Pathogen recognition, inflammation, and ovarian cancer Restricted; Files Only

Mandle, Hannah (Spring 2024)

Permanent URL: https://etd.library.emory.edu/concern/etds/08612p90z?locale=de
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Abstract

Epithelial ovarian cancer (EOC) accounts for roughly 2.5% of all cancers among natal women and yet EOC has the fifth highest mortality rate among female cancers in the US. Although studies have identified factors associated with EOC risk and survival, the underlying biologic mechanisms of these factors are still largely unknown. The overarching goal of this research is to evaluate genetic variants in pathogen recognition and downstream inflammation processes as they relate to EOC and high-grade serous EOC (HGSOC, the most common histotype) risks and survival among Black and White women.

In Aim 1, we investigate the aggregate association of TLR, NFkB and TNF signaling genes and pathways with ovarian cancer risk among Black and White women separately. Per Praw < 0.05, MAPK-related genes, present in all three pathways, were associated with EOC/HGSOC risks among both Black and White women. Among White women MYD88 and CCL2 were associated with EOC risk; PARP1 and TICAM2 were associated with HGSOC risk. Among Black women, MAP3K8, MAP3K7, and PRKCB were associated with EOC risk and indicated to have an interaction with BMI. 

In Aim 2, we investigate the association TLR, NFkB and TNF signaling genes and pathways with EOC/HGSOC 5-year overall survival. AKT3 and CTSK genes were associated with EOC/HGSOC 5-year survival in both Black and White women. LTA was the only gene observed to possibly have a Black EOC 5-year survival association differential by BMI.

In Aim 3, we investigate differentially expressed genes (DEGs) using RNA-Seq data from Black and White HGSOC tumor tissues. Black and White women were analyzed separately, and we compare DEGs between 5-year survival (yes/no) and FIGO stage (early/late). CXCL9 was differentially expressed for survival in both Black and White women. BLNK, CEBPB, PIK3R1, PIK3CD, TLR4, MMP14, JUN, ICAM1, MAPK10, and TRAF6 were also differentially expressed by stage at diagnosis regardless of race.

In this dissertation, we identified genes associated with EOC and/or HGSOC risk and survival that may provide mechanistic insight for ovarian carcinogenesis and progression and possible novel hypothesis generation.

Table of Contents

Table of Contents

List of Tables. 1

List of Figures. 3

Chapter 1: Background and Literature Review.. 5

Ovarian Cancer 5

Epithelial Ovarian Cancer Epidemiology. 5

Biological Hypotheses for Epithelial Ovarian Carcinogenesis. 11

Inflammation and Cancer 11

Inflammation and Innate Immunity: The Toll-Like Receptor Pathway. 15

TLRs/inflammation and Obesity. 17

TLRs, inflammation, and race. 18

TLR polymorphisms and Cancer Risk and Survival 19

Summary of Critical Literature Review.. 19

Chapter 2: Specific Aims. 21

Chapter 3: Data Sources and Methods. 21

3.1. Data Sources. 22

3.1.1 The African American Cancer Epidemiology Study. 22

3.1.2. The Ovarian Cancer Association Consortium.. 22

3.2. Study Populations. 22

3.3. Variables. 23

3.3.1. Exposures. 23

3.3.1a. SNP selection, genotype data and quality control 23

3.3.1b. RNA Extraction and quantification of gene expression data. 24

3.3.2. Outcomes. 25

3.3.3. Covariates. 25

3.4. Analytic Methods. 27

3.4.1. Aim 1. 27

3.4.2. Aim 2. 28

3.4.3. Aim 3. 29

Chapter 4: Aim 1. 30

4.1. Abstract 31

4.2 Introduction. 33

4.3 Methods. 36

4.3.1 Case/control ascertainment and selection. 36

4.3.2. SNP Selection, Genotyping, and Quality Control 36

4.3.3. Genes and Pathways. 37

4.3.4. Statistical Analysis. 37

4.4. Results. 39

4.5. Discussion 41

4.6. Tables and Figures. 48

Chapter 5: Aim 2. 54

5.1. Abstract 55

5.2. Introduction. 56

5.3. Methods. 58

5.3.1. Case ascertainment and vital status. 58

5.3.2. SNP Selection, Genotyping, and Quality Control 59

5.3.3. Genes and Pathways. 60

5.3.4. Statistical Analysis. 60

5.4. Results. 62

5.5. Discussion. 64

5.6. Tables and Figures. 68

Chapter 6: Aim 3. 72

6.1. Abstract 73

6.2 Introduction. 74

6.3. Methods. 76

6.3.1. Study Population. 77

6.3.2. RNA Extraction. 77

6.3.3. Quantification of gene expression data. 78

6.3.4. Germline Genotyping and Quality Control 78

6.3.5. Statistical analysis. 79

6.4. Results. 80

6.4.1. Survival 80

6.4.2. Stage. 81

6.5. Discussion. 82

6.6. Tables and Figures. 86

Chapter 7: Public Health Implications and Future Directions. 96

References. 96

Supplementary Tables and Figures. 119

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