Genomic and transcriptomic alterations of apolipoproteins genes in cancers

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GENOMIC AND TRANSCRIPTOMIC ALTERATIONS OF APOLIPOPROTEINS GENES IN
CANCERS

by
Khadija Swadi

A Thesis Presented to the
FACULTY OF THE USC SCHOOL OF PHARMACY
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(PHARMACEUTICAL SCIENCE)

August 2023

© Copyright 2023

ii

Acknowledgements

In the depths of my soul, I am overwhelmed with profound gratitude as I pour out my heartfelt
appreciation to the pillars of my life: my beloved husband, cherished son, and the unwavering
support of my entire family. Throughout the twists and turns of my academic journey, their
unwavering love, boundless encouragement, and infinite patience have been my anchor. They have
stood by my side, weathering the storms with me, and illuminating the path to my goals. I am truly
blessed to have such an extraordinary support system.

To my esteemed PI, Dr. Houda Alachkar, I extend my deepest appreciation. Your guidance,
expertise, and unwavering belief in my abilities have been the catalysts that propelled me forward.
Your tireless dedication to my academic growth has been a beacon of inspiration on even the darkest
of days. Working under your supervision has been a privilege, and I am grateful for the immeasurable
impact you have had on my journey. Also, I am filled with profound gratitude as I express my
heartfelt appreciation to Mateusz Pospiech, whose fellowship and mentorship have left an indelible
mark on my academic journey. The depth of my emotions cannot be adequately described, as
Mateusz's unwavering dedication to teaching and his unwavering commitment to my growth have
touched the very core of my being.

My gratitude extends further to the exceptional members of my committee: Dr. Ian Haowrth,
Dr. Curtis Okamoto, and Dr. Roger Duncan. Your contributions, insights, and constructive criticism
have breathed life into my research, infusing it with depth and brilliance. Your unwavering
commitment to upholding the highest standards of quality and rigor has pushed me to surpass my
own boundaries. The richness of my work is a testament to the invaluable guidance you have
provided.

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To all those mentioned above, your unwavering support has been the foundation upon which
I have built my success. Your belief in my abilities has fortified my resolve, even in moments of
self-doubt. Without your presence in my life, this monumental achievement would not have been
possible. From the depths of my being, I offer my heartfelt gratitude for your unwavering presence,
your guidance, and your unwavering belief in my potential.

iv

Table of Contents

Acknowledgment ......................................................................................................................................... ii
List of Tables ................................................................................................................................. vi
List of Figures ............................................................................................................................... vii
Abbreviations ............................................................................................................................... viii
Abstract ........................................................................................................................................... x
Chapter 1: Introduction ................................................................................................................... 1
1.1 Introduction to cancer .......................................................................................................... 1
1.2. Lipid metabolism and cancer ............................................................................................... 2
1.3. Role of lipid dysregulation in cancer .................................................................................. 5
a. Lipid dysregulation ....................................................................................................... 5
b. Lipoproteins .................................................................................................................. 5
c. Apolipoproteins ............................................................................................................ 6
d. Plasma lipoproteins classes .......................................................................................... 6
1.4. The role of apolipoproteins in cancer .................................................................................. 7
Chapter 2: Deregulation of Apolipoprotein in Cancer ................................................................ 9
2.1. Materials and methods ................................................................................................. 9
2.1.1. Patient data sets ........................................................................................................... 9
2.1.2. Data Visualization ..................................................................................................... 11
2.1.3. Statistical analysis ..................................................................................................... 11
Chapter 3: Results ......................................................................................................................... 13
3.1. The landscape of APOs genes alterations in cancer .......................................................... 13
3.2. APO genes are frequently altered in patients with cancer ................................................ 14
3.3. APOs genes are highly amplified in cancer ...................................................................... 16
3.4. APOs genes are frequently mutated in cancer .................................................................. 18

v

3.5. The frequency of APOs genes deletions in cancer ........................................................... 19
3.6. APOs genes alterations are associated with shorter cancer overall survival .................. 24
Chapter 4: Discussion and Conclusion ........................................................................................ 31
Conclusion ...................................................................................................................................... 35
References ....................................................................................................................................... 36

vi

List of Tables

Table 1. Summary of APOs genes investigated in various types of cancer and clinical studies on
cBioportal .......................................................................................................................................... 9
Table 2. APO genes deregulation in cancer .................................................................................... 21
Table 3. The most frequent cancer alteration in APO genes with significant survival rate ........... 29

vii

List of Figures

Figure 1. Patterns of APOs genes genomic dysregulation in cancer .............................................. 13
Figure 2. Amplification was significantly more frequent than deletion ......................................... 15
Figure 3. APOs amplification in cancer ......................................................................................... 17
Figure 4. APOs genes commonly exhibit mutations in cancer ....................................................... 18
Figure 5. Deletion frequencies of APO genes across all types of cancer ....................................... 20
Figure 6. Survival Probability in Skin Cutaneous Melanoma Patients with APOJ Gene Alteration:
Altered vs. Unaltered Group ............................................................................................................ 25
Figure 7. Survival Probability in Skin Cutaneous Melanoma Patients with APOL1 Gene
Alteration: Altered vs. Unaltered Group ......................................................................................... 26
Figure 8. Survival Probability in Lung Squamous Cell Carcinoma Patients with APOA4 Gene
Alteration: Altered vs. Unaltered Group ......................................................................................... 27
Figure 9. Survival Probability in Lung Squamous Cell Carcinoma Patients with APOO Gene
Alteration: Altered vs. Unaltered Group ......................................................................................... 28
Figure 10. Survival Probability in Kidney Chromophobe Patients with APOA1 Gene Alteration:
Altered vs. Unaltered Group ............................................................................................................ 29

viii

Abbreviations

ABC ATP-binding cassette transporters
ACC Adrenocortical Carcinoma
AML Acute Myeloid Leukemia
APO Apolipoprotein
APOA1 Apolipoprotein A1
APOA2 Apolipoprotein A2
APOA4 Apolipoprotein A4
APOA5 Apolipoprotein A5
APOB Apolipoprotein B
APOC1 Apolipoprotein C1
APOC2 Apolipoprotein C2
APOC3 Apolipoprotein C3
APOC4 Apolipoprotein C4
APOD Apolipoprotein D
APOE Apolipoprotein E
APOF Apolipoprotein F
APOH Apolipoprotein H
APOJ (CLU) Apolipoprotein J (CLU)
APOL1 Apolipoprotein L1
APOL2 Apolipoprotein L2
APOL3 Apolipoprotein L3
APOL4 Apolipoprotein L4
APOL5 Apolipoprotein L5
APOL6 Apolipoprotein L6
APOM Apolipoprotein M
APOO Apolipoprotein O
BLCA Bladder Urothelial Carcinoma
BRAF V-raf murine sarcoma viral oncogene homolog B1
CESC Cervical Squamous Cell Carcinoma
CHOL Cholangiocarcinoma
COAD Colorectal Adenocarcinoma
DLBC Diffuse Large B-Cell Lymphoma
ERK Extracellularly Regulated Kinases
ESCA Esophageal Adenocarcinoma
FPP Farnesyl pyrophosphate
GBM Glioblastoma Multiforme
GGPP Geranylgeranyl pyrophosphate
HCC Hepatocellular carcinoma
HDL High-density lipoproteins
HER2 Human epidermal growth factor receptor 2
HNSC Head and Neck Squamous Cell Carcinoma
IDL Intermediate-density lipoproteins
KICH Kidney Chromophobe
KIRC Kidney Renal Clear Cell Carcinoma

ix

KIRP Kidney Renal Papillary Cell Carcinoma
LAML Acute Myeloid Leukemia
LDL Low-density lipoproteins
LDLR Low-density lipoprotein receptor
LIHC Liver Hepatocellular Carcinoma
LRP LDL receptor-related protein
LGG Brain Lower Grade Glioma
Lp(a) Lipoprotein
LUSC Lung Squamous Cell Carcinoma
LUAD Lung Adenocarcinoma
MESO Mesothelioma
MVA Mevalonate
O2- Superoxide anion
•OH Hydroxyl radical
OV Ovarian Serous Cystadenocarcinoma
PAAD Pancreatic Adenocarcinoma
PRAD Prostate Adenocarcinoma
PUFAs Polyunsaturated fatty acids
ROS Reactive oxygen species
SARC Sarcoma
SREBPs Sterol regulatory element-binding proteins
STAD Stomach Adenocarcinoma
TC Total cholesterol
TCGA The Cancer Genome Atlas
TG Triglyceride
THCA Thyroid Carcinoma
THYM Thymoma
TP53 Tumor protein 53
UVM Uveal Melanoma
UCEC Uterine Corpus Endometrial Carcinoma
UCS Uterine Carcinosarcoma
VLDL Very-low-density lipoproteins

x

Abstract

Lipid metabolism is a vital source of energy for cancer survival and growth. Apolipoproteins
(APOs) are proteins that bind to lipids and promote diverse lipid metabolic processes. Previous
research has shown that apolipoprotein C2 (APOC2) is upregulated in several varieties of cancer,
where it promotes growth and survival. This study evaluates the types and the frequencies of the
genomic and transcriptomic patterns of the other apolipoproteins in cancer. The Cancer Genome
Atlas (TCGA) data were utilized to analyze 22 apolipoprotein genes in 32 categories of cancer. In
2818 (26%) of the examined patients, amplifications, mutations, and profound deletions were
identified as the primary APOs alterations. Apolipoprotein D (APOD) was the most frequently
amplified gene, which ranged from 0.16% in Colorectal Adenocarcinoma to 29.7% in Lung
Squamous Cell Carcinoma. The incidence of APOs gene mutations was highest in Apolipoprotein
B (APOB), which ranged from 0.8% in Thyroid Carcinoma to 32.88 % in Skin Cutaneous
Melanoma. The frequency of profound deletion was the highest in Apolipoprotein J (APOJ), which
ranged from 0.35% in Kidney Renal Papillary Cell Carcinoma and 6.68% in Prostate
Adenocarcinoma. These analyses suggest that APOs genes are substantially dysregulated in cancer,
and that further functional and mechanistic studies are required to investigate the role of specific
APO genes in specific cancer types.

1

Chapter 1: Background

1.1. Introduction to cancer
Cancer is a complex disease characterized by aberrant cellular growth and proliferation.
According to the World Health Organization (WHO), cancer is one of the world's leading causes of
death, with a projected 10 million fatalities in 2020 alone. The National Cancer Institute (NCI)
characterized cancer by the dysregulated proliferation of malignant cells, which divide and
proliferate abnormally before invading normal tissues and organs and spreading throughout the body.
The accumulation of abnormalities in multiple regulatory systems results in alterations in cell activity
that distinguish cancerous cells from healthy cells (Jacquemin et al., 2022). Moreover, Jacquemin et
al. (2022) describe how cancer cells within a tumor can exhibit significant heterogeneity in terms of
their genetic and epigenetic profiles, as well as their functional and phenotypic characteristics. This
heterogeneity can contribute to variations in tumor growth rates, invasion, and therapeutic response.

The authors of the 2009 article by Sharma, Kelly, and Jones discuss how genetic and epigenetic
alterations contribute to the development and progression of cancer. While oncogenes, which are
mutated genes, and tumor suppressor genes have traditionally been seen as the primary drivers of
cancer, epigenetic alterations, such as DNA methylation, histone modifications, and noncoding RNA
expression, are increasingly being recognized as playing critical roles in regulating gene expression
and maintaining cellular identity. Many of the genetic alterations believed to be responsible for
cancer initiation and progression are epigenetically mediated. (Siegel, R. L., Miller, K. D., & Jemal,
A., 2020).

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Growing evidence suggests that cancer cells reprogram their metabolism to meet their increased
energy demands and biosynthetic requirements. The altered regulation of lipid metabolism, which
involves the synthesis, storage, and degradation of fats, is a crucial aspect of cancer metabolism
(Currie et al., 2013). In addition, the reprogramming of cancer cell metabolism also involves
alterations in signaling pathways. For instance, the MYC and PI3K/Akt/mTOR pathways are
essential signaling pathway that controls the expression of lipid metabolism genes for cell growth
and survival by promoting anabolic metabolism. Overactivation of this pathway, as well as other
lipid signaling pathways such as JAK/STAT3 and Hippo, can lead to increased cholesterol synthesis,
which is associated with cancer (Röhrig & Schulze, 2016).
1.2. Lipid metabolism and cancer
Lipids, along with proteins and nucleic acids, are crucial components of biological membranes
and cellular building elements (Bian et al., 2020). Furthermore, for cells to proliferate and survive,
lipid is an essential component. Studies by Clendening and Penn (2012) have indicated that cancer
cells exhibit an elevated dependence on lipids to sustain their enhanced rates of growth and division.
Recent studies have identified several cholesterol-related genes frequently altered in cancer,
including the low-density lipoprotein receptor (LDLR), sterol regulatory element-binding proteins
(SREBPs), and ATP-binding cassette (ABC) transporters (Giacomini et al., 2011; Lu et al., 2018).
These alterations can result in increased cholesterol uptake, synthesis, and efflux, which contributes
to the survival and growth of cancer cells.

Recent research has linked elevated APOB levels to an increased risk of prostate, colorectal, and
liver cancer (Ye et al, 2019). Additionally, APOB has been identified as a ligand for cell signaling
membrane receptors like CD91 and the low-density lipoproteins (LDL) receptor-related protein
3

(LRP), suggesting its involvement in cellular signaling pathways. The binding of APOB to LRP1
has been linked to the activation of extracellularly regulated kinases 1/2 (ERK1/2) signaling, which
is crucial for cell proliferation and survival in multiple cancers (Gruenbacher et al., 2018; Hu et al.,
2018; Singh et al., 2019; Wu et al., 2021).

It is not completely understood how lipids and lipoproteins contribute to the development of
cancer. Malondialdehyde is a byproduct of peroxidation, which is the degradation of polyunsaturated
fatty acids (PUFAs) in cellular membranes. Research suggests that malondialdehyde may contribute
to the development of cancer by crosslinking DNA in a way that causes cellular mutations. LDL are
especially susceptible to oxidation, which can increase malondialdehyde production and
consequently increase the risk of cancer (Chole et al., 2010). For example, the authors discovered
that measuring serum malondialdehyde levels could be a useful diagnostic tool for both preventative
and therapeutic interventions in oral cancer and precancerous conditions.

It is believed that high-density lipoproteins (HDL) protect cells from the oxidative damage
induced by LDL and prevent the formation of malondialdehyde. Some studies suggest that HDL may
function as a powerful antioxidant, inhibiting the production of cancer-causing oxidative stress such
as superoxide anion (O2-), hydroxyl radical (•OH), and hydrogen peroxide (H2O2) (Bielecka-
Dbrowa et al., 2011; De Jesus et al., 2022). Cowey et al. (2006) hypothesized that the association
between elevated triglyceride (TG) levels and lung cancer risk is due to the initiation of oxidative
stress and the formation of reactive oxygen species (ROS). Moreover, ROS play a crucial role in the
progression of cancer by modulating diverse signaling pathways, DNA damage response, and
immune evasion, and targeting ROS could be a potential cancer treatment strategy (Aggarwal et al.,
2019).
4

Hyperlipidemia is common among cancer patients and survivors (Ray G. & Husain S. (2001) as
a previous study reported that 55% of untreated breast cancer patients were diagnosed with
hyperlipidemia. Furthermore, Ma et al. (2023) reported in their study that dyslipidemia,
characterized by elevated levels of total cholesterol (TC), low-density lipoprotein (LDL) cholesterol,
and triglycerides (TGs), was significantly associated with poor breast cancer prognosis in patients
receiving neoadjuvant chemotherapy. Chandra et al. (2014) found that different types of cancer are
associated with distinct lipid profile differences. Patients with ovarian cancer had the highest serum
triglyceride (TG) levels, while those with colorectal cancer had the lowest. Furthermore, patients
with breast cancer had the highest total cholesterol (TC) and low-density lipoprotein (LDL) levels,
with LDL levels exceeding 110 mg/dL being correlated with lymphatic metastasis (Ghahremanfard
et al, 2015).

Growing evidence suggests a connection between lipid metabolism and cancer. Essential to the
maintenance of cellular homeostasis is the regulation of lipid metabolism, including lipid uptake,
synthesis, and hydrolysis (Bian et al., 2020). Cancer cells display altered lipid metabolism, which
includes increased de novo lipid synthesis, heightened cholesterol production, and enhanced fatty
acid oxidation. In cancer, dysregulation of lipid metabolism is one of the most noticeable metabolic
alterations (Bian et al., 2020). In addition, dysregulation of cholesterol metabolism can lead to the
accumulation of cholesterol intermediates, such as oxysterols, which can induce oxidative stress and
cellular injury, thereby further promoting carcinogenesis (Bjorkhem et al., 2021). Utilizing lipid
metabolism, cancer cells obtain the energy, components for biological membranes, and signaling
molecules required for proliferation, survival, invasion, metastasis, tumor microenvironment impact
response, and cancer therapy (Bian et al., 2020).

5

1.3. Role of lipid dysregulation in cancer
a. Lipid dysregulation

Dysregulated lipid metabolism in cancer cells can promote tumor growth, invasion, and
metastasis, as well as chemotherapy and radiation therapy resistance. Several major enzymes and
signaling pathways involved in lipid metabolism, including fatty acid synthase, acetyl-CoA
carboxylase, and peroxisome proliferator-activated receptor gamma, have been identified as
potential targets for cancer therapy (Liu & Sabatini, 2020). Furthermore, Cruz et al. (2010) found
that elevated cholesterol may promote tumor angiogenesis, reduce apoptosis, and increase
proliferation.
b. Lipoproteins
Lipoproteins are complex particles composed of lipids and proteins that transport hydrophobic
compounds across the hydrophilic environment of plasma. On the basis of their hydrated density,
they are classified as chylomicrons, very-low-density lipoproteins (VLDL), intermediate-density
lipoproteins (IDL), low-density lipoproteins (LDL), and high-density lipoproteins (HDL) based on
their hydrated density (Dominiczak & Caslake, 2011). Firstly, lipoproteins facilitate energy
utilization throughout the body by transporting lipids between organs and tissues. Therefore,
maintaining tissue lipid homeostasis is dependent on lipoprotein metabolism, and any alterations in
this process can affect tissue lipid composition and function (Palm et al., 2012). Secondly,
lipoproteins play a critical role in the management of the extracellular cholesterol reservoir by
regulating cholesterol levels by transporting it to various tissues and organs. This function is essential
for maintaining a healthy balance of cholesterol in the body, which is crucial for overall health (Wang
et al., 2017). Finally, lipoproteins contribute to reverse cholesterol transport by removing excess
cholesterol from peripheral tissues, such as the arteries, and transporting it back to the liver for
excretion. This function is crucial for preventing cholesterol accumulation in peripheral tissues and
6

maintaining healthy cholesterol levels (Wang et al., 2017).

c. Apolipoproteins
Apolipoproteins are essential for lipid metabolism as they serve as templates for lipoprotein
particle assembly, maintain their structure, and direct their metabolism via the binding of membrane
receptors and regulation of enzyme activity. There are 22 APO genes, including APOA1, APOA2,
APOA4, APOA5, APOB, APOC1, APOC2, APOC3, APOC4, APOD, APOE, APOF, APOH, APOJ
(CLU), APOL1, APOL2, APOL3, APOL4, APOL5, APOL6, APOM, APOO (He et al., 2022).
Furthermore, APOs are multifunctional proteins that stabilize and regulate the metabolism of
lipoprotein particles. In addition, they are vital proteins that make up lipoproteins, which transport
lipids in the bloodstream; moreover, they carry lipids and deliver them to various tissues in the body
(Ko et al., 2019). APOs, along with other molecules such as phospholipids and cholesterol, surround
lipid cores to form water-soluble lipoprotein particles with a polar surface due to their amphipathic
structures. This enables the transportation of lipid components in the circulatory system (Saito et al.,
2004). In addition to their role in mediating lipid transport, APOs are also involved in lipoprotein
metabolism. Therefore, they bind to lipoprotein receptors and other lipid transporters, playing a
crucial role in lipoprotein mobilization and clearance (Ryan and van der Horst, 2000).
d. Plasma lipoproteins classes
Plasma lipoproteins can be classified into seven classes based on size, lipid composition, and
apolipoproteins (chylomicrons, chylomicron remnants, VLDL, IDL, LDL, HDL, and Lp(a)).
Chylomicron remnants, VLDL, IDL, LDL, and Lp(a) are all pro-atherogenic, whereas HDL is anti-
atherogenic (Feingold et al., 2021). Furthermore, lipoproteins classified the APOs into:
a) High-density lipoproteins (HDL): Apolipoprotein A-I (APOA1) and Apolipoprotein A-II
7

(APOA2) are the main apolipoproteins associated with HDL. These proteins help transport
and metabolize cholesterol in the body, and HDL is often referred to as "good cholesterol"
because it helps remove excess cholesterol from the bloodstream and transport it back to the
liver for excretion.
a) Low-density lipoproteins (LDL): Apolipoprotein B (APOB) is the main apolipoprotein
associated with LDL. LDL is often referred to as "bad cholesterol" because elevated levels
of LDL in the bloodstream can contribute to the buildup of plaque in the arteries, thereby
increasing the risk of cardiovascular disease.
b) Very low-density lipoproteins (VLDL): Apolipoprotein C2 (APOC2) and Apolipoprotein E
(APOE) are the main apolipoproteins associated with VLDL. These lipoproteins transport
triglycerides and cholesterol in the body, and elevated levels of VLDL in the bloodstream
can contribute to the development of cardiac disease.
c) Chylomicrons: Apolipoprotein B-48 (APOB48) is the main apolipoprotein associated with
chylomicrons. These lipoproteins transport dietary fats and cholesterol from the gut to other
parts of the body.

1.4. The role of apolipoproteins in cancer
Despite extensive research on apolipoproteins (APOs) in various diseases, their roles in cancer
development have not received sufficient attention. However, as early as 1981, studies have shown
that APOs have the potential to serve as biomarkers for diagnosing and prognosing malignancies
such as lung, gastric, and colorectal cancers, indicating their involvement in tumorigenesis and
cancer progression (Zannis et al., 1981; Quan et al., 2017; Wang et al., 2017; Ko et al., 2019). APOs,
or apolipoproteins, are essential in regulating cancer growth by modulating various hallmarks of
cancer, including apoptosis resistance, inflammation promotion, angiogenesis induction, metastasis
8

activation, and sustained proliferation (Ren et al., 2019). Due to their involvement in cancer
progression, APOs have garnered considerable interest as potential biomarkers for monitoring cancer
activity and guiding treatment decisions. (Delk et al., 2021).

The dysregulation of apolipoprotein levels or function can contribute to the initiation and
progression of cancer. For example, the apolipoprotein B (APOB) protein has been linked to cancer
cell proliferation and metastasis. Ye et al. (2022) found that high levels of APOB were linked to an
increased risk of hepatocellular carcinoma (HCC) development and poor prognosis in HCC patients.
Other studies have suggested that the APOB gene may be associated with a higher risk of colorectal
cancer (Mazidi et al., 2020). In addition to genetic factors, lifestyle and environmental factors can
influence the levels and function of apolipoproteins in cancer. For instance, Weitkunat et al. (2017)
reported that animal studies have shown that a high-fat diet can increase APOB levels. Another
example, alterations in APOE gene expression, specifically the APOE 4 allele, have been linked to
an elevated risk of breast and prostate cancer (Yencilek et al., 2016). Furthermore, low APOE levels
have been associated with a worse prognosis in certain types of cancer, such as pancreatic cancer, as
reported by Kwon et al. (2019). Understanding the role of apolipoproteins in cancer could be crucial
for the development of innovative treatment and prevention strategies.

Chapter 2: Deregulation of Apolipoprotein in Cancer
1.1. Materials and methods
2.1.1. Patient data sets
9

In April 2022, patient genetic and clinical data were extracted from the cBioPortal database
1
(Cerami et al., Cancer Discov. 2012, and Gao et al., Sci. Signal. 2013). The dataset included 10,967
samples from 10,953 patients across 32 carefully curated cancer studies, including The Cancer
Genome Atlas Program (TCGA)
1
. Our analysis focused on 22 apolipoprotein genes of interest, and
we utilized data sets containing these genes.

We compiled a list of APOs genes that have been investigated in various types of cancer and
clinical studies on cBioportal (Table 1), which includes information on the different types of studies
available on cBioportal. The table investigated 22 genes across 32 cancer types within 14 clinical
studies. This method enabled an exhaustive and streamlined presentation of the available data, which
facilitated further analysis.
Table 1. Summary of APOs genes investigated in various types of cancer and clinical studies on cBioportal
APOs gene (22 genes)
APOA1, APOA2, APOA4, APOA5, APOB, APOC1, APOC2, APOC3, APOC4, APOD,
APOE, APOF, APOH, APOJ (CLU), APOL1, APOL2, APOL3, APOL4, APOL5, APOL6,
APOM, APOO
Cancer types (32 cancer)
Stomach Adenocarcinoma (STAD) (TCGA, PanCancer Atlas)
Ovarian Serous Cystadenocarcinoma (OV) (TCGA, PanCancer Atlas)
Kidney Renal Clear Cell Carcinoma (KIRC) (TCGA, PanCancer Atlas)
Lung Squamous Cell Carcinoma (LUSC) TCGA, PanCancer Atlas)
Pancreatic Adenocarcinoma (PAAD) (TCGA, PanCancer Atlas)
Uterine Carcinosarcoma (UCS) (TCGA, PanCancer Atlas)
Diffuse Large B-Cell Lymphoma (DLBC) (TCGA, PanCancer Atlas)
Cholangiocarcinoma (CHOL) (TCGA, PanCancer Atlas)
Acute Myeloid Leukemia (LAML) (TCGA, PanCancer Atlas)
Testicular Germ Cell Tumors (TGCT) (TCGA, PanCancer Atlas)

1
https://www.cbioportal.org/
10

Mesothelioma (MESO) (TCGA, PanCancer Atlas)
Breast Invasive Carcinoma (BRCA) (TCGA, PanCancer Atlas)
Head and Neck Squamous Cell Carcinoma (HNSC) (TCGA, PanCancer Atlas)
Uveal Melanoma (UVM) (TCGA, PanCancer Atlas)
Cervical Squamous Cell Carcinoma (CESC) (TCGA, PanCancer Atlas)
Glioblastoma Multiforme (GBM) (TCGA, PanCancer Atlas)
Liver Hepatocellular Carcinoma (LIHC) (TCGA, PanCancer Atlas)
Esophageal Adenocarcinoma (ESCA) (TCGA, PanCancer Atlas)
Lung Adenocarcinoma (LUAD) (TCGA, PanCancer Atlas)
Kidney Chromophobe (KICH) (TCGA, PanCancer Atlas)
Adrenocortical Carcinoma (ACC) (TCGA, PanCancer Atlas)
Thyroid Carcinoma (THCA) (TCGA, PanCancer Atlas)
Pheochromocytoma and Paraganglioma (PCPG) (TCGA, PanCancer Atlas)
Skin Cutaneous Melanoma (SKCM) (TCGA, PanCancer Atlas)
Sarcoma SARC (TCGA, PanCancer Atlas)
Brain Lower Grade Glioma (LGG) (TCGA, PanCancer Atlas)
Kidney Renal Papillary Cell Carcinoma (KIRP) (TCGA, PanCancer Atlas)
Prostate Adenocarcinoma (PRAD) (TCGA, PanCancer Atlas)
Bladder Urothelial Carcinoma (BLCA) (TCGA, PanCancer Atlas)
Uterine Corpus Endometrial Carcinoma (UCEC) (TCGA, PanCancer Atlas)
Thymoma (THYM) (TCGA, PanCancer Atlas)
Colorectal Adenocarcinoma (COAD) (TCGA, PanCancer Atlas)
Clinical studies (14 studies)
TCGA, PanCancer Atlas
Genentech, Nature 2012
SMMU, Eur Urol 2017
11

MSK, Science 2015
UHK, Nat Genet 2011
Broad, Cancer Discov 2014
Broad, Cell 2012
CPTAC, Cell 2020
TCGA, Firehose Legacy
Broad/Cornell, Cell 2013
MSKCC/Broad, Nat Genet 2010
Broad/Cornell, Cell 2013
Fred Hutchinson CRC, Nat Med 2016
MSK/DFCI, Nature Genetics 2018
2.1.2. Data visualization
Using GraphPad Prism (Version 8.0.1), the genetic alterations identified in apolipoprotein genes
across various cancer types were visualized as heat maps. The heat maps utilized the same color
coding as cBioportal, displaying the frequency of APOs alterations, including amplification in red,
mutations in green, and deep deletions in blue for the 22 genes. The intensity of the color represents
the frequency of gene alterations per cancer type.

2.1.3. Statistical analysis
We used a panda package (Python 3.5.) to generate a single txt file for each APO gene using
a Python code. The generated files were used for additional data analysis and visualization.. Each
file contained information on 32 types of cancer, the frequency of alterations (amplification,
mutation, and deletion) related to each of the 22 APO genes, and the number of patients in each
cancer type. The files were then combined into one txt that contains cancer types, APO genes
12

alteration frequencies and copy number (amplification, mutation, and deletion) in each study.

We used GraphPad Prism 8.0.1 to calculate descriptive statistics, including the minimum and
maximum frequency ranges for all alterations across all genes.. Using GraphPad Prism 8.0, we also
compared the frequency of alteration in all APO genes between amplification, mutation, and
deletion.. We performed an ordinary one-way ANOVA test followed by Tukey's multiple
comparisons test to determine the P-value within and between groups. We also compared the overall
survival (OS) between the mutated and unmutated groups across all APO genes, which refers to the
length of time from the start of a treatment or diagnosis of a disease until death from any cause, and
generated Kaplan-Meier survival curves. The statistical significance threshold for all analyses was
set at p<0.05. P value was adjusted by Bonferroni correction for the multiple tests for the survival
analysis.

Chapter 3: Results
3.1. The landscape of APOs genes alterations in cancer
Data on the expression of 22 APOs genes in 10,953 samples from 32 cancer studies were
13

obtained from cBioportal. Figure 1 depicts the major APOs gene alterations observed in this study:
amplification, mutation, and deletion. The 32 cancer types had at least one alteration in each
apolipoprotein gene, with gene amplification and mutations constituting the most prevalent genomic
alterations. APOs gene expression data was downloaded from cBioportal, involving 10,953 samples
from 32 cancer studies and 22 APOs genes.
In figure 1, Lung Squamous Cell Carcinoma and Skin Cutaneous Melanoma exhibited the
highest level of genomic alterations, with around 50% of cases exhibiting amplifications, mutations,
deletions, or multiple alterations. Esophageal Adenocarcinoma and Bladder Urothelial Carcinoma
carcinoma also displayed substantial genomic instability, with alterations in 40% of cases. In
contrast, Thyroid Carcinoma showed the lowest frequency of alterations, with less than 5% of cases
affected.

Figure 1. Patterns of APOs genes genomic dysregulation in cancer.
Figure 1 depicts the analysis of mutation and copy number alterations in Apolipoproteins (APOs)
across different cancers, as determined by cBioPortal. The frequency of various alterations in APOs
genes, such as amplification (in red), mutations (in green), deletions (in blue), and multiple
alterations (in gray).
14

3.2. APO genes are frequently altered in patients with cancer.
Range and mean values for the three categories of APO gene alterations (amplification, mutation,
and deletion) exhibited substantial variation. Breast Invasive Carcinoma exhibited the highest levels
of amplification with 177 patients out of 996 (1.17% APO gene amplification frequencies per
patient). In contrast, Testicular Germ Cell Tumors exhibited the lowest levels of amplification, with
only one patient out of 144 (amplification frequency of 0.03%) exhibiting amplified regions.
Mutations were the second most prevalent form of APO gene alteration. The mutation frequency
was greatest in cutaneous melanoma, with 179 patients out of 363 (3.25%) affected. In contrast,
Uveal Melanoma, Mesothelioma, Pheochromocytoma and Paraganglioma, and Kidney
Chromophobe had the lowest mutation rates, ranging from 0.02-0.06% of cases. However, Breast
Invasive Carcinoma demonstrated the greatest frequency of deletion, affecting 47 patients out of 996
(0.4%). In contrast, Mesothelioma, Acute Myeloid Leukaemia, Kidney Chromophobe, and Thyroid
Carcinoma exhibited no deletions (0 percent frequency of deletions). The higher standard deviations
of 44.02 and 41.05 for amplification and mutation frequencies, respectively, indicate greater
variability. The absence of deletions in certain forms of cancer demonstrates the substantial inter-
tumor variation in genomic instability. At the same time, in some types of cancer, 12.53% of patients
showed at least one deleted region. Deletions, like other measures of genomic alteration, exhibit both
intra- and inter-tumor differences in frequency and distribution.
A one-way ANOVA test was conducted to determine if significant differences existed between
the mean frequencies for all APO genes of the three alteration types: amplification, mutation, and
deletion. The ordinary one-way ANOVA (with Tukey's multiple comparison test) showed that the
frequency of APO gene amplification was higher than deletion, with a statistically significant p-
value of 0.02 (Figure 2). However, there was no statistically significant difference between the
frequency of amplification and mutation (p-value = 0.80) or mutation and deletion (p-value = 0.11).
15

Figure 2. Amplification was significantly more frequent than deletion.
In Figure 2, the patient count was altered (mean ± SD), the frequency of copy number alterations in
cancer patients is depicted by the red, green, and blue bars, representing amplification, mutation, and
deletion, respectively.

The results of the one-way ANOVA test indicate that there are significant differences in the
frequencies of genomic alterations across cancer types. Specifically, the mean amplification
frequency (36.37%) was found to be significantly higher than the mean deletion frequency (12.53%).
This difference had a mean value of 23.84%, with a 95% confidence interval (CI) ranging from
2.624% to 45.06%. However, there was no significant difference observed between the frequencies
of amplification (36.37%) and mutation (30.75%). The mean difference between these two
frequencies was 5.625%, with a 95% confidence interval ranging from -15.59% to 26.84%.
Similarly, there was no significant difference between the frequencies of mutation (30.75%) and
deletion (12.53%). The mean difference between these two frequencies was 18.22%, with a 95%
confidence interval ranging from -3.001% to 39.44%.
16

3.3. APOs genes are highly amplified in cancer.
This study investigated the amplification of APO tumor suppressor genes in various types of
cancer. In figure 3, APO gene amplifications have been observed in various cancers, and this
analysis identified APOA2, APOD, and APOH as the genes most frequently amplified. APOA2
showed the highest amplification in Bladder Urothelial Carcinoma (15.32%), Cholangiocarcinoma
(13.88%), Liver Hepatocellular Carcinoma (11.02%), and Breast Invasive Carcinoma (9.88%).
APOD was most amplified in Lung Squamous Cell Carcinoma (29.77%), Ovarian Serous
Cystadenocarcinoma (15.75%), Cervical Squamous Cell Carcinoma (14.14%), and Esophageal
Adenocarcinoma (18.68%). APOH amplifications occurred at the highest frequencies in
Mesothelioma (5.75%) and Breast Invasive Carcinoma (5.63%). Furthermore, each APO gene shows
a unique distribution of amplifications across tumors. For example, APOA2 is frequently amplified
in urologic, gastrointestinal and breast cancers whereas APOD amplifications predominate in
squamous cell carcinomas and ovarian cancer.

We found that APOD had the highest frequency of gene amplification across all cancer types,
APOD frequencies ranges from (0.16%) in Colorectal Adenocarcinoma to (29.7%) in Lung
Squamous Cell Carcinoma, suggesting distinct molecular mechanisms underlying these changes in
different cancers. The diverse prevalence of amplifications implies that although the same genes are
targeted, they likely contribute to tumorigenesis in distinct ways across cancer groups. In contrast,
APOJ had the lowest frequency of amplification (0.16%) in Colorectal Adenocarcinoma.
The heatmap in Figure 3 provides a visual representation of amplification frequency for each
APO gene in different types of cancer. This figure illustrates that APOD amplifications are prevalent,
but each gene shows a unique distribution of changes across cancers. For instance, APOD
17

amplifications primarily affect squamous cell carcinomas and lung cancer whereas APOA2 changes
are more common in gastrointestinal and breast tumors. However, further experimental evidence is
needed to determine the functional impacts of these alterations and their promise as therapeutic
targets by identifying vulnerabilities that could be exploited clinically.

Figure 3. APOs amplification in cancer.
In figure 3, the frequency of amplification for each APO gene is depicted by the color gradient scale,
ranging from 0-30% to describe the intensity of amplification across different cancer types. In
addition, the intensity of the color represents the frequency of gene alterations per cancer type.

3.4. APOs genes are frequently mutated in cancer.
Mutation frequencies of APO genes exhibited substantial heterogeneity across cancer types,
ranging from (0.02%) in Pheochromocytoma and Paraganglioma to (3.2%) in Skin Cutaneous
18

Melanoma. Figure 4 illustrates that APOB had the highest average mutation frequency (6.0%) across
all genes and was mutated in all cancers except Mesothelioma, Uveal Melanoma, Kidney
Chromophobe, Pheochromocytoma, and Paraganglioma. APOB exhibited the highest mutation
frequencies, with (32.88%) in Skin Cutaneous Melanoma, (18.19%) in Lung Adenocarcinoma, and
(16.26%) in Uterine Corpus Endometrial Carcinoma.
Figure 4. APOs genes commonly exhibit mutations in cancer.
In Figure 4, the frequency of APO gene mutations across different cancer types is depicted using
color gradient scale ranging from 0-30% to describe the frequency of mutation.

Frequencies of APOB mutations ranged from (0.8%) in Thyroid Carcinoma to (32.88%) in Skin
Cutaneous Melanoma, demonstrating its widespread dysregulation as an oncogene. In contrast,
APOC4 exhibited no mutations across 32 cancer types, indicating that it is targeted differently than
other APO genes. Each APO gene showed a unique pattern of mutation frequencies across cancers,
demonstrating substantial heterogeneity despite analyzing the same set of genes. Although some
APO genes, such as APOB, have significant mutation rates in certain cancers, this is not the case for
19

all APO genes.
3.5. The frequency of APOs genes deletions in cancer
The highest frequency of deep deletion, which refers to the loss or removal of a significant
portion of a gene or a section of DNA resulting in the loss or alteration of the genetic information
encoded by that gene, varied from (0.05%) in Glioblastoma Multiforme to (1.23%) in Diffuse Large
B-Cell Lymphoma across all cancers. The analysis revealed that the frequency of genetic alterations
in the APOA, APOJ/CLU, and APOO genes were mostly altered by deep deletion. Figure 5 showed
that APOA1, APOA4, and APOA5 were highly altered in Testicular Germ Cell Tumors (2.68%),
Cervical Squamous Cell Carcinoma (2.02%), and Skin Cutaneous Melanoma (2.48%). While APOJ
is altered more frequently in Prostate Adenocarcinoma (6.68%), Ovarian Serous
Cystadenocarcinoma (6.50%), Liver Hepatocellular Carcinoma (5.91%), Bladder Urothelial
Carcinoma (5.35%), Lung Squamous Cell Carcinoma (4.11%), Breast Invasive Carcinoma (3.97%),
and Cholangiocarcinoma (2.78%). Furthermore, APOO gene deletion was altered in Esophageal
Adenocarcinoma (2.74%), Breast Invasive Carcinoma (2.10%), and Diffuse Large B-Cell
Lymphoma (2.08%).
In contrast, the APOB, APOH, and APOL (L1, L3, L4, L5, L6) genes were frequently altered in
Skin Cutaneous Melanoma compared to other types of cancer, whereas the APOC (C1, C2, C4),
APOE, and APOF genes were highly altered in Uterine Carcinosarcoma. Overall, APOA and APOJ
were the genes most frequently disrupted by deep deletion, but each showed a unique distribution of
changes across tumors. For example, APOJ deletions primarily affected Prostate cancer whereas
APOA deletions predominated in Melanoma subtypes.
20

Figure 5. Deletion frequencies of APO genes across all types of cancer.
In Figure 5, the frequency of APO gene deletions is depicted using a color gradient scale ranging
from 0-2-4-6%, which describes the frequency of deletion across different cancer types.

We have created Table 2, to provide a comprehensive overview of the p-values for APO genes
available on cBioPortal, This table encompasses a column for all APO genes under investigation. A
second column enumerates the names of studies that have examined these APO genes, while
excluding repeated samples from similar studies. A third column includes the number of cases
analyzed for each APO gene and the median survival time in months for cases with and without
mutations in each APO gene. Finally, the statistical p-value that determines the significance of the
survival impact for each APO gene alteration, as calculated by the corresponding study, is integrated
into the table. Additionally, we have created another table, Table 3, using data from the TCGA
PanCancer Atlas. This table shows the highest cancer alteration per gene, along with corresponding
patient numbers, the most significant genes in terms of survival rate, and the corresponding P-values
21

for each cancer type.
Table 2. APO genes deregulation in cancer
APOs
Genes
Studies Number of
Cases
Median Survival Time
(95% CI)
P-Value
APOA1 TCGA, PanCancer Atlas 211 Altered group 55.07
(46.98 - 94.52)

Unaltered group 79.59
(74.73 - 84.66)
0.271
APOA2 TCGA, PanCancer Atlas 514 Altered group 77.62
(55.69 - 102.77)

Unaltered group 79.46
(73.22 - 84.20)
0.808
APOA4 SMMU, Eur Urol 2017 286 Altered group 64.80
(50.89 - NA)

Unaltered group 81.20
(77.00 - 86.14)
0.427
TCGA, PanCancer Atlas
MSK, Science 2015
APOA5 SMMU, Eur Urol 2017 243 Altered group 67.36
(48.33 - 94.52)

Unaltered group 81.20
(76.80 - 86.14)
0.110
(TCGA, PanCancer Atlas
TCGA, PanCancer Atlas
UHK, Nat Genet 2011
APOB TCGA, PanCancer Atla 1270 Altered group 72.06
(63.02 - 94.22)

Unaltered group 81.17
(76.40 - 86.27)
0.0492
Broad, Cancer Discov 2014
Broad, Cell 2012
TCGA, PanCancer Atla
CPTAC, Cell 2020
MSK, Science 2015
APOC1 TCGA, PanCancer Atlas 166 Altered group 44.55
(34.91 - 58.95)

Unaltered group 81.73
(77.10 - 86.60)

2.328e-5
TCGA, Firehose Legacy
Broad/Cornell, Cell 2013
MSKCC/Broad, Nat Genet 2010
22

APOC2 TCGA, PanCancer Atlas 160 Altered group 40.41
(34.91 - 54.77)

Unaltered group 81.63
(77.03 - 86.60)
1.120e-4
Broad/Cornell, Cell 2013
MSKCC/Broad, Nat Genet 2010
Broad, Cell 2012
APOC3 TCGA, PanCancer Atlas 174 Altered group 51.91
(44.61 - 94.52)

Unaltered group 81.20
(77.00 - 86.14)
0.191
SMMU, Eur Urol 2017
Fred Hutchinson CRC, Nat Med
2016
TCGA, PanCancer Atlas
APOC4 TCGA, PanCancer Atlas 146 Altered group 44.55
(34.91 - 58.95)

Unaltered group 81.63
(77.03 - 86.30)
1.707e-4
SMMU, Eur Urol 2017
Broad/Cornell, Cell 2013
MSKCC/Broad, Nat Genet 2010
APOD TCGA, PanCancer Atlas 692 Altered group 61.04
(52.08 - 76.24)

Unaltered group 82.85
(78.02 - 87.06)
0.0360
TCGA, PanCancer Atlas
TCGA, PanCancer Atlas
TCGA, PanCancer Atlas
TCGA, PanCancer Atlas
APOE TCGA, PanCancer Atlas 190 Altered group 43.43
(35.80 - 59.14)

Unaltered group 81.73
(77.19 - 86.60)
3.247e-4
SMMU, Eur Urol 2017
Genentech, Nature 2012
TCGA, Firehose Legacy)
APOF TCGA, PanCancer Atlas 138 Altered group 67.17
(37.94 - NA)

Unaltered group 81.17
(76.80 - 85.77)
0.474
TCGA, PanCancer Atlas
TCGA, PanCancer Atlas
MSKCC/Broad, Nat Genet 2010
APOH TCGA, PanCancer Atlas 304 Altered group 79.59
(55.86 - 105.04)
0.488
TCGA, PanCancer Atlas
23

TCGA, PanCancer Atlas
Unaltered group 81.17
(76.24 - 85.77)
APOJ
(CLU)
Broad/Cornell, Cell 2013 521 Altered group 81.73
(65.00 - 107.37)

Unaltered group 81.17
(75.75 - 86.04)
0.136
SMMU, Eur Urol 2017
TCGA, PanCancer Atlas)
APOL1 TCGA, PanCancer Atlas 151 Altered group 58.85
(47.54 - 70.16)

Unaltered group 81.63
(77.10 - 86.27)
0.0900
TCGA, PanCancer Atlas
UHK, Nat Genet 2011
APOL2 Broad, Cell 2012 138 Altered group 67.46
(58.85 - NA)

Unaltered group 81.17
(76.40 - 85.77)
0.668
TCGA, PanCancer Atlas
TCGA, PanCancer Atlas
APOL3 TCGA, PanCancer Atlas 141 Altered group 80.12
(47.54 - NA)

Unaltered group 81.17
(76.24 - 85.77)
0.925
Broad, Cell 2012
TCGA, PanCancer Atlas
APOL4 Broad, Cell 2012 131 Altered group 75.16
(55.50 - NA)

Unaltered group
81.17
(76.40 - 85.77)
0.838
Genentech, Nature 2012
TCGA, PanCancer Atlas
APOL5 TCGA, PanCancer Atlas 162 Altered group 66.67
(47.54 - NA)

Unaltered group 81.17
(76.40 - 86.04)
0.617
Broad, Cell 2012
TCGA, PanCancer Atlas
APOL6 TCGA, PanCancer Atlas 139 Altered group 78.21
(55.50 - 103.20)

Unaltered group 81.17
(76.24 - 86.04)
0.432
Broad, Cell 2012
TCGA, PanCancer Atlas
APOM TCGA, PanCancer Atlas 211 Altered group 63.86
(46.09 - 102.84)

Unaltered group 81.20
(77.00 - 86.14)
0.455
MSK/DFCI, Nature Genetics
2018
Broad/Cornell, Cell 2013
24

APOO Fred Hutchinson CRC, Nat Med
2016
225 Altered group 56.58
(44.81 - 90.11)

Unaltered group 81.20
(77.00 - 86.27)
0.0569
TCGA, PanCancer Atlas
TCGA, PanCancer Atlas

3.6. APOs genes alterations are associated with shorter cancer overall survival.
Next we evaluated the association between the genomic and transcriptomic alterations in the
APOs genes with patient’s overall survival. The study's results, as shown in the Kaplan-Meier
survival plot, indicate that changes in 22 specific genes have a significant impact on overall survival
in one or more of the 32 types of cancer investigated. In table 3, we observed a significant effect on
the survival rate in the following types of cancer: skin cutaneous melanoma with APOJ (p-value =
0.012) and APOL1 (p-value = 0.021); lung squamous cell carcinoma with APOA4 (p-value = 0.016)
and APOO (p-value = 0.032); and kidney chromophobe with APOA1 (p-value = 0.027). It is
important to note that these analyses are exploratory and not adjusted by multiple comparison.
Based on the previous data from Table 3, the deletion of the APOJ (CLU) gene affected 6% of
patients with skin cutaneous melanoma in a study involving 363 patients (Figure 6). The altered
group, with a median survival time of 46.45 months, exhibited a lower survival rate compared to the
unaltered group, which had a median survival time of 103.26 months. The p-value of 0.012 suggests
a statistically significant difference in survival between the two groups.
25

Figure 6. Survival Probability in Skin Cutaneous Melanoma Patients with APOJ (CLU) Gene
Alteration: Altered vs. Unaltered Group.
In figure 6, Kaplan-Meier estimates demonstrate a significant difference in the probability of
survival between the altered (red) and unaltered (blue) groups, highlighting the potential prognostic
value of APOJ gene alteration in this cancer type.

Additionally, alterations in APOL1 were found in 7% of patients with skin cutaneous melanoma,
significantly impacting survival time (Figure 7). The altered group, with a median survival time of
46.45 months, exhibited a lower survival rate compared to the unaltered group, which had a median
survival time of 103.26 months. The p-value of 0.021 suggests a statistically significant difference
in survival between the two groups.

26

Figure 7. Survival Probability in Skin Cutaneous Melanoma Patients with APOL1 Gene
Alteration: Altered vs. Unaltered Group.
In Figure 7, Kaplan-Meier estimates demonstrate a significant difference in the probability of
survival between the altered (purple) and unaltered (blue) groups, highlighting the potential
prognostic value of APOL1 gene alteration in Skin Cutaneous Melanoma.

We found that the alterations in the APOA4 gene in lung squamous cell carcinoma are associated
with a statistically significant difference in survival time. The p-value of 0.016 suggests that there is
a low probability of observing such a difference in survival time between the group with APOA4
alterations (13 patients) and the unaltered group purely due to chance (Figure 10). Moreover, the
survival time of the group with APOA4 alterations (27.16 months) appears to be significantly shorter
compared to the unaltered group (62.86 months). This suggests that the presence of APOA4
alterations may be associated with worse survival outcomes in lung squamous cell carcinoma.

27

Figure 8. Survival Probability in Lung Squamous Cell Carcinoma Patients with APOA4 Gene
Alteration: Altered vs. Unaltered Group.
In Figure 10, Kaplan-Meier estimates demonstrate a significant difference in the probability of
survival between the altered (purple) and unaltered (blue) groups, highlighting the potential
prognostic value of APOA4 gene alteration in Lung Squamous Cell Carcinoma.

Additionally, the presence of alterations in the APOO gene in cases of lung squamous cell
carcinoma is significantly linked to differences in survival time. The obtained p-value of 0.032
indicates a low likelihood of observing such a discrepancy in survival time solely due to chance.
This finding is supported by Figure 11, which depicts a distinct group of 10 patients with APOO
alterations. Moreover, compared to the unaltered group with a survival time of 62.86 months, the
group with APOO alterations exhibits a significantly shorter survival time of 27.16 months. These
results suggest that both APOO alterations and APOA4 may be associated with unfavorable survival
outcomes in cases of lung squamous cell carcinoma.
28

Figure 9. Survival Probability in Lung Squamous Cell Carcinoma Patients with APOO Gene
Alteration: Altered vs. Unaltered Group.
In Figure 11, Kaplan-Meier estimates demonstrate a significant difference in the probability of
survival between the altered (pink) and unaltered (blue) groups, highlighting the potential prognostic
value of APOO gene alteration in Lung Squamous Cell Carcinoma.

In Figure 12, patients with kidney chromophobe may have alterations in apolipoprotein A1
(APOA1) gene, although the status of APOA1 gene in the unaltered group is unknown. The p-value
for survival analysis was found to be 0.027, indicating a significant difference in survival between
the two groups. The survival time for patients with altered APOA1 was determined to be 24.79
months; however, the survival time for patients with unaltered APOA1 remains unknown. The
sample size for this study was 65 patients in total, with 3% of them having the queried gene alteration
in this type of cancer.

29

Figure 10. Survival Probability in Kidney Chromophobe Patients with APOA1 Gene
Alteration: Altered vs. Unaltered Group.
In Figure 12, Kaplan-Meier estimates demonstrate a significant difference in the probability of
survival between the altered (yellow) and unaltered (blue) groups, highlighting the potential
prognostic value of APOA1 gene alteration in Kidney Chromophobe.

Table 3. The most frequent cancer alteration in APO genes with significant survival
rate
Cancer type Total
samples/
patients
Gene Number of samples Altered vs
Unaltered
P-value
Skin Cutaneous
Melanoma

363 patients APOL1 Queried gene is altered
in 24 patients (7%)
Altered 46.45
(41.59 - NA)

Unaltered 103.26
(65.92 - 167.90)
0.0205
APOJ
(CLU)
Queried gene is altered
in 21 patients (6%)

Altered 46.45
(26.37 - NA)

Unaltered 103.26
(65.92 - 167.90)
0.0116
30

Lung squamous cell
Carcinoma
469 patients APOA4 Queried gene is altered
in 13 patients (2.8%)
Altered 27.16
(6.97 - NA)

Unaltered 62.86
(46.88 - 86.76)
0.0159
APOO Queried gene is altered
in 10 patients (2.1%)
Altered 27.16
(18.84 - NA)

Unaltered 62.86
(46.88 - 86.76)
0.0323
Cervical Squamous
Cell Carcinoma

278 patients APOH Queried gene is altered
in 8 patients (2.9%)
Altered 21.11
(11.51 - NA)

Unaltered NA
0.0326
APOM Queried gene is altered
in 4 patients (1.4%)
Altered 21.11
(18.25 - NA)

Unaltered NA
0.0279
Pheochromocytoma
and paraganglioma
161 patients APOA2 Queried gene is altered
in 5 patients (3%)
Altered NA

Unaltered NA

0.0108
Kidney
Chromophobe
65 patients APOA1 Queried gene is altered
in 2 patients (3%)
Altered 24.79
(24.79 - NA)

Unaltered NA
0.0273
APOL1
APOL2
APOL3
APOL4
APOL5
APOL6
Queried gene is altered
in 1 patient (1.5%)
Altered 10.68

Unaltered NA
5.66e-15

31

Chapter 4: Discussion and Conclusion
Our study emphasizes the importance of apolipoproteins in cancer, as alterations in these genes
occurred frequently in patients with different cancers and some of which were found to affect patient
survival rates. The findings are consistent with the previous study by Liu et al. (2021), which
demonstrated that APOC2 alterations were prevalent in cancer and associated with poor clinical
outcomes. Additionally, APOC2 upregulation was found to be common in several malignancies, and
its alterations were frequently observed in patients with TP53 mutations (Liu et al., 2021). These
results imply that APOC2 might serve as a viable therapeutic target in cancer treatment. Studies have
also shown that some APOs genes are more frequently mutated in certain types of cancer than others,
such as the APOB gene in colorectal cancer, the APOE gene in breast cancer, and the APOA1 gene
in lung cancer (Gara et al, 2020, Van Dyk et al, 2021, Georgila et al, 2019). It is important to note
that more research is needed to fully understand the relationship between APOs and cancer and the
specific mechanisms by which these mutations may contribute to the development and progression
of cancer. Future studies could investigate the utilization of APOC2 inhibitors and explore the
functional characterization of their anti-tumor effects. Overall, the findings illuminate the potential
role of apolipoproteins in cancer and the need for further research in this area.

In this study, the frequently altered genes associated with 32 different types of cancer were
analyzed. Our analysis revealed that the APOD gene has the highest amplification across all 22 genes
in cancer. It is important to recognize that the expression and function of the APOD gene may vary
between different cancer types. Our data suggests that APOD amplifications are most commonly
observed in squamous cell carcinomas and ovarian cancer. According to Rassart et al. (2020), the
APOD gene is implicated in modulating growth factors that activate cell migration, which may
contribute to cancer progression by facilitating the migration of cancer cells to other parts of the
32

body. However, the impact of APOD may differ in distinct cancer types. Sarjeant et al. (2003)
reported that increased APOD mRNA levels were associated with decreased survival rates in patients
with breast and colorectal cancer. Conversely, Ren et al (2019) identified higher APOD expression
in patients with melanoma, prostate cancer, and renal carcinoma, suggesting that APOD may have
opposite effects on progression and prognosis depending on the tumor. Therefore, future research is
required to fully comprehend the role of APOD gene expression in cancer.

Our study found that the APOB gene is frequently mutated in several cancer types, with Skin
Cutaneous Melanoma, Lung Adenocarcinoma, and Uterine Corpus Endometrial Carcinoma
exhibiting the highest mutation rates. On the other hand, a study by Mazidi et al. (2020) linked
alterations in the APOB gene to increasing the risk of colorectal cancer development. Additionally,
high levels of APOB have been detected in specific cancer types, such as colorectal, liver, and breast
cancer, with some research suggesting that elevated APOB levels may promote cellular growth and
metastasis (Ye et al., 2019). This study highlights the importance of the APOB gene in different
types of cancer and its potential role in promoting cellular growth and metastasis in other cancer
types. The findings, along with previous research, indicate that a more comprehensive understanding
of the diverse functions of the APOB gene in various types of cancer is required.

For instance, Karlsson et al. (2021) found that APOJ was one of the most differentially expressed
genes between immunotherapy responders and non-responders in cutaneous melanoma patients. The
study also found that APOA1 and APOC1 were among the top apolipoprotein genes differentially
expressed between responders and non-responders to immunotherapy in cutaneous melanoma
patients, supporting the potential of apolipoproteins, including APOJ, APOA1, and APOC1, as
biomarkers for predicting response to immunotherapy in cutaneous melanoma patients.
33

Our data indicate that alterations in APOA4 is associated with shorter survival time in Lung
Squamous Cell Carcinoma. This finding aligns with a study conducted by Lee et al. (2012) explores
a new technique for identifying non-small cell lung cancer by analyzing multiple serum biomarkers
using bead-based profiling. The authors specifically employ APOA4 as a biomarker in their method
to detect lung cancer.

Our findings establish a correlation between APOA1 variants and renal cancer, specifically
linked to kidney chromophobe. Georgila et al. (2019) reported that APOA1 is involved in cancer
progression and metastasis, with varying expression levels observed across different cancer types.
the authors noted that increased APOA1 levels have been observed in small-cell lung carcinoma,
hepatocellular carcinoma, and bladder cancer, while ovarian cancer, non-small cell lung carcinoma,
colorectal cancer, lymphoma, prostate cancer, and kidney renal cell cancer have decreased APOA1
levels.

In summary, analysis of genomic data reveals that APO genes, including APOA1, are frequently
altered in various cancers, with amplifications and mutations being the most common changes.
However, the mechanisms by which these genetic alterations contribute to cancer development and
progression remain unclear. Further research on the relationship between APO genes and cancer
could lead to new diagnostic and treatment options for patients. Additional studies are necessary to
better understand the role of APO genes in cancer, which could advance cancer research and care.

The significant difference in the mean value of amplification is higher than the mean values of
mutation and deletion, and the mean value of mutation is higher than the mean value of deletion.
34

Amplification increases the number of gene copies and their expression, while deletion decreases
gene copy number and expression. The higher mean value of amplification in comparison to deletion
indicates that increased APO expression may be more prevalent than decreased expression in the
studied population. Further research is needed to determine the specific types of amplifications,
mutations, and deletions that occur in the APO gene, as well as their effects on APO expression and
subsequent biological consequences.

Recent advancements in cancer research have led to a deeper understanding of the complex
genetic and molecular mechanisms underlying the development and progression of cancer. For
instance, studies have identified specific genes and pathways that are involved in cancer growth and
metastasis, leading to the development of targeted therapies that inhibit the activity of these genes or
pathways. For example, a study by Rizvi et al. (2015) identified a novel gene signature that predicts
the response to immune checkpoint blockade therapy in patients with melanoma. They found that
the expression of specific genes involved in immune cell activation and regulation was associated
with enhanced treatment response and survival. This finding has significant implications for the
development of personalized cancer treatments that can target specific molecular pathways and
improve patient outcomes. Similarly, a study by Xu et al. (2021) identified genes regulating glucose
metabolism overexpressed in pancreatic cancer cells. They showed that inhibiting the activity of
these genes using a small molecule inhibitor could effectively induce cancer cell death and improve
the efficacy of chemotherapy in preclinical models. This approach may represent a promising avenue
for developing novel cancer treatments that target the specific metabolic vulnerabilities of cancer
cells.
Conclusion
This study concludes with substantial insights into the potential significance of
35

apolipoproteins in cancer. The connections between alterations in APO genes and cancer are
complex and vary between different forms of cancer. Each gene has a different action depending on
the gene itself or the type of cancer. For example, APOD was highly amplified, APOB was highly
mutated, and APOJ was highly deleted. Additionally, the average frequency of amplification was
higher than deletion, while the comparisons between amplification vs. mutation or mutation vs.
deletion were not statistically significant.

We have identified associations between alterations in APOA1, APOA4, APOJ, APOL1 and
APOO with survival rates and poor prognosis in various types of cancer. For example, alterations in
the APOJ gene may serve as a therapeutic target in Skin Cutaneous Melanoma as it is linked to poor
prognosis or outcomes. Additionally, APOA1 and APOL1 gene variants are linked to kidney disease
risk and mortality in renal cancers. In summary, our findings highlight the need for further research
on apolipoproteins to better understand their functions in the development and progression of cancer.
A deeper understanding of the relationships between apolipoproteins and cancer could lead to the
development of more effective diagnostic and treatment strategies that are tailored to the specific
needs of individual patients and cancers. Continuing investigation in this field could lead to
discoveries that advance precision oncology and reduce cancer mortality.
36

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Asset Metadata

Creator Swadi, Khadija Hafed (author)

Core Title Genomic and transcriptomic alterations of apolipoproteins genes in cancers

Contributor Electronically uploaded by the author (provenance)

School School of Pharmacy

Degree Master of Science

Degree Program Pharmaceutical Sciences

Degree Conferral Date 2023-08

Publication Date 08/28/2023

Defense Date 08/08/2023

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

Tag alteration,amplification,apolipoprotein,cancer,deletion,lipid,mutation,OAI-PMH Harvest

Format theses (aat)

Language English

Advisor Alachkar, Houda (committee chair), Haworth, Ian (committee member), Okamoto, Curtis (committee member)

Creator Email pharmd.khadija@gmail.com,swadi@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113302375

Unique identifier UC113302375

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Format theses (aat)

Rights Swadi, Khadija Hafed

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Type texts

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Repository Email uscdl@usc.edu

Abstract (if available)

Abstract Lipid metabolism is a vital source of energy for cancer survival and growth. Apolipoproteins (APOs) are proteins that bind to lipids and promote diverse lipid metabolic processes. Previous research has shown that apolipoprotein C2 (APOC2) is upregulated in several varieties of cancer, where it promotes growth and survival. This study evaluates the types and the frequencies of the genomic and transcriptomic patterns of the other apolipoproteins in cancer. The Cancer Genome Atlas (TCGA) data were utilized to analyze 22 apolipoprotein genes in 32 categories of cancer. In 2818 (26%) of the examined patients, amplifications, mutations, and profound deletions were identified as the primary APOs alterations. Apolipoprotein D (APOD) was the most frequently amplified gene, which ranged from 0.16% in Colorectal Adenocarcinoma to 29.7% in Lung Squamous Cell Carcinoma. The incidence of APOs gene mutations was highest in Apolipoprotein B (APOB), which ranged from 0.8% in Thyroid Carcinoma to 32.88 % in Skin Cutaneous Melanoma. The frequency of profound deletion was the highest in Apolipoprotein J (APOJ), which ranged from 0.35% in Kidney Renal Papillary Cell Carcinoma and 6.68% in Prostate Adenocarcinoma. These analyses suggest that APOs genes are substantially dysregulated in cancer, and that further functional and mechanistic studies are required to investigate the role of specific APO genes in specific cancer types.