Our study adds important insights into the function of CD99 isoforms in the context of
AML, which has not been established before.
Our studies have revealed that CD99 monoclonal antibody reduced cell viability, colony
formation, cell migration as well as induced cell differentiation and apoptosis in leukemia
cell lines and primary blasts. Based on this, we then developed and tested the efficacy of
a new therapeutic scFv against CD99, which showed that the α-CD99-A192 was able to
induce cell apoptosis and decrease cell viability in AML cell lines. This effect was also
reflected in primary AML cells. Furthermore, α-CD99-A192 treatment in MOLM-13
xenograft mice demonstrated a significant decrease in leukemia burden and improved
survival. With CD99 serving a therapeutic target for various malignancies, we have
developed a novel therapeutic approach to target CD99 in AML using α-CD99-A192
The fusion of ELP to α-CD99 scFv forms biologically active nanoworms. With CD99
serving a therapeutic target for various malignancies, our study suggests α-CD99 scFv-
ELP fusion protein can be a great candidate to be a therapeutic agent for AML. α-CD99-
A192 also has further scope in the clinical setting than evaluated here. Apart from AML,
we also speculate that this new scFv against CD99 could be used in several other disease
128
models like Ewing sarcoma and gliomas therapeutically and for diagnostic purposes.
Since previous reports have shown CD99 mAb sensitizes chemo-resistant cells, this
fusion protein can possibly be used along with other drug combinations to expand its
scope in the clinical setting.
Overall, through this study, we have determined the clinical significance of CD99
overexpression in AML and analyzed the function and mechanistic role of CD99 isoforms,
evaluated the therapeutic effect of monoclonal CD99 antibody and based on this
successfully validated the pre-clinical significance of a new therapeutic CD99 scFv
conjugated to ELP which has excellent in vitro and in vivo anti-leukemic effect.
129
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Abstract (if available)
Abstract
Acute Myeloid Leukemia (AML) is a heterogeneous, hematological malignancy of the hematopoietic stem cells that results from a block in the differentiation with uncontrolled proliferation of leukemic blasts. The outcome of patients with AML remains dismal due to the high relapse rate(Lowenberg, 2008). In order to address this need, we analyzed various Oncomine data sets for gene expression data of normal hematopoietic vs AML cells and found CD99 to be significantly upregulated in AML. CD99 (E2, MIC2) is a human 32-kD transmembrane sialo-glycoprotein expressed on many hematopoietic and non-hematopoietic cells. In hematopoietic stem cells, CD99 is differentially expressed based on distinct maturation stages: initially, CD99 expression is high in multipotent CD34⁺ cells in the bone marrow but the expression declines as these cells differentiate into mature blood cells. CD99 is highly expressed in Ewing's Sarcoma (EWS) and gliomas and is associated with poor prognosis. Contrary to these studies, in non-small cell lung carcinoma and osteosarcoma, higher CD99 expression was associated with better prognosis and acts as an onco-suppressor. ❧ We analyzed CD99 expression across various AML datasets and found that CD99 was significantly higher in patients with AML compared with healthy donor samples. Additionally, high CD99 was associated with better outcome in cytogenetically abnormal AML. In a panel of AML cell lines, CD99 surface levels were higher than that of healthy cord blood cells. CD99 gene encodes two isoforms with distinct expression and functional profiles in both normal and malignant tissues. We analyzed CD99 RNAseq data of AML patients for protein coding transcripts and found that the those encoding for the long and short isoform are the main transcripts expressed in AML. Based on this we used lentivirus mediated overexpression of CD99 long and short isoforms to determine its functional relevance in AML. We found that CD99 long isoform (CD99-L) initially induces an increase in cell proliferation as well as it induces higher levels of reactive oxygen species (ROS), DNA damage, apoptosis and subsequent decrease in cell viability compared with AML cells transduced with empty vector or CD99-S isoform. In several leukemia murine models including mice engrafted with primary blasts, the CD99-L overexpression significantly delayed disease progression and resulted in lower leukemia engraftment in the bone marrow and peripheral blood compared with mice engrafted with leukemic cells overexpressing empty vector or CD99-S isoform. Mechanistically, CD99-L resulted in transient induction followed by a dramatic decrease of both ERK and SRC phosphorylation. ❧ Furthermore, commercially available CD99 monoclonal antibody reduced cell viability, colony formation, cell migration as well as induced cell differentiation and apoptosis in leukemia cell lines and primary blasts. Based on this we then developed and evaluated the efficacy of α-CD99-A192 nanoworms as a therapy for AML. In vitro analyses showed promising anti-leukemic activity of α-CD99-A192 by reducing cell proliferation and inducing cell apoptosis. Furthermore, α-CD99-A192 had an excellent in vivo efficacy and significantly increased survival of mice in MOLM-13 xenograft model. ❧ Overall, this study established the clinical role of CD99, the functional and mechanistic role of CD99 through in vitro and in vivo analyses and developed and validated a therapeutic approach to target CD99 for AML.
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Creator
Vaikari, Vijaya Pooja (author)
Core Title
Clinical, functional and therapeutic analysis of CD99 in acute myeloid leukemia
School
School of Pharmacy
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Doctor of Philosophy
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Clinical and Experimental Therapeutics
Publication Date
05/07/2020
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05/06/2020
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AML
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