MECHANISMS of TUMORIGENESIS in AFRICAN AMERICAN COLORECTAL CANCER by Gaius J. Augustus

Mechanisms of Tumorigenesis in African American Colorectal Cancer

Item Type text; Electronic Dissertation

Authors Augustus, Gaius Julian

Publisher The University of Arizona.

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MECHANISMS OF TUMORIGENESIS IN AFRICAN AMERICAN COLORECTAL CANCER

Gaius J. Augustus

A Dissertation Submitted to the Faculty of the

GRADUATE INTERDISCIPLINARY PROGRAM IN CANCER BIOLOGY

In Partial Fulfillment of the Requirements

For the Degree of

DOCTOR OF PHILOSOPHY

In the Graduate College

THE UNIVERSITY OF ARIZONA

2019

Mechanisms of Tumorigenesis in African American CRC

Acknowledgements

This work was supported by grants from the National Cancer Institute (U01

CA153060 and P30 CA023074, NAE; RO1 CA204808, HRG, EM, LTH; RO1

CA141057, BJ) and the American Cancer Society Illinois Division (223187, XL). GJA was supported by a Cancer Biology Training Grant (T32CA009213). The funders had no role in the design of the study; the collection, analysis, or interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication.

The author gratefully acknowledges the recruiters of the CCCC for their dedication and integrity, including Maggie Moran, Timothy Carroll, Katy Ceryes, Amy

Disharoon, Archana Krishnan, Katie Morrissey, Maureen Regan, and Katya Seligman.

Zarema Arbieva and the University of Illinois at Chicago Genomics Core in the Research

Resources Core performed the hybridization and initial analysis of CytoScan HD arrays.

The author additionally thanks Mary Yagle and Johnathan Blohm for their assistance in SNP genotyping.

Mechanisms of Tumorigenesis in African American CRC

Dedication

I dedicate this work to DiAngele Augustus, without whom none of my success would be possible.

Mechanisms of Tumorigenesis in African American CRC

Table of Contents

ABSTRACT 8

CHAPTER 1 - COLORECTAL CANCER DISPARITY IN AFRICAN AMERICANS: RISK FACTORS AND CARCINOGENIC MECHANISMS 9

ABSTRACT 10 INTRODUCTION 11 IMPACT OF RISK FACTORS ON CRC INCIDENCE 11 ENDOSCOPIC SCREENING REDUCES CANCER INCIDENCE 11 GENETIC RISK FACTORS AND CRC INCIDENCE 15 CAN VITAMIN D LEVELS EXPLAIN DIFFERENCES IN CRC INCIDENCE IN AFRICAN AMERICANS? 24 DIETARY INFLUENCES ON CRC AND THE GUT MICROBIOME 26 ARE CARCINOGENIC MECHANISMS DIFFERENT IN AFRICAN AMERICAN CRC? 29 SIMILAR FREQUENCIES OF MICROSATELLITE INSTABILITY 30 SOMATIC MUTATIONS IN AFRICAN AMERICAN CRC 31 EPIGENETIC CHANGES IN AFRICAN AMERICAN CRC 34 CRC-SPECIFIC GENE DYSREGULATION 38 THE CONTINUING PROBLEM OF CRC MORTALITY IN AFRICAN AMERICANS 39

CHAPTER 2 - IS INCREASED COLORECTAL SCREENING EFFECTIVE IN PREVENTING DISTANT DISEASE? 42

ABSTRACT 43 INTRODUCTION 45 MATERIALS AND METHODS 46 DATA ACQUISITION 46 STATISTICAL ANALYSES 48 AVAILABILITY OF DATA AND MATERIAL 48 RESULTS 49 DECREASE IN INCIDENCE RATE OF DISTANT CRC IS SLOWER THAN THE DECREASE IN INCIDENCE RATES OF LOCALIZED AND REGIONAL CRC 49 DECREASE IN INCIDENCE RATE OF DISTANT CRC IS SLOWER IN PATIENTS DIAGNOSED WITH CRC AT 50 OR MORE YEARS OF AGE 54 DECREASE IN INCIDENCE RATE OF DISTANT CRC IS SLOWER FOR BOTH PROXIMAL AND DISTAL CRCS 56 DECREASE IN INCIDENCE RATE OF DISTANT CRC IS SLOWER FOR MOST ETHNIC GROUPS 57 DECREASE IN INCIDENCE RATE OF DISTANT CRC IS SLOWER IN BOTH MALES AND FEMALES 57 DISCUSSION 58 INADEQUATE SCREENING DOES NOT EXPLAIN THE SLOW DECREASE IN INCIDENCE OF DISTANT CRC 60 MORE RAPIDLY ADVANCING CANCERS OF THE SERRATED ADENOMA PATHWAY CAN ONLY EXPLAIN PART OF THE SLOW DECREASE IN INCIDENCE OF DISTANT CRC 61 HYPOTHESIS OF NONMSI CRC THAT ADVANCES RAPIDLY 62 LIMITATIONS AND ALTERNATIVE THEORIES 64

Mechanisms of Tumorigenesis in African American CRC

CHAPTER 3 - RACE-DEPENDENT ASSOCIATION OF SULFIDOGENIC BACTERIA WITH COLORECTAL CANCER 66

ABSTRACT 67 ABBREVIATIONS 69 INTRODUCTION 70 MATERIALS AND METHODS 71 HUMAN SUBJECTS 71 QUANTITATIVE POLYMERASE CHAIN REACTION (QPCR) ANALYSIS 72 STATISTICAL ANALYSIS 75 ANALYSIS OF DIETARY INTAKE 75 RESULTS 76 RACE-SPECIFIC DIFFERENCES IN MUCOSAL SULFIDOGENIC BACTERIA 76 ASSOCIATIONS BETWEEN DIET AND SULFIDOGENIC BACTERIA 81 DISCUSSION 92

CHAPTER 4 - LACK OF APC SOMATIC MUTATION IS ASSOCIATED WITH EARLY-ONSET COLORECTAL CANCER IN AFRICAN AMERICANS 96

ABSTRACT 97 INTRODUCTION 99 MATERIALS AND METHODS 100 ASCERTAINMENT, RECRUITMENT, AND BIOSPECIMEN COLLECTION 100 DNA SEQUENCE ANALYSIS 101 COPY NUMBER ANALYSIS 102 METHYLATION ANALYSIS 103 STATISTICAL ANALYSIS 103 RESULTS 104 APC MUTATION-NEGATIVE TUMORS ARE ASSOCIATED WITH EARLY-ONSET CRC 115 UNDER-REPRESENTATION OF KNOWN DRIVER GENES IN AFRICAN AMERICAN CRCS 119 COPY NUMBER VARIATION IN AFRICAN AMERICAN CRCS 123 METHYLATION PATTERNS IN APC MUTATION-NEGATIVE VS. MUTATION-POSITIVE TUMORS 127 DISCUSSION 134

CHAPTER 5 - DECREASED COPY-NEUTRAL LOSS OF HETEROZYGOSITY IN AFRICAN AMERICAN COLORECTAL CANCERS 139

ABSTRACT 140 INTRODUCTION 142 METHODS 146 DATA ACQUISITION 146 DATA PROCESSING 147 SMALL INTERSTITIAL CNLOH ANALYSIS 149 STATISTICAL ANALYSES 151 RESULTS 153 AFRICAN AMERICANS AND WHITES HAVE SIMILAR FREQUENCIES OF COPY NUMBER GAINS AND LOSSES 153

Mechanisms of Tumorigenesis in African American CRC

WHITE CRCS HAVE A HIGHER FREQUENCY OF CNLOH THAN AFRICAN AMERICAN CRCS FOR MOST CHROMOSOME ARMS 153 WHITE CRCS HAVE MORE CHROMOSOME ARMS AFFECTED BY CNLOH THAN AFRICAN AMERICAN CRCS AFTER ADJUSTMENT FOR COVARIATES 162 SMALL INTERSTITIAL COPY-NEUTRAL LOSS OF HETEROZYGOSITY (SI-CNLOH) 166 DISCUSSION 180 CONCLUSIONS 186

CHAPTER 6 - IMPLICATIONS AND FUTURE DIRECTIONS FOR AFRICAN AMERICAN COLORECTAL CANCER 187

INTRODUCTION 188 SUSCEPTIBILITY 189 TUMORIGENESIS 190 LIMITATIONS AND FUTURE DIRECTIONS 191

APPENDIX A 192

APPENDIX B 193

APPENDIX C 194

APPENDIX D 202

REFERENCES 207

Mechanisms of Tumorigenesis in African American CRC

Abstract

While colorectal cancer (CRC) incidence has decreased over the past 20 years, the reduction in incidence has not been uniform across all stages of disease. The reduction in late stage (distant) CRC was significantly less than that of than earlier stage CRC, a trend enriched for early-onset CRCs. African Americans have the highest incidence and mortality rates of CRC of any ethnic group in the United States and are more likely to present before recommended guidelines for screening (i.e., age of 50 years). Despite this ongoing health disparity, relatively few studies have sought to address risk factors and etiological signatures unique to African American CRC. We hypothesized that molecular characteristics in the gut microenvironment and tumor mutation profiles of African

American CRCs are unique. The studies presented here sought to address this hypothesis through molecular studies in a low-income cohort from urban Chicago, the Chicago

Colorectal Cancer Consortium, as well as a publicly available cohort, The Cancer

Genome Atlas. We found that African Americans have higher abundances of the sulfidogenic bacterium Bilophila wadsworthia, a trend that remained after adjusting for covariates including diet. African American cases had significantly higher abundances than African American controls, a trend that did not exist in non-Hispanic Whites. We found that African American CRCs had molecular features that were distinct from non-

Hispanic Whites. CCCC African American CRCs had significantly fewer mutations than expected in APC, a gene typically mutated in 80% of CRCs, and that the lack of APC mutation was associated with younger age, chromosome stability, and a non-CIMP DNA methylation profile. Together, the findings presented here suggest that unknown risk factors and unique tumorigenic processes drive CRC in African Americans.

Mechanisms of Tumorigenesis in African American CRC

Chapter 1

Colorectal Cancer Disparity in African Americans: Risk Factors and Carcinogenic Mechanisms

Originally published in the American Journal of Pathology (Permissions can be found in Appendix A) Augustus GJ, Ellis NA. Colorectal Cancer Disparity in African Americans: Risk Factors and Carcinogenic Mechanisms. Am J Pathol. 2018;188(2):291-303. doi:10.1016/J.AJPATH.2017.07.023

9 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Abstract

African Americans have the highest incidence and mortality rates of colorectal cancer

(CRC) of any ethnic group in the United States. Although some of these disparities can be explained by differences in access to care, cancer screening, and other socioeconomic factors, disparities remain after adjustment for these factors. Consequently, an examination of recent advances in the understanding of ethnicity-specific factors, including genetic and environmental factors relating to risk of CRC, the biology of CRC progression, and the changes in screening and mortality, is important for evaluating our progress toward eliminating the disparities. An overarching limitation in this field is the number and sample size of studies performed to characterize the etiological bases of CRC incidence and mortality in African Americans. Despite this limitation, significant differences in etiology are manifest in many studies. These differences need validation, and their impacts on disparities need more detailed investigation. Perhaps most heartening, improvements in CRC screening can be attributed to the smallest difference in CRC incidence between African Americans and whites since the late 1980s. Cancer mortality, however, remains a persistent difference.

10 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Introduction

Colorectal cancer (CRC) is the third most common cancer in both men and women in the US and the second most common cause of cancer-related death1. African

Americans bear a disproportionate burden with an incidence of CRC that is more than

20% higher than in whites and an even larger difference in mortality2. In particular,

African Americans are more often diagnosed with CRC at an earlier age and with more advanced disease; and African Americans have a greater proportion of CRCs in the proximal colon3. While some of these differences can be explained by access to care, screening, and other socioeconomic factors, there remains a significant portion of the disparity that remains after adjustment for these factors4. In this chapter, we examine the recent literature on genetic and environmental risk factors, molecular characteristics of

CRC tumors, screening, and cancer-related mortality and how these factors contribute to our understanding of the cancer health disparity in African Americans.

Impact of Risk Factors on CRC Incidence

Endoscopic Screening Reduces Cancer Incidence

Data from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute (https://seer.cancer.gov/data/seerstat/nov2016/, Incidence -

SEER 9 Regs Research Data, Nov 2016 Sub (1973-2014)

Adjustment>) shows that CRC incidence has been decreasing in recent years (Figure

1.1A). The change in CRC incidence is mostly attributed to increased endoscopic examination of the colorectum and the resulting removal of adenomatous and other polyps that are precancerous lesions1. The SEER program also reports trends that reflect

11 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Figure 1.1 (A) Age-adjusted incidence rates of colorectal cancer (CRC) in African

Americans (purple) and whites (green; explicitly non-Hispanic whites) from1992 to2014, all ages, both sexes [data from Surveillance, Epidemiology, and End Results (SEER) 13,

Incidence–SEER 13 Regs Research Data, November 2016 Sub (1992 to 2014)

; https:// seer.cancer.gov/data/seerstat/nov2016, accessed April 14, 2017]. Annual percentage change is depicted as text above data, where

12 Mechanisms of Tumorigenesis in African American CRC Chapter 1 negative values indicate a decreasing trend and positive values indicate an increasing trend. Asterisks denote a rising or falling trend, where the entire 95% CI is above or below 0, respectively. No asterisk indicates a stable trend. (B) Age- adjusted US mortality rates of CRC in African Americans (purple) and whites (green; explicitly non-

Hispanic whites) from1992 to2014, all ages, both sexes (data from SEER 13). Annual percentage change is depicted as text above data, where negative values indicate a decreasing trend.

13 Mechanisms of Tumorigenesis in African American CRC Chapter 1 annual percent change of rates across certain time segments, which we have included above each corresponding segment. Whites (depicted in green) have seen a decrease in

CRC incidence since the 1990s. The incidence of CRC in African Americans (depicted in purple) began to decrease in the early 2000s. The incidence in the US of CRC in African

Americans was 26% higher than whites in 2013. The newest data from the SEER program shows that African Americans have an 11% higher incidence than whites, the lowest difference since the late 1980s. Although screening has clearly achieved substantial reductions in incidence, less than full compliance, early-onset CRCs, and missed lesions will resist further reductions; therefore, efforts to understand genetic and environmental risk factors continue to be important.

The increased risk of disease and cancer-related death in African Americans has led to changes in the screening recommendations in this population, specifically in lowering the age to begin colonoscopic screening to 45 years5–7. Historically, African

Americans have had lower compliance to CRC screening guidelines. Efforts to increase screening has resulted in an increase in compliance, which has been reviewed elsewhere8.

Increased colonoscopic screening in African Americans has been cited as a major reason for the recent decrease in incidence in this population2 (Figure 1.1A).

Continued efforts to increase knowledge of new screening guidelines in African

American communities are necessary. Additionally, because patient follow-up is lower in

African Americans after an abnormality is found, community-based support programs should be developed to improve follow-up rates9. Importantly, access to screening options and affordable care are essential to decrease the burden of CRC faced by African

Americans, and these barriers must be addressed by communities across the country5.

14 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Genetic Risk Factors and CRC Incidence

It is estimated that genetic factors contribute to as much as 35% to the overall risk of CRC10. Our understanding of genetic risk factors is anchored in Mendelian genetics, that is, in single gene defects that are associated with a high risk of CRC development11.

Mutations in the adenomatous polyposis coli (APC) gene are linked to familial adenomatous polyposis (FAP). APC mutations ablate a key factor in the regulation of the

WNT signaling pathway (Figure 1.2). WNTs are a large family of secreted glycoproteins that regulate cell proliferation, differentiation, polarity, and migration12. In the adult intestine, WNTs control homeostasis by maintaining stem cell populations in the base of the crypts. In the canonical WNT signaling cascade, WNT stimulation prevents degradation of the transcription factor -catenin by inhibition of the destruction complex.

The destruction complex consists of the proteins APC, axis inhibition protein (Axin), glycogen synthase kinase 3 (GSK3), and casein kinase 1 (CK1). In the absence of

WNT, the complex mediates the phosphorylation of -catenin, which targets -catenin to the proteasome. In the presence of WNT, -catenin degradation is inhibited, and it migrates into the nucleus where it mediates the transcriptional activation of genes such as

MYC and Cyclin D1. Bi-allelic mutation of APC is associated with failure to down- regulate -catenin, causing over-expansion of the stem cell compartment and the development of an adenomatous polyp. Over time, adenomatous polyps can progress to carcinoma as other cancer driver mutations in genes such as KRAS, SMADs, and TP53 arise in the polyp. FAP is a classical autosomal dominant condition in which persons inherit a mutation in APC from one parent. Mutations in the working APC gene copy occur in somatic cells in the colon, giving rise to hundreds to thousands of adenomatous

15 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Figure 1.2 Cellular pathways dysregulated in colorectal cancer (CRC). Specific genetic factors that are altered in CRC and discussed in this review are blue. Figure altered from original by Wikipedia user RoadNotTaken

(https://commons.wikimedia.org/wiki/File:Signal_transduction_pathways.svg, last accessed June 20, 2017). This image is being used with permission under the terms of the

GNU Free Documentation License, version 1.2 or any later version, published by the

Free Software Foundation (with no invariant sections, no front-cover texts, and no back- cover texts). The image herein originally appeared on November 18, 2010, and is current as of publication of this article. APC, adenomatous polyposis coli; BMP, bone morphogenetic protein; CDK, cyclin-dependent kinase; CREB, CAMP-responsive element-binding protein; EGF, epidermal growth factor; EPC, endothelial progenitor cell

16 Mechanisms of Tumorigenesis in African American CRC Chapter 1 factors; ERK, extracellular signal–regulated kinase; FADD, Fas-associated protein with death domain; FasR, Fas receptor; GPCR, G protein–coupled receptor; GSK, glycogen synthase kinase; IGF, insulin-like growth factor; JAK, Janus-activating kinase; JNK, c-

Jun N-terminal kinase; MAPK, mitogen-activated protein kinase; MEK, MAPK/ERK kinase; MEKK, MAP kinase kinase kinase; MKK, mitogen-activated protein kinase kinase; PI3K, phosphatidylinositol 3-kinase; PLC, phospholipase C; RSMAD, receptor phosphorylated SMAD; RTK, receptor tyrosine kinase; SARA, SMAD anchor for receptor activation; SMO, smoothened; SOS, son of sevenless; TCF, T-cell factor; TGF, transforming growth factor; Tnf, tumor necrosis factor.

17 Mechanisms of Tumorigenesis in African American CRC Chapter 1 polyps. Bi-allelic somatic mutations in APC are found in approximately 80% of all sporadic CRC cases, making APC the predominant gatekeeper gene to the development of CRC.

More recently, bi-allelic mutations in the base excision repair gene MUTYH have been associated with a recessive CRC polyposis syndrome. Base excision repair is a system that removes damaged bases in DNA, particularly oxidized guanine bases, followed by polymerase-associated insertion of the correct nucleotide and ligation.

MUTYH specifically operates on lesions in which the oxidized guanine base had undergone DNA replication resulting in an oxidized guanine:adenine mismatch. To prevent mutation, MUTYH protein initiates a repair event in which a cytosine base is inserted opposite the oxidized guanine base. In the absence of MUTYH function, this form of DNA repair is defective, and there results an increase in guanine to thymine mutations. The colonic epithelium is evidently more dependent on MUTYH function than are most other cells in the body. Various reasons for the increased dependence have been cited, including the high proliferation rate of colonic stem cells, high levels of reactive oxygen species in the gut epithelium, and an over-representation of mutation hot spots in the APC gene13.

Mutations in the mismatch repair (MMR) genes MLH1, MSH2, MSH6, and PMS2 are associated with Lynch syndrome (LS), which is the most common hereditary CRC syndrome, accounting for as much as 3% of all CRCs11. The MMR system removes mismatched bases that have been improperly incorporated into DNA during replication.

LS is associated with a wide array of cancer sites, including the uterus, ovary, stomach, small intestine, bile ducts, ureter and transitional cells in the kidney, brain, and skin.

18 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Mutations in the APC, MUTYH, and MMR genes together with a number of much less frequently mutated syndrome-causing genes contribute to approximately 5% of all

CRCs and constitute at most 40% of the total genetic variance in CRC risk. In the past 10 years, there have been attempts to close the gap between Mendelian genetics and the genetic variance that remains to be explained via the conduct of genome-wide association studies (GWAS). GWAS compare the frequencies of common genetic variation—single nucleotide polymorphisms (SNPs)—in CRC cases vs. controls to identify SNPs associated with disease. These studies were successful in the identification of many new

CRC risk factors across the genome; however, the proportion of the genetic variance in

CRC that is explained by these newly identified risk factors is at most 5%14. The effect sizes of these common genetic risk factors are relatively small (ORs from 1.04 to 1.56); consequently, very large studies (samples sizes in the hundreds of thousands or millions) are required to identify all the common genetic risk factors. Recent work is focusing on genetic variation that is less common (allele frequencies <5%) and on gene-environment interactions that might explain the so-called “missing” genetic variance.

It is against this backdrop of the rare, the common, and the unknown, that we will consider the current state of affairs in the understanding of genetic risk factors for CRC in

African Americans. First, as expected, African Americans are not exempt from occurrence of the rare hereditary syndromes. Early evidence showed that African

Americans with hereditary forms of CRC harbored novel mutations in the MMR genes15.

Recent clinic-based reports have gone further to detail many more genetic mutations in

APC and MUTYH16 and in the MMR genes17 in the African American population.

Differences in the numbers or proportions of hereditary cases identified in African

19 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Americans compared to whites most likely reflect differences in the ordering of genetic testing rather than differences in the frequencies or the phenotypes associated with these mutations, although more extensive investigation of these questions is needed.

Population-based studies have not addressed questions relating to the frequency of mutations in the known hereditary genes in black populations, so that we do not know the impact of hereditary mutations on the incidence of CRC in African Americans and on the disparity in incidence. In the white population, hereditary mutations account for approximately 5% of all CRCs; thus, the difference in frequency of hereditary mutations would have to be large in order to explain the difference in incidence. Moreover, there is evidence against a large excess of MMR gene mutations—the largest class of hereditary mutations—based on phenotypic testing of African American CRCs (see below).

GWAS have identified over 40 risk-associated regions based on analysis of SNP data generated predominantly in European-ancestry CRC cases compared to controls18.

Theoretically, a higher frequency of common genetic risk factors predisposing to CRC in

African Americans could explain differences in incidence between whites and African

Americans; however, taking into account the differences in allele frequencies and odds ratios between the two populations, there is substantially more attributable risk estimated for the known risk-associated regions in European-ancestry populations compared to that in African Americans. This conclusion emanates from two studies, each including over

1800 African American subjects, who were tested for replication of known risk- associated SNPs (Table 1.1). The studies found that slightly less than half of the known risk-associated regions were significantly associated with CRC in African Americans19–

21. African American populations have been included as part of larger

Table 1.1 Associations Identified in Two Replication Studies that Tested for Association at Known Susceptibility Regions

Gene regionA Chr SNP ID Position, bp Allele F(A) OR P value Ref Notes

LINC01655 1q41 rs12759486 222,066,536 T 0.58 0.86 1.5 × 10−4 19 Fine-mapping SNP C5orf66 5q31.1 rs647161 134499052 A 0.55 1.14 0.002 19 Index SNP SLC22A3B 6q26-27 rs7758229 160,840,252 T 0.11 1.08 0.056 19 Index SNP EIF3H 8q23.3 rs16892766 117,630,683 C 0.13 1.17 0.0058 19 Index SNP EIF3H 8q23.3 rs16892766 117,630,683 C 0.13 1.15 0.19 20 Index SNP MYC 824.21 rs6983267 128,413,305 T 0.13 0.87 0.029 19 Index SNP MYC 824.21 rs6983267 128,413,305 T 0.12 0.87 0.21 20 Index SNP MYC 824.21 rs7014346 128,424,792 G 0.39 1.05 0.27 19 Index SNP MYC 824.21 rs7014346 128,424,792 G 0.39 1.15 0.06 20 Index SNP POLD3 11q13.4 rs3824999 74,345,550 G 0.2 1.15 0.009 19 Index SNP GREM1 15q13.3 rs16969681 32,993,111 T 0.13 1.16 0.01 19 Index SNP GREM1 15q13.3 rs10318 33,025,979 T 0.03 1.45 0.04 20 Index SNP GREM1 15q13.3 rs11632715 33,004,247 A 0.38 1.04 0.34 19 Index SNP C 20 GREM1 15q13.3 rs11632715 33,004,247 A 0.29 2.36 0.004 Index SNP C −4 21 GREM1 15q13.3 rs17816285 33,039,298 G 0.29 3.13 2 × 10 Novel SNP association CDH1 16q22.1 rs9929218 68,820,946 A 0.29 0.93 0.12 19 Index SNP CDH1 16q22.1 rs1862748 68,832,943 T 0.2 0.82 0.023 20 Index SNP RHPN2 19q13.1 rs7252505 33,575,064 A 0.62 0.85 1.8 × 10−4 19 Fine-mapping SNP RHPN2 19q13.1 rs113984415 33,555,034 A 0.19 0.13 8 × 10−5 21 Novel SNP association CASC20 20p12.3 rs961253 6,404,281 A 0.36 1.08 0.054 19 Index SNP CASC20 20p12.3 rs961253 6,404,281 A 0.37 0.93 0.3 20 Index SNP

The studies by Wang et al19 and Kupfer et al20 included African American subjects comparing 1894 cases with 4703 controls and 795 cases with 985 controls, respectively. Wang et al19 tested 21 risk-associated regions, and Kupfer et al20 tested 10 risk-

associated regions. The two studies share a small subset of North Carolina subjects. Two novel associations were reported for GREM1 and RHPN2 in the study by Kupfer et al.21 Fine-mapping SNP is an SNP correlated with the index SNP that showed a stronger association P value. Unless otherwise stated, a log-additive model was used to estimate effect size and P value.

AAssignment of a gene to the association is based on proximity to the nearest risk-associated SNP.

BThe association shown was observed for left-sided colorectal cancer only. No association was observed for all colorectal cancer.

CRecessive model.

Allele, allele used as reference; Chr, chromosome; F(A), frequency of the reference allele; ID, identification; OR, odds ratio (not adjusted for local ancestry); P value, P value of association; Ref, article from which data were reproduced; SNP, single-nucleotide polymorphism.

Mechanisms of Tumorigenesis in African American CRC Chapter 1

GWAS, for example, in the identification of SNP associations in VTI1A22. Because patterns of linkage disequilibrium differ between European- and African-ancestry populations, associations with SNPs in African Americans that are different from the index SNP in European-ancestry populations have been observed in several instances. In addition, novel associations within known risk-associated regions have been reported19,23.

Finally, using a GWAS design, a novel CRC African American-specific association with the SYMPK gene was identified24.

Lack of replication for European-ancestry SNP associations has also been observed in Asian CRC GWAS25. Differences in allele frequencies and linkage disequilibrium structure between populations and population-specific gene-gene and gene-environment interactions have been proposed as explanations. Lack of adequate power to detect associations remains a problem in the African American GWAS. The observation of novel associations in which the risk-associated SNP is absent or present only at very low frequencies in European-ancestry populations indicates the existence of population-specific or population-restricted risk alleles23,24; many more of this kind of risk factor is very likely to be encountered as investigations turn to alleles with frequencies less than 5%.

In summary, GWAS in African American CRC has uncovered a limited number of risk-associated regions, and additional GWAS are needed to fully explore the genetic architecture of CRC risk in African Americans. Analysis of risk alleles that have frequencies less than 5% will face an additional obstacle from the higher frequencies of benign genetic variation in African-ancestry populations, making the distinction between signal and noise more challenging.

Mechanisms of Tumorigenesis in African American CRC Chapter 1

Can Vitamin D Levels Explain Differences in CRC Incidence in African Americans?

Vitamin D is a hormone the production of which is initiated in basal keratinocytes in the skin as result of exposure to ultraviolet B (UVB – 280-320 nm) rays in sunlight.

The cholecalciferol generated in the skin is converted to calcidiol in the liver and calcidiol is converted to calcitriol, which is the active hormone, by the kidney and in other tissues. Approximately 95% of the total vitamin D is produced endogenously as opposed to obtained through diet or dietary supplementation26. Vitamin D has numerous physiological effects, including regulation of calcium homeostasis, immunity, insulin secretion, blood pressure, and carcinogenesis. In case-control and cohort studies, higher levels of serum vitamin D are associated with a lower frequency of CRC27,28and administration of vitamin D can suppress CRC in animal models29.

Because cutaneous melanin absorbs UVB wavelengths, persons with darker skin colors require more sun exposure to achieve equivalent levels of serum vitamin D in persons with lighter skin colors30. One apparent consequence of this difference is that

African Americans have substantially lower levels of serum vitamin D than their white counterparts, especially in northern parts of the US. Consequently, it has been hypothesized that some part of the disparity in CRC incidence could be explained by lower vitamin D levels in African Americans27. In addition, lower vitamin D levels could also be associated with the higher rate of CRC-specific mortality in African

Americans31,32.

Due to the link between colorectal adenoma and CRC, one expectation of this hypothesis is that vitamin D levels should be inversely associated with adenoma occurrence, but the data in favor of this expectation has been inconsistent33–35. Inverse

24 Mechanisms of Tumorigenesis in African American CRC Chapter 1 association with vitamin D levels could be restricted to advanced adenomas36, which are more predictive of CRC risk. Another expectation is that supplementation with vitamin D should reduce the frequency of adenoma recurrence. Negative results from a large prevention trial, in which 1000 IU of vitamin D3 were administered for three to five years, argue against a strong effect of vitamin D supplementation on adenoma recurrence37. This prevention trial also challenged the commonly held view that calcium supplementation reduces adenoma recurrence, although the prevalence of obesity in the study population may have attenuated response. The study did not address whether longer periods or higher levels of supplementation would provide protection from CRC and the extent to which vitamin D reduces progression of CRC. Moreover, few African

Americans, the population with the highest risk due to low levels of serum vitamin D, were included in it.

Evidence for a contribution to African American CRC of genetic risk factors in vitamin D pathway genes is mostly negative38–40, consistent with the finding that genetic variance contributes very little to the variance in total vitamin D levels41. There is evidence that persons with specific vitamin D receptor (VDR) genotypes might respond favorably to vitamin D supplementation, and by extension to higher levels of vitamin D whatever the source42. Moreover, there are differences between African- and European- ancestry persons in the transcriptional response of colonic epithelial cells to active vitamin D hormone administered in vitro, suggesting that ethnicity-dependent regulatory circuitry could play a role in response to vitamin D levels in vivo43. At a broader level, many of the genetic variants that are associated with differences in gene expression levels in gut epithelial cells are population differentiated (as defined by an FST > 0.25),

25 Mechanisms of Tumorigenesis in African American CRC Chapter 1 suggesting that this genetic variation is subject to natural selection driven by local adaptations to the environment44.

Dietary Influences on CRC and the Gut Microbiome

Migration studies strongly support a dominant role for environmental factors in the etiology of CRC45,46. Populations migrating from countries with a low prevalence of

CRC to countries with a high prevalence of CRC acquire the higher CRC prevalence of their new country within a generation or less. Individual dietary components are often credited for increasing (e.g., red meat consumption) or decreasing (e.g., fiber) CRC risk, but the evidence is uneven and relatively weak47,48. For example, persons in the highest quartile of red meat consumption have an approximately 40% increased risk of CRC over persons in the lowest quartile49,50Interestingly, this association was observed in retrospective studies but was not significant in prospective studies. African Americans have been underrepresented in most studies; however, observations made in the North

Carolina Colon Cancer Study and a sister study administered by the same group that included rectal cancer cases suggest that dietary patterns may explain some of the racial differences in CRC51,52.

More recently, attention has turned to the gut environment, specifically its microbial communities, to better understand the interplay between dietary factors and host microbiota in the development of CRC. The gut microbiota consists of trillions of microbes, the vast majority of which are bacteria53. The term “microbiome” refers to the collective genome harbored by the microbiota. Microbiota-host interactions comprise a continuum of symbiosis, commensalism, and pathogenicity54. Growing evidence

26 Mechanisms of Tumorigenesis in African American CRC Chapter 1 implicates biofilms and adverse species of adherent bacteria in the process of CRC development55. Broadly, there are three ways in which the microbiota may contribute to carcinogenesis56: (i) by acting as cancer-initiating microbes (“oncomicrobes”); (ii) by guiding adverse immune system function; and (iii) by producing carcinogenic metabolites. There is solid evidence for all three mechanisms but the relative contribution of each is unknown.

Incidence rates of CRC are vastly different for African Americans (60 per

100,000 per year) and South African blacks (5 per 100,000 per year). Of the many differences that characterize the environment for these different peoples, diet could play an outsize role in the incidence rates for CRC. The diet for rural South African blacks is highly enriched in fiber and low in meat and fat whereas the Western diet is low in fiber and high in meat and fat. O’Keefe and colleagues57 conducted a diet switch in which they gave Pittsburgh African Americans the traditional South African black diet whereas they gave rural South African blacks the Western diet. They then examined changes in the gut microbiome and fecal metabolites. Reciprocal changes were observed in the gut microbiome and the metabolome within two weeks of diet switch. African Americans receiving the high-fiber, low-fat diet exhibited increases in the abundance of microbial species involved in fiber fermentation, including species that metabolize butyrate and other short-chain fatty acids and the hydrogenotrophic microbes that remove hydrogen, including methanogens, acetogens, and sulfate-reducing bacteria. Concomitantly, there was suppression of microbial species that process bile acids, including bile acid deconjugators and the pathogenic sulfidogenic bacteria Bilophila wadsworthia and

Fusobacterium nucleatum. South Africans receiving the low-fiber, high-fat diet exhibited

27 Mechanisms of Tumorigenesis in African American CRC Chapter 1 the opposite pattern, that is, a lower abundance of species engaged in saccharolytic fermentation and higher bile-acid deconjugating species. In addition, there were also reciprocal changes in gut epithelial cell proliferation, which is a marker for cancer development. The secondary bile acids deoxycholic acid and lithocholic acid have long been hypothesized as carcinogenic, and they are metabolized from glycine- and taurine- conjugated primary bile acids by gut microbes58,59; consequently, dietary influences on the microbiome that affect production of secondary bile acids and other carcinogens are particularly important areas of future research.

One study has examined differences in the gut microbes in CRC cases between

African Americans and whites. Yazici and colleagues60 (Chapter 3) measured the abundances of sulfidogenic bacteria, including sulfate-reducing bacteria and Bilophila wadsworthia, in a well-characterized series of Chicago CRC cases and endoscopy clinic- screening controls. Irrespective of disease status, African Americans exhibited much greater abundances of sulfidogenic bacteria than whites. In addition, African American

CRC cases had higher levels of Bilophila wadsworthia than African American controls whereas controls had higher levels of sulfate-reducing bacteria. Although African

Americans consumed higher levels of fat and protein than their white counterparts, only a relatively small proportion of the difference in microbial abundance could be accounted for by differences in dietary intake.

Causal connections are being sought between obesity and all the major human cancers, including CRC61,62. Increased consumption of red meat and high-fat and high- glycemic index foods, coupled with reduced levels of physical activity, has fueled an epidemic of obesity and type 2 diabetes at ever younger ages63. African Americans have

28 Mechanisms of Tumorigenesis in African American CRC Chapter 1 higher rates of diabetes than whites64, more insulin resistance, and more hyperinsulinemia. On the other hand, measures of metabolic syndrome are paradoxically lower because African Americans have paradoxically lower levels LDL-cholesterol, higher HDL-cholesterol, lower serum fatty acids and triacylglyercol levels65,66. Although it is not known whether these differences in pancreatic beta cell and liver functions are environmentally or genetically driven (or both), they could play into the racial difference in CRC incidence. Further studies are needed to investigate the links among diabetes, obesity, and CRC in African Americans.

Are Carcinogenic Mechanisms Different in African American CRC?

In addition to risk of CRC, the frequencies of various clinicopathologic features of tumors that arise in African Americans are different from the frequencies found in whites. African Americans have a higher likelihood of a diagnosis in the proximal colon and have a higher prevalence of proximal adenomas than whites3. These differences are important to note because until recently lesions in the proximal colon were more frequently missed during colonoscopy. African Americans also are often diagnosed at a younger age (median ages of 66 and 70 years for African American men and women compared with 72 and 77 years for white men and women, respectively)67. Moreover,

African Americans are two times more likely to be diagnosed with CRC before age 50, which justified the recommendation to begin endoscopic screening at age 45 instead of

50. The mechanisms driving early-onset CRC are not known, but a growing body of evidence suggests that they may be different from the mechanisms underlying the older age-of-onset CRCs. Although the field of carcinogenesis in African American CRC has advanced in its efforts to further investigate clinicopathologic differences, our

29 Mechanisms of Tumorigenesis in African American CRC Chapter 1 understanding of the molecular pathogenesis of the CRCs that arise in this population group remains in an early stage. Recent papers have gone beyond the anecdotal evidence and raised questions about the progression of molecular events in CRCs in African

Americans.

Similar Frequencies of Microsatellite Instability

A subset of CRCs is driven by a deficiency in DNA MMR genes, which causes a type of genomic instability known as microsatellite instability (MSI). Deficiency of an

MMR gene results in increased instability particularly in microsatellite loci leading to frequent changes in repeat sequence length in tumor DNA when compared to normal tissue. In the general population, MSI occurs in approximately 15% of CRCs, and it has hereditary and sporadic forms. Patients with LS carry a germline mutation in one of the

MMR genes, and MSI develops when the remaining normal copy of the gene is mutated in a cancer precursor cell. The sporadic form of MSI usually develops as result of DNA methylation of the MLH1 promoter, and sporadic MSI is associated with more elderly, female cases of CRC68. Tumors that exhibit MSI have distinctive clinical features, including increased tumor-infiltrating lymphocytes and a Crohn’s disease-like inflammatory reaction; an association with right-sided disease; and an association with high-grade tumors with poorly differentiated, mucinous, or signet-ring phenotypes.

Despite the higher grade of MSI tumors, affected persons have a slightly better prognosis68, and recently it has been found that MSI tumors are more likely to respond to immune checkpoint therapy69, very likely due to the generation of excess neo-antigens caused by the genomic instability.

30 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Early reports suggested that African Americans had a higher frequency of CRC tumors with MSI70–72. This was an interesting hypothesis because it had the potential to explain the higher frequency of right-sided CRC in African Americans. However, equal or lower frequencies of MSI in African American CRCs were observed in larger, subsequent studies73–75. Eaton and colleagues76 studied a previously identified polymorphism in 5,10 methylenetetrahydrofolate reductase (MTHFR), whose effect on

MSI status of a tumor was mediated by folate status, where the higher the folate intake, the lower the risk of MSI tumor. Because this protective allele is less common in African

Americans, if MSI frequency was increased in this population, then theoretically, it would contribute to an increased incidence of MSI.

A recent meta-analysis of 22 studies with a total of 12,611 CRC patients compared MSI frequencies in African Americans and whites77. Conclusively, no difference in MSI frequencies was found. It is currently unknown the extent to which biological variables account for differences between studies. MSI is a relatively well- studied CRC subtype; however, it is currently unknown how much survival of patients with MSI differs by race, which may be important in addressing the health disparity in

CRC mortality.

Somatic Mutations in African American CRC

Our understanding of molecular characteristics of microsatellite stable (MSS)

CRCs in African Americans has been lacking in the past because of the limited integration of these communities into population level studies. This has improved in the last five years with studies focusing on chromosomal instability and single nucleotide

31 Mechanisms of Tumorigenesis in African American CRC Chapter 1 variants (SNVs) in African Americans.

Two studies which characterized broad copy number variation (CNVs) in African

American CRCs (i.e., gains or losses that occur across chromosome arms or entire chromosomes) both found frequencies of gains and losses to be similar to those seen in previous studies of primarily white patients78,79. Frequent arm-level losses are seen in 1p,

8p, 14q, 15q, 18p, and 18q, while arm-level gains are frequently seen in 1q, 7p, 8q, 13q,

19q, 20p, and 20q. These alterations have been characterized in previous studies and do not differ from what has been observed in whites. Another study80,81found that arm-level changes were different between the two populations (n = 27 whites; n = 30 African

Americans). A study from our group (Chapter 4) examined chromosome-arm copy number alterations but did not see qualitative differences; however, chromosome-arm gains were less frequent in African American CRCs82. Adjustments for factors such as age and stage are needed to account for possible sampling bias in these studies. In addition, larger studies are necessary to determine the extent to which clinicopathological features can be explained by CNVs.

Our group also explored copy neutral loss of heterozygosity (cnLOH), a form of genomic instability where the copy number remains intact though the genomic information from one parent is lost at a particular allele (Chapter 5). These events typically occur at a chromosome-arm or chromosome-wide level with mechanisms that differ from copy number changes. The study from our group shows that cnLOH has a reduced frequency in African American CRCs, even after adjustment for age, tumor stage, race, cohort, and BMI. The difference seen in cnLOH frequency between whites and African Americans was not restricted to one mechanism of cnLOH or to one

32 Mechanisms of Tumorigenesis in African American CRC Chapter 1 particular chromosome arm. Therefore, this form of genomic instability is less frequent in

African Americans, though it is still unknown how frequency of cnLOH is related to genetic or environmental factors.

Different focal copy number alterations may exist in African Americans78,79, however larger, platform-matched studies are necessary to determine a reliable list of affected genes. Despite these advances in exploring CNVs in African American CRCs, data are still limited. Current studies have relied on small sample sizes (Varadan et al.79, n

= 30 for sequence data and n = 12 for array data; Ashktorab et al.80, n = 15), and they did not account for differences in tumor location, stage, or differentiation status.

Genomic instability has also been noted in patient samples with elevated microsatellite alterations at selected tetranucleotide repeats (EMAST). This EMAST instability phenotype has been described to be present in 60% of sporadic CRC cases, specifically in MSI, but also often in non-MSI cases83. In a cohort of rectal cancer patients (n = 147, 26% African American), EMAST phenotype was more frequent in

African Americans, and it was associated with advanced stage84. Because EMAST has been described in both MSI and MSS tumors, the etiological basis of EMAST may be heterogeneous. Further study is needed to understand the relationship of this instability to tumor progression and outcome in African American CRC.

DNA sequencing studies have been used to investigate somatic mutations in

African American CRCs to determine the extent to which genes involved in tumor development are different in African American colorectal carcinogenesis85,86. For the known cancer driver genes (KRAS, BRAF, TP53, PIK3CA, and APC; Figure 1.2), frequencies of somatic mutations have been reported for relatively limited sample series

33 Mechanisms of Tumorigenesis in African American CRC Chapter 1

(Table 1.2). Significant differences were not reported. A number of groups have focused on the identification of novel driver genes that might explain features of the cancer health disparity. Ashktorab et al.85 identified SNVs in CRC initiator APC that were unique to

African Americans. Guda et al.86 concentrated their efforts on identifying novel genes involved in advanced CRCs in African Americans. To do so, they sequenced 31 late- stage, MSS CRCs from Case Medical Center and identified a 15-gene set that they followed up in a series of 129 African American cases in a replication stage. Most frequently mutated in this gene set was EPHA6, a member of the ephrin receptor tyrosine kinase family that has been previously implicated in CRC development. Another frequently mutated gene of interest was CHD5, a chromatin-remodeling protein that was also frequently mutated in a study by our group (unpublished). This gene set was used to determine differences in survival. It predicted poorer survival, especially in later stage

African American CRCs (n = 66)87. Large, multi-institutional studies are needed to confirm and extend these results.

Epigenetic Changes in African American CRC

There has been an increasing interest in changes to gene expression and DNA methylation in CRC, with several groups comparing African American CRCs to tumors from whites. An early study88 (n = 102, 50% African American) used methylation- specific PCR to look at methylation in promoters of a candidate cancer gene panel of 14 genes.

Three genes were found to be hypermethylated in African Americans as compared to white samples. Among them was CHD5, a tumor suppressor that was

Table 1.2 Frequency of Mutations in Selected Colorectal Cancer Driver Genes

Study APC, % BRAF, % PIK3CA, % KRAS, % TP53, %

Katkoori et al (2009)89 68/137 (49.6)

Sylvester et al (2012)74 6/170 (3.5) 57/170 (33.5)

Xicola et al (2014)76 16/408 (3.9) 44/192 (22.9) Ashktorab et al (2015)85 8/12 (66.7) 1/12 (8.3) 2/12 (16.7) 6/12 (50) 2/12 (16.7) Guda et al (2015)86 22/29 (75.9) 2/29 (6.9) 5/29 (17.2) 16/29 (55.2) 20/29 (69) Kang et al (2013)∗90 – (18) – (28.3) – (68.5) Data are given as number/total (percentage). None of the cited reports claimed that the frequencies of the driver mutations tested in African American colorectal cancers were significantly different from the frequencies reported for white driver mutations. Empty cells indicate that the gene was not tested in the study.

∗ n = 67

– numerators were not provided in the article

Mechanisms of Tumorigenesis in African American CRC Chapter 1 identified as a recurrently mutated gene that may be important in African American CRC development86. This epigenetic silencing was further studied by Fatemi et al.91 (n = 18 adenomas, n = 6 healthy normal), who validated the downregulation of CHD5 in adenoma samples and noted that this may be an early event in CRC tumor progression of

African Americans. Additionally, the promoters of ICAM5 — part of the intercellular adhesion molecule family — and GPNMB — a glycoprotein — were hypermethylated in

African American CRCs in the Mokarram et al. study88.

Further studies have used more comprehensive technologies to discover more genes with DNA hypermethylation in African American CRC. The development of methylation microarrays, such as Illumina’s HumanMethylation27 and

HumanMethylation450, and bisulfite sequencing techniques allow scientists to look genome-wide for differential DNA methylation. Using microarray technology, Ashktorab and colleagues92 found 16 genes with consistent promoter hypermethylation in a small cohort of African Americans (n = 12 CRCs, n = 8 adenomas, n = 2 normal colon).

Among these genes were previously identified ICAM5 as well as DCC, which was studied in the Mokarram et al. study88 but not found to be differentially methylated.

Additionally, the promoter of EVL was found to be more highly methylated in their

African American CRC cohort than reported in other white cohorts. Well-known tumor suppressors were also included in this list, including APC and PTEN.

Reduced representation bisulfite sequencing (RRBS) gives an even more granular look at the epigenome by increasing the number of CpGs covered into the millions.

Ashktorab et al.93 sought to identify potential biomarkers for African American CRC by identifying novel hypermethylated genes using RRBS. This study elucidated four genes

36 Mechanisms of Tumorigenesis in African American CRC Chapter 1 that were hypermethylated, including EID3, GPR75, GAS7, and BMP3. The latter two of these genes are in the insulin and TGFβ network, and other G-protein coupled receptors are within this network as well. This interesting result connects tumorigenesis with insulin signaling that is affected in diabetes. Other studies have shown that diabetes can increase a person’s risk for CRC94, however the biological basis of this association is not yet known. In another study from the same group92, additional CpG islands were identified as hypermethylated in African American CRC, including L3MBTL1, NKX6-2,

PREX1, TRAF7, PRDM14, and NEFM. This small study focused on increased methylation from normal to adenoma to malignancy (n = 5 CRCs, n = 2 adenoma, n = 1 blood, n = 1 normal colon). These genes map to pathways often dysregulated during cancer development, namely WNT/β-catenin, PI3K, AKT, VEGF, and JAK/STAT3 signaling pathways. The methylation of these genes was specific to CRCs and not found in adenomas.

Another study95 took a comparative approach, comparing DNA methylation in

African American and white CRCs (n = 6 African Americans, n = 7 whites). Several differentially methylated genes were microRNAs, two of which (i.e., miR-9 and miR-

124) have previously been implicated in CRC. Among the differentially methylated microRNAs was miR-124-3p, which was hypermethylated in African American CRCs compared to white CRCs. RNAseq analysis found that two targets of this microRNA

(i.e., POLR2B and CYP1B1) were among the upregulated genes in these samples.

These studies are limited by their sample size of cancer patients, as most incorporated less than ten samples into their genome-wide analyses. In addition, integration of methylation data with clinicopathological and molecular features is needed.

37 Mechanisms of Tumorigenesis in African American CRC Chapter 1

For example, it is known that DNA methylation and expression profiles differ in CRCs with MSI96, therefore stratifying analyses based on this criterion could remove some heterogeneity. Notably, there was no overlap in the genes identified in different studies, which raises the question of reproducibility.

CRC-specific Gene Dysregulation

A recent landmark paper based on European-ancestry CRC cases described four major expression-based CRC subtypes, referred to as consensus molecular subtypes96.

CMS1 closely represents the MSI-immune CRCs, with BRAF mutations, hypermutation, a hyper-methylation phenotype, and immune cell infiltration. CMS2 represents the canonical CRC subtype, driven by WNT signaling and MYC activation and containing excess copy number alterations. CMS3 represents metabolic CRC, driven by KRAS mutations and associated with metabolic dysregulation and higher genome stability.

Finally, CMS4 represents mesenchymal CRC, associated with stromal infiltration, TGF activation, and angiogenesis markers. These subtypes are important because CMS1 is associated with worse survival after relapse and CMS4 is associated with worse relapse- free and overall survival.

In studies of African American CRC, this area suffers from some of the same limitations (i.e., reproducibility and covariate availability issues) as others when looking at its impact on the health disparity. Two studies compared gene expression in African

American and white CRCs95,97. These studies identified 142 and 10 dysregulated genes, respectively, of which no genes were identified in both studies. The larger of the two studies, by Jovov and colleagues97, validated expression of their 10 genes in an

38 Mechanisms of Tumorigenesis in African American CRC Chapter 1 independent set of patients (n = 86, 50% African American). It would be interesting to re- analyze these data in light of the CMS subtype classification system96, including the

CMS1 subtype which is associated with MSI status.

Additionally, two studies have focused on microRNA expression. Bovell et al.98

(n = 106 African Americans; n = 239 whites) found high miR-203 expression to be associated with poor survival in early-stage African American CRCs, whereas high miR-

181b expression was associated with poor survival in Stage III CRCs from African

Americans. The prognostic value differed from the white patients in the study, suggesting that expression profiles may have different prognostic value depending on a patient’s race as well as the stage of their disease. Li et al.99 found 5 microRNAs whose expression levels differed by race in their cohort (n = 30 African Americans; n = 31 whites).

Specifically, miR-182 was upregulated in African American CRCs compared to white

CRCs, and two potential miR-182 targets — FOXO1 and FOXO3A — were expressed at lower levels in African American CRCs.

Both expression of genes and expression of regulatory molecules such as microRNAs could act as possible prognostic biomarkers for CRCs in African Americans.

Replication studies are necessary to validate the above findings. Additionally, application of molecular pathological epidemiology100, integrating information from multiple sources, such as CMS status, clinicopathological features, and environmental/behavioral factors, would result in better design of future studies.

The Continuing Problem of CRC Mortality in African Americans

As previously mentioned, African Americans have the highest mortality rate of

CRC of any ethnic group in the US. This disparity has been noted in previous 101–103,

39 Mechanisms of Tumorigenesis in African American CRC Chapter 1 which looked to behaviors, stage of tumor, treatment, and socioeconomic status as potential explanations. Some of this difference can be explained by tumor stage and socioeconomics, but the disparity remains even after accounting for tumor stage at diagnosis, as well as after adjusting for socioeconomics, comorbidities, and treatment4,104,105. The effect of body mass index on survival was assessed, and while it did have an effect on survival, it was determined not to contribute to the disparity106.

The rate of mortality for CRC has decreased since the early 2000s; however, the mortality rate of African Americans is still 35% higher than of whites (Figure 1.1B). The rate of decrease in mortality has improved as well, with both African Americans and whites having annual percent changes in rate of -2.5 - 3%. Increased endoscopic screening by African Americans has contributed to the decrease in mortality.

Several biomarkers have been proposed to enable a more accurate prognosis for

African American CRC patients. Some, including nuclear accumulation of p53107,108and

MUC-1109, have been unsuccessful. Others have been weak markers for prognosis, such as Bcl2108,110— whose lack of expression was weakly associated with survival particularly in distal tumors — and p27kip1 111 — whose lowered expression was associated with worse survival in African Americans and whites but only in stage III

CRCs.

Jones et al.112 identified a polymorphism in the glutathione S-transferase gene

(GSTP1) that is associated with a decreased risk of death for the genotypes Ile/Val or

Val/Val. This effect was more pronounced in patients who underwent chemotherapy.

However, the genotype frequency did not vary by race, and was determined not to contribute to the disparity.

40 Mechanisms of Tumorigenesis in African American CRC Chapter 1

Additional work was done to identify if somatic gene mutations could predict a

CRC patient outcome87. This study tested for KRAS, BRAF, and PIK3CA mutations as well as MSI status. They found that KRAS mutations were more frequent in African

Americans and were associated with advanced stage in these patients. PIK3CA mutations were associated with decreased survival when adjusted for MSI, education, and income; however, the confidence interval for the hazard ratio estimate was wide, limiting the interpretation of this piece of data. The authors suggest that the different frequency of somatic alterations may explain some of the differences in survival, a gap that needs to be addressed in future research.

Overall, despite research that has given us valuable knowledge about factors that have effects on CRC mortality, we still know relatively little about the molecular mechanisms underpinning why African Americans with CRC are more likely to die from the disease than other ethnic groups. More work is necessary to determine the effectiveness of current treatments in this population. Additionally, tumor progression differences that have begun to emerge may explain some of the differences in mortality87; however, further research is needed to determine if validated prognostic biomarkers can be developed.

41 Mechanisms of Tumorigenesis in African American CRC

Chapter 2

Is increased colorectal screening effective in preventing distant disease?

Originally published in PLOS ONE (Permissions can be found in Appendix B)

Augustus GJ, Roe DJ, Jacobs ET, Lance P, Ellis NA. Is increased colorectal screening effective in preventing distant disease? PLoS One. 2018;13(7):e0200462. doi:10.1371/journal.pone.0200462

42 Mechanisms of Tumorigenesis in African American CRC Chapter 2

Abstract

Background Screening in the average risk population for colorectal cancer (CRC) is expected to reduce the incidence of distant (i.e., metastatic) CRCs at least as much as less advanced CRCs. Indeed, since 2000, during which time colonoscopy became widely used as a screening tool, the overall incidence of CRC has been reduced by 29%.

Objective The purpose of the current study was to determine whether the reduction of incidence rates is the same for all stages of disease.

Methods We evaluated incidence data from the Surveillance, Epidemiology, and End

Results (SEER) program from 2000–2014 for Localized, Regional, and Distant disease.

Joinpoint models were compared to assess parallelism of trends. Data were stratified by race, age, tumor location, and sex to determine whether these subgroupings could explain overall trends.

Results Inconsistent with the expectations of a successful screening program, the reduction in incidence rates of distant CRCs from 2000–2014 has been slower than the reductions in incidence rates of both regional and localized CRCs. This trend is evident even when the data are stratified by age at diagnosis, sex, race, or tumor location.

Conclusions The slower decrease in the incidence rate of distant disease is not consistent with a screening effect, that is, CRC screening may not be effective in preventing many distant CRCs. As a consequence, distant CRCs represent an increasing fraction of all CRCs, accounting for 21% of all CRCs in 2014. The analysis indicates that inadequate screening does not explain the slower decrease in incidence of distant CRCs. Consequently, we suggest that a subtype of CRC exists that advances rapidly, evading detection because screening intervals are too long to prevent it. Microsatellite unstable tumors represent a

43 Mechanisms of Tumorigenesis in African American CRC Chapter 2 known subtype that advances more rapidly, and we suggest that another rapidly advancing subtype very likely exists that is microsatellite stable.

44 Mechanisms of Tumorigenesis in African American CRC Chapter 2

Introduction

Colorectal cancer (CRC) remains the second most common fatal malignancy after lung cancer in the United States and other developed countries 113. The prevailing concept for the formation of sporadic CRCs is that most of them develop over a period of 7 to 15 years from benign adenomatous polyps (adenomas) 114. In the United States, screening for

CRC by fecal blood test, flexible sigmoidoscopy, or colonoscopy is recommended for all individuals between the ages of 50 and 75 years 115. Screening by colonoscopy is recommended every 10 years, with 3- to 5-year follow-up if an adenoma is detected.

Positive results from a fecal blood test or flexible sigmoidoscopy are verified by colonoscopy. The rationale for CRC screening is that (i) asymptomatic adenomas can be detected and removed before ever progressing to cancer, and (ii) histological stage at the time of treatment is the most predictive marker of long-term prognosis. Assuming CRC is indeed a slow-growing malignancy, current screening guidelines should be effective in meeting these two criteria.

A successful CRC screening program is one that decreases incidence rates of CRC by adenoma removal and that shifts the burden of invasive disease at the time of diagnosis from more advanced (i.e., regional and distant/metastatic) tumors to less advanced

(localized) tumors, which are more readily cured by surgical resection. Since 2000, the quality of colonoscopy has improved and an increasing percentage of US persons have adopted CRC screening 116,117. In support of screening efficacy, fecal blood testing and colonoscopy, respectively, have been reported to reduce CRC mortality by as much as 32%

118 and 68% 119. Consistent with the increased adoption of CRC screening since 2000, the overall incidence of CRC has decreased 29% from 2000-2014 (SEER program, Nov 2016

45 Mechanisms of Tumorigenesis in African American CRC Chapter 2 submission).

The primary objective of our study was to determine whether the reduction in CRC incidence has been equal for all stages of disease. The prevailing concept is that CRCs progress from adenoma to localized cancer to regional to distant disease. Consequently, detection and removal of early lesions through screening should decrease the incidence of later-stage disease (Figure 2.1). By this reasoning, distant CRCs should show the largest reduction in incidence. Here, we analyzed incidence rate data from the Surveillance,

Epidemiology, and End Results (SEER) program and present evidence of a disturbing trend: from 2000-2014 the incidences of localized and regional CRC have decreased substantially whereas the incidence rate of distant (i.e., metastatic) CRC has not.

Materials and Methods

Data acquisition

We used data from the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program database. Incidence rate data queries were made to the

SEER 18 (SEER 18 Regs Research Data + Hurricane Katrina Impacted Louisiana Cases,

Nov 2016 Sub (2000-2014) - Linked To County

Attributes - Total U.S., 1969-2015 Counties) registry data using SEER*Stat v8.3.4. This database includes data from 18 regions from 2000 to 2014. From the full SEER dataset, we restricted our case definition to patients with cancers of the colon or rectum (Site recode

ICD-O-3/WHO 2008). All age-adjusted incidence rate data were expressed as cases per

100,000 as calculated from the 2000 US standard population.

46 Mechanisms of Tumorigenesis in African American CRC Chapter 2

Figure 2.1 Model of a successful screening program. X-axis is disease progression. Y- axis is incidence. Axes are not to scale. The widely accepted concept is that colonic neoplasia progress from less advanced to more advanced stages (from adenoma to localized to regional to distant) and become more symptomatic as they progress. As screening quality is improved and more people are being screened, as has been the case in the US since 2000, we expect a screening effect that reduces the incidence rates of all stages of disease. This model predicts that a successful screening program would exert its largest reduction in incidence on distant CRC.

47 Mechanisms of Tumorigenesis in African American CRC Chapter 2

Stage data – Summary stage 2000 (1998+) – defines stage as Localized, Regional, Distant, or Unknown/unstaged. Definitions for this model of staging can be found at the SEER website (https://seer.cancer.gov).

Statistical analyses

To evaluate the data for significant linear trends, we used the Joinpoint Regression

Program v4.5.0.1 (Joinpoint Regression Program, Version 4.5.0.1 - June 2017; Statistical

Methodology and Applications Branch, Surveillance Research Program, National Cancer

Institute). We stratified by age of diagnosis (Early: < 50; Middle: 50-64; Late: 65+), by race

(American Indian/Alaska Native, Asian or Pacific Islander, Black or African American,

White), by tumor location (Proximal: cecum, appendix, ascending colon, hepatic flexure, and transverse colon; Distal: splenic flexure, descending colon, sigmoid colon, rectum, and rectosigmoid junction), and by sex (Male, Female). We also used comparability tests to compare trends in regional vs. distant disease and localized vs. distant disease. The test of parallelism determined whether trends of regional and distant CRC and localized and distant

CRC were parallel over given time periods, again using p < 0.05 as an indicator of non- parallel trends.

Statistics were conducted in Joinpoint Regression Program, and figures were produced in R version 3.3.2 (dplyr v0.5.0, ggplot2 v2.2.1, scales v0.4.1, readr v1.0.0, cowplot v0.8.0, and all dependencies).

Availability of data and material

All data that support the findings of this study are publicly available from SEER

48 Mechanisms of Tumorigenesis in African American CRC Chapter 2

(http://seer.cancer.gov) using SEER*Stat. Minimal data for reproducibility and all code used in the processing of the data and visualizations, input for and output of the Joinpoint

Regression Program, and tables generated for analysis during the current study are available in the gaiusjaugustus/DistantCRCRates repository on GitHub. Code at the time of submission is available at the following release: https://github.com/gaiusjaugustus/DistantCRCRates/releases/tag/20180413

(doi:10.5281/zenodo.1218098).

Results

Decrease in incidence rate of distant CRC is slower than the decrease in incidence rates of localized and regional CRC

Since 2000, CRC incidence for the overall US population has seen a reduction of

2.3% per year from 2000-2008 and 4.6% per year from 2008-2011, and it has been stable from 2011-2014 [annual percentage change (APC) = -1.3]. In 2000, incidence rates of localized, regional, and distant CRC were 21.22, 19.98, and 9.44 cases per 100,000, respectively (Figure 2.2). In 2014, the rates of localized and regional CRC had decreased, respectively, by 6 points to 15.23 (a 28.3% reduction) and by 6.8 points to13.19 (a 34% reduction). However, distant CRC incidence rates had only decreased by 1.2 points to 8.24

(a 12.8% reduction). In 2000, localized, regional, and distant CRC accounted for 39%,

36.8%, and 17.3% of CRCs, respectively. In 2014, localized had remained a stable proportion of CRCs (39.2%), regional had decreased to 34%, and distant CRCs had increased to 21.1% of all CRCs. The remaining proportion of disease is unstaged CRC and was omitted from further analysis.

To determine whether the incidence rate of distant disease was also less than

49 Mechanisms of Tumorigenesis in African American CRC Chapter 2

Figure 2.2 The incidence rate of distant CRC is decreasing much more slowly than non-distant disease. Green squares, localized; yellow triangles, regional; red stars, distant.

Incidence rates are expressed per 100,000.

In order to determine whether or not the decrease in regional disease differed from that of distant disease, we performed a comparison analysis of joinpoint models (Table 2.1).

Regional CRC decreased by 3.10% per year (APC = -3.10, p < 0.001). Distant CRC was statistically stable from 2000-2002 (APC = 0.92, p = 0.24) before incidence began to decline in 2002. Incidence declined by 1.6% per year from 2002 to 2012 (APC = -1.60, p < 0.001), then remained statistically stable from 2012 to 2014 (APC = 0.2, p = 0.8). A pairwise comparison of the two joinpoint regressions indicated that the trends of regional and distant

50 Mechanisms of Tumorigenesis in African American CRC Chapter 2

CRC are statistically different from each other (p < 0.001), with distant CRC decreasing at a significantly slower rate than regional CRC.

Table 2.1 Summary of localized, regional, and distant joinpoint models

Localized Regional Distant Pairwise Comparison Year APC p-value Year APC p-value Year APC p-value Localized Regional /Distant /Distant Overall 2000-2008 -1.6 < 0.001 2000-2014 -3.10 < 0.001 2000-2002 0.92 0.24 < 0.001 < 0.001 population 2008-2011 -5.22 0.01 2002-2012 -1.61 < 0.001 2011-2014 -1.80 0.07 2012-2014 0.18 0.81 Age of diagnosis Early diagnosis 2000-2014 1.39 < 0.001 2000-2014 1.33 < 0.001 2000-2014 2.90 < 0.001 < 0.001 < 0.001 ( < 50 ) Middle diagnosis 2000-2014 -1.25 < 0.001 2000-2011 -2.36 < 0.001 2000-2014 -0.44 0.004 0.007 < 0.001 ( 50 - 64 ) 2011-2014 0.74 0.52 Late diagnosis 2000-2007 -2.28 < 0.001 2000-2008 -3.86 < 0.001 2000-2002 0.24 0.90 < 0.001 < 0.001 ( 65+ ) 2007-2014 -5.01 < 0.001 2008-2014 -4.96 < 0.001 2002-2014 -2.83 < 0.001 Tumor Location Proximal 2000-2008 -0.26 0.50 2000-2014 -3.39 < 0.001 2000-2014 -1.56 < 0.001 0.029 < 0.001 2008-2011 -4.97 0.16 2011-2014 -0.33 0.85 Distal 2000-2007 -2.44 < 0.001 2000-2014 -2.88 < 0.001 2000-2002 1.83 0.13 < 0.001 < 0.001 2007-2014 -4.16 < 0.001 2002-2012 -1.71 < 0.001 2012-2014 1.20 0.27 Race Black/African 2000-2007 0.36 0.40 2000-2014 -3.39 < 0.001 2000-2012 -1.32 < 0.001 0.022 < 0.001 American 2007-2014 -3.85 < 0.001 2012-2014 -6.02 0.05 White 2000-2008 -1.91 < 0.001 2000-2014 -3.01 < 0.001 2000-2002 1.09 0.18 < 0.001 < 0.001 2008-2011 -5.67 0.015 2002-2012 -1.62 < 0.001 2011-2014 -1.37 0.18 2012-2014 0.99 0.21

Native American 2000-2014 -1.4 0.057 2000-2014 -1.62 0.02 2000-2014 0.39 0.58 0.083 0.10 or Alaska Native Asian or Pacific 2000-2008 -0.6 0.23 2000-2014 -3.67 < 0.001 2000-2014 -1.52 < 0.001 0.296 0.001 Islander 2008-2014 -3.76 < 0.001 Sex Female 2000-2008 -1.4 < 0.001 2000-2014 -3.07 < 0.001 2000-2014 -1.36 < 0.001 < 0.001 < 0.001 2008-2011 -4.22 0.038 2011-2014 -1.63 0.096 Male 2000-2008 -1.95 < 0.001 2000-2014 -3.23 < 0.001 2000-2014 -1.33 < 0.001 < 0.001 < 0.001 2008-2011 -6.18 0.02 2011-2014 -2.04 0.096 Summary of localized, regional, and distant joinpoint models for the general population as well as stratified by age of diagnosis, tumor location, race, and sex. Each segment is given as a year range with the estimate of the annual percent change (APC) and the p-value associated with the APC. Pairwise comparison p-values (testing for parallel trends) of regional and distant are given for each stratum.

Mechanisms of Tumorigenesis in African American CRC Chapter 2 localized disease, we again compared joinpoint models. Localized CRC decreased 1.6% per year from 2000-2008 (APC = -1.6, p < 0.001), decreased 5.22% from 2008-2011

(APC = -5.22, p = 0.01) and decreased 1.8% from 2011-2014 (APC = -1.8, p = 0.07). The two trends of localized and distant disease were also not statistically parallel (p < 0.001), again with distant CRC decreasing at a significantly slower rate than localized CRC.

Decrease in incidence rate of distant CRC is slower in patients diagnosed with CRC at 50 or more years of age

Because persons under 50 years old only screen for CRC if they have a first- degree relative with CRC, which comprises less than 20% of the population, we compared incidence rates of persons younger than 50 with persons 50-64 years old and persons 65 years and older. As has been reported previously 120, we found that early-onset

CRCs, defined as CRCs diagnosed before age 50, are more likely to present at more advanced stages compared to CRCs from patients 50 or more years of age. Figure 2.3A shows that the rate of distant early-onset CRCs is increasing more rapidly than localized or regional early-onset CRCs (Table 2.1, localized vs distant, p < 0.001; regional vs distant, p < 0.001). From 2000-2014, localized and regional early-onset CRC incidence rates increased by 1.39% and 1.33% per year (localized, APC = 1.39, p < 0.001; regional,

APC = 1.33, p < 0.001), respectively. During the same time, the incidence rate of distant

CRC increased by 2.9% per year (APC = 2.90, p < 0.001), over two times the percentage increase as localized and regional early-onset CRC.

In contrast, in both age groups diagnosed with CRC at 50 or more years of age

(middle: 50-64 years; late: 65+ years), incidence rates for all three stages decreased from

Mechanisms of Tumorigenesis in African American CRC Chapter 2

Figure 2.3 Incidence rates of distant, regional, and localized CRC by age, sex, site, and race. Change in the incidence rates (per 100,000) of CRC by stage stratified by (A) age (<50, 50-64, 65+), (B) site (distal, proximal), (C) race (Native American/Alaskan

Native, Asian or Pacific Islander, Black or African American, and White), and (D) sex.

Green squares, localized; yellow triangles, regional; red stars, distant.

Mechanisms of Tumorigenesis in African American CRC Chapter 2

2000-2014. As seen with the unstratified data, the decrease in incidence rate of distant disease was significantly slower compared both to the decrease in incidence rate of regional disease (middle, p < 0.001; late, p < 0.001) and to the decrease in incidence rate of localized disease (middle, p = 0.007; late, p < 0.001).

Decrease in incidence rate of distant CRC is slower for both proximal and distal CRCs

To address whether tumor location might explain the slower reduction of distant

CRCs, we stratified joinpoint models by distal and proximal CRC (Figure 2.3B, Table

2.1). In proximal CRCs, from 2000-2014, the incidence rate of distant disease decreased annually by 1.56% (p < 0.001), whereas the incidence rate of regional disease decreased annually by 3.39% (p < 0.001). Localized disease was relatively stable throughout this period (Table 1). In distal CRCs, the incidence rate of distant disease was stable from

2000-2002 (APC = 1.83, p = 0.13), then it decreased annually by 1.71% from 2002-2012

(p < 0.001), and it was again stable from 2012-2014 (APC = 1.2, p = 0.27). The incidence rate of regional disease in distal tumors decreased by 2.88% from 2000-2014 (APC = -

2.88, p < 0.001) and the incidence rate of localized disease decreased annually by 2.44% from 2000-2007 (p < 0.001) and by 4.16% from 2007-2014 (p < 0.001).

Thus, over the time period from 2000-2014, incidence rate models for distant CRC and regional CRC were statistically different for both distal and proximal disease (p < 0.001 for both comparisons). Similarly, incidence rate models for distant

CRC and localized CRC were statistically different for distal disease (p < 0.001) and for proximal disease (p = 0.029). In all cases, distant CRC incidence rates decreased significantly more slowly than non-distant disease.

Mechanisms of Tumorigenesis in African American CRC Chapter 2

Decrease in incidence rate of distant CRC is slower for most ethnic groups

Because non-white ethnic groups have lower rates of colorectal cancer screening than whites 121,122, to address whether differences in the frequency of screening might explain the slower reduction of distant CRCs, we stratified joinpoint models by race.

African Americans have the highest CRC incidence rates of all ethnic groups in the US and are also more likely to be diagnosed at later stages 123. This observation is reflected in Figure 2.3C, where incidence rates of distant CRC are higher than rates in other races over the same period of time. The lower rates of CRC screening in the

African American population might be expected to result in more comparable decreases in rates in distant and earlier-stage disease; however, joinpoint models for distant CRC in

African Americans compared both to regional and to localized CRC in African

Americans were statistically different, that is, the incidence rate of distant CRC decreased more slowly than the incidence rates of less advanced tumors (Table 2.1; localized vs. distant, p = 0.022; regional vs. distant, p < 0.001). For Asians, the incidence rate of distant CRC decreased more slowly than the incidence rate of regional (p = 0.001), whereas the decrease in the incidence rate for localized disease was not statistically different from that for distant disease. For Native Americans, joinpoint models of all stages were statistically similar (localized vs. distant, p = 0.083; regional vs. distant, p =

0.10). The smaller population sizes underpinning the data from the Native American population make rate comparisons less certain.

Decrease in incidence rate of distant CRC is slower in both males and females

To address whether sex might explain the slower decrease in incidence rate of

Mechanisms of Tumorigenesis in African American CRC Chapter 2 distant disease compared to that of earlier-stage disease, we stratified the data by sex

(Figure 2.3D). The incidence rate of distant disease decreased by 1.36% and 1.33% each year for females (APC = -1.36, p < 0.001) and males (APC = -1.33, p < 0.001), respectively, whereas the incidence rate of regional disease decreased annually by 3.07% for females (p < 0.001) and annually by 3.23% for males (p < 0.001). In females, localized CRC decreased annually by 1.4% from 2000-2008 (p = 0.001) and by 4.22% from 2008-2011 (p = 0.038), then it was stable from 2011-2014 (APC = -1.63, p =

0.096). For males, localized disease decreased annually by 1.95% (p = 0.001) from 2000-

2008 and by 6.18% from 2008-2011 (p = 0.02), then it was stable from 2011-2014 (APC

= -2.04, p = 0.096). Overall, the joinpoint models of distant CRC differed from those of regional and localized CRC for both males and females (Table 2.1; p < 0.001 for all comparisons).

Discussion

Analysis of incidence data for CRC from the SEER program over the years 2000-

2014 shows that the overall incidence rate of CRC has decreased by 29.7%, an outcome ascribed by some to an increase in CRC screening in the general population.

Paradoxically, the reduction in incidence has not been evenly distributed over all stages of disease at diagnosis. Overall, the incidence rate of distant disease, which is predominated by CRC that has metastasized to the liver, has decreased by 12.8%, whereas the incidence rate of regional and localized disease has decreased by 34% and

28%, respectively. Our analysis has shown that these differences in incidence rates are statistically significant, with the decrease in distant disease being slower than the decrease in regional and localized disease. 58

Mechanisms of Tumorigenesis in African American CRC Chapter 2

In consideration of the impact of these epidemiologic trends, it is first important to acknowledge that these differences in percentage change are not small. It is unlikely that they will be explained by small differences in epidemiologic variables. Secondly, although joinpoint modeling suggests that rates of change can vary over different periods in the 2000-2014 time, the conclusions from joinpoint models are not substantially different from the conclusions drawn from linear models (analysis not shown). Thirdly, in persons less than 50 year old—a population subgroup that is predominantly not screening—the incidence rates of CRC are increasing for all stages 124, but the incidence rate of distant CRC is increasing faster than localized and regional. Finally, we found that profound differences in percentage change between distant and non-distant CRC were present in every subgroup in which it was possible to stratify the data, namely, age, sex, race, and tumor location. Consequently, these differences cannot be ascribed to variables that predominate in one subgroup over another.

As noted above, the model upon which screening recommendations rely conceives CRC as a disease that takes 10-20 years to develop. Evidence from the

Minnesota Colon Cancer Control Study suggest that changes in screening rates can take over 10 years to have an impact on incidence rates [6]. If this lag time is correct, then changes in screening rates 1990-2004 should effect changes in incidence rates of cancer

2000-2014. The percentage of the general population undergoing colorectal screening in

1992 has been estimated at 25%125, and it increased to approximately 50% by 2005 126.

Recent studies have suggested that up to 60% of CRCs can be prevented by CRC screening, suggesting that at least some of the change in incidence rates 2000-2014 can be ascribed to increased colorectal screening 127,128. Based on the predominant model of

Mechanisms of Tumorigenesis in African American CRC Chapter 2

CRC progression (Figure 2.1), colorectal screening should prevent distant CRC more effectively than regional and localized disease. We conclude therefore that the relative stability of distant disease from 2000-2014 is not consistent with a screening effect. At the population level represented by SEER data, increases in CRC screening are associated with decreases in localized and regional disease, whereas increased screening has not been associated with the same amount of reduction in the incidence of distant disease. Given the success of CRC screening in reducing the incidence of CRC overall, we find this result both perplexing and disturbing. The analysis of SEER data presented here raises the question whether screening strategies can be modified in practical terms to reverse these trends 129,130.

Inadequate screening does not explain the slow decrease in incidence of distant CRC

Why is the incidence rate of distant CRC not decreasing as quickly as expected?

Could the slower decrease of distant CRC arise from inadequate screening? If the difference in rate decreases were due to inadequate screening, we would expect an association between differences in screening rates and differences in incidence rates.

Because incidence and screening rates differ by race with whites having higher screening rates than non-whites 121,122, inadequate screening predicts that the decrease in incidence rate of distant disease in less frequently screening populations should be slower than in the higher frequency screening populations. Although the incidence of distant disease is higher in African Americans compared to whites, the rate of decrease in the incidence is similar between the two ethnic groups (Figure 2.3C), despite the fact that African

Americans have until recently undergone CRC screening considerably less frequently

Mechanisms of Tumorigenesis in African American CRC Chapter 2 than whites. The same trend is apparent in the Asian and Pacific Islander ethnic populations, which are populations that also have lower screening rates than whites. The finding that the slower decrease of distant CRCs is observed in a range of populations with different screening rates suggests that a defect in screening does not explain the incidence rate difference.

We considered whether tumor location might explain the slow decrease in distant

CRCs because benign lesions are more likely to be missed in the proximal colon and adenocarcinoma is less likely to be detected by non-colonoscopic screening modalities.

Going against this explanation, however, we found that the incidence rates of distant

CRCs are decreasing at statistically slower paces compared to regional and localized disease among both proximal and distal CRCs. Thus, trends in distant CRC incidence rates are similar in both tumor locations (Figure 2.3B).

The lack of association between screening rates and incidence rates of distant

CRC and between tumor location and incidence rates of distant CRC suggest that inadequate CRC screening is not sufficient to explain the slower decrease in the rate of distant disease, that is, it is not consistent with a screening effect.

More rapidly advancing cancers of the serrated adenoma pathway can only explain part of the slow decrease in incidence of distant CRC

Most CRCs take a decade or more to develop to advanced stages, justifying the currently suggested screening intervals that are used to detect early lesions. CRCs that progress and metastasize quickly would therefore resist detection by screening because screening intervals are too long to prevent them.

Mechanisms of Tumorigenesis in African American CRC Chapter 2

There is a CRC subtype consisting of 10% to 15% of sporadic CRCs that is thought to develop more rapidly than the majority of CRCs, namely, CRCs that exhibit microsatellite instability (MSI) 131. Sporadic CRCs that exhibit MSI develop predominantly due to methylation of the promoter region of mismatch repair gene MLH1

132–135. Sporadic MSI CRCs are associated with a CpG island methylator phenotype, older age of diagnosis, and female sex 136. They arise more frequently in the proximal colon, progress more rapidly 137, and are more likely to be diagnosed at a later stage 138. There is evidence that tumors with MSI develop from flat lesions via mutation in RNF43 (serrated adenoma pathway) rather than the adenoma to adenocarcinoma pathway, which is associated with gatekeeper mutations in the APC gene 139. Moreover, CRC development in Lynch syndrome, which is associated with disease-causing mutations in mismatch repair genes, progresses more rapidly 140, leading to the recommendation of annual screening colonoscopy 141. These data therefore suggest that screening is less effective for sporadic CRCs that develop via the serrated adenoma pathway. However, our analysis of

SEER data showed that the decrease in incidence rate of distant CRCs was similar in the distal colorectum and in the proximal colon and there was no sex difference in the decrease in distant CRCs (Figure 2.3B & 2.3D), suggesting that CRCs of the MSI subtype are very likely not the sole explanation for the slower rate of decrease of distant cancers.

Hypothesis of nonMSI CRC that advances rapidly

Our analysis has shown that the incidence of distant CRC is decreasing at a slower rate than localized and regional CRC, a trend which is not explained by a

Mechanisms of Tumorigenesis in African American CRC Chapter 2 particular age group at diagnosis, tumor location, race, or sex. We propose that the difference in distant and non-distant CRC incidence reductions suggests the existence of rapidly advancing forms of CRC that develop and metastasize too quickly for screening to prevent them. Based on the considerations cited above, we hypothesize that there exists a microsatellite stable (i.e., nonMSI) CRC subtype that develops and progresses more rapidly than conventional CRC. Moreover, based on the more rapidly increasing incidence rate of distant CRC in the early-onset CRC age group, the unchanging incidence rate in the 50-64 age group, and the decreasing incidence rate in the 65+ age group, we suggest that this rapidly advancing cancer occurs more frequently in younger persons than in older persons.

Our hypothesis makes predictions that can be tested. First, the hypothesis predicts that a significant fraction of CRCs that present at a metastatic stage at initial diagnosis would be of the rapidly developing subtype. Consequently, we would expect cluster analysis of somatic mutations or expression profiles in these tumors to reveal either a distinct subtype or a significantly different distribution of known subtypes. Secondly, interval and early-onset cancers that present as metastatic CRCs should possess molecular signatures that are similar to those found in primary metastatic CRCs identified in non-screening patients. An important question is whether the molecular pathogenesis of the proposed aggressive nonMSI CRC subtype differs from the canonical adenoma- carcinoma sequence that is initiated by mutations of the Adenomatous Polyposis Coli

(APC) gene, because this well-studied pathway is known to take 10 to 20 years to progress to CRC.

Mechanisms of Tumorigenesis in African American CRC Chapter 2

Limitations and alternative theories

Limitations of the present study include the unavailability of information on whether CRC cases were screening, the frequency and modes of CRC screening, and clinical and molecular data such as mismatch repair gene immunohistochemistry. An important question raised by our analysis is whether the slower decrease in the incidence rate of distant CRCs could be explained by changes in exposures to the adverse lifestyle factors of diet and physical inactivity that are known to increase overall CRC risk, the times at which these exposures occur, or changes in usage of medications that reduce

CRC risk, such as aspirin usage 142,143. Unfortunately, it is not possible to assess the impact of exposures using SEER data140,141.

As mentioned above, it is currently estimated that 60% of CRCs can be prevented by colonoscopy. Approximately three quarters of the CRCs that arise after a negative colonoscopy are due to missed lesions 144–146. These considerations suggest that, even if all lesions were identified by colonoscopy, some fraction of interval cancers are new cancers. Importantly, it is difficult to distinguish missed lesions from newly developed cancers 147. Although colonoscopy studies suggest that all stages of CRC are reduced by screening 119, the present study raises the question whether this conclusion is correct at the population level. Moreover, there is epidemiologic evidence that colorectal screening does not explain all of the reduction in CRC incidence since 1980148. Consequently, the slower rate of reduction of distant cancers from 2000-2014 may be associated with a risk variable, such as low socioeconomic status, education, or medication history. In order to test this hypothesis, more comprehensive and individualized demographic and exposure data are needed.

Mechanisms of Tumorigenesis in African American CRC Chapter 2

Whatever the explanation for the differences in decrease of incidence rate by stage of presentation, a better understanding of the biology and epidemiology underlying this phenomenon is urgently needed. If CRC screening is truly ineffective in preventing metastatic disease at presentation, then biomarkers for possible early detection and targeted therapies for this type of metastatic disease are needed to improve survivorship of these patients. Further studies of CRCs that are metastatic at presentation would help us understand the biological and epidemiologic mechanisms underlying their occurrence and provide new approaches to impact the public health consequences of distant disease.

Mechanisms of Tumorigenesis in African American CRC

Chapter 3

Race-dependent association of sulfidogenic bacteria with colorectal cancer

Originally published in Gut (Permissions can be found in Appendix C)

Yazici C, Wolf PGPG, Kim H, et al. Race-dependent association of sulfidogenic bacteria with colorectal cancer. Gut. 2017;66(11):gutjnl-2016-313321. doi:10.1136/gutjnl- 2016-313321

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Abstract

Background Colorectal cancer (CRC) incidence is higher in African Americans compared with non-Hispanic whites (NHWs). A diet high in animal protein and fat is an environmental risk factor for CRC development. The intestinal microbiota is postulated to modulate the effects of diet in promoting or preventing CRC. Hydrogen sulfide, produced by autochthonous sulfidogenic bacteria, triggers proinflammatory pathways and hyperproliferation, and is genotoxic.

Objective We hypothesized that sulfidogenic bacterial abundance in colonic mucosa may be an environmental CRC risk factor that distinguishes African American and NHW.

Methods Colonic biopsies from uninvolved or healthy mucosa from CRC cases and tumor-free controls were collected prospectively from five medical centers in Chicago for association studies. Sulfidogenic bacterial abundance in uninvolved colonic mucosa of

African American and NHW CRC cases was compared with normal mucosa of African

American and NHW controls. In addition, 16S rDNA sequencing was performed in

African American cases and controls. Correlations were examined among bacterial targets, race, disease status and dietary intake.

Results African Americans harbored a greater abundance of sulfidogenic bacteria compared with NHWs regardless of disease status. Bilophila wadsworthia-specific dsrA was more abundant in African American cases than controls. Linear discriminant analysis of 16S rRNA gene sequences revealed five sulfidogenic genera that were more abundant in African American cases. Fat and protein intake and daily servings of meat were significantly higher in African Americans compared with NHWs, and multiple dietary components correlated with a higher abundance of sulfidogenic bacteria.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Conclusions These results implicate sulfidogenic bacteria as a potential environmental risk factor contributing to CRC development in African Americans.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Abbreviations

CRC, Colorectal Cancer; AA, African Americans; NHW, Non-Hispanic Whites; H2S,

Hydrogen Sulfide; SRB, Sulfate-Reducing Bacteria; IRB, Institutional Review Boards;

BMI, Body Mass Index; NSAIDS, Non-Steroidal Anti-Inflammatory Drugs; qPCR,

Quantitative Polymerase Chain Reaction; DSB, Desulfobacter spp.; DBB, Desulfobulbous spp.; DFM, Desulfotomaculum spp.; DSV, Desulfovibrio spp.; dsrA, Dissimilatory Sulfite

Reductase A; dsrA-BW, Bilophila wadsworthia Specific Dissimilatory Sulfite Reductase

A; OTU, Operational Taxonomic Unit; LDA, Linear Discriminant Analysis; BBFFQ,

Block Brief 2000 Food Frequency Questionnaire.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Introduction

Colorectal cancer (CRC) is the third most frequent cancer in the United States with an estimated 134,490 new cases and 49,190 deaths in 2016. African Americans have a CRC incidence 10-30% higher than other races and ethnicities, and even greater disparities in mortality rates149. African Americans are diagnosed at earlier ages and have more proximal CRC compared to non-Hispanic Whites (NHWs)7. Although some types of CRC are influenced by genetic risk factors or disease, the majority occur sporadically as a consequence of environmental exposures that promote colonocyte hyperproliferation, loss of apoptotic control and epithelial barrier integrity, and excess production of pro- inflammatory immunomodulatory factors150.

Significant differences in fecal and colonic microbial composition in healthy subjects and cancer patients have been identified151–160, but the impact remains uncertain.

Compared with tumor-free controls, CRC subjects have higher levels of stool hydrogen

57 sulfide (H₂S) . Higher levels of fecal H2S have been detected in patients with colitis, who have an increased susceptibility of CRC161–163. Exogenous H₂S is genotoxic at levels commonly found in the colon. This bacterial-derived gas induces proliferative and pro- inflammatory pathways and inhibits β-oxidation of butyrate—an anti-carcinogenic metabolite and favored substrate of colonocytes164–167. Multiple bacterial species produce

H₂S, including taurine-respiring Bilophila wadsworthia, cysteine-utilizing Fusobacterium nucleatum, and sulfate-reducing bacteria (SRB) such as Desulfovibrio spp168–170.

Additionally, higher levels of fecal bile acids have been observed in CRC cases than controls57, which could be associated with increased abundance of taurocholate-utilizing

B. wadsworthia.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Because exposure to H2S could promote CRC development, we hypothesized that sulfidogenic bacteria contribute to a microenvironment conducive to colorectal carcinogenesis through production of H2S. Accordingly, we examined sulfidogenic bacterial abundance in uninvolved mucosa of subjects with CRC compared to tumor-free controls. Of particular interest was whether differences in sulfidogenic bacteria between

African Americans and NHWs might contribute to racial differences in CRC incidence rates.

Materials and Methods

Human Subjects

The Chicago Colorectal Cancer Consortium prospectively ascertained incident

CRC cases from surgery and endoscopy units and tumor-free controls undergoing routine screening colonoscopy from five Chicago medical centers, including University of

Illinois Hospital and Health Sciences System, Jesse Brown Veterans Administration,

John H. Stroger Hospital of Cook County, University of Chicago Medicine, and Rush

University Medical Center, over a two-year period (2011-2012), as previously described75. The parent study received approval for human subjects research from the institutional review boards (IRBs) of each participating medical center; the parent protocol was administered by the IRB at University of Illinois Hospital and Health

Sciences System (2010-0168). Colonic tissue biopsies from uninvolved or healthy mucosa were studied from 329 subjects after routine bowel preparation. The cases were persons with adenocarcinoma of the colon or rectum detected during patient workup due to gastrointestinal symptoms or collected at the time of surgical resection. Control subjects were persons undergoing colonoscopy in whom tumors were not identified. In 71

Mechanisms of Tumorigenesis in African American CRC Chapter 3

CRC cases, biopsies were collected approximately 10 cm away from the tumor location.

Samples were taken either with endoscopic biopsy or surgical forceps. Included were 97

African American and 56 NHW CRC cases, and 100 African American and 76 NHW controls. Persons with a personal history of cancer, inflammatory bowel disease, adenomatous or benign polyps, polyposis, or tumors with microsatellite instability were excluded75. Clinical data were extracted from medical records, and epidemiologic and demographic information were obtained using subject questionnaires as previously described75. Factors analyzed included age, sex, race; tumor or biopsy site, tumor stage; body weight, body mass index (BMI); education and income level; usage of tobacco products and alcohol; and usage of omega-3 fatty acids and non-steroidal anti- inflammatory drugs (NSAIDs) (Table 3.1). Significantly different factors were used as covariates for potential confounder adjustment.

Quantitative Polymerase Chain Reaction (qPCR) Analysis

Mucosal biopsies were placed into RNAlater and stored at 4° C overnight, after which they were stored at -80° C until extraction. DNA was isolated from mucosal biopsies using commercial DNA extraction kits (Promega, Madison, WI; Mobio,

Carlsbad, CA), quantified, and diluted to 5 ng/μL. Examination of bacterial target abundances of NHW cases prepared with the two kits yielded similar results, indicating that DNA extraction method did not introduce bias. Sulfidogenic bacteria abundance was quantified in triplicate with a 7900HT Fast Real-Time PCR System (Applied Biosystems,

Foster City, CA). Small subunit rRNA genes of SRBs including Desulfobacter spp.

(DSB), Desulfobulbus spp. (DBB), Desulfotomaculum spp. (DFM), and Desulfovibrio

Table 3.1 Clinical and demographic characteristics of African American (AA) and non-Hispanic white (NHW) subjects

African Americans (n=197) NHWs (n=132) Clinical variable Controls N Cases N p-value Controls N Cases N p-value

Age, mean in years±SD 55.5±9.6 100 59.8±10.8 97 0.003 55±12.91 76 59.6±10.1 56 0.047 Biopsy, left/right large 55/45 100 55/42 97 0.886 50/25 75 42/13 55 0.248 bowelA Gender, F/M 46/54 100 40/57 97 0.566 32/44 76 18/38 56 0.28 Weight, mean in lb±SD 198.1±43.9 100 178.8±41.9 97 0.007 177.3±37.1 76 189.1±45.1 56 0.024 BMI in kg/m2±SD 30.4±6.1 100 28.3±6.5 97 0.043 27.5±6.5 76 28.4±5.9 56 0.046 College education, %B 59.6 99 35.5 97 <0.001 69.7 76 52.7 55 0.047 Annual income, % 100 96 0.032 75 55 0.384 <25 000 60 60 75 72 36 27 47.3 26 25 000 –75 000 29 29 21.9 21 36 27 32.7 18 ≥750 000 11 11 3.1 3 28 21 20 11 Omega-3, % usersC 27.6 87 14.6 41 0.174 50 50 27.3 22 0.07 Alcohol, % current users 31.3 99 24.2 91 0.33 48.7 76 32.1 53 0.06 Smoking, mean pack years 6.1±10.7 46 7.6±14.8 70 0.73 12±21.8 39 14.9±26.3 44 0.92 NSAID use in yearsD 4.9±6.8 93 3.03±7.8 95 0.084 7.6±9.2 75 3.1±7 51 <0.001 TNM stageE 89 50 Stage 0 and 1 28 (31.5%) 14 (28%) Stage 2 23 (25.8%) 16 (32%) Stage 3 23 (25.8%) 12 (24%) Stage 4 15 (16.9%) 8 (16%)

Statistical comparisons between cases and controls within each ethnic group were performed using Wilcoxon rank-sum or t-test for

continuous variables and χ2 or Fisher's exact test for dichotomous variables. Annual income in US$.

AThe right side of the large bowel includes the caecum and appendix, ascending colon, hepatic flexure and transverse colon. The left side includes the splenic flexure, descending colon, sigmoid colon and rectum.

B Percent of subjects who graduated from a 4-year undergraduate scholastic program.

CPercent of subjects who reported dietary supplementation with omega-3 fatty acids in the last 5 years.

DNSAID used included Ibuprofen, Advil or Motrin.

EThe p value for the comparison of stages between African American CRCs and NHW CRCs was 0.89.

BMI, body mass index; CRC, colorectal cancer; N, number of subjects from whom information was available; NSAID, non-steroidal anti-inflammatory drug; TNM, tumor node metastasis classification of malignant tumors.

Mechanisms of Tumorigenesis in African American CRC Chapter 3 spp. (DSV) were targeted and validated as previously described171. In addition, functional

172 genes from the H2S production pathway, pan-dissimilatory sulfite reductase A (dsrA) harbored by all SRB173 and B. wadsworthia-specific dsrA (dsrA-BW)167 were quantified.

Statistical Analysis

To test differences between groups, Wilcoxon Rank Sum test or t-test, for continuous variables, and chi-square or Fisher exact test for dichotomous variables were used. Because bacterial targets were not normally distributed, data was log-transformed.

For binary outcome analyses (African American vs. NHW and case vs. control), logistic regression models were used adjusting for selected covariates. In all models, age, sex, and biopsy location were included. For sulfidogenic bacterial analysis in African

Americans, BMI, education level, and annual income level were included. In NHWs,

BMI, education level, and NSAID use were included. Spearman correlation analysis was used to test associations between sulfidogenic bacteria. Statistical tests were conducted using SAS 9.3 (SAS Inc., Cary, NC).

Analysis of Dietary Intake

Dietary intake was obtained using the Block Brief 2000 Food Frequency

Questionnaire (BBFFQ) from a subset of subjects, including 50 African American and 31

NHW CRC cases and 30 African American and 24 NHW controls174. The questionnaires were administered within three weeks of the diagnostic procedure to reduce recall bias.

NutritionQuest (Berkeley, CA) processed completed BBFFQs. The Diet and Behavior

Shared Resource of the University of Illinois-Chicago Cancer Center prepared a dataset

Mechanisms of Tumorigenesis in African American CRC Chapter 3 for statistical analysis.

Dietary intake data from outliers were excluded [<600 kcals (n = 11) or >3500 kcals (n = 1)]. Because energy intake is highly correlated with macro and micronutrient intake,175 nutrient or food group was adjusted per 1000 calories. Density variables were created for total fat (g), saturated fat (g), monounsaturated fat (g), polyunsaturated fat (g), protein (g), total carbohydrate (g), total fiber (g), cysteine (mg), calcium (mg), iron (mg), alcohol (g), omega-6 fatty acids (g), and daily food group servings of meat, vegetables, fruit, total grains, and dairy. Percent kcals from fat, protein, and carbohydrate were also examined.

Differences in intake of nutritional variables between African Americans and

NHWs were assessed using the Wilcoxon Signed Rank test or t-test, as appropriate. To analyze the relationship between selected dietary intake variables (cysteine, total fat, and daily servings of dairy) and sulfidogenic bacterial abundance, linear regression models were created using R version 3.3.1 and adjusted for age, sex, race, disease status, and

BMI176–178. Due to the high degree of co-linearity between these variables and other dietary factors of interest, it was necessary to isolate the independent effect of these intake variables. Consequently, we residualized each variable by obtaining the residuals for a model fit with all correlated variables > 0.50 as explanatory and used these residuals in our final model.

Results

Race-Specific Differences in Mucosal Sulfidogenic Bacteria

Comparison of sulfidogenic bacterial targets between races revealed pan-dsrA,a measure of SRB abundance across a range of species, to be 10 times higher in African 76

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Figure 3.1 Differences in mean gene copy numbers of sulfidogenic bacteria comparing colorectal cancer cases and controls in African Americans and non-Hispanic Whites. A.

Scatterplot representations of mean gene copy numbers per nanogram of DNA of

Mechanisms of Tumorigenesis in African American CRC Chapter 3 sulfidogenic bacterial targets in African Americans compared to non-Hispanic Whites with median and upper and lower quartiles indicated. African Americans are represented in green and non-Hispanic Whites are represented in purple. All comparisons had a p<0.001. B. Scatterplot representations of mean gene copy numbers per nanogram of

DNA of sulfidogenic bacterial targets in cases and controls in each racial group. African

Americans cases are represented in light green and controls in dark green. Non-Hispanic

White cases are represented in light purple and controls in dark purple.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Americans compared to NHWs (p<0.001) irrespective of disease status (Figure 3.1A).

Abundance of individual SRB genera were higher in African Americans compared to

NHWs for all species except DBB; DBB levels were mostly undetectable in African

Americans. Similarly, the abundance of B. wadsworthia was 2.5 times higher in African

Americans compared to NHWs irrespective of disease status (p<0.001). These differences in abundance remained statistically significant after adjustment for clinical and epidemiological variables that were different between races (Table 1).

Comparison of sulfidogenic bacterial targets between CRC cases and controls within each racial group revealed the mean abundance of pan-dsrA to be 1.8 times higher in African American controls than African American CRC cases (p<0.001) (Figure 3.1B).

By contrast, this target was 2.9 times higher in NHW CRC cases than NHW controls

(p<0.001). These racial differences remained significant after adjusting for age, sex, biopsy site, BMI, education, income level, and NSAID use (Table 3.1).

The taurine-respiring sulfidogenic bacterium B. wadsworthia was 1.9 times more abundant in African American CRC cases than African American controls (p<0.001), and remained significant after adjusting for demographic factors mentioned previously. On the other hand, abundance of B. wadsworthia did not differ between NHW cases and controls.

Consistent with the pan-dsrA results, the abundance of DSB (p<0.001) and DFM

(p<0.001) was significantly higher in African American controls than African American

CRC cases. On the other hand, abundance of DSB (p=0.018) and DBB (p<0.001) was significantly higher in NHW CRC cases than NHW controls. These data demonstrate that

African American and NHW cases and controls display reciprocal differences in SRB

Mechanisms of Tumorigenesis in African American CRC Chapter 3 abundance, which remained after adjusting for tumor stage. Additionally, Spearman’s correlation analysis revealed that SRBs correlated positively with B. wadsworthia in

NHWs but not in African Americans (Table 3.2).

Associations between Diet and Sulfidogenic Bacteria

To examine whether diet differed between African Americans and NHWs, dietary intake was analyzed with the BBFFQ, focusing on nutrient and dietary factors associated with the typical mixed Western-style diet, namely intake of total fat, animal fat, and protein. Overall, dietary fat and protein intake per 1000 kcals was significantly greater in

African American compared to NHW subjects; on the other hand, calcium intake and servings of dairy per 1000 kcals were lower (Table 3.3). To examine the effect of dietary intake on sulfidogenic target abundance, these dietary variables were examined using linear regression models (Figure 3.2; Figure 3.3; Table 3.4). As observed in the larger dataset (Figure 3.1), the three major sulfidogenic bacteria tested (pan-dsrA, B. wadsworthia, and DSV) strongly associated with race─the main variable that explained differences between African Americans and NHWs (Figure 3.2). In the models, pan-dsrA abundance also significantly associated with residuals for cysteine (p=0.016), total fat

(p=0.011), and daily servings of dairy (p=0.007), as well as male sex (p=0.0032). DSV abundance was not significantly associated with dietary variables, but trends were observed with cysteine and male sex. Similarly, B. wadsworthia abundance was not significantly associated with dietary variables, but there was a strong association with age

(Figure 3.2; p=0.001).

Table 3.2 Pair-wise comparisons of sulfidogenic bacteria in African Americans and in non-Hispanic Whites tested by Spearman correlation analysis.

Log pan-dsrA Log DSV Log DSB Log DBB Log DFM Log B. wads African Americans Log pan-dsrA 1 (190)

Log DSV 0.260 (179) 1 (185) <0.001 Log DSB 0.501 (185) 0.147 (179) 1 (190) <0.001 0.05 Log DBB 0.016 (186) –0.32 (182) 0.037 (186) 1 (193) 0.83 0.67 0.62 Log DFM 0.519 (187) 0.208 (181) 0.593 (186) 0.076 (189) 1 (193) <0.001 0.005 <0.001 0.30 Log B. wads 0.093 (185) 0.195 (182) –0.082 (185) –0.155 (188) –0.197 (188) 1 (192) 0.21 0.008 0.27 0.03 0.007 Non-Hispanic Whites Log pan-dsrA 1 (114)

Log DSV 0.528 (91) 1 (97) <0.001 Log DSB 0.771 (114) 0.599 (96) 1 (131) <0.001 <0.001 Log DBB 0.656 (112) 0.454 (96) 0.474 (128) 1 (129) <0.001 <0.001 <0.001 Log DFM 0.643 (112) 0.555 (97) 0.772 (125) 0.423 (123) 1 (126) <0.001 <0.001 <0.001 <0.001 Log B. wads 0.297 (109) 0.279 (92) 0.459 (123) 0.175 (121) 0.321 (118) 1 (124) 0.002 0.007 <0.001 0.05 <0.001

The Spearman rho value is the upper value in each cell with the total n is in parenthesis. The p-value of the comparison is the lower value in each cell. Bilophila wadsworthia, B. wads; Desulfobacter spp., DSB; Desulfobulbus spp., DBB; Desulfotomaculum spp.,

DSM; Desulfovibio spp., DSV; Dissimilatory sulfite reductase A, dsrA.

Table 3.3 Comparisons of key dietary nutrients in African Americans and non-Hispanic Whites.

Dietary variables African Americans Non-Hispanic Whites P-values (n=73) (n=50) Total kilocalories 1269.2 ± 521.3 1400.9 ± 555.5 0.183 Total protein (g) 38.9 ± 6.9 39 ± 7 0.946 Daily servings of meat 1.44 ± 0.49 1.18 ± 0.51 0.006 Cysteine (mg) 565.6 ± 104.9 515.5 ± 94.3 0.008 Total iron (mg) 13.9 ± 14.8 12 ± 11.9 0.456 Daily servings of dairy 0.55 ± 0.43 0.97 ± 0.85 <0.001 Calcium (mg) 341.8 ± 130.5 450.8 ± 206.8 <0.001 Daily servings of vegetables 1.9 ± 1.7 2 ± 1.4 0.678 Daily servings of grains 2.29 ± 0.93 2.11 ± 0.91 0.303 Daily servings of fruits 1.08 ± 0.93 1.13 ± 0.96 0.801 Total fiber (g) 9.4 ± 4.8 9.6 ± 4.7 0.833 Total fat (g) 44.3 ± 8.1 40.7 ± 10.3 0.033 % of kilocalories from fat 35.9 ± 14.2 29 ± 10.4 0.004 Saturated fat (g) 14.3 ± 3.3 13.7 ± 4.3 0.371 Monounsaturated fat (g) 16.9 ± 3.8 15.8 ± 4.6 0.155 Trans fats (g) 1.6 ± 0.7 1.2 ± 0.5 <0.001 Polyunsaturated fat (g) 9.5 ± 2.8 7.8 ± 2.3 <0.001 Dietary PUFA (~N-6) 8.2 ± 1.8 6.8 ± 1.8 <0.001 18:2 (g) Dietary PUFA (~N-6) 0.93 ± 0.33 0.78 ± 0.27 0.007 18:3 (g) Dietary PUFA (~N-6) 0.017 ± 0.013 0.015 ± 0.014 0.259 20:5 (g) Omega-6 FA (g) 8.3 ± 1.8 6.9 ± 1.8 <0.001 Omega-3 FA (g) 0.99 ± 0.34 0.82 ± 0.27 0.003 Total alcohol (g) 3.4 ± 8.2 5.6 ± 12.3 0.248

Nutrient intakes are reported in either gram (g), milligram (mg), daily servings or percent (%) kilocalories (kcal), adjusted for total calorie intake. Mean intake ± standard deviations are per 1000 calorie intake except the total kilocalories variable. A significance threshold (p<0.0063) was set for each major food group, herein shown as protein, dairy, fat, vegetables, fiber, alcohol; the significant values are in bold.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Figure 3.2 Comparison of selected factors that explain differences in sulfidogenic bacteria in African American and non-Hispanic Whites. A. Scatter plot representations of residuals of linear models for selected bacterial targets, namely, pan-dsrA, Desulfovibrio spp., and B. wadsworthia. African Americans are represented in green, non-Hispanic whites are represented in purple. Cases are represented as open circles and controls as closed circles. B. Forest plots of effect size estimates from the linear models. Outcome variables were log transformed gene copy abundances of pan-dsrA, Desulfovibrio spp., and B. wadsworthia. Points and lines on each plot represent the point estimate and 95% confidence interval, respectively, for each covariate in the model. Estimates reflect predicted change in variable for one unit change in outcome. Positive associations are in blue, negative associations are in red. P value for each covariate is represented on the right, and statistically significant values after Bonferroni correction are in bold. The wide confidence interval seen in the BMI, underweight class is explained by the small number of observations in this class.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Figure 3.3. Linear regression models showing effect of selected factors in African

American and non-Hispanic Whites. Scatterplots representing model residuals of selected variables. In each panel, symbols are shaded to indicate the residual of the variable indicated. African Americans are represented by triangles and non-Hispanic

Whites by circles. The intensity of the color represents the variable as shown in the inset.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

The indicated variables were chosen because they trended towards significance in the linear regression models.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Table 3.4 Statistics from reduced linear regression models (after parameter reduction) for the selected sulfidogenic bacteria measured by quantitative polymerase chain reaction.

Dietary variable Estimate Std. error t value Pr(>t) Log Pan-dsrA Total protein -0.035 0.013 -2.73 0.0075 Total fat (g) 0.23 0.099 2.32 0.022 Calcium (mg) 0.0023 0.00081 2.86 0.0052 Daily dairy servings- 0.47 0.18 -2.5 0.013 Cysteine (mg) 0.0019 0.00085 2.2 0.032 Polyunsaturated fat (g) -0.23 0.11 -2.2 0.032 Monosaturated fat (g) -0.21 0.11 -2.0 0.051 Saturated fat (g) -0.27 0.10 -2.7 0.0084 Age (NHW) -0.0038 0.0046 -0.82 0.42 Sex (male) 0.31 0.11 2.9 0.0043 Race -0.88 0.11 -7.9 4.3 x 10-12 Disease status 0.075 0.094 0.80 0.42 BMI (healthy weight) -0.74 0.49 -1.5 0.13 BMI (overweight) -0.58 0.48 -1.2 0.23 BMI (obese weight) -0.81 0.48 -1.7 0.095 Intercept 2.1 0.68 3.031 0.0031 Log DSV Total protein -0.020 0.017 -1.2 0.25 Total fat (g) 0.055 0.077 0.71 0.48 Calcium (mg) 0.00049 0.00061 0.81 0.42 Daily meat servings- 0.047 0.14 -0.33 0.74 Daily dairy servings -0.060 0.14 -0.44 0.66 Cysteine (mg) 0.0014 0.00062 2.4 0.021 Polyunsaturated fat (g) -0.036 0.084 -0.43 0.67 Monosaturated fat (g) -0.056 0.083 -0.68 0.50 Trans fat (g) 0.053 0.065 0.81 0.42 Saturated fat (g) -0.066 0.079 -0.84 0.40 % calories from protein-0.0068 0.030 -0.23 0.82 % calories from fat -0.0014 0.013 -0.11 0.91 Age -0.0031 0.003 -0.92 0.36 Sex (male) 0.13 0.075 1.74 0.085 Race (NHW) -0.19 0.078 -2.5 0.015 Disease status 0.070 0.067 1.0 0.30 BMI (healthy weight) 0.099 0.34 0.30 0.77 BMI (overweight) 0.085 0.33 0.26 0.80 BMI (obese weight) -0.0096 0.33 -0.029 0.98 Intercept 2.2 0.52 4.21 6.1 x 10-05 Log B. wadsworthia Calcium (mg) -0.00084 0.00053 -1.6 0.12 Daily dairy servings 0.27 0.13 2.0 0.047

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Trans fat (g) -0.14 0.065 -2.1 0.038 Age 0.011 0.0037 2.8 0.0057 Sex (male) -0.018 0.084 -0.22 0.83 Race (NHW) -0.35 0.083 -4.2 5.1 x 10-05 Disease status 0.11 0.077 1.5 0.14 BMI (healthy weight) 0.058 0.40 0.14 0.89 BMI (overweight) 0.038 0.40 0.096 0.92 BMI (obese weight) -0.11 0.40 -0.27 0.79 Intercept 1.3 0.47 2.8 0.0058 Bilophila wadsworthia, B. wadsworthia; Desulfovibrio spp., DSV; Pan- dissimilatory sulfate reductase, pan-dsrA; std. error, standard error. The estimate provides the increase (or decrease) in bacterial abundance per each unit of variable. 51% of the variance in the abundance of pan-dsrA is explained by the present model; 24% of the abundance of B. wadsworthia; and 13% of the abundance of DSV.

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Discussion

The present results demonstrate that the microbiome of uninvolved mucosa in CRC cases is distinct from tumor-free controls and implicate sulfidogenic bacteria as potential contributors to CRC development. One of the more striking observations was the greater abundance of SRBs and B. wadsworthia in African Americans compared to NHWs irrespective of disease status. Pan-dsrA was 10-fold and B. wadsworthia dsrA 2.5 fold more abundant in African American colonic mucosa, and overall, analysis of individual sulfidogenic bacterial species confirmed this difference. Secondly, reciprocal differences in sulfidogenic bacterial abundance were observed in both African American and NHW

CRC cases compared to controls. Notably, similar reciprocal differences were observed during diet exchange between rural South African blacks and African Americans living in

Pittsburgh.57

It has been demonstrated previously that human colonic mucosa is persistently colonized by sulfidogenic bacteria178. Constitutive bacterial-derived sulfide may have a protective anti-microbial effect, based on the susceptibility of resident microbes to sulfide179. Sulfide production may become deleterious when the provision of organic sources of sulfur promotes growth of taurine and cysteine utilizing bacteria, increasing sulfide to pro-inflammatory and genotoxic concentrations. Taurine provided by bacterial deconjugation of taurocholic acid acts as a substrate for anaerobic respiration by B.

180 wadsworthia, generating genotoxic H2S . Once deconjugated, free primary bile acids are further metabolized by colonic bacteria to genotoxic and pro-inflammatory secondary bile acids. Specifically, the secondary bile acid, deoxycholic acid, acts as a tumor promoter, causing membrane perturbations leading to arachidonic acid release. 92

Mechanisms of Tumorigenesis in African American CRC Chapter 3

Arachadonic acid is converted by COX-2 and lipooxygenase to pro-inflammatory and pro-angiogenic prostaglandins and reactive oxygen species, damaging DNA and inhibiting DNA repair enzymes180. Accordingly, these data support the hypothesis that differences in sulfidogenic bacteria between African Americans and NHWs may contribute to variations in CRC incidence between these two populations.

A meta-analysis of prospective cohorts revealed increased CRC incidence among persons who consume a diet high in red and processed meat50. Consistently, the present study observed a higher intake of dietary fat and protein in African Americans, who are at higher risk of CRC development compared with NHWs. A Western diet is thought to be a major contributor to CRC incidence variance in different countries. For example, rural

South African blacks, who consume a diet low in fat and animal protein have a negligible risk of CRC compared to African Americans and American NHWs, who on average consume a diet high in animal products166. A recent comparison of African American and rural South African blacks showed significantly higher levels of both primary and secondary bile acids in African Americans, as well as reciprocal changes in secondary bile acids and colonic microbiota after diet exchange166. Additionally, there are rapid changes in “bile-tolerant” organisms upon consumption of a diet rich in fat and animal protein, including two genera abundant in this study, namely, Alistipes and Bilophila181.

Notably, species of Cetobacterium, a taxon observed to be significant in African

American CRC, are also bile tolerant182. Similarly, B. wadsworthia was significantly more abundant in mice fed a high milk fat diet and increased severity of symptoms in

DSS induced colitis183. A high fat diet, rich in the sulfur-containing amino acids cysteine and taurine increases bile secretion, and shifts the taurine:glycine bile acid ratio towards

Mechanisms of Tumorigenesis in African American CRC Chapter 3 taurine conjugation184.

A key advantage of the present study is that recruited subjects represent an urban

American population of average to low-income persons with predominantly high school or some college education, enabling a more generalizable examination of health and dietary disparities than performed previously159,182,185,186. Additionally epithelial cell function is affected to a greater extent by mucosally-associated microbes187–189 as measured herein, functional differences have been observed between mucosal and luminal microbiota190, and mucosal but not fecal microbiota may discriminate between disease status and health.191

Our study is limited by use of the BBFFQ to measure habitual dietary intake of subjects. It is well established that diet assessment methods which rely on self-report are prone to underreporting of nutrient intake due to socially-desirable responses and recall bias 192,193. The BBFFQ has a reduced food list (only 70 foods/beverages) and thus inherently will result in energy and macronutrient estimates lower than actual intake.

With this in mind, nutrient density (per 1000 kcals) variables were created for dietary components of interest and have been suggested to more closely correlate with “true” intake versus estimates of absolute intake194. Given the limitations of self-report diet assessment methods, to best understand the impact of diet composition in the manipulation of bile acid ratios and microbial metabolites, controlled feeding studies are warranted. Additional limitations include lack of information on probiotic and antibiotic use by subjects. Metabolites and histologic biomarkers were not examined in the present study; these variables should be evaluated in future studies.

Our analysis revealed that race was the strongest variable associated with

Mechanisms of Tumorigenesis in African American CRC Chapter 3 differences in sulfidogenic bacteria in African American compared to NHWs, and that dietary differences had relatively small effects; consequently, we propose some other latent variable explains this difference. Identifying that latent variable is an important future direction. In the meantime, it is clear a greater understanding of sulfidogenic bacteria associated with the colonic mucosa and development of novel CRC prediction models using key sulfidogenic bacteria may provide substantial knowledge for prevention and early detection of CRC particularly in the African American population.

Mechanisms of Tumorigenesis in African American CRC

Chapter 4

Lack of APC somatic mutation is associated with early-onset colorectal cancer in African Americans

Originally published in Carcinogenesis (Permissions can be found in Appendix D) Xicola RM, Manojlovic Z, Augustus GJ, et al. Lack of APC somatic mutation is associated with early-onset colorectal cancer in African Americans. Carcinogenesis. 2018;39(11):1331-1341. doi:10.1093/carcin/bgy122

Mechanisms of Tumorigenesis in African American CRC Chapter 4

Abstract

Background & Objective African Americans have higher incidence and mortality rates of colorectal cancer (CRC) compared with other US populations. They present with more right-sided, microsatellite stable disease and are diagnosed at earlier ages compared with non-Hispanic Whites (NHWs).

Methods To gain insight into these trends, we conducted exome sequencing (n = 45), copy number (n = 33) and methylation analysis (n = 11) of microsatellite stable African

American CRCs. Results were compared with data from The Cancer Genome Atlas

(TCGA).

Results Two of the 45 tumors contained POLE mutations. In the remaining 43 tumors, only 27 (63%) contained loss-of-function mutations in APC compared with 80% of

TCGA NHW CRCs. APC-mutation-negative CRCs were associated with an earlier onset of CRC (P = 0.01). They were also associated with lower overall mutation burden, fewer copy number variants and a DNA methylation signature that was distinct from the CpG island methylator phenotype characterized in microsatellite unstable disease. Three of the

APC-mutation-negative CRCs had loss-of-function mutations in BCL9L. Mutations in driver genes identified by TCGA exome analysis were less frequent in African American

CRC cases than TCGA NHWs. Genes that regulate the WNT signaling pathway, including SOX9, GATA6, TET1, GLIS1 and FAT1, were differentially hypermethylated in APC-mutation-negative CRCs, suggesting a novel mechanism for cancer development in these tumors.

Mechanisms of Tumorigenesis in African American CRC Chapter 4

Conclusions In summary, we have identified a subtype of CRC that is associated with younger age of diagnosis, lack of APC mutation, microsatellite and chromosome stability, lower mutation burden and distinctive methylation changes.

Mechanisms of Tumorigenesis in African American CRC Chapter 4

Introduction

Colorectal cancer (CRC) is the third most common cancer in both men and women in the US and the second most common cause of cancer-related deaths 149.

African Americans bear a disproportionate burden with an incidence that is approximately 20% higher than in Non-Hispanic Whites (NHWs) and an even larger difference in mortality 195. Furthermore, African Americans are more often diagnosed with CRCs at an earlier age, which a decade ago prompted the recommendation of CRC screening for average risk African Americans to be started at age 45 instead of at age 506.

The early-onset CRC seen in African Americans is more associated with distal location and toxic exposures 67,75.

Other biological differences have been described comparing CRCs arising in

African Americans compared to NHWs. African Americans have a greater proportion of proximal cancers 196,197. Proximal CRCs have a higher percentage of microsatellite instability (MSI), increased gene promoter hypermethylation, and increased gene mutation rates in comparison to distal cancers 198. Interestingly, the excess of proximal cancers in African Americans in comparison to NHWs is mostly made of microsatellite stable tumors that commonly present with lymphocytic infiltrate and are less often associated with toxic exposures or a higher BMI compared to the distal cancers 75. In terms of hereditary risk, some CRC risk alleles are shared between NHWs and African

Americans but others are population-specific 19,20,23,199.

Large exome sequencing studies have been performed on CRCs, but they have included few tumors from African American patients 198,200. One recent study sought to characterize somatic mutations in a significant number of microsatellite stable (MSS),

Mechanisms of Tumorigenesis in African American CRC Chapter 4 non-hypermutated CRCs from African American patients 86. In that study, although genes that are commonly mutated in NHW CRCs were also found mutated in African American

CRCs, mutations in 15 distinct genes were identified that were associated with CRCs in

African Americans but had not been previously associated with CRC in NHWs. Some of these somatic mutations, such as those in ephrin type A receptor 6 (EPHA6), foliculin

(FLCN), and 5-hydroxytryptamine (serotonin) receptor 1F (HTR1F), were detected exclusively in African American CRCs.

In order to further characterize tumorigenic mechanisms in African American

CRCs and better understand biological and clinical differences between CRCs that arise in African Americans and NHWs, we analyzed the somatic mutational, copy number variation, and methylation profiles in a group of African American patients from a series of newly diagnosed CRC cases.

Materials and methods

Ascertainment, recruitment, and biospecimen collection

The Chicago Colorectal Cancer Consortium (CCCC) ascertained incident CRC cases from surgery and endoscopy units and healthy controls undergoing routine screening colonoscopy from five large Chicago medical centers, including University of

Illinois Hospital and Health Sciences System, Jesse Brown Veterans Administration,

John H. Stroger Hospital of Cook County, University of Chicago Medicine, and Rush

University Medical Center, over a two-year period (2011-2012). Biological specimens and patient information were collected as described previously 75. In the present study, only prospectively ascertained African American patients with a diagnosis of adenocarcinoma of the colon or rectum were included (n=54). Patients with CRC 100

Mechanisms of Tumorigenesis in African American CRC Chapter 4 recurrence, inflammatory bowel disease, or non-adenocarcinoma tumors were excluded.

All patients in the study provided written informed consent. The parent study received approval for human subjects research from the institutional review boards of each participating medical center and the parent protocol was administered by the institutional review board at University of Illinois Hospital and Health Sciences System (2010-0168).

MSI was determined in paired DNA samples from tumor and uninvolved tissue as previously described 201. To estimate percentage of West African ancestry, a panel of

1000 ancestry informative markers was genotyped and analyzed as previously described202.

DNA sequence analysis

Sequence analysis was performed as previously described 203. Briefly, genomic

DNA (1 microgram) from tumor and normal samples was sheared employing the Covaris system (Covaris, Inc., Woburn, MA) to target fragment sizes of 150-200 bp. Whole exome sequencing libraries were created using the TruSeq DNA Sample Prep Kit A and

TruSeq Exome Kit (Illumina, Inc.) using the manufacturer’s recommendations. Libraries were subsequently sequenced using Illumina TruSeq SBS v3 chemistry, to generate 83 cycles x 7 x 83 cycles run on the Illumina HiSeq 2000 system. All sequencing reads were converted to industry standard FASTQ files using the Bcl Conversion and

Demultiplexing tool (Illumina, Inc). Population genotype PCA was performed using SNP

& Variation Suite v8.4.1 (Golden Helix, Inc., Bozeman, MT, www.goldenhelix.com) tool.

101

Mechanisms of Tumorigenesis in African American CRC Chapter 4

Sequencing reads were aligned to the GRCh37 reference genome using the MEM module of BWA v0.7.8 204 and SAMTOOLS v0.1.19 to produce BAM files. After alignment, the base quality scores were recalibrated and joint insertion/deletion realignment was performed on the BAM files using GATK v3.1-1 205. Duplicate read pairs were marked using PICARD v1.111205. Final BAM files were then used to identify germline and somatic events. Germline SNP and insertion/deletions were identified using

GATK HaplotypeCaller in the constitutional sample.

SNVs and insertions/deletions were identified using STRELKA somatic variant caller 206. To identify cancer drivers, analysis with MutSigCV (Mutation Significance) was performed 207 with set perimeters of q <0.1 and p <0.05 to identify significant genes.

Mutational Signature Analysis Tool (https://bitbucket.org/jtr4v/analysis-of-mutational- signatures) was used to determine mutation signatures.

Copy number analysis

Copy number analysis on CCCC samples was conducted using the Affymetrix

CytoScan HD array carried out in the University of Illinois at Chicago Genomics Core according to the manufacturer’s instructions. CEL files were processed using Affymetrix

Chromosome Analysis Suite (Version 3.0.0.42) using default quality control settings.

TCGA CEL files were obtained from the Genomic Data Commons. Circular Binary

Segmentation was run on samples using default settings 208. Cumulative copy number variation that exceeded a length threshold of 50% of a chromosome arm was recorded as an arm gain or loss, as this was the method adopted by the TCGA. Visualization of genome-wide copy number alterations was completed using Rawcopy (Version 1.0) with

102

Mechanisms of Tumorigenesis in African American CRC Chapter 4 default settings. Chromosome-arm gains and losses were compared to frequencies reported by the TCGA by Fisher’s exact test and adjustment for multiple testing was made by the Bonferroni correction.

Methylation analysis

DNA methylation arrays were processed using the Infinium Human Methylation

450 BeadChip Kit 209,210 carried out in the Northwestern University Center for Genomic

Medicine. Array data was processed using the ‘minfi’ package 211 and the ‘noob’ preprocessing scheme 212. We then employed the DMRcate procedure of Peters 213 to identify statistically significant differences in regional DNA methylation. DMRs were mapped to chromatin states using ChromHMM 214. Infinium Human Methylation 450

BeadChip Kit DNA methylation data for TCGA samples were downloaded from the

Genomic Data Commons and preprocessed as described above. APC mutation status was obtained from Mutect2 MAF files downloaded from GDC using TCGAbiolinks (Version

2.7.6). All NHW APC mutation-negative samples (n=15), a random subset of NHW APC mutation-positive samples (n=29), and all available NHW normal samples (n=8) from the

TCGA were used for subsequent analysis. Heatmaps were generated in R (version 3.4.3) using the ComplexHeatmap package (version 1.12.0).

Statistical analysis

Statistical tests of continuous variables were performed by the t-test and of categorical variables by the Fisher exact test or chi square test, as appropriate. Wilcoxon non-parametric test was used for comparison of age at diagnosis between groups. To

103

Mechanisms of Tumorigenesis in African American CRC Chapter 4 make comparisons with the TCGA exome sequence data, we used processed mutation data from 189 non-hypermutable CRCs downloaded from http://cbioportal.org 215,216, from which three were excluded based on failure to cluster with European populations in the PCA analysis. Statistical software packages such as R (https://www.r-project.org;

Versions 3.1.1 & 3.3.2) and GraphPad Prism 7 (GraphPad Software, Inc.) were used to perform statistical analysis.

Results

To define the somatic mutational spectrum in African American CRCs, we conducted a whole exome analysis of selected tumors from the CCCC. Tumor samples collected fresh by the CCCC were subjected to MSI analysis 75. We excluded MSI tumors from the analysis and performed exome capture and DNA sequencing on 45 tumor- normal pairs. Sequence depth was greater than 100 genome equivalents on average in tumor DNA and 30 genome equivalents in normal DNA (Table 4.1). In the CCCC cohort, race was assigned by self-report. Mean West African ancestry was over 73% as assessed using genotype data from ancestry informative markers (Table 4.2A & B). We further confirmed genetic ancestry using principal component analysis (PCA) of the exome sequence data 217,218. All the CCCC African American CRC cases clustered with African- ancestry populations (Figure 4.1).

In CRC_46 and CRC_08, there were 4,431 single nucleotide variants (SNVs) and

2,923 SNVs per sample, respectively. CRC_46 and CRC_08 contained mutations in the proof-reading domain of POLE, namely V411L in case CRC_46, which is in the active site of the exonuclease domain, and S459F in case CRC_08, which is in the RNAse H- like domain. Both mutations have been previously associated with hypermutation in 104

Mechanisms of Tumorigenesis in African American CRC Chapter 4

Table 4.1 Sequencing depth, tumor cellularity, and total number of sequence variants of the colorectal cancers analyzed in this study.

Sample Sequencing Depth Tumor Cellularity Estimate Total mutationsA (%) CRC_01 142.87 79.1 194 CRC_02 83.29 68.3 217 CRC_03 72.94 72.5 156 CRC_06 32.66 67.1 157 CRC_08 67.63 77.3 2895 CRC_09 73.60 79.3 47 CRC_10 50.58 75.8 36 CRC_11 33.00 78.7 157 CRC_12 117.71 81.2 46 CRC_14 82.84 59.9 164 CRC_16 62.24 82.9 166 CRC_17 111.57 68.3 144 CRC_19 76.43 73.2 111 CRC_20 42.23 71.9 103 CRC_21 75.40 71.9 162 CRC_22 46.36 78.7 136 CRC_23 62.91 74.1 170 CRC_24 22.10 64.5 99 CRC_26 101.72 72.3 159 CRC_27 90.21 78.7 129 CRC_28 103.30 78.9 330 CRC_29 87.53 78.3 188 CRC_30 111.15 72.1 14 CRC_31 41.82 69.3 127 CRC_33 17.50 77.3 134 CRC_34 27.40 70.4 127 CRC_35 95.78 68.3 318 CRC_36 53.89 70.1 192 CRC_37 52.58 78.7 187 CRC_38 50.72 68.3 133 CRC_41 14.00 68.3 145 CRC_42 41.81 74.9 222 CRC_45 57.70 73.3 300 CRC_46 69.25 71.2 4306 CRC_47 54.88 86 1110 CRC_48 33.01 58.9 20

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CRC_49 88.23 66.4 39 CRC_51 78.65 74.9 206 CRC_52 103.88 65.8 324 CRC_53 53.69 59.8 257 CRC_54 101.12 62.9 98 CRC_56 107.22 70.7 238 CRC_57 82.27 64.5 191 CRC_58 104.28 68.3 103 CRC_59 104.07 66.5 180

AMutations included single nucleotide variants and small insertions and deletions.

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Table 4.2 Clinical, epidemiological, and molecular data for each individual colorectal cancer case

Sample Sex Age WAA FDRca<60 PreCancers Location Stage Grade BMI Exercise Smoking (%) CRC_01 M 82 99 No Sigmoid IIA Moderate 27 No Ever CRC_02 M 64 85.5 Yes Lu @61, Rectum IIIC NA 33.9 No Ever Pr @56 CRC_03 F 52 93.6 No Splenic flexure IIA Moderate 26.3 Yes Never CRC_06 F 38 ND Yes Descending IV Moderate 40.1 No Ever CRC_09 M 52 69.1 Yes Rectum IIA NA 24.1 No Never CRC_10 F 45 77.8 No Cecum IVB Moderate 29.8 No Ever CRC_11 M 46 ND No Cecum IIIC Low 24.1 No Ever CRC_12 M 38 76.6 Yes Rectum IIC Moderate 20.6 No Ever CRC_14 M 65 72.6 No Rectum IIA Moderate 21.9 Yes Never CRC_16 M 48 82.7 No Recto-sigmoid IIIB Low 21.9 Yes Never CRC_17 M 70 80.2 No Splenic flexure IIA Low 32.7 No Ever CRC_19 F 51 48 No UtCS @44 Recto-sigmoid IIA Low 34.8 No Ever CRC_20 M 51 92 Yes Rectum I Moderate 29 No Ever CRC_21 M 56 ND No Recto-sigmoid IIIB Moderate 26.1 No Ever CRC_22 F 56 71 No Rectum IIA Low 26.5 No Never CRC_23 M 46 19 Yes Rectum IV Moderate 31.9 Yes Never CRC_24 F 60 68 No Sigmoid IIIB Moderate 24.4 Yes Ever CRC_26 M 70 95.9 No Sigmoid I Low 30.1 Yes Never CRC_27 F 69 88 No Sigmoid 0 NA 29.7 No Ever CRC_28 F 43 80.9 No Ascending IIIC Low 27.1 No Never CRC_29 F 44 73.7 No Ov @40 Sigmoid IIA Low 29.8 No Ever CRC_30 F 71 75 Yes Br @68 Recto-sigmoid IIIC High 43 No Ever CRC_31 M 85 81.4 Yes Sigmoid NA Moderate 22.1 No Ever

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CRC_33 F 29 ND No Appendix IIIC High 35.5 No Never CRC_34 M 65 66.3 No Sigmoid IIC Moderate 25.1 No Ever CRC_35 M 77 64 No Splenic flexure I Moderate 36.6 No Ever CRC_36 M 66 80.8 No Sigmoid IV NA 22.3 No Ever CRC_37 M 57 77.8 No Recto-sigmoid IV Low 24.9 No Ever CRC_38 M 50 89.6 Yes Sigmoid IV Moderate 32.2 No Never CRC_41 F 77 77.7 Yes Cecum IV High 27.6 No Never CRC_42 F 42 93.1 Yes Sigmoid IV Moderate 29.2 No Never CRC_45 M 63 94.8 Yes Sigmoid IVA Moderate 17.8 No Ever CRC_47 M 49 81.3 No Sigmoid 0 Low 43 No Ever CRC_48 M 56 ND No Cecum IIIB Moderate 26.5 No Ever CRC_49 F 56 83.9 Yes Br @46 Ascending IIA Moderate 26.7 No Never CRC_51 F 69 29 Yes R IV NA 20.5 No Ever CRC_52 F 62 78 No Ileocecal valve IIIB Moderate 25.9 No Never CRC_53 M 75 ND Yes Cecum I Low 24.9 Yes Ever CRC_54 M 60 46 No Hepatic flexure IV Moderate 19 No Ever CRC_56 F 61 98 No Ascending IIIB Moderate 33.1 Yes Never CRC_57 M 60 79.3 Yes Cecum I Low 31.1 No Ever CRC_58 M 63 97.1 No Ascending IIA Low 24.3 No Ever CRC_59 M 62 96.5 No Transverse IIA Low 29.5 No Ever

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Table 4.2B Clinical, epidemiological, and molecular data for each individual colorectal cancer case.

Sample Drinking Education Income Arm Arm Total APC TP53 KRAS gainA lossA mutations CRC_01 Ever College Graduate NA ND ND 194 p.R876* None p.A146T CRC_02 Never College Graduate < $25,000 4 11 217 p.R1450*, p.R282W p.G12D p.N1473I CRC_03 Never College Graduate > $75,000 2 7 156 p.R232*, None p.G12D 3’-SS DEL1 CRC_06 Never Some College < $25,000 ND ND 157 None p.G245S p.G12V CRC_09 Ever Some College < $25,000 0 0 47 None None None CRC_10 Never NA NA 8 1 36 None None None CRC_11 Ever Some College $25,000 - 2 0 157 p.Y935*, None p.G12D $75,000 p.R1450* CRC_12 Ever High School $25,000 - ND ND 46 None None None $75,000 CRC_14 Ever High School $25,000 - 3 7 164 None p.R175H None $75,000 CRC_16 Never High School < $25,000 2 4 166 p.R232* p.G245S p.G12D CRC_17 Never High School < $25,000 5 6 144 p.S1327* None p.G13D CRC_19 Never Some College $25,000 - 8 10 111 None None None $75,000 CRC_20 Ever High School < $25,000 2 4 103 None p.H179Y None CRC_21 Ever Some College < $25,000 3 9 162 p.1224A_1225Kfs p.G245S None CRC_22 Never High School < $25,000 0 0 136 None p.R342* None CRC_23 Ever High School < $25,000 1 0 170 p.1394S_1395Ffs p.R175H None CRC_24 Never High School < $25,000 2 5 99 p.1026Y_1027Sfs p.R282W None

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CRC_26 Ever Post-Graduate $25,000 - 0 0 159 p.E1295* None p.G13D $75,000 CRC_27 Ever Elementary School $25,000 - 0 3 129 p.401R_402Efs, None None $75,000 p.1363S_1364Gfs CRC_28 Ever High School $25,000 - 10 1 330 p.R554*, None p.G121 $75,000 p.1436K_1437Tfs V CRC_29 Ever High School < $25,000 1 5 188 None None p.G12S CRC_30 Never High School < $25,000 ND ND 14 None None None CRC_31 Ever Middle School < $25,000 ND ND 127 p.Q1035* p.R248W p.G12V CRC_33 Never High School < $25,000 2 0 134 None 5’-SS p.G12D SNV3 CRC_34 Ever High School < $25,000 7 13 127 p.Q238* 5’-SS None SNV3 CRC_35 Ever High School $25,000 - 1 5 318 p.R216*, p.R175H None $75,000 p.Q1378* CRC_36 Ever High School < $25,000 2 16 192 p.Q1406* p.R196* p.G12V CRC_37 Ever High School < $25,000 ND ND 187 p.R302*, p.R306* None p.1410S_1411Gfs CRC_38 Ever High School < $25,000 4 10 133 p.Q1367* 5’-SS None SNV3 CRC_41 Never Some College < $25,000 4 4 145 p.Q1291*, p.P250L p.G12D p.1573I_1574Lfs CRC_42 Never High School < $25,000 8 6 222 p.R302*, p.1450* p.R248Q p.G12A

CRC_45 Ever Some College < $25,000 8 13 300 p.S1327* p.225G_2 None 26Sfs CRC_47 Ever High School < $25,000 ND ND 1110 None None None CRC_48 Ever Middle School < $25,000 0 0 20 None None None CRC_49 Never Some College < $25,000 ND ND 39 None None None

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CRC_51 Ever High School < $25,000 ND ND 206 p.Q1228*, None p.G13R p.R1450* CRC_52 Never High School < $25,000 11 9 324 None p.P278T p.G12D CRC_53 Ever High School < $25,000 0 2 257 p.775I_777Nfs, p.K132E p.G13D p.R1450* CRC_54 Ever High School < $25,000 0 0 98 None p.R282W p.G12V CRC_56 Ever High School < $25,000 ND ND 238 p.R332*, 5’-SS p.G12D p.1572E_1573Ifs SNV3 CRC_57 Never High School $25,000 - 0 1 191 p.R904*, p.1450* None p.G13D $75,000 CRC_58 Ever Some College < $25,000 4 1 103 p.E1322* None None CRC_59 Ever High School < $25,000 9 9 180 p.Q1291*, 5’-SS p.G12D p.1290Q_1291Tfs SNV3 Body mass index, BMI; breast, Br; copy number variant, CNV; no data, ND; first-degree relative with cancer, FDRca; female, F; male, M; ovarian, Ov; prostate, Pr; uterine carcinosarcoma, UtCS; West African ancestry, WAA.

AThe number of chromosome arms gained or lost as determined by the Affymetrix CytoScan data.

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Figure 4.1 Principal coordinates analysis of exome sequence variation of the Chicago colorectal cancer cases and continental reference populations from the 1000 genomes.

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CRC 198,219. The frequency of MSI-negative, POLE-associated hypermutable CRCs we detected in the CCCC series (2/45 = 4.4%) was not statistically different from the frequency reported by the TCGA (7/165 = 4.2%) and it was similar to the frequency reported for the Case Western series (2/41 = 4.9%) 86. For subsequent analyses, these two tumors were removed. In the remaining tumors, the average number of SNVs per tumor was 180.

Using the list of somatic mutations generated by STRELKA, we carried out mutation analysis using MutSig and ranked potential cancer driver genes based on the q value <0.1

(Figure 4.2). Each of the 32 genes in Figure 4.2 had at least three non-silent mutations in the CCCC African American CRC series. Seven of the 32 genes in Figure 4.2 are well established CRC driver genes, including APC, TP53, KRAS, SMAD4, FBXW7, PIK3CA, and ATM. At least two novel genes represent reasonable driver gene candidates, including

PREX1, which is a guanine nucleotide exchange factor for RAC that has been previously studied in breast and prostate cancer and in melanoma 220–222, and BCL9L (see below).

We matched the MutSig output with their rank by FLAGS (FrequentLy mutAted GeneS) in public exomes 223 (available in the supplementary documentation of Xicola et al82) and observed that the mutations identified in FLG, HRNR, AHNAK2, and RP1L1 are very likely miscalled due to bioinformatics challenges with gene families. The mutations in

CPAMD8, MUC4, TCHH, and LAMC3 may also be questioned for the same reason even though these genes did not make the top 100 on the FLAGS list. We also found many of the specific mutations in these eight genes, which were called as somatic mutations, in the germline exomes of the ExAc database, suggesting a general problem with mutation calling for these genes. The complete list of somatic mutations detected in this sampling

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Figure 4.2 Candidate driver genes in African American colorectal cancers. The top panel shows the number of single nucleotide variants in each of the 43 tumors included in the analysis, coded by mutation type. The bottom panel shows the 32 genes in order of q value rank up to the threshold 0.1, matching the sample to the mutation, coded by mutation type.

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 of tumors is available in the supplementary documentation of Xicola et al82.

APC mutation-negative tumors are associated with early-onset CRC

Mutations in the three most commonly mutated genes in CRC, namely APC,

TP53, and KRAS were significantly associated with CRC in the MutSig analysis

(p<0.05). While the frequencies of TP53 and KRAS mutations in African American CRCs were not statistically different from those in NHW CRCs, the frequency of APC mutations in African American CRCs was 63% (27 of 43), whereas in the TCGA NHWs it was 80% (151 of 186; p=0.03; calculated from TCGA data based on 186 non- hypermutated CRCs in NHWs; Figure 4.3A). Because mutations in APC are less frequent in right-sided CRCs even taking into account MSI status 224–226 and African Americans have a greater proportion of MSS right-sided CRCs 75, we considered the possibility that the difference in APC mutation frequency could be explained by the proportion of right- sided CRCs in African Americans. In the present series, there were 16 right-sided and 27 left-sided African American CRCs; 7 of 16 (0.56 of total) right-sided CRCs had at least one APC mutation whereas 18 of 27 (0.67 of total) of the left-sided CRC had at least one

APC mutation (Table 4.3). Thus, the frequency of APC mutations in the left-sided CRCs is still lower than what is reported in the TCGA.

The low frequency of APC mutations raised the question whether the APC mutation-negative tumors are associated with a distinct tumor type (Table 4.3). Gender, tumor location by side, tumor stage, histological grade, family history of cancer, and epidemiological features were not different in the APC mutation-positive and APC mutation-negative tumors. On the other hand, the median mutation frequencies were

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Table 4.3 Comparison of the clinical-pathological, epidemiological, and molecular features of African American colorectal cancer cases with and without an APC mutation.

Feature All cases APC mutation- APC mutation- P valueA (n=43) positive (n=27) negative (n=16) Clinical-pathological Gender, males/females 26/17 19/8 7/9 0.11 Age at diagnosis, median 60 63 51.5 0.009 Percent WAAB, mean (SD) 77 80 73 0.019 FDRC with cancer <60 (%) 16 (37) 10 (37) 6 (38) 1 Cases with a previous cancer (%) 5 (12) 1 (4) 4 (25) 0.06 Tumor location (R/L) 15/28 9/18 6/10 1 TNM stageD 20/22 11/15 9/7 0.52 Grade, Low+Moderate/High 26/12 13/10 13/2 0.08 Cytogenetic (stable/unstable)E 5/28 1/21 4/7 0.03 Epidemiological Body mass index, median 27 27 28 0.43 Frequent exerciseF (%) 8 (19) 7 (26) 1 (6) 0.22 Smoking, ever/never 27/15 17/9 10/6 1 Drinking, ever/never 20/16 13/8 7/8 0.49 High school educationG (%) 26 (60) 16 (59) 10 (66) 0.75 Household income (<$25,000) (%) 31 (72) 19 (73) 12 (80) 0.72 MolecularH Total SNVs, median 157 170 107 0.006 TP53 mutation (%) 24 (56) 17 (63) 7 (44) 0.34 KRAS mutation (%) 22 (51) 17 (63) 5 (31) 0.06 BCL9L mutation (%) 3 (7) 0 (0) 3 (19) 0.04 C2ORF78 mutation (%) 3 (7) 0 (0) 3(19) 0.04

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AP-values were calculated for APC mutation-positive and APC mutation-negative comparisons. Fisher exact test was performed for comparisons of categorical variables and Mann-Whitney for comparisons of continuous variables. Only non-hypermutable tumors were analyzed.

BPercent West African ancestry (WAA) was estimated from ancestry informative markers using an algorithm implemented in

STRUCTURE, and significance was tested by t-test. Ancestry informative markers were unavailable from 37 cases.

CFDR, first-degree relative with a cancer diagnosed before age 60.

DComparison of T0+TI+TII and TIII+TIV. Staging unavailable from two tumors.

EChromosome stability was defined as no chromosome arms gained or lost in the tumor as determined by analysis of Affymetrix

CytoScan HD array data (n=33).

FFrequent exercise was defined as three or more exercise sessions per week; does not take into account occupation-associated physical activity.

GNumber of cases in which completion of high school was highest education level.

HComparisons of mutation frequencies (APC mutation-positive vs APC mutation-negative) were performed on the 32 genes identified by q<0.1 in the MutSig analysis. The P values were not adjusted for multiple testing; see text. The complete set of statistical comparisons is provided in Table 4.1.

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 significantly different (170 in APC mutation-positive vs. 107 in APC mutation-negative; p=0.006, Mann-Whitney test). In addition, the APC mutation-negative tumors were more likely to be classified chromosomally stable (see below). Importantly, APC-negative tumors were associated with younger age of diagnosis (p=0.02). We also observed a trend for previous history of cancer in the APC-negative tumors (p=0.06). Whilst the frequency of TP53 mutations were similar in the two groups (17 of 27 vs. 7 of 16, respectively; p=0.34), KRAS mutations trended toward lower frequency in the APC mutation-negative group (17 of 27 vs. 5 of 16; p=0.06).

Because we found APC-negative tumors were associated with younger age of diagnosis, we investigated whether this association can be detected in TCGA NHW

CRCs. From the cbioportal server, we identified 219 NHW cases with a non- hypermutated tumor. Of these 219 cases, 181 tumors were APC-mutation positive and 38 were APC-mutation negative. The median age for the APC mutation-positive group was

68 years of age, and for the APC mutation-negative group it was 54.5. The association between APC-mutation negative tumors and early-onset CRC was significant (p<10-5).

BCL9L in the MutSig q<0.1 group was more frequently mutated than expected in the APC mutation-negative tumors (p=0.05; Figure 4.2). The cases CRC_06, CRC_29, and CRC_49 exhibited somatic mutations in BCL9L. These tumors contained the nonsense mutations Q654*, observed once, and R415*, observed twice. All three cases were female, with an average age at diagnosis of 46, and they had a striking family history of cancer. The mother and aunt of CRC_06 had breast cancer in their 40s.

CRC_29 had a previous ovarian cancer and her aunt had a uterine cancer in her 40s.

CRC_49 had a preceding breast cancer at 46 and her mother a breast cancer at 48. No

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(BRCA1, BRCA2, PALB2, etc.), nor in BCL9L itself were identified in these three cases; thus, the observation of family history of cancer and its possible connection to somatic mutations in BCL9L remains to be explained. Cases CRC_29 and CRC_49 had co- occurring mutations in BRAF — p.G469E and p.K601E, respectively — both of which activate the kinase domain. In the non-hypermutated, NHW TCGA series, BCL9L mutation was present in 2.6% of tumors, but it was not associated with APC mutation- negative tumors.

Mutations in C2ORF78 were also more frequent than expected in the APC mutation-negative group (p=0.05). The non-silent mutation frequency in colorectal cancer in TCGA was 0.9%, which is not significantly associated with CRC. A possible role for C2ORF78 in colon carcinogenesis needs to be further investigated.

Under-representation of known driver genes in African American CRCs

We next considered the other most frequently mutated genes identified in the

MutSig analysis by the TCGA 198, which, except for TTN, are considered to be driver genes for CRC (Figure 4.3A). In the African American CRCs, zero non-silent mutations were identified in ACVR1B, EDNRB, FAM123B, GPC6, KIAA1804, NRAS, SMAD2, and

SOX9; only one mutation in CTNNB1; and two in TCF7L2. In contrast, in non- hypermutated, NHW CRCs from the TCGA, there were a total of 101 mutations in these genes. From the tumor-specific perspective, we found that only 3 African American

CRCs of 43 tested (7%) carried a non-silent somatic mutation in at least 1 these 10 genes, whereas 79 NHW CRCs of 186 (41.8%) tested did. The under-representation of known

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Figure 4.3 The contribution of known cancer-associated genes to African American colorectal cancers. (A) Under-representation of mutations in the most frequently mutated

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 colorectal cancer driver genes identified in TCGA. (B) Over-representation of cancer- associated genes.

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 driver genes predominantly affects the genes with lower frequencies of mutations, as the frequency of non-silent mutations at TP53, KRAS, FBWX7, SMAD4, and TTN were comparable in African American and NHW CRCs. To rule out inadequate sequence coverage as a trivial explanation for the observed difference, we manually checked the numbers of reads for each exon of each of these genes to confirm that there were at least

30 sequencing reads in each.

To determine whether other driver genes may compensate for the under- representation of TCGA driver genes, we identified all genes mutated in African

American CRCs that were two-fold or greater in frequency compared to non- hypermutated NHW CRCs in the TCGA, removing FLAGs genes that are frequently identified as mutated for technical reasons 223 and filtering the gene list using the merged lists of CRC-associated genes from the COSMIC and the Atlas of Genetics and

Cytogenetics databases (Figure 4.3B). Five of the 13 genes that passed this screen are significantly associated with African American CRCs, including CHD5, FLT3, MUC4,

SMO, and TOP1. CHD5 was one of the genes of interest identified in the Case Western study 86 and it has been implicated in cancer development in methylation studies88,91.

None of the three oncogenic mutations in BRAF were V600E, but it is important to point out that these mutations are occurring in the context of MSS tumors. Mutations in AXIN2 are also overrepresented in African American CRCs. These data underscore the role of alternative driver genes operating in African American CRCs.

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Copy number variation in African American CRCs

To examine the question whether differences in mutational mechanisms might underpin differences in APC mutation-negative and mutation-positive tumors, we analyzed mutagenesis patterns and copy number variation. We compared the frequencies of mutant triplets in exome sequence data from CCCC and TCGA CRCs (Figure 4.4). As expected, hypermutable tumors with mutations of the proof-reading exonuclease domain had a predominance of TCT to TAT and TCG to TTG mutations.

Microsatellite stable tumors had a predominance of C to T mutations in the CpG dinucleotide, reflecting a mutational process dominated by deamination of methylated cytosines. The frequencies of triplets in these two groups were indistinguishable in

African American compared to NHW CRCs. Mutational signatures in APC mutation- negative and mutation-positive tumors were also indistinguishable.

To address the question whether gross chromosomal abnormalities were different in APC mutation-negative and mutation-positive tumors, we performed a copy number analysis in CCCC African American CRCs using Affymetrix CytoScan HD array analysis on 33 that were co-analyzed by whole exome sequencing. We also compared results to TCGA data collected using the Affymetrix GenomeWide Human SNP Array

6.0. In African American CRCs, the most frequently gained chromosome arms (those occurring in >20% of CRCs) were 7p and q, 8p and q, 12p, 13q, and 20p and q (Table

4.4). The most frequently lost chromosomes arms (those occurring in >20% of CRCs) were 4p and q, 8p, 14q, 15q, 17p, 18p and q, 20p, 21q, and 22q. As expected, loss of heterozygosity was frequently observed at APC (5q), TP53 (17p), and SMAD4 (18q)

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Figure 4.4 Comparison of mutation types as a function of sequence context (triplets) in hypermutable (mutated for the polymerase epsilon proof-reading domain) and microsatellite stable colorectal cancers for African American colorectal cancer from the

CCCC and for non-Hispanic White colorectal cancer from the TCGA.

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Table 4.4 Frequency of chromosome arm gains and losses in colorectal cancers from African American and non-Hispanic Whites.

CCCC AA CRC TCGA NHW CRC Arm Gain Loss Gain Loss Gain Gain Loss Loss frequency frequency frequency frequency difference1 P value2 difference3 P value2 1p 0 0.15 0.03 0.19 0.03 0.6 0.04 0.81 1q 0.09 0.03 0.17 0.1 0.08 0.32 0.07 0.34 2p 0.09 0 0.08 0.03 -0.01 0.74 0.03 0.6 2q 0.12 0 0.1 0.03 -0.02 0.76 0.03 0.6 3p 0.03 0 0.06 0.09 0.03 1 0.09 0.09 3q 0 0 0.10 0.05 0.10 0.05 0.05 0.37 4p 0 0.3 0.01 0.25 0.01 1 -0.05 0.53 4q 0 0.33 0.04 0.24 0.04 0.61 -0.09 0.29 5p 0.06 0.09 0.14 0.10 0.08 0.28 0.01 1 5q 0 0.12 0.07 0.17 0.07 0.24 0.05 0.62 6p 0.15 0.09 0.14 0.07 -0.01 0.79 -0.02 0.72 6q 0.06 0.12 0.14 0.10 0.08 0.28 -0.02 0.76 7p 0.33 0 0.47 0.01 0.14 0.14 0.01 1 7q 0.27 0.06 0.41 0.01 0.14 0.18 0.05 0.1 8p 0 0.33 0.28 0.50 0.28 6x10-5 0.17 0.09 8q 0.12 0 0.46 0.12 0.34 1x10-4 0.12 0.03 9p 0.03 0.03 0.18 0.08 0.15 0.02 0.05 0.49 9q 0 0.03 0.15 0.09 0.15 0.01 0.06 0.33 10p 0 0.18 0.05 0.09 0.05 0.37 -0.09 0.12 10q 0 0.12 0.02 0.13 0.02 1 0.01 1 11p 0.15 0.03 0.09 0.09 -0.06 0.34 0.06 0.33 11q 0.09 0.06 0.07 0.11 -0.02 0.72 0.05 0.55 12p 0.12 0.03 0.21 0.09 0.09 0.35 0.06 0.33 12q 0.06 0.03 0.18 0.07 0.12 0.13 0.04 0.71 13q 0.27 0 0.56 0.04 0.29 0.003 0.04 0.61 14q 0.03 0.27 0.05 0.30 0.02 1 0.03 0.84

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15q 0 0.27 0.02 0.32 0.02 1 0.05 0.69 16p 0.18 0 0.18 0.05 <0.01 1 0.05 0.37 16q 0.15 0.03 0.18 0.06 0.03 0.81 0.03 1 17p 0.03 0.58 0.05 0.56 0.02 1 -0.02 1 17q 0.06 0.09 0.12 0.15 0.06 0.4 0.06 0.44 18p 0.03 0.49 0.09 0.61 0.06 0.33 0.13 0.19 18q 0 0.49 0.01 0.66 0.01 1 0.18 0.05 19p 0.09 0.03 0.11 0.04 0.02 1 0.01 1 19q 0.09 0 0.15 0.05 0.06 0.44 0.05 0.37 20p 0.24 0.12 0.58 0.32 0.34 3x10-4 0.20 0.02 20q 0.36 0 0.72 0.15 0.36 1x10-4 0.15 0.01 21q 0.03 0.15 0.02 0.22 -0.01 0.52 0.07 0.5 22q 0 0.24 0.03 0.26 0.03 0.60 0.02 1 Mean 0.086 0.126 0.167 0.17 0.081 <0.0001 0.044 <0.0001 African American, AA; Chicago Colorectal Cancer Consortium, CCCC; colorectal cancer, CRC; non-Hispanic white, NHW; The

Cancer Genome Atlas, TCGA.

1The fractional difference in chromosome arm gains, subtracting the frequency of arm gains in CCCC AA CRC cases from the frequency in TCGA NHW CRC cases. Gains in excess of 15% are shaded bold.

2P values were calculated by Fisher exact test. Values in bold are significant after Bonferroni correction.

3The fractional difference in chromosome arm losses, subtracting the frequency of arm losses in CCCC AA CRC cases from the frequency in TCGA NHW CRC cases. Losses in excess of 15% are shaded bold.

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(Table 4.5). Using the R package Rawcopy, we observed substantially lower levels of chromosome-arm gains and losses in the APC mutation-negative tumors compared to the

APC mutation-positive tumors (Figure 4.5A). Defining a chromosomally stable tumor as one that contains no chromosome arm gains or losses, we found that the APC mutation- negative CRCs were associated with chromosome stability (Table 4.3; p=0.03). The most frequent gains and losses in African American CRCs were the same as in NHWs (Figure

4.5B); however the average frequencies of chromosome-arm gains was 8.1% lower in

African American compared to NHW CRCs (p<0.0001), and for chromosome-arm losses it was 4.4% lower (p<0.0001). These lower frequencies are mostly likely explained by the lower levels of chromosome-arm gains and losses occurring in APC mutation- negative cancers.

Methylation patterns in APC mutation-negative vs. mutation-positive tumors

Because tumor mutation burden was lower in APC mutation-negative tumors, we investigated whether distinct epigenetic mechanisms operate as drivers of carcinogenesis in these tumors. Illumina Infinium Human Methylation 450 BeadChip data from matched tumor and normal samples were available from a previous study of right-sided CRC cases. This previous study included 11 of the cases studied here—5 APC mutation- negative and 6 APC mutation-positive tumors. Tumor-specific DNA methylation changes were identified, revealing 5,923 differentially methylated regions (DMRs)(Figure 4.6A), of which 3,596 (60%) were wider than one nucleosome footprint (200bp) and 4,471

(75%) overlapped regions of tumor-specific hypermethylation. APC mutation-positive tumors were broadly characterized by genome-wide hypomethylation with focal

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Table 4.5 Copy number changes and mutations in the four most frequently altered colorectal cancer driver genes.

APC TP53 KRAS SMAD4 Case ID CNa Mutation CNa Mutation CN Mutation CN Mutation

CRC_02 2LOH p.R1450*, p.N1473I 1 p.R282W 2 p.G12D 1 p.G419V CRC_03 2LOH p.R232*, 3’-SS DELb 1 None 2 p.G12D 2 None CRC_09 2 None 2 None 2 None 1 None CRC_10 2 None 2 None 2 None 2 None CRC_11 2 p.Y935*, p.R1450* 2 None 2 p.G12D 1 None CRC_14 1 None 2 p.R175H 2 None 1 None CRC_16 2 p.R232* 2 p.G245S 2 p.G12D 2 None CRC_17 2LOH p.S1327* 2 None 1 p.G13D 2 None CRC_19 2LOH None 2 None 2 None 2 None CRC_20 2 None 2 p.H179Y 2 None 2 None CRC_21 2 p.1224A_1225Kfs 1 p.G245S 2 None 1 None CRC_22 2 None 2 p.R342* 2 None 2 None CRC_23 2 p.1394S_1395Ffs 2 p.R175H 2 None 2 None CRC_24 2 p.1026Y_1027Sfs 2 p.R282W 2 None 2 None CRC_26 2LOH p.E1295* 2 None 2 p.G13D 2 None CRC_27 2 p.401R_402Efs, 2 None 2 None 1 None p.1363S_1364Gfs CRC_28 2 p.R554*, p.1436K_1437Tfs 2 None 2 p.G121V 2 None CRC_29 2 None 2 None 2 p.G12S 2 None CRC_33 2 None 2 5’-SS SNVb 2 p.G12D 1 p.20H21Sfs CRC_34 2LOH p.Q238* 1 5’-SS SNVb 2 None 2 None CRC_35 2 p.R216*, p.Q1378* 2 p.R175H 2 None 1 None CRC_36 2 p.Q1406* 1 p.R196* 2 p.G12V 2 None

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CRC_38 2 p.Q1367* 1 5’-SS SNVb 2 None 2 None CRC_41 2 p.Q1291*, p.1573I_1574Lfs 1 p.P250L 2 p.G12D 1 None CRC_42 2 p.R302*, p.1450* 1 p.R248Q 2 p.G12A 2 None CRC_45 2LOH p.S1327* 1 p.225G_226Sfs 2 None 1 None CRC_48 2 None 2 None 2 None 2 None CRC_52 1 None 1 p.P278T 2 p.G12D 1 None CRC_53 2 p.775I_777Nfs, p.R1450* 1 p.K132E 3 p.G13D 2 p.R531W CRC_54 2 None 2 p.R282W 2 p.G12V 2 None CRC_57 2 p.R904*, p.1450* 1 None 2 p.G13D 2 None CRC_58 2 p.E1322* 2 None 2 None 1 None CRC_59 2 p.Q1291*, p.1290Q_1291Tfs 2LOH 5’-SS SNVb 2 p.G12D 1 p.D351Y APC is localized to chromosome 5q22.2, TP53 to chromosome 17p13.1, KRAS to 12p12.1, and SMAD4 to 18q21.2. CN, copy number. aAn entry of 2LOH indicates that copy-neutral loss of heterozygosity is present and includes the relevant gene. bMutation of one of the highly conserved bases of the splice donor (5’-SS) or splice acceptor (3’-SS) sites by either deletion (DEL) or nucleotide substitution (SNV).

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Figure 4.5 APC mutation-negative colorectal cancers exhibit greater chromosome stability. (A) Comparison of copy number changes in APC mutation-negative vs. APC mutation-positive colorectal cancers. (B) Comparison of copy number changes in African

American CCCC vs. Non-Hispanic White TCGA colorectal cancers.

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Figure 4.6 Differentially methylated regions in APC mutation-negative tumors cluster with adjacent normal tissue relative to APC mutation-positive tumors. (A) Heatmap from unsupervised cluster analysis of the top 200 most variable differentially methylated regions in the 6 APC mutation-positive and 5 APC mutation-negative CRCs from the

CCCC. (B) Unsupervised cluster analysis using the same 200 most variable differentially methylated regions in 15 APC mutation-positive and 29 APC mutation-negative CRCs from the TCGA.

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 hypermethylation whereas APC mutation-negative tumors were characterized by genome-wide hypermethylation, similar to levels in matched normal adjacent colon but easily distinguished from it.

Because APC mutation-negative tumors in the CCCC series were associated with global hypermethylation, we tested whether the methylation signature identified in the

Chicago series could be identified in TCGA NHW CRCs. Consequently, we performed cluster analysis of 44 samples from TCGA NHWs using the 200 most variable differentially methylated regions identified in the CCCC series (Figure 4.5B). Twelve of

15 (80%) of the APC mutation-negative TCGA NHW CRCs clustered with normal tissue controls compared to 9 of 29 (31%; p = 0.004) of the APC mutation-positive TCGA

NHW CRCs. These results suggest that the collection of differentially methylation regions in APC mutation-negative CRCs represents a novel epigenetic subtype of CRC.

To gauge the impact of methylation changes on genomic regulatory features, we used the

Reference Epigenome Mapping Consortium’s chromatin state map for normal colonic mucosa based on ChIP-seq data 227 to annotate DMRs. As noted above, DMRs in APC mutation-positive tumors exhibited genome-wide hypomethylation with focal hypermethylation (Figure 4.7A). In particular, DNA hypermethylation strongly favored bivalent H3K4me3- and H3K27me3-associated promoters, which are critical regulatory switches in differentiation controlled by Polycomb repressor complex binding sites 228. In contrast, APC mutation-negative tumors revealed substantially less dramatic gains and losses in DNA methylation at these sites relative to normal tissues (Figure 4.6.5B). There was proportionately greater methylation of CpG island regions in the APC mutation- negative tumors; however, based on the five marker genes used to determine the CpG-

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Figure 4.7 Co-localization of DMRs in APC mutation-positive and mutation negative tumors with seven chromatin states in all based on Reference Epigenome Mapping

Consortium’s CHIP-seq data. (A) Comparison of 11 colorectal cancers to adjacent normal tissue demonstrates global hypomethylation with focal hypermethylation. (B)

Comparison of 5 APC mutation-negative tumors with adjacent normal tissue demonstrates increased methylation in the absence of global hypomethylation.

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 island methylator phenotype 136, all five APC mutation-negative CRCs are classified

CIMP-0. There was an intriguing enrichment of DMRs in methylated enhancer regions

(839) compared to enhancer regions in overall tumor vs normal DMRs (200). Finally, in the analysis of differentially methylated probes, three TCGA-identified cancer driver genes, including SOX9, GPC6, and KIAA1804, were hypermethylated in APC mutation- negative tumors whereas the same sites were hypomethylated in APC mutation-positive tumors. Differential hypermethylation between APC mutation-negative and mutation- positive tumors was also observed in key WNT signaling pathway genes including

GATA6, TET1, FAT1, and GLIS1.

Discussion

In our analysis of African American CRCs from the CCCC, we found that APC mutations were significantly less frequent in this series compared to the TCGA. The 16

APC mutation-negative cases were younger and more often affected by previous cancer.

The association between APC mutation-negative CRC and earlier age of onset was also detected in the TCGA series, which is an independent validation of the result identified in the CCCC series. In addition, we found that APC mutation-negative tumors exhibited lower numbers of somatic mutations, and they were more chromosome stable. In this context, known driver genes were strikingly underrepresented whereas other cancer- associated genes were overrepresented. Finally, APC mutation-negative tumors exhibited a distinct methylation signature, characterized by hypermethylation of select regulatory regions, affecting in particular genes in the WNT signaling pathway. This methylation signature was also enriched in APC mutation-negative CRCs in TCGA NHWs.

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In three of the APC mutation-negative cases, we found mutations in BCL9L, which is a negative regulator of the -catenin. The BCL9L cases had a strong family history of early-onset cancer and was associated with somatic mutations in BRAF that activate the kinase domain, co-occurring in two of the three cases. BCL9 and BCL9L are homologs of the fruitfly legless gene, and they are essential components of WNT signaling, mediating interaction between beta-catenin and Pygopus homologs. There is a growing body of evidence that indicates that BCL9 and BCL9L are important in carcinogenesis 229–231; hypothetically, BCL9L acts as a tumor suppressor, with truncating mutations leading to oncogenic up-regulation of -catenin.

Our study is the second to focus on somatic mutations in African American CRC.

The Case Western study performed exome sequencing of 31 African American CRC cases. They used a two-stage discovery-validation approach to identify novel cancer driver genes present in African American CRCs that had not been previously found in the white population, including somatic mutations in ephrin type A receptor 6 (EPHA6) and folliculin (FLCN). In the CCCC series, we found no mutations in EPHA6 and one missense allele in FLCN. We found two missense mutations in the chromatin remodeling gene CHD5, which was one of the genes over-represented in the CCCC African

Americans compared to the TCGA NHWs (Figure 4.3B). Of the remaining 17 candidate cancer-driving genes reported in the Case Western series, we found non-silent mutations in four—GPR149, ZNF862, MGAT4C, and WDR87—each in a single case. Clinical differences between the two series might explain some of the variance in results. For example, the Case Western series was entirely from the colon, whereas 7 of the CCCC cases were rectal cancers and 5 were from the rectosigmoid junction. Other possibilities

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 include the age distribution, which was not reported in that study, and the stage distribution. Nearly all the Case Western cases were Stage IV, whereas only 10 of the

CCCC cases were.

In our earlier characterization of CRC in Chicago African Americans 75, we found the median age of diagnosis (n=62) was younger compared to the median age in Chicago

NHWs (n=65), with over 15% of cases diagnosed before the age of 50 compared to 7% in

NHWs. In the CCCC cases sequenced here, the median age (n=60) was younger than in the CCCC African American series from as a whole, with 26% of the cases diagnosed before age 50. Thus, younger cases are oversampled in our exome sequence data, and the enrichment of APC mutation-negative CRCs is very likely a consequence of this oversampling, reflecting differences in the process of carcinogenesis between early-onset

CRC and late-onset CRC. Previous reports on sporadic early-onset CRCs have shown they are more frequently located in the distal colon or rectum than late-onset CRCs

2,232,233; they affect females and males nearly equally whereas late-onset CRC patients are more frequently male 2; they are relatively more frequent in Hispanics and African

Americans than in NHWs 67,75,234. Early-onset CRC more often presents with venous or lymphovascular invasion with aggressive features (signet ring or mucinous); it is more often poorly differentiated 235,236; and cases more often present with advanced disease 237.

Previously reported molecular features that have been associated with early-onset CRC include microsatellite and chromosome stability 238,239, CIMP-low and CIMP-0 240, and

LINE1 “extreme hypomethylation” 241. Expression profiles of early-onset CRCs are easily distinguishable from late-onset CRCs, characterized by up-regulation of beta- catenin 242–244. Our analysis here is broadly consistent with this previous work. In

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Mechanisms of Tumorigenesis in African American CRC Chapter 4 addition, we have found an excess of APC mutation-negative tumors, reduced tumor mutation burden, and distinctive methylation changes.

Increased methylation in APC mutation-negative tumors was observed at several genes that regulate the WNT signaling pathway, the dysregulation of which may help explain the absence of APC mutations. SOX9 is often over-expressed in CRCs, and its function has been linked to maintenance of stem cell phenotype through activation of

WNT signaling 245,246. Similarly, GATA6 maintains stem cell phenotype by up-regulating

LGR5 expression and down-regulating BMP2 247, and GLIS1 is involved in the autocrine activation of WNT signaling 248. On the other hand, TET1 and FAT1 are tumor suppressors. TET1 binds to DKK gene inhibitors of WNTs to maintain their expression

249 and FAT1 binds directly to β-catenin to suppress its function 250. Future studies are needed to analyze the role of methylation in expression and function of these genes in

APC-mutation negative CRCs.

Limitations of the study include issues relating to comparisons between CCCC and TCGA datasets (differences in sequencing platforms and bioinformatics processing pipelines) and small sample size affecting the analysis of methylation data. Large-scale analysis is needed to validate the association between APC mutation-negative cancer and early-onset CRC and the distinctive methylation profile observed in these tumors.

Together, the results on APC-mutation-negative CRCs point to a non-canonical carcinogenic process that is more dominated by epigenetic changes, less dominated by somatic mutational changes, and occurring at earlier ages. We suggest that the development of early-onset CRC might often occur in an accelerated timeframe spurred by environmental factors that impinge on epigenetic mechanisms, and recent analysis of

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SEER data on CRC incidence stratified by stage at diagnosis broadly supports this interpretation251. What environmental factors associate with early-onset CRC is a matter of considerable interest. We have recently reported a strong association between African

American CRC and sulfidogenic bacteria; in particular the taurine-respiring species

Bilophila wadsworthia was 2.5 times more abundant in African Americans compared to

NHWs irrespective of disease status, and it was 1.9 times more abundant in African

American CRC cases compared to African American controls 60. Moreover, we have found that serum 25-hydroxy-vitamin D levels were significantly lower in Chicago

African Americans compared to Chicago NHWs, and low vitamin D levels were associated with CRC in African Americans (unpublished observations from the CCCC).

How factors such as these might interact to impel higher rates of early-onset CRC in

African Americans is not understood. Further studies are needed to understand and prevent early-onset CRC in the African American and in other populations.

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Chapter 5

Decreased copy-neutral loss of heterozygosity in African American colorectal cancers

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Abstract

Background Despite improvements over the past 20 years, African Americans continue to have the highest incidence and mortality rates of colorectal cancer (CRC) in the US.

While previous studies have found that copy number variations (CNVs) occur at similar frequency in African American and White CRCs, copy neutral loss of heterozygosity

(cnLOH) has not been investigated.

Methods In the present study, we used publicly available data from The Cancer Genome

Atlas (TCGA) as well as data from an African American CRC cohort, the Chicago

Colorectal Cancer Consortium (CCCC), to compare frequencies of CNVs and cnLOH events in CRCs in the two racial groups. Using genotype microarray data, we analyzed large-scale CNV and cnLOH events from 166 microsatellite stable CRCs—31 and 39

African American CRCs from TCGA and the CCCC, respectively, and 96 White CRCs from TCGA).

Results As reported previously, the frequencies of CNVs were similar between African

American and White CRCs; however, there was a significantly lower frequency of cnLOH events in African American CRCs compared to White CRCs, even after adjusting for demographic and clinical covariates. Although larger differences for chromosome 18 were observed, a lower frequency of cnLOHs events in African American CRCs was observed for nearly all chromosomes.

Conclusions These results suggest that mechanistic differences, including differences in the frequency of cnLOH, could contribute to clinicopathological disparities between

African Americans and Whites. Additionally, we observed a previously uncharacterized

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 phenomenon we refer to as small interstitial cnLOH, in which segments of chromosomes from 1-5 Mb long were affected by cnLOH.

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Introduction

Despite the decrease in incidence and increase in survival of colorectal cancer

(CRC) in the US over the past 20 years199, the health disparity affecting African

American patients is still a major concern. African Americans continue to have the highest incidence and mortality rates of colorectal cancer in the US. Additionally, African

American CRCs are more likely to present at a more advanced stage and to present with disease on the right side of the colorectum. The disparity remains even after correcting for socioeconomic factors, indicating that there is a biological component of CRC development in African Americans that contributes to these differences199.

Most CRCs are driven at least in part by a chromosomal instability that results in copy number variation (CNV). CNVs can be focal, affecting a small segment of the genome, but many studies focus on recurrent large-scale CNVs, which affect whole chromosome arms or entire chromosomes. These large-scale events are common in CRC and can result in dosage changes of oncogenes or tumor suppressors that drive tumorigenesis forward. Previous studies have investigated large-scale CNVs (i.e., chromosome gains and losses) in African American CRCs. These studies found that large-scale CNVs occur at similar frequencies in African American and White

CRCs78,79,82. However, there is a source of chromosomal instability that has not yet been investigated, namely, copy-neutral loss of heterozygosity (cnLOH).

Tumor-specific cnLOH events are somatic mutations that cause reduction to homozygosity, that is, they generate regions of the chromosome that retain two copies of syntenic loci that are derived from either the maternal or paternal homolog in the tumor but that are bi-parental in the progenitor non-neoplastic tissue. Reduction to

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 homozygosity can drive tumorigenesis if, for example, the genetic change results in the loss of a functional copy of a tumor suppressor gene and the retention of two non- functional copies. Large-scale cnLOH is generated by at least two different molecular mechanisms, including a DNA repair mechanism and a chromosome non-disjunction mechanism, as compared to chromosome-wide gains and losses, which arise predominantly by a chromosome non-disjunction mechanism (Figure 5.1). The DNA repair mechanism occurs by an inter-homolog recombination event that upon mitotic segregation results in chromosome-arm cnLOH (Figure 5.1A). Reduction to homozygosity via the homologous recombination mechanism frequently occurs as a tumor-initiating event at the APC gene252. The non-disjunction mechanism occurs during mitosis due to syntelic attachments and centromere division failure, resulting in both chromatids segregating to one pole and neither chromatid to the other. A second chromosome non-disjunction event is then required to eliminate the homolog or to reduplicate the chromosome to create a cell with a copy neutral change (Figure 5.1B).

These two genetic mechanisms result in cnLOH events that typically span a large segment of a chromosome arm (i.e., homologous recombination class) or the entire chromosome or chromosome arm (i.e., loss and reduplication).

In the present study, we used publicly available data from The Cancer Genome

Atlas (TCGA) as well as data from an African American CRC cohort, the Chicago

Colorectal Cancer Consortium75 (CCCC), to compare frequencies and locations of cnLOH events in CRCs in the two racial groups. We hypothesized that differences in the frequency of cnLOH could contribute to clinicopathological disparities between African

Americans and Whites. We, therefore, investigated the frequency of cnLOH in African

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Figure 5.1 Model of mechanisms of copy-neutral loss of heterozygosity. (A) After an interhomolog recombination event affecting a given allele (i.e., the B allele, but not the A allele), mitotic segregation can result in either a reduction of homozygosity (from Bb in parental cell to BB or bb in daughter cell) or retention of heterozygosity (Bb in both parental and daughter cell). (B) A non-disjunction event during mitosis can lead to daughter cells with either an extra paternal chromatid or the loss of a paternal chromatid.

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Subsequent elimination of the single-copy chromosome in the former or duplication of the remaining chromosome in the latter results in cnLOH.

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Mechanisms of Tumorigenesis in African American CRC Chapter 5

American CRCs and White CRCs. Surprisingly, we found that cnLOH occurs at a lower frequency in African American CRCs compared to White CRCs. Additionally, we identified a previously uncharacterized phenomenon we refer to as small interstitial cnLOH (si-cnLOH), in which small segments of chromosomes from 1-5 Mb long are affected by cnLOH.

Methods

Data acquisition

Fresh CRC tissue samples in the CCCC were collected from five major medical centers in Chicago between 2011 and 201275. Tumor samples and non-involved mucosal samples were obtained during surgery or endoscopy. Non-involved tissues were sampled from tissue >10 cm away from the tumor. These samples were cryopreserved in

RNAlater. Microsatellite instability (MSI) status was determined by polymerase chain reaction201. CRCs that exhibited MSI were excluded because it is known that the genomic instability that drives this subtype of CRC is a defect in mismatch repair, microsatellite unstable tumors tend to be chromosomally stable, and the frequency of MSI in African

Americans and Whites is similar77. Data on CNVs in tumor and normal samples from 39 microsatellite stable African American CRCs from the CCCC were acquired on the

Affymetrix CytoScan HD microarray platform with the help of the University of Illinois at Chicago Genomics Core.

Raw CNV data (CEL files) from microsatellite stable CRCs in TCGA (African

American n = 31; non-Hispanic White n = 96, hereafter referred to as White) were obtained via the NCI’s Genomic Data Commons (GDC) website (June 8, 2017). These microarray data were generated on the Affymetrix GenomeWide SNP Array 6.0 146

Mechanisms of Tumorigenesis in African American CRC Chapter 5 platform. MSI status was determined by accessing clinical covariates available from the

GDC.

The three cohorts were similar in sex, BMI, and tumor stage distributions (Table

5.1). The two African American cohorts were younger than the White cohort (mean in

CCCC African Americans, 56.9 years; mean in TCGA African Americans, 61.4 years; mean in TCGA Whites, 67.2 years; p < 0.001, Table 5.1), a known clinical difference between the two ethnic groups199.

Data processing

Array data from TCGA and the CCCC were processed using Affymetrix Power

Tools (APT, version 1.18.1). Population frequency of B allele (PFB) files were generated for each population (i.e., CCCC and TCGA African Americans and TCGA Whites) using compile_pfb.pl script provided by PennCNV (version 1.0.4). PennCNV was used to generate segments using default settings except for using our generated PFB files.

Adjacent CNV segments were merged using PennCNV’s clean_cnv.pl script.

For CNV analysis, segments of gain and loss were aggregated to determine the proportion of each chromosome arm affected in each patient sample. Chromosome arms were then categorized as affected or unaffected by gain and loss, where having >27% of the arm affected was used as the threshold. This threshold was chosen because it was the mean percent affected amount across all chromosomes in all samples. Additionally, because gain and loss events can affect only part of a chromosome arm, a lower threshold was deemed appropriate to accurately capture chromosome arms affected by a copy

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Table 5.1 Clinical characteristics of patients in the three cohorts included in the study.

______CCCC Black or TCGA Black or TCGA White p-value African American African American N=39 (38 complete) N=31 N=96 ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ Tumor stage: 0.513 Stage I 5 (15.6%) 5 (16.1%) 15 (16.3%) Stage II 11 (34.4%) 6 (19.4%) 30 (32.6%) Stage III 10 (31.2%) 10 (32.3%) 33 (35.9%) Stage IV 6 (18.8%) 10 (32.3%) 14 (15.2%) Age (years) 56.9 (11.2) 61.4 (12.2) 67.2 (11.9) <0.001 Sex: 0.555 Female 15 (39.5%) 13 (41.9%) 47 (49.0%) Male 23 (60.5%) 18 (58.1%) 49 (51.0%) BMI A: 0.521 Normal 14 (36.8%) 6 (23.1%) 26 (32.9%) Underweight 1 (2.63%) 0 (0.00%) 0 (0.00%) Overweight 14 (36.8%) 9 (34.6%) 27 (34.2%) Obese 9 (23.7%) 11 (42.3%) 26 (32.9%) ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ A BMI, body mass index

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 number change. For the purposes of the present analysis, we did not differentiate between gain or loss of 1 or >1 copy (i.e., a copy number of 1 or 0, or a copy number of 3 or more). This analysis differs from the analysis reported in Xicola et al. (2018)82 due to the inclusion of African American TCGA CRC samples and the exclusion of MSI samples.

Similarly, to analyze large-scale cnLOH, segments of cnLOH were aggregated to determine the proportion of each chromosome arm affected. Chromosome arms were then categorized as affected or unaffected, where having >50% of the arm affected was used as the threshold. This threshold was chosen because cnLOH often affects most or all of a chromosome arm. It is also the threshold used by TCGA investigators198. For completeness, a 27% threshold was also assessed for cnLOH. This threshold did not change the overall results or interpretation (see below).

Small interstitial cnLOH analysis

Array data from CCCC tumor/normal pairs (i.e., tumor and normal samples from the same individual) were processed in APT using default settings. After identifying possible si-cnLOH events in the allelic difference data by visual inspection, we attempted to develop a method to automate the detection of si-cnLOH events. Several algorithms, including PennCNV and Paired PSCBS using Aroma (version 3.0.0), were assessed to determine an optimal program to complete segmentation of copy number data and identify small copy-neutral segments. Additionally, we developed a bioinformatic approach that used statistical and biological assumptions to extract si-cnLOH events from both non-segmented and segmented data. For each algorithm, we produced a set of images that could be manually confirmed as potential si-cnLOH events. Our priority for

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 this study was to confirm the existence of these events. Therefore, the aim was to deploy a method of si-cnLOH detection that produced a reasonable number of images (<500 images) from the algorithm that we could evaluate allelic difference plots visually and subsequently test with SNP genotyping. Ultimately, the following method was determined to be optimal for this limited purpose.

Segments for cnLOH generated from APT were compared for each pair of samples. Non-tumor-specific cnLOH segments (i.e., cnLOH segments that appear in both tumor and normal samples) were removed using the tidygenomics R package (version

0.1.0). Upon inspection of remaining segments, we found a bimodal distribution where segments less than 5 Mb were most likely to be si-cnLOH events. We therefore selected regions that were tumor-specific and less than 5 Mb in length. Allelic difference plots of identified regions were generated for manual curation. A positive for a si-cnLOH was determined to be any region where heterozygosity exists in the normal sample but is lost in the tumor sample, and where the tumor sample retained two copies. Additionally, for a region to be classified as a si-cnLOH, there must not be cnLOH in the adjacent regions flanking it according to the segmentation data. Importantly, because the analysis is based on segmentation methods, start and end positions of si-cnLOH events are approximate.

Using this method, we generated 495 images. Of these 495, a rater classified each image (i.e., si-cnLOH) as “definitely”, “possibly”, or “not” a si-cnLOH. All images from the “definitely” and “possibly” class were then shown to an independent rater to reclassify. Images that both raters defined as “definitely” were included in the present study. Interrater reliability was >99%. From our 495 images from 39 samples, 465

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 images were classified as “not” si-cnLOH events, 7 were classified as “possibly” si- cnLOH events, and 24 were classified as “definitely” si-cnLOH events.

Validation of the microarray data was completed for 3 si-cnLOH events using

PCR, restriction enzyme digestion, and agarose gel analysis to genotype SNPs inside the si-cnLOH and in the flanking regions in both tumor and non-involved samples. The SNPs that were genotyped and the associated primer pairs designed for validation can be found in Table 5.2.

To identify genes overlapping si-cnLOH locations, we used the GenomicRanges

(version 1.34.0) and annotatr (version 1.8.0) under Bioconductor (version 3.7).

Additional R (version 3.5.1) packages used for analysis of data include readr (version

1.3.1), ggplot2 (version 3.1.0), tidyr (version 0.8.2), dplyr (version 0.7.8), and stringr

(version 1.3.1).

Statistical Analyses

Comparisons of events within categorical variables were determined by chi square or Fisher exact tests where appropriate. Comparison of number of events with categorical and continuous variables were determined by Wilcoxon Rank Sum tests or Spearman’s correlation, respectively. All p-values were adjusted for multiple testing using a

Bonferroni correction. Linear regression models were used to determine associations between the number of chromosome arms affected by cnLOH in an individual and covariates. Covariates included age at diagnosis, sex, BMI, and tumor stage at diagnosis.

Additional covariates for appropriate linear models included race (i.e., African American or White) and cohort (i.e., TCGA or CCCC).

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Table 5.2 Primers designed to genotype SNPs inside and outside si-cnLOHs. rsID Forward Primer Reverse Primer rs7800785 ATGAAAGGCACCAGCCCTCT ATATCGACACAAGGGGGCAA rs6977375 AGCTGTTTGCAATTAGTCCACTG AACCAGCTGGGGTAAGAGAGA rs7791836 TCAGCCAGAGCTTTCATCAC AAACTGAGCCCCCTGCATAA rs41532145 TACTCTCCCCCATTTGTGTGC TTCCTGCCAACCCCATTGATT rs7778221 ACGTAGACCTGGCATGATGT CCCACACAGCTGAAATGGGT rs17036942 ATCAGGGAAGGCCTTGTTTGTC GGCTGGACGGTGTTCTCCTC rs6711902 GAGACTCAGAACGGGAAGGC CCCAGGGCTACACAGTTGAC rs55985145 GCCATGGCTGTCCTCTCAAT ACTGGAAGCTGAATGTCCTTT rs2192969 CAGTGACTGGCCTGGGTTTC CCCGATGTGGTATCATGCTCA rs16847624 GGACCAGCAGAGCCAAGTAT CTGTGGTCCCAATGCTGTAG rs74641552 TTGTTGCACTCTCACATGGC ACAATCTGATCAAGGGAGGCT rs10912722 TTGCTCTCTAGGCCTGCTTC AAACAGCTGGTTCCCACCTA rs4565663 CAGGGTGAATGGAGACATCCC AGCTGTTCTGCCCTATTCTCC rs6425201 ACAACAATGGCACTCTCTCACA AAGGATGGAGCCACTCAACT

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Results

African Americans and Whites have similar frequencies of copy number gains and losses

The frequency of copy number gains and losses on each chromosome arm were compared in microsatellite stable CRCs from TCGA and the CCCC. African American and White CRCs had similar frequencies of chromosome-arm gains for all chromosomes as well as overall (Table 5.3). Likewise, African American CRCs had similar frequencies of chromosome-arm losses as White CRCs for all chromosome arms (Table 5.4). The overall frequency of copy number losses was significantly higher in TCGA African

American CRCs compared to TCGA White CRCs (9.4% vs 6.3%, p = 0.01), but the frequency of chromosome losses in CCCC African American CRCs was slightly lower than in TCGA White CRCs (5.2% vs 6.3%, p = 1). No other comparison of chromosome losses was significantly different. Together, these results confirm findings of other studies78,79,82 that chromosome-arm copy number gains and losses occur at similar frequencies in African American and White CRCs.

White CRCs have a higher frequency of cnLOH than African American CRCs for most chromosome arms

In order to determine if there was a difference in overall burden of cnLOH between African American and White CRCs, we compared the frequency of cnLOH across the genome in all samples. Chromosome arms in CCCC African American CRCs,

TCGA African American CRCs, and combined African American CRCs were affected at a frequency of 2.6%, 6.5%, and 4.3%, respectively, while 11.8% of chromosome arms of

White CRCs were affected by cnLOH (Figure 5.2, Table 5.5, p < 0.001 for all

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Table 5.3 Frequency of chromosome arms affected and total burden of copy number gains with fold differences for MSS CRCs.

number of patients with copy number gain Fold Change (Whites vs African Americans) on chromosome arm (% patients) Chromosome CCCC African TCGA African TCGA Whites TCGA Whites v TCGA Whites v TCGA Whites v Arm Americans Americans CCCC African TCGA African Combined African n=39 n=31 n=96 Americans Americans Americans 1p 0 (0%) 0 (0%) 0 (0%) - - - 1q 2 (5.1%) 5 (16.1%) 8 (8.3%) 1.6 0.5 0.8 2p 0 (0%) 1 (3.2%) 3 (3.1%) - 1 2.2 2q 0 (0%) 1 (3.2%) 4 (4.2%) - 1.3 2.9 3p 0 (0%) 0 (0%) 0 (0%) - - - 3q 1 (2.6%) 0 (0%) 2 (2.1%) 0.8 - 1.5 4p 0 (0%) 0 (0%) 0 (0%) - - - 4q 0 (0%) 0 (0%) 0 (0%) - - - 5p 2 (5.1%) 1 (3.2%) 4 (4.2%) 0.8 1.3 1 5q 0 (0%) 1 (3.2%) 1 (1%) - 0.3 0.7 6p 3 (7.7%) 2 (6.5%) 4 (4.2%) 0.5 0.6 0.6 6q 1 (2.6%) 0 (0%) 2 (2.1%) 0.8 - 1.5 7p 13 (33.3%) 10 (32.3%) 30 (31.2%) 0.9 1 1 7q 8 (20.5%) 6 (19.4%) 17 (17.7%) 0.9 0.9 0.9 8p 1 (2.6%) 0 (0%) 6 (6.2%) 2.4 - 4.4 8q 12 (30.8%) 11 (35.5%) 32 (33.3%) 1.1 0.9 1 9p 1 (2.6%) 5 (16.1%) 3 (3.1%) 1.2 0.2 0.4 9q 0 (0%) 1 (3.2%) 3 (3.1%) - 1 2.2 10p 1 (2.6%) 2 (6.5%) 1 (1%) 0.4 0.2 0.2 10q 0 (0%) 0 (0%) 0 (0%) - - - 154

11p 1 (2.6%) 2 (6.5%) 4 (4.2%) 1.6 0.6 1 11q 3 (7.7%) 4 (12.9%) 3 (3.1%) 0.4 0.2 0.3 12p 5 (12.8%) 1 (3.2%) 13 (13.5%) 1.1 4.2 1.6 12q 1 (2.6%) 0 (0%) 8 (8.3%) 3.2 - 5.8 13q 14 (35.9%) 16 (51.6%) 50 (52.1%) 1.5 1 1.2 14q 1 (2.6%) 0 (0%) 2 (2.1%) 0.8 - 1.5 15q 0 (0%) 0 (0%) 1 (1%) - - - 16p 4 (10.3%) 4 (12.9%) 3 (3.1%) 0.3 0.2 0.3 16q 3 (7.7%) 2 (6.5%) 4 (4.2%) 0.5 0.6 0.6 17p 0 (0%) 0 (0%) 0 (0%) - - - 17q 0 (0%) 5 (16.1%) 4 (4.2%) - 0.3 0.6 18p 0 (0%) 1 (3.2%) 1 (1%) - 0.3 0.7 18q 0 (0%) 0 (0%) 0 (0%) - - - 19p 1 (2.6%) 1 (3.2%) 3 (3.1%) 1.2 1 1.1 19q 1 (2.6%) 0 (0%) 7 (7.3%) 2.8 - 5.1 20p 5 (12.8%) 8 (25.8%) 34 (35.4%) 2.8 1.4 1.9 20q 17 (43.6%) 19 (61.3%) 64 (66.7%) 1.5 1.1 1.3 21q 1 (2.6%) 0 (0%) 1 (1%) 0.4 - 0.7 22q 1 (2.6%) 0 (0%) 0 (0%) 0 - 0 Total Burden 103 (6.8%) 109 (9%) 322 (8.6%) 1.3 1 1.1 * p<0.1; ** p<0.05; *** p<0.01 “-“ indicates no fold difference was calculated because a zero appeared in the denominator.

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Table 5.4 Frequency of chromosome arms affected and total burden of copy number losses with fold differences for MSS CRCs.

number of patients with copy number loss Fold Change (Whites vs African Americans) on chromosome arm (% patients) Chromosome CCCC African TCGA African TCGA Whites TCGA Whites v TCGA Whites v TCGA Whites v Arm Americans Americans CCCC African TCGA African Combined n=39 n=31 n=96 Americans Americans African Americans 1p 1 (2.6%) 3 (9.7%) 7 (7.3%) 2.8 0.8 1.3 1q 1 (2.6%) 0 (0%) 0 (0%) 0 - 0 2p 1 (2.6%) 0 (0%) 0 (0%) 0 - 0 2q 0 (0%) 0 (0%) 0 (0%) - - - 3p 0 (0%) 2 (6.5%) 3 (3.1%) - 0.5 1.1 3q 0 (0%) 0 (0%) 0 (0%) - - - 4p 3 (7.7%) 4 (12.9%) 5 (5.2%) 0.7 0.4 0.5 4q 2 (5.1%) 3 (9.7%) 9 (9.4%) 1.8 1 1.3 5p 1 (2.6%) 0 (0%) 1 (1%) 0.4 - 0.7 5q 0 (0%) 2 (6.5%) 7 (7.3%) - 1.1 2.6 6p 2 (5.1%) 0 (0%) 0 (0%) 0 - 0 6q 1 (2.6%) 2 (6.5%) 1 (1%) 0.4 0.2 0.2 7p 0 (0%) 0 (0%) 0 (0%) - - - 7q 0 (0%) 0 (0%) 1 (1%) - - - 8p 9 (23.1%) 12 (38.7%) 30 (31.2%) 1.4 0.8 1 8q 0 (0%) 0 (0%) 1 (1%) - - - 9p 2 (5.1%) 2 (6.5%) 1 (1%) 0.2 0.2 0.2 9q 0 (0%) 3 (9.7%) 1 (1%) - 0.1 0.2 10p 0 (0%) 1 (3.2%) 1 (1%) - 0.3 0.7

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10q 2 (5.1%) 3 (9.7%) 6 (6.2%) 1.2 0.6 0.9 11p 0 (0%) 0 (0%) 0 (0%) - - - 11q 1 (2.6%) 0 (0%) 4 (4.2%) 1.6 - 2.9 12p 0 (0%) 1 (3.2%) 1 (1%) - 0.3 0.7 12q 1 (2.6%) 1 (3.2%) 0 (0%) 0 0 0 13q 0 (0%) 1 (3.2%) 1 (1%) - 0.3 0.7 14q 0 (0%) 10 (32.3%) 11 (11.5%) - 0.4 0.8 15q 3 (7.7%) 8 (25.8%) 15 (15.6%) 2 0.6 1 16p 0 (0%) 0 (0%) 3 (3.1%) - - - 16q 1 (2.6%) 0 (0%) 0 (0%) 0 - 0 17p 11 (28.2%) 15 (48.4%) 26 (27.1%) 1 0.6 0.7 17q 1 (2.6%) 1 (3.2%) 1 (1%) 0.4 0.3 0.4 18p 11 (28.2%) 13 (41.9%) 30 (31.2%) 1.1 0.7 0.9 18q 12 (30.8%) 15 (48.4%) 45 (46.9%) 1.5 1 1.2 19p 0 (0%) 2 (6.5%) 3 (3.1%) - 0.5 1.1 19q 0 (0%) 0 (0%) 2 (2.1%) - - - 20p 4 (10.3%) 3 (9.7%) 8 (8.3%) 0.8 0.9 0.8 20q 0 (0%) 0 (0%) 0 (0%) - - - 21q 3 (7.7%) 3 (9.7%) 4 (4.2%) 0.5 0.4 0.5 22q 6 (15.4%) 4 (12.9%) 6 (6.2%) 0.4 0.5 0.4 Total Burden 79 (5.2%) 114 (9.4%) 234 (6.2%) 1.2 0.7** 0.9 * p<0.1; ** p<0.05; *** p<0.01 “-“ indicates no fold difference was calculated because a zero appeared in the denominator.

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Figure 5.2 African American CRCs have a decreased frequency of cnLOH across the genome compared to White CRCs. Frequency of cnLOH by chromosome arm (expressed as the proportion of CRCs affected by cnLOH) is given for each chromosome arm in

CCCC African Americans (top, grey), TCGA African Americans (middle, green), and

TCGA Whites (bottom, purple).

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Table 5.5 Frequency of chromosome arms affected and total burden of cnLOH with fold differences for MSS CRCs.

Number of patients with cnLOH on Fold difference (Whites vs African Americans) chromosome arm (% patients) Chromosome CCCC African TCGA African TCGA Whites TCGA Whites v TCGA Whites v TCGA Whites v Arm Americans Americans CCCC African TCGA African Combined African n=39 n=31 n=96 Americans Americans Americans 1p 2 (5.1%) 1 (3.2%) 10 (10.4%) 2.0 3.2 2.4 1q 1 (2.6%) 0 (0%) 4 (4.2%) 1.6 - 2.9 2p 1 (2.6%) 2 (6.5%) 9 (9.4%) 3.7 1.5 2.2 2q 1 (2.6%) 2 (6.5%) 9 (9.4%) 3.7 1.5 2.2 3p 0 (0%) 3 (9.7%) 11 (11.5%) - 1.2 2.7 3q 0 (0%) 2 (6.5%) 4 (4.2%) - 0.6 1.5 4p 1 (2.6%) 0 (0%) 10 (10.4%) 4.1 - 7.3 4q 2 (5.1%) 1 (3.2%) 9 (9.4%) 1.8 2.9 2.2 5p 2 (5.1%) 1 (3.2%) 9 (9.4%) 1.8 2.9 2.2 5q 7 (17.9%) 6 (19.4%) 31 (32.3%) 1.8 1.7 1.7 6p 3 (7.7%) 1 (3.2%) 20 (20.8%) 2.7 6.5 3.6 6q 4 (10.3%) 2 (6.5%) 11 (11.5%) 1.1 1.8 1.3 7p 0 (0%) 1 (3.2%) 2 (2.1%) - 0.6 1.5 7q 0 (0%) 2 (6.5%) 6 (6.2%) - 1.0 2.2 8p 1 (2.6%) 4 (12.9%) 11 (11.5%) 4.5 0.9 1.6 8q 0 (0%) 0 (0%) 12 (12.5%) - - -* 9p 0 (0%) 1 (3.2%) 10 (10.4%) - 3.2 7.3 9q 0 (0%) 1 (3.2%) 15 (15.6%) - 4.8 10.9* 10p 0 (0%) 1 (3.2%) 7 (7.3%) - 2.3 5.1 10q 1 (2.6%) 1 (3.2%) 10 (10.4%) 4.1 3.2 3.6

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11p 0 (0%) 0 (0%) 5 (5.2%) - - - 11q 0 (0%) 0 (0%) 10 (10.4%) - - - 12p 2 (5.1%) 2 (6.5%) 11 (11.5%) 2.2 1.8 2.0 12q 2 (5.1%) 2 (6.5%) 16 (16.7%) 3.3 2.6 2.9 13q 2 (5.1%) 0 (0%) 4 (4.2%) 0.8 - 1.5 14q 0 (0%) 1 (3.2%) 13 (13.5%) - 4.2 9.5 15q 2 (5.1%) 5 (16.1%) 18 (18.8%) 3.7 1.2 1.9 16p 1 (2.6%) 2 (6.5%) 3 (3.1%) 1.2 0.5 0.7 16q 0 (0%) 4 (12.9%) 4 (4.2%) - 0.3 0.7 17p 2 (5.1%) 6 (19.4%) 30 (31.2%) 6.1* 1.6 2.7 17q 1 (2.6%) 6 (19.4%) 17 (17.7%) 6.9 0.9 1.8 18p 0 (0%) 2 (6.5%) 21 (21.9%) -** 3.4 7.7** 18q 0 (0%) 1 (3.2%) 20 (20.8%) -** 6.5 14.6*** 19p 0 (0%) 2 (6.5%) 8 (8.3%) - 1.3 2.9 19q 0 (0%) 3 (9.7%) 4 (4.2%) - 0.4 1.0 20p 1 (2.6%) 2 (6.5%) 15 (15.6%) 6.1 2.4 3.6 20q 1 (2.6%) 2 (6.5%) 4 (4.2%) 1.6 0.6 1.0 21q 2 (5.1%) 1 (3.2%) 9 (9.4%) 1.8 2.9 2.2 22q 1 (2.6%) 5 (16.1%) 19 (19.8%) 7.7 1.2 2.3 Total Burden 43 (2.8%) 78 (6.5%) 441 (11.8%) 4.2*** 1.8*** 2.7*** * p<0.1; ** p<0.05; *** p<0.01 “-“ indicates no fold difference was calculated because a zero appeared in the denominator.

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 comparisons).

To determine if the difference in cnLOH frequency was a global phenomenon or driven by a subset of chromosome arms, we compared the frequency of cnLOH on each chromosome arm between African Americans and Whites. Overall, White CRCs exhibited a 2.7-fold higher frequency of cnLOH compared to African American CRCs

(Table 5.5). The higher frequency of cnLOH on chromosome arm 18q in White CRCs was statistically significant, specifically compared to CRCs from the CCCC (White

CRCs vs CCCC African American CRCs, >20.8 fold [0% vs 20.8%], p = 0.034; vs

TCGA African American CRCs, 6.5-fold, p = 0.95; vs all African American CRCs, 14.6- fold, p = 0.003; Table 5.5). Similarly, there was a higher frequency of cnLOH on chromosome arm 18p. The higher frequency of cnLOH on chromosome arm 17p in

White CRCs was statistically significant when compared to the frequency of CCCC

African American CRCs but not of African American TCGA CRCs (6.1-fold, p = 0.03 vs

1.6-fold, p = 1.00; Table 5.5). For no other comparison was the difference in frequency statistically significant after correction for multiple testing. Yet, large fold-change differences in cnLOH frequency were seen for many chromosomes.

Several chromosome arms showed greater than 2-fold differences between White and African American CRCs in all population comparisons, including 1p, 6p, 10p, 12q, and 20p (Table 5.5). Chromosome arms 9p, 10q, and 18p showed a greater than 3-fold increased frequency of cnLOH events in White CRCs in comparison to African American

CRCs in all population comparisons and chromosome arms 4p, 9q, 14q, and 18q showed a greater than 4-fold increased frequency in all population comparisons. Several chromosome arms had no cnLOH events in either African American group whereas

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 events were found in White CRCs, specifically chromosome arms 8q, 11p, and 11q. With the exception of chromosome arms 16p, 16q, 19q, and 20q, all chromosome arms showed a higher frequency of cnLOH in White CRCs when compared to African American

CRCs. For the most part, the greater fold difference in Whites CRCs vs African

American CRCs was evident in both the CCCC and TCGA datasets. These data indicate that, although the fold difference between Whites CRCs and African American CRCs is demonstrably driven by oncogenesis for one specific chromosome, namely 18, where

SMAD4 is localized, the higher frequency of cnLOH in Whites CRCs is a global phenomenon.

White CRCs have more chromosome arms affected by cnLOH than African American

CRCs after adjustment for covariates

We found that the mean number of cnLOH events per tumor was higher in TCGA

White CRCs (mean 11.8%) than in both TCGA African American CRCs (mean 6.5%) or

CCCC African American CRCs (2.9%; Figure 5.3). Univariate analysis revealed that the number of chromosome arms affected by cnLOH was higher in White CRCs than in

African American CRCs (mean of White CRCs, 4.6; mean of African American CRCs,

1.7; p < 0.0001), but did not differ by sex (mean of female CRCs, 3.6; mean of male

CRCs, 3.2; p = 1). Age was not correlated with the number of chromosomes arms affected by cnLOH (rs(165) = 0.19, which is the Spearman correlation with n = 165).

Because of possible differences between cohorts, we compared the African American

CRCs from the CCCC and TCGA. The number of cnLOH-affected chromosome arms was not different in African Americans based on sex (mean of female CRCs, 2.3; mean

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Figure 5.3 African American CRCs have fewer chromosome arms affected by cnLOH than White CRCs. Number of chromosome arms affected by cnLOH in each CRC

(expressed as percentage of total chromosome arms) is represented as a dot on the graph, stratified into CCCC African Americans (left, grey), TCGA African Americans (middle, green), and TCGA Whites (right, purple). Boxes represent 25th, 50th, and 75th quartiles, while whiskers represent 1.5 interquartile range for that data series. Note that many samples had no arms affected and that the maximum percentage of arms affected for any individual was < 40%.

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 of male CRCs, 1.4; p = 1). Additionally, we found no significant difference between

CCCC and TCGA African American CRCs by cohort, though there was a trend toward fewer chromosome arms affected by cnLOH in CCCC African American CRCs than in

African American TCGA CRCs (mean in CCCC, 1.1; mean in TCGA, 2.5; p = 0.10). The main difference between these cohorts was age (Table 5.1), therefore we tested for a correlation between age and number of chromosome arms affected by cnLOH in African

American CRCs. Age was not correlated with the number of chromosome arms affected by cnLOH (rs(69) = 0.12, which is the Spearman correlation with n = 69).

We used multivariate linear regression models to determine if differences in the numbers of cnLOH events per CRC were associated with race after adjusting for covariates (Table 5.6). White race remained significantly associated with a higher frequency of cnLOH even after adjusting for age, BMI, tumor stage, sex, and cohort.

After stratification by race, stage II CRC was associated with a higher frequency of cnLOH in African American CRCs after adjusting for other covariates. However, neither stage III nor stage IV CRC were associated with cnLOH. In the model of White CRCs, no variable was significantly associated with number of chromosome arms affected by cnLOH. The above associations remained whether we looked at single chromosome arm events or whole chromosome events. Overall, the above results indicate that African

American CRCs have a reduced frequency of cnLOH, even after adjusting for age, sex, tumor stage, cohort, and BMI.

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Table 5.6 Linear model shows reduced cnLOH affected chromosomes in African Americans after adjustment for covariates. (1) All

African American and White complete cases from TCGA and CCCC, (2) African American complete cases from TCGA and CCCC,

(3) White complete cases from TCGA.

Dependent variable: Number of arms affected by cnLOH (1) (2) (3) Age (years) 0.01 (-0.05, 0.06) -0.01 (-0.06, 0.04) 0.02 (-0.07, 0.11) African American Race -3.02*** (-4.67, -1.37) Underweight BMI 1.32 (-5.78, 8.42) 0.54 (-3.65, 4.73) Overweight BMI 0.09 (-1.40, 1.57) 1.19 (-0.25, 2.64) -1.16 (-3.47, 1.15) Obese BMI 0.17 (-1.36, 1.70) 0.82 (-0.54, 2.17) -0.13 (-2.52, 2.26) Tumor Stage II 0.68 (-1.25, 2.61) 2.01** (0.29, 3.73) -0.44 (-3.54, 2.65) Tumor Stage III 1.09 (-0.79, 2.97) 0.13 (-1.52, 1.77) 1.57 (-1.44, 4.58) Tumor Stage IV 1.51 (-0.65, 3.67) 0.44 (-1.38, 2.26) 2.30 (-1.36, 5.96) TCGA Cohort 0.83 (-1.04, 2.70) 0.97* (-0.14, 2.08) Male Gender -0.18 (-1.45, 1.08) -0.20 (-1.39, 1.00) 0.42 (-1.59, 2.43) Intercept 2.88 (-1.43, 7.19) 0.42 (-3.03, 3.86) 3.12 (-3.06, 9.30) Observations 135 58 77 Note: p<0.1; p<0.05; p<0.01

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Small interstitial copy-neutral loss of heterozygosity (si-cnLOH)

Unexpectedly, during our investigation of large-scale cnLOH events, we identified small regions of cnLOH that occur interstitially within the chromosome. In order to identify these si-cnLOH events, we compared microarray data from paired tumor and non-involved CRC samples from the CCCC. We identified 24 si-cnLOH events in 5 of 39 patients in the series (Table 5.7). These 5 patients had varying numbers of si- cnLOH events, ranging from 1 to 13 with a median of 3 and an average of 4.8 si-cnLOH events per sample. Out of the 24 si-cnLOH events, 6 occurred on chromosome 7 (across

3 samples), 4 occurred on chromosome 2 (across 3 samples), 3 on chromosome 8 (in one sample), and 2 occurred on chromosomes 1, 3, and 5 (with two events in 2 samples). The remaining events occurred on single chromosomes in single samples (chromosomes 9,

11, 12, 13, and 17). The average segment of chromosome subject to si-cnLOH was 1.6

Mb long (median 1.4 Mb) with the shortest being approximately 200 kb and longest 3.5

Mb.

In order to validate the microarray data, we interrogated 3 si-cnLOH events

(Figure 5.4), using PCR, restriction enzyme digestion, and agarose gel analysis to genotype SNPs inside the segment affected by si-cnLOH and in the flanking regions in both tumor and non-involved samples. In each case, tumor heterozygosity was retained outside of the si-cnLOH but lost inside the segment affected by si-cnLOH (Figure 5.4).

Two of the five CRCs that exhibited si-cnLOH events overlapped with CRCs from which we had mutation data from our previous exome sequencing study82. Although the 24 regions encompassed by si-cnLOH events overlapped with some gene and promoter regions (Tables 5.8 & 5.9), there were no mutations in the two CRCs from which we had

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Table 5.7 Numbers of si-cnLOH events and their chromosome locations in the patients in whom they were identified.

Patient F95 Patient 20018 Patient C1 Patient R27 Patient U83 Total Events Chr 7 4 - 1 A 1 - 6 Chr 2 1 1 2 A - - 4 Chr 8 3 - - - - 3 Chr 1 1A - - - 1 2 Chr 3 1 1 - - - 2 Chr 5 2 - - - - 2 Chr 9 - 1 - - - 1 Chr 11 1 - - - - 1 Chr 12 - - 1 - - 1 Chr 13 - - - 1 - 1 Chr 17 - - 1 - - 1 Total Events 13 3 5 2 1 A One si-cnLOH from this cell was validated by genotyping SNPs inside and outside of region.

“-“ indicates no events occurred on this chromosome in this tumor

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Figure 5.4 Allelic difference plots, patient IDs, chromosomal location, and rsIDs of

SNPs validated within si-cnLOHs. X-axis represents chromosomeal location in Mb. Y- axis represents allelic difference. Each point is one SNP, given a normalized value based on microarray detected intensity. A value of +/-1 is interpreted as n=2 of a particular

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 allele (e.g., AA or TT), whereas a value of 0 is interpreted equal numbers of two different alleles (e.g., AT).

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Mechanisms of Tumorigenesis in African American CRC Chapter 5

Table 5.8 Location of identified si-cnLOH events. Start and end base pair positions are based on bioinformatic segmentation analysis, and are thus meant to be interpreted as approximate locations.

Patient ID Chromosome Start End F95 1 173888093 174927958 F95 2 194730749 195754794 F95 3 165414837 166620855 F95 5 32026726 33527307 F95 5 41034601 42047741 F95 7 43302127 45221903 F95 7 63549822 63766980 F95 7 91195587 94679602 F95 7 156689927 157049809 F95 8 47507335 48027102 F95 8 66946079 68339848 F95 8 88211003 90476201 F95 11 30685132 31943636 20018 2 187402812 188628343 20018 3 135793657 137313340 20018 9 94646983 95910508 C1 2 24190632 25304287 C1 2 69135190 70545542 C1 7 89308529 89362189 C1 12 113033800 113198828 C1 17 28687518 29767086 R27 7 115615760 116450855 R27 13 51892490 53343054 U83 1 72980805 74193940

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Table 5.9 Genes overlapping identified si-cnLOH events.

Chromosome Start Position End Position Annotation Annotation Annotated Gene Annotation Type Start Position End Position chr1 173888093 174927958 174127552 174128551 RABGAP1L promoters chr1 173888093 174927958 174416212 174417211 GPR52 promoters chr1 173888093 174927958 173962211 173963210 RC3H1 promoters chr11 30685132 31943636 31390377 31391376 DNAJC24 promoters chr11 30685132 31943636 31530297 31531296 ELP4 promoters chr11 30685132 31943636 31837114 31838113 PAX6-AS1 promoters chr11 30685132 31943636 31837114 31838113 RCN1 promoters chr11 30685132 31943636 30946956 30947955 NA promoters chr11 30685132 31943636 31391358 31392357 DCDC1 promoters chr11 30685132 31943636 31531170 31532169 IMMP1L promoters chr11 30685132 31943636 31825595 31826594 PAX6 promoters chr3 165414837 166620855 165555254 165556253 BCHE promoters chr5 32026726 33527307 32098280 32099279 PDZD2 promoters chr5 32026726 33527307 32584605 32585604 SUB1 promoters chr5 32026726 33527307 32709743 32710742 NPR3 promoters chr5 32026726 33527307 32946549 32947548 LINC02120 promoters chr5 32026726 33527307 33439802 33440801 TARS promoters chr5 32026726 33527307 32174426 32175425 GOLPH3 promoters chr5 32026726 33527307 32313115 32314114 MTMR12 promoters chr5 32026726 33527307 32383926 32384925 ZFR promoters chr5 32026726 33527307 33527287 33527471 ADAMTS12 exons chr5 41034601 42047741 41903470 41904469 C5orf51 promoters chr5 41034601 42047741 41924356 41925355 FBXO4 promoters chr5 41034601 42047741 41058327 41059326 MROH2B promoters chr5 41034601 42047741 41213696 41214695 C6 promoters chr5 41034601 42047741 41510731 41511730 PLCXD3 promoters

171

chr5 41034601 42047741 41794338 41795337 OXCT1 promoters chr7 43302127 45221903 43621692 43622691 STK17A promoters chr7 43302127 45221903 43797272 43798271 BLVRA promoters chr7 43302127 45221903 43965035 43966034 UBE2D4 promoters chr7 43302127 45221903 44039489 44040488 SPDYE1 promoters chr7 43302127 45221903 44077648 44078647 LINC00957 promoters chr7 43302127 45221903 44083239 44084238 DBNL promoters chr7 43302127 45221903 44142960 44143959 AEBP1 promoters chr7 43302127 45221903 44149448 44150447 MIR4649 promoters chr7 43302127 45221903 44239578 44240577 YKT6 promoters chr7 43302127 45221903 44645121 44646120 OGDH promoters chr7 43302127 45221903 44787180 44788179 ZMIZ2 promoters chr7 43302127 45221903 44835241 44836240 PPIA promoters chr7 43302127 45221903 45038345 45039344 CCM2 promoters chr7 43302127 45221903 45196367 45197366 RAMP3 promoters chr7 43302127 45221903 43562142 43563141 LUARIS promoters chr7 43302127 45221903 43769141 43770140 COA1 promoters chr7 43302127 45221903 43909146 43910145 MRPS24 promoters chr7 43302127 45221903 43946232 43947231 URGCP-MRPS24 promoters chr7 43302127 45221903 43929234 43930233 URGCP promoters chr7 43302127 45221903 44058749 44059748 POLR2J4 promoters chr7 43302127 45221903 44078576 44079575 RASA4CP promoters chr7 43302127 45221903 44105187 44106186 PGAM2 promoters chr7 43302127 45221903 44122130 44123129 POLM promoters chr7 43302127 45221903 44163108 44164107 POLD2 promoters chr7 43302127 45221903 44180917 44181916 MYL7 promoters chr7 43302127 45221903 44198888 44199887 GCK promoters chr7 43302127 45221903 44365231 44366230 CAMK2B promoters chr7 43302127 45221903 44521062 44522061 NUDCD3 promoters chr7 43302127 45221903 44560727 44561726 NPC1L1 promoters 172

chr7 43302127 45221903 44614138 44615137 DDX56 promoters chr7 43302127 45221903 44621828 44622827 TMED4 promoters chr7 43302127 45221903 44887726 44888725 H2AFV promoters chr7 43302127 45221903 44924961 44925960 PURB promoters chr7 43302127 45221903 45014827 45015826 MYO1G promoters chr7 43302127 45221903 45026237 45027236 SNHG15 promoters chr7 43302127 45221903 45025110 45026109 SNORA9 promoters chr7 43302127 45221903 45128494 45129493 NACAD promoters chr7 43302127 45221903 45147064 45148063 TBRG4 promoters chr7 43302127 45221903 45144642 45145641 SNORA5C promoters chr7 43302127 45221903 45145699 45146698 SNORA5B promoters chr7 43302127 45221903 43351362 43351686 HECW1 exons chr7 63549822 63766980 63666581 63667580 ZNF735 promoters chr7 63549822 63766980 63687852 63688851 ZNF679 promoters chr7 91195587 94679602 91569189 91570188 AKAP9 promoters chr7 91195587 94679602 91874548 91875547 ANKIB1 promoters chr7 91195587 94679602 92075762 92076761 GATAD1 promoters chr7 91195587 94679602 92157087 92158086 RBM48 promoters chr7 91195587 94679602 92860653 92861652 VPS50 promoters chr7 91195587 94679602 93219885 93220884 GNGT1 promoters chr7 91195587 94679602 93345240 93346239 MIR4652 promoters chr7 91195587 94679602 93550016 93551015 GNG11 promoters chr7 91195587 94679602 94022873 94023872 COL1A2 promoters chr7 91195587 94679602 94138170 94139169 CASD1 promoters chr7 91195587 94679602 94284637 94285636 PEG10 promoters chr7 91195587 94679602 94535949 94536948 PPP1R9A promoters chr7 91195587 94679602 91510017 91511016 MTERF1 promoters chr7 91195587 94679602 91763841 91764840 CYP51A1 promoters chr7 91195587 94679602 91808395 91809394 LRRD1 promoters chr7 91195587 94679602 91870467 91871466 KRIT1 promoters 173

chr7 91195587 94679602 92157846 92158845 PEX1 promoters chr7 91195587 94679602 92219707 92220706 FAM133B promoters chr7 91195587 94679602 92463232 92464231 CDK6 promoters chr7 91195587 94679602 92747337 92748336 SAMD9 promoters chr7 91195587 94679602 92777681 92778680 SAMD9L promoters chr7 91195587 94679602 92848871 92849870 HEPACAM2 promoters chr7 91195587 94679602 93116320 93117319 CALCR promoters chr7 91195587 94679602 93112168 93113167 MIR653 promoters chr7 91195587 94679602 93113332 93114331 MIR489 promoters chr7 91195587 94679602 93520304 93521303 TFPI2 promoters chr7 91195587 94679602 93633691 93634690 BET1 promoters chr7 91195587 94679602 94285522 94286521 SGCE promoters chr7 156689927 157049809 156741417 156742416 NOM1 promoters chr7 156689927 157049809 156802551 156803550 MNX1-AS1 promoters chr7 156689927 157049809 156930655 156931654 UBE3C promoters chr7 156689927 157049809 156802130 156803129 MNX1 promoters chr8 47507335 48027102 47751508 47752507 LINC00293 promoters chr8 66946079 68339848 67038278 67039277 TRIM55 promoters chr8 66946079 68339848 67103349 67104348 LINC00967 promoters chr8 66946079 68339848 67340263 67341262 RRS1 promoters chr8 66946079 68339848 67343718 67344717 ADHFE1 promoters chr8 66946079 68339848 67404491 67405490 VXN promoters chr8 66946079 68339848 67578787 67579786 C8orf44 promoters chr8 66946079 68339848 67578787 67579786 C8orf44-SGK3 promoters chr8 66946079 68339848 67623653 67624652 SGK3 promoters chr8 66946079 68339848 67781984 67782983 MCMDC2 promoters chr8 66946079 68339848 67975603 67976602 CSPP1 promoters chr8 66946079 68339848 67090847 67091846 CRH promoters chr8 66946079 68339848 67341213 67342212 RRS1-AS1 promoters chr8 66946079 68339848 67525481 67526480 MYBL1 promoters 174

chr8 66946079 68339848 67579453 67580452 VCPIP1 promoters chr8 66946079 68339848 67680241 67681240 PTTG3P promoters chr8 66946079 68339848 67837778 67838777 SNHG6 promoters chr8 66946079 68339848 67834785 67835784 SNORD87 promoters chr8 66946079 68339848 67874826 67875825 TCF24 promoters chr8 66946079 68339848 67940787 67941786 PPP1R42 promoters chr8 66946079 68339848 67974260 67975259 COPS5 promoters chr8 66946079 68339848 68179678 68180677 ARFGEF1 promoters chr8 66946079 68339848 66955723 66955846 DNAJC5B exons chr8 66946079 68339848 68334405 68334926 CPA6 exons chr8 88211003 90476201 88886297 88887296 DCAF4L2 promoters chr8 88211003 90476201 89339718 89340717 MMP16 promoters chr8 88211003 90476201 88218221 88218366 CNBD1 exons chr2 187402812 188628343 187453790 187454789 ITGAV promoters chr2 187402812 188628343 187557789 187558788 FAM171B promoters chr2 187402812 188628343 187713898 187714897 ZSWIM2 promoters chr2 187402812 188628343 188313022 188314021 CALCRL promoters chr2 187402812 188628343 188419220 188420219 TFPI promoters chr3 135793657 137313340 135968167 135969166 PCCB promoters chr3 135793657 137313340 136536861 136537860 SLC35G2 promoters chr3 135793657 137313340 136580050 136581049 NCK1 promoters chr3 135793657 137313340 136675707 136676706 IL20RB promoters chr3 135793657 137313340 135913311 135914310 MSL2 promoters chr3 135793657 137313340 136471246 136472245 STAG1 promoters chr3 135793657 137313340 135797209 135797295 PPP2R3A exons chr9 94646983 95910508 94894116 94895115 LOC100128076 promoters chr9 94646983 95910508 94902749 94903748 LINC00475 promoters chr9 94646983 95910508 95086741 95087740 CENPP promoters chr9 94646983 95910508 95379332 95380331 LOC100128361 promoters chr9 94646983 95910508 95570893 95571892 ANKRD19P promoters 175

chr9 94646983 95910508 95708601 95709600 FGD3 promoters chr9 94646983 95910508 95819989 95820988 SUSD3 promoters chr9 94646983 95910508 95857450 95858449 CARD19 promoters chr9 94646983 95910508 94711163 94712162 ROR2 promoters chr9 94646983 95910508 94877691 94878690 SPTLC1 promoters chr9 94646983 95910508 95051709 95052708 IARS promoters chr9 94646983 95910508 95054876 95055875 SNORA84 promoters chr9 94646983 95910508 95087877 95088876 NOL8 promoters chr9 94646983 95910508 95166938 95167937 OGN promoters chr9 94646983 95910508 95186837 95187836 OMD promoters chr9 94646983 95910508 95244845 95245844 ASPN promoters chr9 94646983 95910508 95298375 95299374 ECM2 promoters chr9 94646983 95910508 95290341 95291340 MIR4670 promoters chr9 94646983 95910508 95398431 95399430 IPPK promoters chr9 94646983 95910508 95527084 95528083 BICD2 promoters chr9 94646983 95910508 95640321 95641320 ZNF484 promoters chr9 94646983 95910508 95896571 95897570 NINJ1 promoters chr17 28687518 29767086 28704942 28705941 CPD promoters chr17 28687518 29767086 28803426 28804425 GOSR1 promoters chr17 28687518 29767086 28885042 28886041 TBC1D29P promoters chr17 28687518 29767086 28902483 28903482 LRRC37BP1 promoters chr17 28687518 29767086 28950336 28951335 SH3GL1P2 promoters chr17 28687518 29767086 29035626 29036625 SUZ12P1 promoters chr17 28687518 29767086 29158023 29159022 ATAD5 promoters chr17 28687518 29767086 29247754 29248753 ADAP2 promoters chr17 28687518 29767086 29296956 29297955 RNF135 promoters chr17 28687518 29767086 29301353 29302352 DPRXP4 promoters chr17 28687518 29767086 29420945 29421944 NF1 promoters chr17 28687518 29767086 29717642 29718641 RAB11FIP4 promoters chr17 28687518 29767086 29151779 29152778 CRLF3 promoters 176

chr17 28687518 29767086 29233287 29234286 TEFM promoters chr17 28687518 29767086 29421444 29422443 MIR4733 promoters chr17 28687518 29767086 29624381 29625380 OMG promoters chr17 28687518 29767086 29641131 29642130 EVI2B promoters chr17 28687518 29767086 29648768 29649767 EVI2A promoters chr2 24190632 25304287 24231953 24232952 MFSD2B promoters chr2 24190632 25304287 24271584 24272583 FKBP1B promoters chr2 24190632 25304287 24298728 24299727 FAM228B promoters chr2 24190632 25304287 24396531 24397530 FAM228A promoters chr2 24190632 25304287 24786179 24787178 NCOA1 promoters chr2 24190632 25304287 25015175 25016174 CENPO promoters chr2 24190632 25304287 25193981 25194980 DNAJC27-AS1 promoters chr2 24190632 25304287 25263973 25264972 EFR3B promoters chr2 24190632 25304287 24270297 24271296 WDCP promoters chr2 24190632 25304287 24299315 24300314 SF3B6 promoters chr2 24190632 25304287 24307202 24308201 TP53I3 promoters chr2 24190632 25304287 24346152 24347151 PFN4 promoters chr2 24190632 25304287 24583398 24584397 ITSN2 promoters chr2 24190632 25304287 25016252 25017251 PTRHD1 promoters chr2 24190632 25304287 25064537 25065536 ADCY3 promoters chr2 24190632 25304287 25194486 25195485 DNAJC27 promoters chr2 24190632 25304287 24191789 24191905 UBXN2A exons chr2 69135190 70545542 69200705 69201704 GKN1 promoters chr2 69135190 70545542 69239276 69240275 ANTXR1 promoters chr2 69135190 70545542 69329814 69330813 MIR3126 promoters chr2 69135190 70545542 69968127 69969126 ANXA4 promoters chr2 69135190 70545542 70055818 70056817 GMCL1 promoters chr2 69135190 70545542 70120075 70121074 SNRNP27 promoters chr2 69135190 70545542 70141173 70142172 MXD1 promoters chr2 69135190 70545542 70313585 70314584 PCBP1 promoters 177

chr2 69135190 70545542 70483842 70484841 PCYOX1 promoters chr2 69135190 70545542 69180103 69181102 GKN2 promoters chr2 69135190 70545542 69614387 69615386 GFPT1 promoters chr2 69135190 70545542 69664761 69665760 NFU1 promoters chr2 69135190 70545542 69870978 69871977 AAK1 promoters chr2 69135190 70545542 69747304 69748303 SNORA36C promoters chr2 69135190 70545542 70189398 70190397 ASPRV1 promoters chr2 69135190 70545542 70224021 70225020 PCBP1-AS1 promoters chr2 69135190 70545542 70352449 70353448 LINC01816 promoters chr2 69135190 70545542 70418152 70419151 C2orf42 promoters chr2 69135190 70545542 70475780 70476779 TIA1 promoters chr2 69135190 70545542 70520565 70521564 SNRPG promoters chr2 69135190 70545542 70529221 70530220 FAM136A promoters chr13 51892490 53343054 51914168 51915167 SERPINE3 promoters chr13 51892490 53343054 52125725 52126724 MIR4703 promoters chr13 51892490 53343054 52157484 52158483 WDFY2 promoters chr13 51892490 53343054 52435117 52436116 CCDC70 promoters chr13 51892490 53343054 52585523 52586522 ALG11 promoters chr13 51892490 53343054 52585523 52586522 UTP14C promoters chr13 51892490 53343054 53028495 53029494 CKAP2 promoters chr13 51892490 53343054 53062128 53063127 TPTE2P3 promoters chr13 51892490 53343054 53190605 53191604 HNRNPA1L2 promoters chr13 51892490 53343054 53225831 53226830 SUGT1 promoters chr13 51892490 53343054 51922776 51923775 MIR5693 promoters chr13 51892490 53343054 51958828 51959827 INTS6 promoters chr13 51892490 53343054 52378299 52379298 DHRS12 promoters chr13 51892490 53343054 52419287 52420286 TMEM272 promoters chr13 51892490 53343054 52534147 52535146 ATP7B promoters chr13 51892490 53343054 52703215 52704214 NEK5 promoters chr13 51892490 53343054 52731621 52732620 NEK3 promoters 178

chr13 51892490 53343054 52768603 52769602 MRPS31P5 promoters chr13 51892490 53343054 52980630 52981629 THSD1 promoters chr13 51892490 53343054 53024334 53025333 VPS36 promoters chr13 51892490 53343054 53313948 53314947 CNMD promoters chr7 115615760 116450855 115849547 115850546 TES promoters chr7 115615760 116450855 115927127 115928126 CAV2 promoters chr7 115615760 116450855 115928906 115929905 CAV1 promoters chr7 115615760 116450855 116311459 116312458 MET promoters chr7 115615760 116450855 116450124 116451123 CAPZA2 promoters chr7 115615760 116450855 115670868 115671867 TFEC promoters

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 exome sequence data that overlapped with regions affected by si-cnLOH events. We therefore conclude that these events predominantly occur at random regions of the genome.

Discussion

The present study is the first to report that cnLOH is less frequent in the African

American CRCs than in White CRCs. The lower frequency of cnLOH was detected in two independent cohorts of African American CRCs in comparison to a much larger series of White CRCs from TCGA. A lower frequency was observed with TCGA African

American CRCs compared to TCGA White CRCs, arguing against the idea that a detection difference between the array platforms used in the CCCC and TCGA explains the effect. In our multivariate models, race was the dominant predictor of lower cnLOH, whereas age, sex, BMI, and tumor stage did not predict lower cnLOH. This result indicates that African American CRCs are less likely to exhibit this particular form of genomic instability. We found no compensatory increase in copy number gains or losses, consistent with previous studies’ assessment of CNVs between White and African

American CRCs78,79,82. Thus, the results suggest that the overall frequency of chromosome instability is lower in African American CRCs than in White CRCs.

We found that the fold difference in cnLOH frequency was greatly elevated over the average fold difference for specific chromosomes that carry genes important in tumor development, such as chromosome 18. However, a fold difference >1 was seen for almost every chromosome comparing White CRCs to African American CRCs, indicating that the difference is likely the result of a genome-wide effect. In our univariate analysis,

CCCC African American CRCs were associated with less frequent cnLOH events than 180

Mechanisms of Tumorigenesis in African American CRC Chapter 5

TCGA African American CRCs (Supplementary Table 5.4, 2.8% in CCCC CRCs vs

6.5% in TCGA CRCs, p < 0.0001). Differences between the two African American cohorts include older age in TCGA than in the CCCC as well as more stage IV and less stage II disease. After adjusting for age, tumor stage, and other covariates, the association was no longer significant (Table 5.3). Overall, our findings lend credence to the hypothesis that African American CRCs develop via different genetic mechanisms than

White CRCs do. The lower frequency of cnLOH in African American CRCs could reflect innately higher chromosome stability in African American cells. Alternatively, African

American cells could be more tolerant of aneuploidy, although the similar frequencies of

CNVs in White and African American CRCs argues against this.

We are not the first to suggest a mechanistic difference in the development of

CRC in African Americans. Work by our and the Cleveland group identified SNVs in genes in African American CRCs that are rarely observed in White CRCs82,85,86. These independent studies present evidence that the tumorigenic processes may differ by ethnic group, but interpretation of results is limited because the sample size of these studies are relatively small and therefore possibly subject to selection bias.

Is it possible that cnLOH is induced by an environmental carcinogenic exposure?

If this were the case, then we would infer that Whites are more exposed than African

Americans to the inducing agent. However, we are not aware of any known carcinogenic exposures that have been documented as greater or more frequent in Whites compared to

African Americans. Another possibility is that the carcinogenic mechanisms that operate in African Americans favor epigenetic over somatic mutational mechanisms. We recently reported that early-onset CRCs in African Americans more frequently develop by an

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 epigenetic mechanism82, however, we found no association between age and cnLOH, which argues against this idea.

The present study is also the first to describe and characterize a novel type of chromosomal mutation in CRC, the si-cnLOH event. There is, as far as we could find, no previous evidence of si-cnLOH events in CRC. Previous studies in lymphoma have mentioned the existence of si-cnLOH events in leukemias253,254, noting that tumor-normal pairs (i.e., tumor tissue and adjacent uninvolved tissue from the same patient) are necessary for their validation. Tumor-normal pairs are necessary because regions of homozygosity (ROHs) exist in the germline255. An ROH is a relatively small segment of the genome in which there is an excess of contiguous SNVs that are homozygous. ROHs are thought to result from gene-conversion-type recombination events in evolutionary history256,257. We obtained paired samples for every patient included in our CCCC cohort in order to identify tumor-specific si-cnLOH events by removing germline ROHs that were present in the normal patient tissue. We also found that the Affymetrix

GenomeWide 6.0 Array, used in most genomic CNV studies, including TCGA’s CRC study, did not provide adequate resolution to identify si-cnLOH events. Here, we used the

Affymetrix CytoScan HD array, which has higher resolution and less variability, allowing us to detect these previously elusive events.

The 5 of 39 CRCs which exhibited si-cnLOH events each had a differing frequency of events. No si-cnLOH was recurrent, suggesting that it is an event that affects random segments of the genome. A mechanism to generate a tumor-specific si- cnLOH is currently unknown, but the mechanism is very likely the same as that which creates ROHs in the germline. We speculate that si-cnLOH events are generated by a

182

Mechanisms of Tumorigenesis in African American CRC Chapter 5 break-induced replication (BIR) mechanism in which sequences are copied from the homologous chromosome to repair a double strand break (Figure 5.4). BIR has been demonstrated in mammalian cells258–260. BIR that copies from the sister chromatid results in no change in genetic constitution, but when the homologous chromosome is used for repair, an ROH results. Repair using the homologous chromosome should be less likely to occur than using the sister chromatid, which agrees with the general rarity of these events. BIR has been documented in mitosis-associated DNA synthesis—a repair process that is stimulated by conditions of replication stress260.

We recognize that the method of identification for si-cnLOH events is in need of further development to improve sensitivity and specificity of results. Because of this, we do not claim that the current study is fully representative of the actual frequency of si- cnLOH events in CRC. The actual frequency could be higher than what is presented in this study, both in the number of events and in the number of patients affected. Improved methods are needed to meet the challenge of detecting and verifying these small copy- neutral events.

The rate of si-cnLOH mutation events in normal cell division is unknown; however, given the apparently high frequency of events in patient F95 (n = 13) and the range of frequencies seen in the 5 patients exhibiting the si-cnLOH phenotype, it seems plausible that elevated frequencies of si-cnLOH events could be a novel although rare form of chromosome instability and that cancer-specific events may be identified in future studies. While si-cnLOH events appear to be random, we cannot rule out the possibility that some si-cnLOH events drive tumor progression. Further studies are

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Mechanisms of Tumorigenesis in African American CRC Chapter 5

Figure 5.5 Break-induced DNA replication model for the generation of small-interstitial, copy-neutral loss of heterozygosity (si-cnLOH). (I) DNA replication encounters DNA damage that leads to a replication-associated, single-ended DNA break. The letters variants “A” and “a” represent a DNA polymorphism at a locus that is different between the homologous chromosomes. (II) Normally, repair of the replication-associated break is

184

Mechanisms of Tumorigenesis in African American CRC Chapter 5 carried out by homologous recombination using the closely apposite sister chromatid; however, on rare occasions, repair is carried out using the homologous chromosome instead (represented by the blue lines). (III) The homologous recombination protein

RAD51 catalyzes invasion of the single-stranded DNA with a 3’ end, pairing with the homologous sequence and forming a displacement loop. (IV) The 3’ hydroxyl from the invading DNA strand is available for incorporation by DNA polymerase delta. At the same time as polymerase is extending the invading strand, a DNA helicase displaces the nascent DNA behind polymerase. This generates a moving bubble. As the nascent DNA is displaced, the nascent DNA is replicated by lagging strand synthesis. (V) The break- induced replication mechanism copies variants from the homologous chromosome onto the chromosome that suffered the replication-associated DNA break by conservative

DNA synthesis. This copy mechanism maintains copy number and reduces variants to homozygosity. The copy mechanism ends at some point when the invading strand is fully displaced, is recaptured by the sister chromatid, and meets a replication fork that converges upon it from the opposite direction.

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Mechanisms of Tumorigenesis in African American CRC Chapter 5 necessary to determine the role si-cnLOH events play, if any, in colorectal tumorigenesis, and to determine whether the frequency of si-cnLOH events differs by race.

Conclusions

We found that cnLOH is less frequent in African American CRCs than in White

CRCs, suggesting a biological difference based on ancestry in the frequency of cnLOH events in tumorigenesis. The results add to mounting evidence that genetic mechanisms in CRC initiation and progression are different in African Americans compared to

Whites. In addition, we are the first to describe a novel genetic mechanism in CRC based on si-cnLOH, which may comprise a new form of genomic instability.

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Mechanisms of Tumorigenesis in African American CRC Appendix A

Chapter 6

Implications and Future Directions for African American Colorectal Cancer

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Mechanisms of Tumorigenesis in African American CRC Chapter 6

Introduction

Colorectal cancer (CRC) is the third most common cancer in both men and women in the US and the second most common cause of cancer-related death1. The incidence of CRC in African Americans is more than 20% higher than in whites and an even larger difference exists in mortality2. African Americans are more often diagnosed with CRC at an earlier age and tend to present with more advanced disease. Additionally,

African American CRCs have a greater proportion of tumors in the proximal colon3.

Using data collected from an urban low-income cohort, we sought to gain more comprehensive insights into CRCs from African Americans by integrating multiple platforms in a single study. In addition to our data from the Chicago Colorectal Cancer

Consortium (CCCC), we used data publicly available from The Cancer Genome Atlas

(TCGA), a similar study that consisted of data primarily from non-Hispanic White CRCs.

We approached the study of African American CRC from two angles: susceptibility and tumorigenesis. Our goal for addressing susceptibility was to gain a better understanding of potential risk factors and environmental exposures that may help to explain African Americans’ increased risk for colorectal cancer. In looking at the mutational spectrum of African American CRCs, we attempted to determine molecular characteristics unique to African American CRCs. Our two-pronged approach was strengthened by the use of data obtained from an urban, low-income community, which is likely more representative of CRC patients in the African American community who are at greatest risk of being diagnosed with and dying from CRC.

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Mechanisms of Tumorigenesis in African American CRC Chapter 6

Susceptibility

In order to gain insight into environmental risk factors for CRC in African

Americans, we obtained gut microbiome and dietary data from our CCCC cohort.

Because hydrogen sulfide is genotoxic and pro-inflammatory165–167, our studies were driven by the hypothesis that hydrogen sulfide, which is increased in patients with colitis183 and is produced by sulfidogenic bacteria in the gut, increases the risk of colorectal cancer. We found significantly higher abundances of sulfidogenic bacteria in samples from African Americans than in non-Hispanic Whites (Chapter 3). We stratified by disease status in order to identify bacterial species whose abundance was associated with CRC. Despite higher abundances of many sulfidogenic bacteria in African

Americans, we found that of the sulfidogenic species tested, only Bilophila wadsworthia was more abundant in African American CRCs than African American controls. This difference in the abundance of Bilophila wadsworthia was not present in non-Hispanic

Whites.

Because diet could promote increased abundance of Bilophila wadsworthia, we compared dietary factors between ethnic populations. While there was an increased intake of protein and fat in African Americans, race remained the most significantly associated variable in Bilophila wadsworthia abundance after adjustment for covariates and diet. This result suggests that a latent variable that is highly correlated with race exists which explains the higher abundances of sulfidogenic bacteria in the gut of African

Americans. Further studies are required to identify this latent variable. Moreover, it will be important to test for Bilophila wadsworthia in other African American and non-

Hispanic White populations.

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Mechanisms of Tumorigenesis in African American CRC Chapter 6

The next steps in addressing susceptibility in African Americans should rely on a larger set of intermediate phenotypes that could give insight into how genetics and environment interact, such as gut biodiversity, metabolism, and lipidomics. Integrating multiple types of molecular data will assist in finding associations that evaluate important risk factors in CRC development in African Americans.

Tumorigenesis

We used a comprehensive set of mutational analyses to identify genetic factors that are associated with African American CRCs. Our goal was to gain an understanding of how African American CRC etiology might differ from previously captured data from whites. To achieve this goal, we obtained copy number, exome sequencing, and DNA methylation data from the CCCC and TCGA, integrating data where possible.

We found that African Americans from the CCCC have a lower than expected frequency of mutations in APC (Chapter 4), a well-studied gatekeeper gene the mutation of which initiates approximately 80% of CRCs. Comparing CRCs with and without APC mutations, we found that a lack of mutation in APC was associated with younger age of diagnosis, a lower mutational burden, more chromosome stability, and a unique, non-

CIMP DNA methylation signature that was enriched for enhancer hypermethylated regions. We additionally found that African Americans have a reduced frequency of copy neutral loss of heterozygosity (cnLOH), a mechanism associated with the loss of tumor suppressors such as APC and TP53 (Chapter 5).

Taken together, our findings suggest the existence of a novel mutational landscape that drives CRC in African Americans. It is currently unknown whether this landscape is genetic or environmental in origin. One possibility is that common 190

Mechanisms of Tumorigenesis in African American CRC Chapter 6 environmental exposures drive CRC through different mechanisms in African Americans because they have a West African genetic background. However, we cannot exclude the idea that unique environmental exposures related to socioeconomic status may be behind our observations.

In Chapter 2, we hypothesized a novel form of CRC exists that advances rapidly, thus evading screening. It is possible that, if such a CRC subtype exists, that it is related to the DNA methylation signature seen in our APC mutation-negative CRC cohort. More data is necessary to identify candidate driver regions that are negatively affected by differential methylation, and transcriptome data would be invaluable to verify that DNA methylation changes are affecting transcriptional regulation.

Limitations and Future Directions

African Americans remain the ethnic group most at risk of being diagnosed with and dying from CRC. Current studies are small in number, yet consistently show that there are distinct factors for susceptibility and tumorigenesis that deserve further study.

The interpretation of the studies presented here are limited by sample size and incomplete patient overlap. However, the strength in our studies are the comprehensive analyses of a more representative population of African American patients.

Future studies will benefit from larger sample sizes that include more comprehensive environmental and exposure data from an inclusive and diverse cohort of patients representative of the at-risk populations in the US. Intervention studies will be an important step to determining ways to mitigate CRC risk, and community-based participatory research programs will continue to be important for culturally competent education of research findings. 191

Mechanisms of Tumorigenesis in African American CRC Appendix A

Appendix A

Title: Colorectal Cancer Disparity in African Americans Risk Factors and Carcinogenic Mechanisms Author: Gaius J. Augustus, Nathan A. Ellis Publication: The American Journal of Pathology Publisher: Elsevier Date: February 2018 © 2018 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Please note that, as the author of this Elsevier article, you retain the right to include it in a thesis or dissertation, provided it is not published commercially. Permission is not required, but please ensure that you reference the journal as the original source. For more information on this and on your other retained rights, please visit: https://www.elsevier.com/about/our-business/policies/copyright#Authorrights

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Appendix B

Copyright: © 2018 Augustus et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin.

2016;66(1):7-30. doi:10.3322/caac.21332

2. Siegel R, Desantis C, Jemal A. Colorectal cancer statistics, 2014. CA Cancer J

Clin. 2014;64(2):104-117. doi:10.3322/caac.21220

3. Dimou A, Syrigos KN, Saif MW, Wasif Saif Online Submissions M, Wasif Saif

M, Casadesus Rodriguez D. Disparities in Colorectal Cancer in African-

Americans vs Whites: Before and after Diagnosis. Vol 15.; 2009:3734-3743.

doi:10.3748/wjg.15.3734

4. Alexander DD, Waterbor J, Hughes T, Funkhouser E, Grizzle W, Manne U.

African-American and Caucasian disparities in colorectal cancer mortality and

survival by data source: an epidemiologic review. Cancer Biomark.

2007;3(6):301-313.

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2667694&tool=pmcen

trez&rendertype=abstract.

5. Agrawal S, Bhupinderjit A, Bhutani MS, et al. Colorectal cancer in African

Americans. Am J Gastroenterol. 2005;100(3):515-23; discussion 514.

doi:10.1111/j.1572-0241.2005.41829.x

6. Rex DK, Johnson DA, Anderson JC, et al. American College of Gastroenterology

guidelines for colorectal cancer screening 2009 [corrected]. Am J Gastroenterol.

2009;104(3):739-750. doi:10.1038/ajg.2009.104

7. Carethers JM. Screening for Colorectal Cancer in African Americans:

Determinants and Rationale for an Earlier Age to Commence Screening. Dig Dis

207

Mechanisms of Tumorigenesis in African American CRC References

Sci. 2015;60(3):711-721. doi:10.1007/s10620-014-3443-5

8. Powe BD, Faulkenberry R, Harmond L. A Review of Intervention Studies That

Seek to Increase Colorectal Cancer Screening among African-Americans. Vol 25.;

2010:92-99. doi:10.4278/ajhp.080826-LIT-162

9. Ashktorab H, Vilmenay K, Brim H, Laiyemo AO, Kibreab A, Nouraie M.

Colorectal Cancer in Young African Americans: Is It Time to Revisit Guidelines

and Prevention? Dig Dis Sci. 2016;61(10):3026-3030. doi:10.1007/s10620-016-

4207-1

10. Lichtenstein P, Holm N, Verkasalo P, et al. Environmental and heritable factors in

the causation of cancer analyses of cohorts of twins from Sweden, Denmark, and

Finland,. N Engl J Med. 2000;343(2):78-85. doi:10.1016/S0039-6257(00)00165-X

11. Kupfer SS, Ellis NA. Hereditary Colorectal Cancer. In: Coleman WB, Tsongalis

GJ, eds. The Molecular Basis of Human Cancer. 2nd ed. New York, NY: Humana

Press; 2017:381-400. doi:10.1007/978-1-59745-458-2_25

12. Krausova M, Korinek V. Wnt signaling in adult intestinal stem cells and cancer.

Cell Signal. 2014;26:570-579. doi:10.1016/j.cellsig.2013.11.032

13. Poulsen MLM, Bisgaard ML. MUTYH Associated Polyposis (MAP). Vol 9.; 2008.

doi:10.2174/138920208785699562

14. Jiao S, Peters U, Berndt S, et al. Estimating the heritability of colorectal cancer.

Hum Mol Genet. 2014;23(14):3898-3905. doi:10.1093/hmg/ddu087

15. Weber TK, Chin HM, Rodriguez-Bigas M, et al. Novel hMLH1 and hMSH2

germline mutations in African Americans with colorectal cancer. JAMA.

1999;281(24):2316-2320. doi:10.1001/jama.281.24.2316

208

Mechanisms of Tumorigenesis in African American CRC References

16. Inra J a., Steyerberg EW, Grover S, McFarland A, Syngal S, Kastrinos F. Racial

variation in frequency and phenotypes of APC and MUTYH mutations in 6,169

individuals undergoing genetic testing. Genet Med. 2015;17(January):1-7.

doi:10.1038/gim.2014.199

17. Guindalini RSCRSC, Win AKAK, Gulden C, et al. Mutation Spectrum and Risk of

Colorectal Cancer in African American Families with Lynch Syndrome.

Gastroenterology. 2015;149(6):1446-1453. doi:10.1053/j.gastro.2015.07.052

18. Peters U, Bien S, Zubair N. Genetic architecture of colorectal cancer. Gut.

2015;64:gutjnl-2013-306705-. doi:10.1136/gutjnl-2013-306705

19. Wang H, Haiman C a., Burnett T, et al. Fine-mapping of genome-wide association

study-identified risk loci for colorectal cancer in African Americans. Hum Mol

Genet. 2013;22(24):5048-5055. doi:10.1093/hmg/ddt337

20. Kupfer SS, Anderson JR, Hooker S, et al. Genetic heterogeneity in colorectal

cancer associations between African and European Americans. Gastroenterology.

2010;139(5):1677-1685. doi:10.1053/j.gastro.2010.07.038

21. Lemire M, Qu C, Loo LWM, et al. A genome-wide association study for colorectal

cancer identifies a risk locus in 14q23.1. Hum Genet. 2015;134(11-12):1249-1262.

doi:10.1007/s00439-015-1598-6

22. Wang H, Burnett T, Kono S, et al. Trans-ethnic genome-wide association study of

colorectal cancer identifies a new susceptibility locus in VTI1A. Nat Commun.

2014;5:4613. doi:10.1038/ncomms5613

23. Kupfer SS, Skol AD, Hong E, et al. Shared and independent colorectal cancer risk

alleles in TGFβ-related genes in African and European Americans.

209

Mechanisms of Tumorigenesis in African American CRC References

Carcinogenesis. 2014;35(9):2025-2030. doi:10.1093/carcin/bgu088

24. Wang H, Schmit SL, Haiman CA, et al. Novel colon cancer susceptibility variants

identified from a genome-wide association study in African Americans.

2017;140:2728-2733. doi:10.1002/ijc.30687

25. Zeng C, Matsuda K, Jia W-HH, et al. Identification of Susceptibility Loci and

Genes for Colorectal Cancer Risk. Gastroenterology. 2016;150(7):1633-1645.

doi:10.1053/j.gastro.2016.02.076

26. Holick MF, Chen TC. Vitamin D deficiency: A worldwide problem with health

consequences. Am J Clin Nutr. 2008;87(4):1080S-6S. doi:87/4/1080S [pii]

27. Giovannucci E. Vitamin D and Cancer Incidence in the Harvard Cohorts. Vol 19.;

2009:84-88. doi:10.1016/j.annepidem.2007.12.002

28. Woolcott CG, Wilkens LR, Nomura AMY, et al. Plasma 25-hydroxyvitamin D

levels and the risk of colorectal cancer: the multiethnic cohort study. Cancer

Epidemiol Biomarkers Prev. 2010;19(1):130-134. doi:19/1/130

[pii]\r10.1158/1055-9965.EPI-09-0475

29. Fichera A, Little N, Dougherty U, et al. A Vitamin D Analogue Inhibits Colonic

Carcinogenesis in the AOM/DSS Model. J Surg Res. 2007;142(2):239-245.

doi:10.1016/j.jss.2007.02.038

30. Matsuoka LY, Wortsman J, Haddad JG, Kolm P, Hollis BW. Racial Pigmentation

and the Cutaneous Synthesis of Vitamin D. Arch Dermatol. 1991;127(4):536.

doi:10.1001/archderm.1991.04510010104011

31. Grant WB, Peiris AN. Differences in vitamin D status may account for

unexplained disparities in cancer survival rates between African and white

210

Mechanisms of Tumorigenesis in African American CRC References

Americans. Dermatoendocrinol. 2012;4(2):85-94. doi:10.4161/derm.19667

32. Fiscella K, Winters P, Tancredi D, Hendren S, Franks P. Racial disparity in death

from colorectal cancer: Does vitamin D deficiency contribute? Cancer.

2011;117(5):1061-1069. doi:10.1002/cncr.25647

33. Zheng XE, Lipka S, Li T, et al. The relationship of vitamin D status, smoking, and

colorectal adenoma: a retrospective study in an ethnically diverse community. J

Steroid Biochem Mol Biol. 2013;136:280-283. doi:10.1016/j.jsbmb.2012.09.018

34. Lepane CA, Singh G, Spanier-Stiasny JA, Svinarich DM, Rasansky RJ, Hoffman

SMJ. Implications of Serum 25-Hydroxyvitamin D on the Prevalence of

Neoplastic Polyps: A Cross-Sectional Study. Gastroenterol Res. 2011;4(2):43-50.

doi:10.4021/gr291e

35. Ashktorab H, Nguza B, Fatemi M, et al. Case-Control Study of Vitamin D,

dickkopf homolog 1 (DKK1) Gene Methylation, VDR Gene Polymorphism and

the Risk of Colon Adenoma in African Americans. PLoS One. 2011;6(10):e25314.

doi:10.1371/journal.pone.0025314

36. Ahmad II, Trikudanathan G, Feinn R, et al. Low Serum Vitamin D: A Surrogate

Marker for Advanced Colon Adenoma? J Clin Gastroenterol. 2016;00(00):1-5.

doi:10.1097/MCG.0000000000000497

37. Baron JA, Barry EL, Mott LA, et al. A Trial of Calcium and Vitamin D for the

Prevention of Colorectal Adenomas. N Engl J Med. 2015;373(16):1519-1530.

doi:10.1056/NEJMoa1500409

38. Slattery ML, Herrick J, Wolff RK, Caan BJ, Potter JD, Sweeney C. CDX2 VDR

polymorphism and colorectal cancer. Cancer Epidemiol Biomarkers Prev.

211

Mechanisms of Tumorigenesis in African American CRC References

2007;16(12):2752-2755. doi:10.1158/1055-9965.EPI-07-2611

39. Kupfer SS, Anderson JR, Ludvik AE, et al. Genetic associations in the vitamin D

receptor and colorectal cancer in African Americans and Caucasians. Ashktorab H,

ed. PLoS One. 2011;6(10):e26123. doi:10.1371/journal.pone.0026123

40. Pibiri F, Kittles RA, Sandler RS, et al. Genetic variation in vitamin D-related

genes and risk of colorectal cancer in African Americans. Cancer Causes Control.

2014;25(5):561-570. doi:10.1007/s10552-014-0361-y

41. Hiraki LT, Qu C, Hutter CM, et al. Genetic Predictors of Circulating 25-

Hydroxyvitamin D and Risk of Colorectal Cancer. Cancer Epidemiol Biomarkers

Prev. 2013;22(11):2037-2046. doi:10.1158/1055-9965.EPI-13-0209

42. Barry EL, Peacock JL, Rees JR, et al. Vitamin D Receptor Genotype, Vitamin D 3

Supplementation, and Risk of Colorectal Adenomas. JAMA Oncol.

2016;10(4):e0124339. doi:10.1001/jamaoncol.2016.5917

43. Alleyne D, Witonsky DB, Mapes B, et al. Colonic transcriptional response to

1a,25(OH) 2 vitamin D 3 in African- and European-Americans. 2017.

doi:10.1016/j.jsbmb.2017.02.001

44. Hulur I, Gamazon ER, Skol AD, et al. Enrichment of inflammatory bowel disease

and colorectal cancer risk variants in colon expression quantitative trait loci. BMC

Genomics. 2015;16:138. doi:10.1186/s12864-015-1292-z

45. Moradi T, Delfino RJ, Bergström SR, Yu ES, Adami HO, Yuen J. Cancer risk

among Scandinavian immigrants in the US and Scandinavian residents compared

with US whites, 1973-89. Eur J cancer Prev. 1998;7(2):117-125.

http://www.ncbi.nlm.nih.gov/pubmed/9818773. Accessed April 17, 2017.

212

Mechanisms of Tumorigenesis in African American CRC References

46. Flood DM, Weiss NS, Cook LS, Emerson JC, Schwartz SM, Potter JD. Colorectal

cancer incidence in Asian migrants to the United States and their descendants.

Cancer Causes Control. 2000;11(5):403-411.

http://www.ncbi.nlm.nih.gov/pubmed/10877333. Accessed April 17, 2017.

47. Willett WC, Stampfer MJ. Current Evidence on Healthy Eating. Annu Rev Public

Health. 2013;34(1):77-95. doi:10.1146/annurev-publhealth-031811-124646

48. Potter JD. Nutritional epidemiology-there’s life in the old dog yet! Cancer

Epidemiol Biomarkers Prev. 2015;24(2):323-330. doi:10.1158/1055-9965.EPI-14-

1327

49. Ananthakrishnan AN, Du M, Berndt SI, et al. Red meat intake, NAT2, and risk of

colorectal cancer: A pooled analysis of 11 studies. Cancer Epidemiol Biomarkers

Prev. 2015;24(1):198-205. doi:10.1158/1055-9965.EPI-14-0897

50. Chan DSM, Lau R, Aune D, et al. Red and processed meat and colorectal cancer

incidence: Meta-analysis of prospective studies. PLoS One. 2011;6(6).

doi:10.1371/journal.pone.0020456

51. Satia JA, Tseng M, Galanko JA, Martin C, Sandler RS. Dietary patterns and colon

cancer risk in Whites and African Americans in the North Carolina Colon Cancer

Study. Nutr Cancer. 2009;61(2):179-193. doi:10.1080/01635580802419806

52. Williams CD, Satia JA, Adair LS, et al. Dietary patterns, food groups, and rectal

cancer risk in whites and African-Americans. Cancer Epidemiol Biomarkers Prev.

2009;18(5):1552-1561. doi:10.1158/1055-9965.EPI-08-1146

53. Gill SR, Pop M, Deboy RT, et al. Metagenomic analysis of the human distal gut

microbiome. Science (80- ). 2006;312(5778):1355-1359.

213

Mechanisms of Tumorigenesis in African American CRC References

doi:10.1126/science.1124234

54. Hooper L V, Gordon JI. Commensal host-bacterial relationships in the gut. Science

(80- ). 2001;292(5519):1115-1118. doi:10.1126/science.1058709

55. Drewes JL, Housseau F, Sears CL. Sporadic colorectal cancer: microbial

contributors to disease prevention, development and therapy. Br J Cancer.

2016;115(3):273-280. doi:10.1038/bjc.2016.189

56. Sears CL, Garrett WS. Microbes, microbiota, and colon cancer. Cell Host

Microbe. 2014;15(3):317-328. doi:10.1016/j.chom.2014.02.007

57. O’Keefe SJD, Li J V, Lahti L, et al. Fat, fibre and cancer risk in African

Americans and rural Africans. Nat Commun. 2015;6(May 2014):6342.

doi:10.1038/ncomms7342

58. Ridlon JM, Harris SC, Bhowmik S, Kang DJ, Hylemon PB. Consequences of bile

salt biotransformations by intestinal bacteria. Gut Microbes. 2016;7(1):22-39.

doi:10.1080/19490976.2015.1127483

59. Tsuei J, Chau T, Mills D, Wan Y-JY. Bile acid dysregulation, gut dysbiosis, and

gastrointestinal cancer. Exp Biol Med. 2014;239(11):1489-1504.

doi:10.1177/1535370214538743

60. Yazici C, Wolf PGPG, Kim H, et al. Race-dependent association of sulfidogenic

bacteria with colorectal cancer. Gut. 2017;66(11):gutjnl-2016-313321.

doi:10.1136/gutjnl-2016-313321

61. Goodwin PJ, Stambolic V. Impact of the obesity epidemic on cancer. Annu Rev

Med. 2015;66:281-296. doi:10.1146/annurev-med-051613-012328

62. Iyengar NM, Hudis CA, Dannenberg AJ. Obesity and cancer: local and systemic

214

Mechanisms of Tumorigenesis in African American CRC References

mechanisms. Annu Rev Med. 2015;66(1):297-309. doi:10.1146/annurev-med-

050913-022228

63. Pereira MA, Kartashov AI, Ebbeling CB, et al. Fast-food habits, weight gain, and

insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet.

2005;365(9453):36-42. doi:10.1016/S0140-6736(04)17663-0

64. Harris MI. Noninsulin-dependent diabetes mellitus in black and white Americans.

Diabetes Metab Rev. 1990;6(2):71-90.

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt

=Citation&list_uids=2198151.

65. Tsai CJ, Giovannucci EL. Hyperinsulinemia, insulin resistance, vitamin d, and

colorectal cancer among whites and African Americans. Dig Dis Sci.

2012;57(10):2497-2503. doi:10.1007/s10620-012-2198-0

66. Gaillard T, Schuster D, Osei K. Metabolic syndrome in black people of the African

diaspora: The paradox of current classification, definition and criteria. In: Ethnicity

and Disease. Vol 19. ; 2009.

67. Desantis CE, Siegel RL, Sauer AG, et al. Cancer statistics for African Americans,

2016: Progress and opportunities in reducing racial disparities. CA Cancer J Clin.

2016;66:290-308. doi:10.3322/caac.21340.

68. Vilar E, Gruber SB. Microsatellite instability in colorectal cancer-the stable

evidence. Nat Rev Clin Oncol. 2010;7(3):153-162. doi:10.1038/nrclinonc.2009.237

69. Le DT, Uram JN, Wang H, et al. PD-1 Blockade in Tumors with Mismatch-Repair

Deficiency. n engl j med. 2015;372(26):2509-2529. doi:10.1056/NEJMoa1500596

70. Ashktorab H, Smoot DT, Carethers JM, et al. High incidence of microsatellite

215

Mechanisms of Tumorigenesis in African American CRC References

instability in colorectal cancer from African Americans. Clin Cancer Res.

2003;9(3):1112-1117.

71. Ashktorab H, Smoot DT, Farzanmehr H, et al. Clinicopathological features and

microsatellite instability (MSI) in colorectal cancers from African Americans. Int J

Cancer. 2005;116(6):914-919. doi:10.1002/ijc.21062

72. Brim H, Mokarram P, Naghibalhossaini F, et al. Impact of BRAF, MLH1 on the

incidence of microsatellite instability high colorectal cancer in populations based

study. Mol Cancer. 2008;7:68. doi:10.1186/1476-4598-7-68

73. Sylvester BE, Huo D, Khramtsov A, et al. Molecular analysis of colorectal tumors

within a diverse patient cohort at a single institution. Clin Cancer Res.

2012;18(2):350-359. doi:10.1158/1078-0432.CCR-11-1397

74. Carethers JM, Murali B, Yang B, et al. Influence of race on microsatellite

instability and CD8+ T cell infiltration in colon cancer. PLoS One. 2014;9(6).

doi:10.1371/journal.pone.0100461

75. Xicola RM, Gagnon M, Clark JR, et al. Excess of proximal microsatellite-stable

colorectal cancer in african americans from a multiethnic study. Clin Cancer Res.

2014;20(18):4962-4970. doi:10.1158/1078-0432.CCR-14-0353

76. Eaton AM, Sandler R, Carethers JM, Millikan RC, Galanko J, Keku TO. 5,10-

Methylenetetrahydrofolate reductase 677 and 1298 polymorphisms, folate intake,

and microsatellite instability in colon cancer. Cancer Epidemiol Biomarkers Prev.

2005;14(8):2023-2029. doi:10.1158/1055-9965.EPI-05-0131

77. Ashktorab H, Ahuja S, Kannan L, et al. A meta-analysis of MSI frequency and

race in colorectal cancer. Oncotarget. 2016;7(23):34546-34557.

216

Mechanisms of Tumorigenesis in African American CRC References

doi:10.18632/oncotarget.8945

78. Ashktorab H, Schaffer AA, Daremipouran M, et al. Distinct genetic alterations in

colorectal cancer. PLoS One. 2010;5(1). doi:10.1371/journal.pone.0008879

79. Varadan V, Singh S, Nosrati A, et al. ENVE: a novel computational framework

characterizes copy-number mutational landscapes in African American colon

cancers. Genome Med. 2015;7(1):69. doi:10.1186/s13073-015-0192-9

80. Brim H, Lee E, Abu-Asab MS, et al. Genomic aberrations in an African American

colorectal cancer cohort reveals a MSI-specific profile and chromosome X

amplification in male patients. PLoS One. 2012;7(8).

doi:10.1371/journal.pone.0040392

81. Brim H, Abu-Asab MS, Nouraie M, et al. An integrative CGH, MSI and candidate

genes methylation analysis of colorectal tumors. Peng D, ed. PLoS One.

2014;9(1):e82185. doi:10.1371/journal.pone.0082185

82. Xicola RM, Manojlovic Z, Augustus GJ, et al. Lack of APC somatic mutation is

associated with early-onset colorectal cancer in African Americans.

Carcinogenesis. 2018;39(11):1331-1341. doi:10.1093/carcin/bgy122

83. Haugen AC, Goel A, Yamada K, et al. Genetic instability caused by loss of MutS

homologue 3 in human colorectal cancer. Cancer Res. 2008;68(20):8465-8472.

doi:10.1158/0008-5472.CAN-08-0002

84. Devaraj B, Lee A, Cabrera BL, et al. Relationship of EMAST and Microsatellite

Instability Among Patients with Rectal Cancer. J Gastrointest Surg.

2010;14(10):1521-1528. doi:10.1007/s11605-010-1340-6

85. Ashktorab H, Daremipouran M, Devaney J, et al. Identification of novel mutations

217

Mechanisms of Tumorigenesis in African American CRC References

by exome sequencing in African American colorectal cancer patients. Cancer.

2015;121(1):34-42. doi:10.1002/cncr.28922

86. Guda K, Veigl ML, Varadan V, et al. Novel recurrently mutated genes in African

American colon cancers. Proc Natl Acad Sci U S A. 2015;112(4):1149-1154.

doi:10.1073/pnas.1417064112

87. Wang Z, Li L, Guda K, et al. Adverse Clinical Outcome Associated With

Mutations That Typify African American Colorectal Cancers. J Natl Cancer Inst.

2016;108(12):djw164. doi:10.1093/jnci/djw164

88. Mokarram P, Kumar K, Brim H, et al. Distinct high-profile methylated genes in

colorectal cancer. Zanger U, ed. PLoS One. 2009;4(9):e7012.

doi:10.1371/journal.pone.0007012

89. Katkoori VR, Jia X, Shanmugam C, et al. Prognostic Significance of p53 Codon

72 Polymorphism Differs with Race in Colorectal Adenocarcinoma. Clin Cancer

Res. 2009;15(7):2406-2416. doi:10.1158/1078-0432.CCR-08-1719

90. Kang M, Shen XJ, Kim S, et al. Somatic gene mutations in African Americans

may predict worse outcomes in colorectal cancer. Cancer Biomarkers.

2013;13(5):359-366. doi:10.3233/CBM-130366

91. Fatemi M, Paul TA, Brodeur GM, Shokrani B, Brim H, Ashktorab H. Epigenetic

silencing of CHD5, a novel tumor-suppressor gene, occurs in early colorectal

cancer stages. Cancer. 2014;120(2):172-180. doi:10.1002/cncr.28316

92. Ashktorab H, Rahi H, Wansley D, et al. Toward a comprehensive and systematic

methylome signature in colorectal cancers. Epigenetics. 2013;8(8):807-815.

doi:10.4161/epi.25497

218

Mechanisms of Tumorigenesis in African American CRC References

93. Ashktorab H, Daremipouran M, Goel A, et al. DNA methylome profiling identifies

novel methylated genes in African American patients with colorectal neoplasia.

Epigenetics. 2014;9(4):503-512. doi:10.4161/epi.27644

94. Peeters PJHL, Bazelier MT, Leufkens HGM, de Vries F, De Bruin ML. The Risk

of Colorectal Cancer in Patients With Type 2 Diabetes: Associations With

Treatment Stage and Obesity. Diabetes Care. 2015;38:495-502. doi:10.2337/dc14-

1175

95. Wang X, Ji P, Zhang Y, et al. Aberrant DNA methylation: Implications in racial

health disparity. PLoS One. 2016;11(4):1-16. doi:10.1371/journal.pone.0153125

96. Guinney J, Dienstmann R, Wang X, et al. The consensus molecular subtypes of

colorectal cancer. Nat Med. 2015;21(11):1350-1356. doi:10.1038/nm.3967

97. Jovov B, Araujo-Perez F, Sigel CS, et al. Differential gene expression between

African American and European American colorectal cancer patients. PLoS One.

2012;7(1):e30168. doi:10.1371/journal.pone.0030168

98. Bovell LC, Shanmugam C, Putcha BDK, et al. The prognostic value of

MicroRNAs varies with patient race/ethnicity and stage of colorectal cancer. Clin

Cancer Res. 2013;19(14):3955-3965. doi:10.1158/1078-0432.CCR-12-3302

99. Li E, Ji P, Ouyang N, et al. Differential expression of miRNAs in colon cancer

between African and Caucasian Americans: Implications for cancer racial health

disparities. Int J Oncol. 2014;45(2):587-594. doi:10.3892/ijo.2014.2469

100. Ogino S, Chan AT, Fuchs CS, Giovannucci E. Molecular pathological

epidemiology of colorectal neoplasia: an emerging transdisciplinary and

interdisciplinary field. Gut. 2011;60(3):397-411. doi:10.1136/gut.2010.217182

219

Mechanisms of Tumorigenesis in African American CRC References

101. Rabeneck L, El-Serag H, Davila J, Sandler R. Outcomes of colorectal cancer in the

United States: no change in survival (1986-1997). Am J Gastroenerol.

2003;98(2):471-477.

102. James AS, Campbell MK, DeVellis B, Reedy J, Carr C, Sandler RS. Health

behavior correlates among colon cancer survivors: NC STRIDES baseline results.

Am J Health Behav. 2006;30(6):720-730. doi:10.5555/ajhb.2006.30.6.720

103. Polite BN, Dignam JJ, Olopade OI. Colorectal cancer model of health disparities:

understanding mortality differences in minority populations. J Clin Oncol.

2006;24(14):2179-2187. doi:10.1200/JCO.2005.05.4775

104. Alexander D, Chatla C, Funkhouser E, Meleth S, Grizzle WE, Manne U.

Postsurgical disparity in survival between African Americans and Caucasians with

colonic adenocarcinoma. Cancer. 2004;101(1):66-76. doi:10.1002/cncr.20337

105. Alexander D, Jhala N, Chatla C, et al. High-grade tumor differentiation is an

indicator of poor prognosis in African Americans with colonic adenocarcinomas.

Cancer. 2005;103(10):2163-2170. doi:10.1002/cncr.21021

106. Hines RB, Shanmugam C, Waterbor JW, et al. Effect of comorbidity and body

mass index on the survival of African-American and Caucasian patients with colon

cancer. Cancer. 2009;115(24):5798-5806. doi:10.1002/cncr.24598

107. Manne U, Weiss HL, Myers RB, et al. Nuclear accumulation of p53 in colorectal

adenocarcinoma prognostic importance differs with race and location of the tumor.

Cancer. 1998;83(12):2456-2467. doi:10.1002/(SICI)1097-

0142(19981215)83:12<2456::AID-CNCR8>3.0.CO;2-5

108. Grizzle WE, Manne U, Weiss HL, Jhala N, Talley L. Molecular staging of

220

Mechanisms of Tumorigenesis in African American CRC References

colorectal cancer in African-American and caucasian patients using phenotypic

expression of p53, Bcl-2, MUC-1 and p27kip-1. Int J Cancer. 2002;97(4):403-409.

doi:10.1002/ijc.1617

109. Manne U, Weiss HL, Grizzle WE. Racial differences in the prognostic usefulness

of MUC1 and MUC2 in colorectal adenocarcinomas. Clin Cancer Res.

2000;6(10):4017-4025.

110. Manne U, Weiss HL, Grizzle WE. Bcl-2 expression is associated with improved

prognosis in patients with distal colorectal adenocarcinomas. Int J Cancer.

2000;89(5):423-430. doi:10.1002/1097-0215(20000920)89:5<423::AID-

IJC5>3.0.CO;2-T [pii]

111. Manne U, Jhala NC, Jones J, et al. Prognostic significance of p27(kip-1)

expression in colorectal adenocarcinomas is associated with tumor stage. Clin

Cancer Res. 2004;10(5):1743-1752.

http://www.ncbi.nlm.nih.gov/pubmed/15014027.

112. Jones BA, Christensen AR, Wise JP, Yu H. Glutathione S-transferase

polymorphisms and survival in African-American and White colorectal cancer

patients. Cancer Epidemiol. 2009;33(3-4):249-256.

doi:10.1016/j.canep.2009.08.004

113. Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin.

2017;67:7-30. doi:10.3322/caac.21387

114. Leslie A, Carey FA, Pratt NR, Steele RJC. The colorectal adenoma-carcinoma

sequence. Br J Surg. 2002;89(7):845-860. doi:10.1046/j.1365-2168.2002.02120.x

115. US Preventive Services Task Force. Screening for Colorectal Cancer. JAMA.

221

Mechanisms of Tumorigenesis in African American CRC References

2016;315(23):2564-2575. doi:10.1001/jama.2016.5989

116. Kaminski MF, Wieszczy P, Rupinski M, et al. Increased Rate of Adenoma

Detection Associates With Reduced Risk of Colorectal Cancer and Death.

Gastroenterology. 2017;153(1):98-105. doi:10.1053/j.gastro.2017.04.006

117. U.S. Cancer Statistics Working Group. United States Cancer Statistics: 1999–2014

Incidence and Mortality Web-Based Report. Atlanta (GA); 2017.

http://www.cdc.gov/uscs.

118. Shaukat A, Mongin SJ, Geisser MS, et al. Long-term mortality after screening for

colorectal cancer. N Engl J Med. 2013;369(12):1106-1114.

doi:10.1056/NEJMoa1300720

119. Nishihara R, Wu K, Lochhead P, et al. Long-Term Colorectal-Cancer Incidence

and Mortality after Lower Endoscopy. N Engl J Med. 2013;369(12):1095-1105.

doi:10.1056/NEJMoa1301969

120. Siegel RL, Miller KD, Fedewa SA, et al. Colorectal cancer statistics, 2017. CA

Cancer J Clin. 2017;67(3):177-193. doi:10.3322/caac.21395

121. Coughlin SS, Blumenthal DS, Seay SJ, Smith SA. Toward the Elimination of

Colorectal Cancer Disparities Among African Americans. J Racial Ethn Heal

Disparities. 2016;3(4):555-564. doi:10.1007/s40615-015-0174-z

122. Jerant AF, Fenton JJ, Franks P. Determinants of Racial/Ethnic Colorectal Cancer

Screening Disparities. Arch Intern Med. 2008;168(12):1317.

doi:10.1001/archinte.168.12.1317

123. Augustus GJ, Ellis NA. Race in Cancer Health Disparities Theme Issue Colorectal

Cancer Disparity in African Americans: Risk Factors and Carcinogenic

222

Mechanisms of Tumorigenesis in African American CRC References

Mechanisms. Am J Pathol. November 2017. doi:10.1016/J.AJPATH.2017.07.023

124. Siegel RL, Fedewa SA, Anderson WF, et al. Colorectal Cancer Incidence Patterns

in the United States, 1974–2013. J Natl Cancer Inst. 2017;109(8):djw322.

doi:10.1093/jnci/djw322

125. Centers for Disease Control and Prevention (CDC). Trends in cancer screening--

United States, 1987 and 1992. MMWR. 1996;45(3):57-61.

http://www.ncbi.nlm.nih.gov/pubmed/8544808. Accessed April 13, 2018.

126. Centers for Disease Control and Prevention (CDC). Use of colorectal cancer tests--

United States, 2002, 2004, and 2006. MMWR. 2008;57(10):253-258.

127. Brenner H, Stock C, Hoffmeister M. Effect of screening sigmoidoscopy and

screening colonoscopy on colorectal cancer incidence and mortality: systematic

review and meta-analysis of randomised controlled trials and observational studies.

Br Med J. 2014;348:g2467. doi:10.1136/bmj.g2467

128. Austin H, Henley SJ, King J, Richardson LC, Eheman C. Changes in colorectal

cancer incidence rates in young and older adults in the United States: what does it

tell us about screening HHS Public Access. Cancer Causes Control.

2014;25(2):191-201. doi:10.1007/s10552-013-0321-y

129. Friis R, Sellers T. Epidemiology for Public Health Practice. 5th ed. Burlington,

MA: Jones & Bartlett Learning; 2014.

130. Croswell JM, Ransohoff DF, Kramer BS. Principles of Cancer Screening: Lessons

from History and Study Design Issues. Semin Oncol. 2010;37(3):202-215.

doi:10.1053/j.seminoncol.2010.05.006.Principles

131. Thibodeau S, Bren G, Schaid D. Microsatellite Instability in Cancer of the

223

Mechanisms of Tumorigenesis in African American CRC References

Proximal Colon. Science (80- ). 1993;260(5109):816-819.

doi:10.1126/science.8484122

132. Kane MF, Loda M, Gaida GM, et al. Methylation of the hMLH1 promoter

correlates with lack of expression of hMLH1 in sporadic colon tumors and

mismatch repair-defective human tumor cell lines. Cancer Res. 1997;57(5):808-

811. http://www.ncbi.nlm.nih.gov/pubmed/9041175. Accessed November 21,

2017.

133. Herman JG, Umar A, Polyak K, et al. Incidence and functional consequences of

hMLH1 promoter hypermethylation in colorectal carcinoma. Genetics.

1998;95:6870-6875. http://www.pnas.org/content/95/12/6870.full.pdf. Accessed

November 21, 2017.

134. Cunningham JM, Christensen ER, Tester DJ, et al. Hypermethylation of the

hMLH1 promoter in colon cancer with microsatellite instability. Cancer Res.

1998;58(15):3455-3460. http://www.ncbi.nlm.nih.gov/pubmed/9699680. Accessed

November 21, 2017.

135. Veigl ML, Kasturi L, Olechnowicz J, et al. Biallelic inactivation of hMLH1 by

epigenetic gene silencing, a novel mechanism causing human MSI cancers. Genet

Contrib by Paul L Modrich. 1998;95:8698-8702.

http://www.pnas.org/content/95/15/8698.full.pdf. Accessed November 21, 2017.

136. Weisenberger DJ, Siegmund KD, Campan M, et al. CpG island methylator

phenotype underlies sporadic microsatellite instability and is tightly associated

with BRAF mutation in colorectal cancer. Nat Genet. 2006;38(7):787-793.

doi:10.1038/ng1834

224

Mechanisms of Tumorigenesis in African American CRC References

137. Arain M a, Sawhney M, Sheikh S, et al. CIMP status of interval colon cancers:

another piece to the puzzle. Am J Gastroenterol. 2010;105(5):1189-1195.

doi:10.1038/ajg.2009.699

138. Chao A, Gilliland F, Willman C, et al. Patient and tumor characteristics of colon

cancers with microsatellite instability: A population-based study. Cancer

Epidemiol Biomarkers Prev. 2000;9(6):539-544.

139. Bond CE, McKeone DM, Kalimutho M, et al. RNF43 and ZNRF3 are commonly

altered in serrated pathway colorectal tumorigenesis. Oncotarget.

2016;7(43):70589-70600. doi:10.18632/oncotarget.12130

140. Edelstein DL, Axilbund J, Baxter M, et al. Rapid development of colorectal

neoplasia in patients with Lynch syndrome. Clin Gastroenterol Hepatol.

2011;9(4):340-343. doi:10.1016/j.cgh.2010.10.033

141. Syngal S, Brand RE, Church JM, et al. ACG clinical guideline: Genetic testing and

management of hereditary gastrointestinal cancer syndromes. Am J Gastroenterol.

2015;110(2):223-62; quiz 263. doi:10.1038/ajg.2014.435

142. Colditz GA, Wolin KY, Gehlert S. Applying What We Know to Accelerate Cancer

Prevention. Sci Transl Med. 2012;4(127):127rv4-127rv4.

doi:10.1126/scitranslmed.3003218

143. Emmons KM, Colditz GA. Realizing the Potential of Cancer Prevention — The

Role of Implementation Science. N Engl J Med. 2017;376(10):986-990.

doi:10.1056/NEJMsb1609101

144. Pabby A, Schoen RE, Weissfeld JL, et al. Analysis of colorectal cancer occurrence

during surveillance colonoscopy in the dietary Polyp Prevention Trial. Gastrointest

225

Mechanisms of Tumorigenesis in African American CRC References

Endosc. 2005;61(3):385-391. http://www.giejournal.org/article/S0016-

5107(04)02765-8/pdf. Accessed January 21, 2018.

145. Robertson DJ, Lieberman DA, Winawer SJ, et al. Colorectal cancers soon after

colonoscopy: a pooled multicohort analysis. Gut. 2014;63(6):949-956.

doi:10.1136/gutjnl-2012-303796.Colorectal

146. Song M, Giovannucci E. Preventable Incidence and Mortality of Carcinoma

Associated With Lifestyle Factors Among White Adults in the United States.

JAMA Oncol. 2016;2(9):1154-1161. doi:10.1001/jamaoncol.2016.0843

147. Sanduleanu S, Masclee AM, Meijer GA. Interval cancers after colonoscopy—

insights and recommendations. Nat Publ Gr. 2012;9(9).

doi:10.1038/nrgastro.2012.136

148. Welch HG, Robertson DJ. Colorectal Cancer on the Decline — Why Screening

Can’t Explain It All. N Engl J Med. 2016;374(17):1605-1607.

doi:10.1056/NEJMp1600448

149. American Cancer Society. Cancer Facts & Figures 2016. Cancer Facts Fig 2016.

2016. doi:10.1097/01.NNR.0000289503.22414.79

150. Cho M, Carter J, Harari S, Pei Z. The interrelationships of the gut microbiome and

inflammation in colorectal carcinogenesis. Clin Lab Med. 2014.

doi:10.1016/j.cll.2014.08.002

151. Schulz MD, Atay Ç, Heringer J, et al. High-fat-diet-mediated dysbiosis promotes

intestinal carcinogenesis independently of obesity. Nature. 2014.

doi:10.1038/nature13398

152. Kostic AD, Chun E, Robertson L, et al. Fusobacterium nucleatum Potentiates

226

Mechanisms of Tumorigenesis in African American CRC References

Intestinal Tumorigenesis and Modulates the Tumor-Immune Microenvironment.

Cell Host Microbe. 2013. doi:10.1016/j.chom.2013.07.007

153. Gao Z, Guo B, Gao R, Zhu Q, Qin H. Microbiota disbiosis is associated with

colorectal cancer. Front Microbiol. 2015. doi:10.3389/fmicb.2015.00020

154. Kostic AD, Gevers D, Pedamallu CS, et al. Genomic analysis identifies association

of Fusobacterium with colorectal carcinoma. Genome Res. 2012.

doi:10.1101/gr.126573.111

155. Warren RL, Freeman DJ, Pleasance S, et al. Co-occurrence of anaerobic bacteria

in colorectal carcinomas. Microbiome. 2013. doi:10.1186/2049-2618-1-16

156. Wang T, Cai G, Qiu Y, et al. Structural segregation of gut microbiota between

colorectal cancer patients and healthy volunteers. ISME J. 2012.

doi:10.1038/ismej.2011.109

157. Chen W, Liu F, Ling Z, Tong X, Xiang C. Human intestinal lumen and mucosa-

associated microbiota in patients with colorectal cancer. PLoS One.

2012;7(6):e39743. doi:10.1371/journal.pone.0039743

158. Castellarin M, Warren RL, Freeman JD, et al. Fusobacterium nucleatum infection

is prevalent in human colorectal carcinoma. Genome Res. 2012.

doi:10.1101/gr.126516.111

159. Zeller G, Tap J, Voigt AY, et al. Potential of fecal microbiota for early-stage

detection of colorectal cancer. Mol Syst Biol. 2014. doi:10.15252/msb.20145645

160. Zackular JP, Rogers MAM, Ruffin MT, Schloss PD. The human gut microbiome

as a screening tool for colorectal cancer. Cancer Prev Res. 2014.

doi:10.1158/1940-6207.CAPR-14-0129

227

Mechanisms of Tumorigenesis in African American CRC References

161. Pitcher MCL, Beatty ER, Cummings JH. The contribution of sulphate reducing

bacteria and 5-aminosalicylic acid to faecal sulphide in patients with ulcerative

colitis. Gut. 2000. doi:10.1136/gut.46.1.64

162. Gibson GR, Cummings JH, Macfarlane GT. Growth and activities of sulphate‐

reducing bacteria in gut contents of healthy subjects and patients with ulcerative

colitis. FEMS Microbiol Lett. 1991. doi:10.1111/j.1574-6968.1991.tb04799.x

163. Roediger WEW, Moore J, Babidge W. Colonic sulfide in pathogenesis and

treatment of ulcerative colitis. Dig Dis Sci. 1997. doi:10.1023/A:1018851723920

164. Deplancke B, Gaskins HR. Hydrogen sulfide induces serum-independent cell cycle

entry in nontransformed rat intestinal epithelial cells. FASEB J. 2003.

165. Attene-Ramos MS, Nava GM, Muellner MG, Wagner ED, Plewa MJ, Gaskins HR.

DNA damage and toxicogenomic analyses of hydrogen sulfide in human intestinal

epithelial FHs 74 int cells. Environ Mol Mutagen. 2010. doi:10.1002/em.20546

166. Attene-Ramos MS. Evidence That Hydrogen Sulfide Is a Genotoxic Agent. Mol

Cancer Res. 2006. doi:10.1158/1541-7786.mcr-05-0126

167. Attene-Ramos MS, Wagner ED, Gaskins HR, Plewa MJ. Hydrogen Sulfide

Induces Direct Radical-Associated DNA Damage. Mol Cancer Res. 2007.

doi:10.1158/1541-7786.mcr-06-0439

168. Bolstad AI, Jensen HB, Bakken V. Taxonomy, biology, and periodontal aspects of

Fusobacterium nucleatum. Clin Microbiol Rev. 1996.

169. Baron EJ. Bilophila wadsworthia: A unique gram-negative anaerobic rod. In:

Anaerobe. ; 1997. doi:10.1006/anae.1997.0075

170. Carbonero F, Benefiel AC, Alizadeh-Ghamsari AH, Gaskins HR. Microbial

228

Mechanisms of Tumorigenesis in African American CRC References

pathways in colonic sulfur metabolism and links with health and disease. Front

Physiol. 2012. doi:10.3389/fphys.2012.00448

171. Shen W, Wolf PG, Carbonero F, et al. Intestinal and Systemic Inflammatory

Responses Are Positively Associated with Sulfidogenic Bacteria Abundance in

High-Fat–Fed Male C57BL/6J Mice. J Nutr. 2014. doi:10.3945/jn.114.194332

172. Daly K, Sharp RJ, McCarthy AJ. Development of oligonucleotide probes and PCR

primers for detecting phylogenetic subgroups of sulfate-reducing bacteria.

Microbiology. 2000. doi:10.1099/00221287-146-7-1693

173. Klein M, Friedrich M, Roger AJ, et al. Multiple lateral transfers of dissimilatory

sulfite reductase genes between major lineages of sulfate-reducing prokaryotes. J

Bacteriol. 2001. doi:10.1128/JB.183.20.6028-6035.2001

174. Block G, Hartman AM, Naughton D. A reduced dietary questionnaire:

Development and validation. Epidemiology. 1990. doi:10.1097/00001648-

199001000-00013

175. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in

epidemiologic studies. In: American Journal of Clinical Nutrition. ; 1997.

doi:10.1093/ajcn/65.4.1220S

176. R Development Core Team. R: A Language and Environment for Statistical

Computing. R Found Stat Comput. 2016. doi:10.1007/978-3-540-74686-7

177. Baptiste A. gridExtra: Miscellaneous Functions for “Grid” Graphics. 2016.

https://cran.r-project.org/package=gridExtra.

178. Wickham H. tidyverse: Easily Install and Load “Tidyverse” Packages. R Packag

version 1 0 0 https//CRANR-project.org/package=tidyverse {Nava} {GM},

229

Mechanisms of Tumorigenesis in African American CRC References

{Carbonero} {F}, {Croix} {JA}, al {Abundance} Divers mucosa-associated

Hydrog microbes Heal Hum colon {ISME} {J} 2012;6(1)57-70 {S. 22(0.).

179. Schroeder BO, Wu Z, Nuding S, et al. Reduction of disulphide bonds unmasks

potent antimicrobial activity of human b-defensin 1. Nature. 2011;469.

doi:10.1038/nature09674

180. Ridlon JM, Wolf PG, Gaskins HR. Gut Microbes Taurocholic acid metabolism by

gut microbes and colon cancer Taurocholic acid metabolism by gut microbes and

colon cancer. doi:10.1080/19490976.2016.1150414

181. David LA, Maurice CF, Carmody RN, et al. Diet rapidly and reproducibly alters

the human gut microbiome. Nature. 2014;505. doi:10.1038/nature12820

182. Finegold SM, Vaisanen M-L, Molitoris DR, et al. Cetobacterium Somerae Sp.

Nov. from Human Feces and Emended Description of the Genus Cetobacterium.

http://www.urbanfischer.de/journals/sam. Accessed April 18, 2019.

183. Devkota S, Wang Y, Musch MW, et al. Dietary-fat-induced taurocholic acid

promotes pathobiont expansion and colitis in Il10 2/2 mice. 2012.

doi:10.1038/nature11225

184. Willett WC, Stampfer MJ, Colditz GA, Rosner BA, Speizer FE. Relation of Meat,

Fat, and Fiber Intake to the Risk of Colon Cancer in a Prospective Study among

Women. N Engl J Med. 1990;323(24):1664-1672.

doi:10.1056/NEJM199012133232404

185. Fung TT, Hu FB, Wu K, Chiuve SE, Fuchs CS, Giovannucci E. The

Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets and

colorectal cancer. Am J Clin Nutr. 2010;92(6):1429-1435.

230

Mechanisms of Tumorigenesis in African American CRC References

doi:10.3945/ajcn.2010.29242

186. Darfeuille-Michaud A, Boudeau J, Bulois P, et al. High Prevalence of Adherent-

Invasive Escherichia coli Associated With Ileal Mucosa in Crohn’s Disease.

Gastoenterology. 2004;127:412-421. doi:10.1053/j.gastro.2004.04.061

187. Swidsinski A, Ladhoff A, Pernthaler A, et al. Mucosal Flora in Inflammatory

Bowel Disease. 2002;122:44-54. doi:10.1053/gast.2002.30294

188. Zoetendal EG, von Wright A, Vilpponen-Salmela T, Ben-Amor K, Akkermans

ADL, de Vos WM. Mucosa-Associated Bacteria in the Human Gastrointestinal

Tract Are Uniformly Distributed along the Colon and Differ from the Community

Recovered from Feces. Appl Environ Microbiol. 2002;68(7):3401-3407.

doi:10.1128/AEM.68.7.3401-3407.2002

189. San Tang M, Poles J, Leung JM, et al. Inferred metagenomic comparison of

mucosal and fecal microbiota from individuals undergoing routine screening

colonoscopy reveals similar differences observed during active inflammation

Inferred metagenomic comparison of mucosal and fecal microbiota from

individuals undergoing routine screening colonoscopy reveals similar differences

observed during active inflammation. Gut Microbes. 2015;6(1):48-56.

doi:10.1080/19490976.2014.1000080

190. Parthasarathy G, Chen J, Chen X, et al. Relationship Between Microbiota of the

Colonic Mucosa vs Feces and Symptoms, Colonic Transit, and Methane

Production in Female Patients With Chronic Constipation. Gastroenterology.

2016;150:367-379. doi:10.1053/j.gastro.2015.10.005

191. Zoetendal EG, von Wright A, Vilpponen-Salmela T, Ben-Amor K, Akkermans

231

Mechanisms of Tumorigenesis in African American CRC References

ADL, de Vos WM. Mucosa-Associated Bacteria in the Human Gastrointestinal

Tract Are Uniformly Distributed along the Colon and Differ from the Community

Recovered from Feces. Appl Environ Microbiol. 2002;68(7):3401-3407.

doi:10.1128/AEM.68.7.3401-3407.2002

192. Kipnis V, Midthune D, Freedman LS, et al. Empirical Evidence of Correlated

Biases in Dietary Assessment Instruments and Its Implications. Am J Epidemiol.

2001;153(4):394-403. doi:10.1093/aje/153.4.394

193. Subar AF, Freedman LS, Tooze JA, et al. Addressing Current Criticism Regarding

the Value of Self-Report Dietary Data. J Nutr. 2015;145:2639-2645.

doi:10.3945/jn.115.219634

194. Subar AF, Freedman LS, Tooze JA, et al. Addressing Current Criticism Regarding

the Value of Self-Report Dietary Data. J Nutr. 2015;145:2639-2645.

doi:10.3945/jn.115.219634

195. Society AC. Colorectal Cancer Facts & Figures 2014-2016. Color Cancer Facts

Fig. 2014. doi:10.1101/gad.1593107

196. Irby K, Anderson WF, Henson DE, Devesa SS. Emerging and Widening

Colorectal Carcinoma Disparities Between Blacks and Whites in the United States

(1975-2002). Cancer Epidemiol Biomarkers Prev. 2006;15(4):792-797.

doi:10.1158/1055-9965.EPI-05-0879

197. Thornton JDJG, Morris AM, Thornton JDJG, et al. Racial Variation in Colorectal

Polyp and Tumor Location. Vol 99.; 2007:723-728.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2574351/pdf/jnma00206-

0017.pdf. Accessed April 7, 2019.

232

Mechanisms of Tumorigenesis in African American CRC References

198. Muzny DM, Bainbridge MN, Chang K, et al. Comprehensive molecular

characterization of human colon and rectal cancer. Nature. 2012;487:330-337.

doi:10.1038/nature11252

199. Augustus GJ, Ellis NA. Colorectal Cancer Disparity in African Americans: Risk

Factors and Carcinogenic Mechanisms. Am J Pathol. 2018;188:291-303.

doi:10.1016/J.AJPATH.2017.07.023

200. Seshagiri S, Stawiski EW, Durinck S, et al. Recurrent R-spondin fusions in colon

cancer. Nature. 2012;488(7413):660-664. doi:10.1038/nature11282

201. Llor X, Xicola RM, Pons E, et al. Performance of Different Microsatellite Marker

Panels for Detection of Mismatch Repair-Deficient Colorectal Tumors. 2007;99.

doi:10.1093/jnci/djk033

202. Kupfer SS, Torres JB, Hooker S, et al. Novel single nucleotide polymorphism

associations with colorectal cancer on chromosome 8q24 in African and European

Americans. Carcinogenesis. 2009;30(8):1353-1357. doi:10.1093/carcin/bgp123

203. Shanmugam V, Ramanathan RK, Lavender NA, et al. Whole Genome Sequencing

Reveals Potential Targets for Therapy in Patients with Refractory KRAS Mutated

Metastatic Colorectal Cancer.; 2014. doi:10.1186/1755-8794-7-36

204. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler

transform. 2010;26(5):589-595. doi:10.1093/bioinformatics/btp698

205. Mckenna A, Hanna M, Banks E, et al. The Genome Analysis Toolkit: A

MapReduce framework for analyzing next-generation DNA sequencing data.

doi:10.1101/gr.107524.110

206. Saunders CT, Wong WSW, Swamy S, Becq J, Murray LJ, Cheetham RK. Genome

233

Mechanisms of Tumorigenesis in African American CRC References

analysis Strelka: accurate somatic small-variant calling from sequenced tumor-

normal sample pairs. 2012;28(14):1811-1817. doi:10.1093/bioinformatics/bts271

207. Lawrence MS, Stojanov P, Polak P, et al. Mutational heterogeneity in cancer and

the search for new cancer-associated genes. Nature. 2013;499(7457):214-218.

doi:10.1038/nature12213

208. Olshen AB, Venkatraman ES, Lucito R, Wigler M. Circular binary segmentation

for the analysis of array-based DNA copy number data. Biostatistics.

2004;5(4):557-572. doi:10.1093/biostatistics/kxh008

209. Sandoval J, Heyn H, Moran S, et al. Validation of a DNA methylation microarray

for 450,000 CpG sites in the human genome. 2011. doi:10.4161/epi.6.6.16196

210. Legendre CR, Demeure MJM, Whitsett TG, et al. Pathway Implications of

Aberrant Global Methylation in Adrenocortical Cancer. Tost J, ed. PLoS One.

2016;11(3):e0150629. doi:10.1371/journal.pone.0150629

211. Aryee MJ, Jaffe AE, Corrada-Bravo H, et al. Minfi: a flexible and comprehensive

Bioconductor package for the analysis of Infinium DNA methylation microarrays.

2014;30(10):1363-1369. doi:10.1093/bioinformatics/btu049

212. Triche TJ, Weisenberger DJ, Van Den Berg D, Laird PW, Siegmund KD. Low-

level processing of Illumina Infinium DNA Methylation BeadArrays.

doi:10.1093/nar/gkt090

213. Peters TJ, Buckley MJ, Statham AL, et al. METHODOLOGY Open Access De

Novo Identification of Differentially Methylated Regions in the Human Genome.;

2015. http://www.epigeneticsandchromatin.com/content/8/1/6. Accessed April 7,

2019.

234

Mechanisms of Tumorigenesis in African American CRC References

214. Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and

characterization. Nat Methods. 2012;9(3):215-216. doi:10.1038/nmeth.1906

215. Gao J, Arman Aksoy B, Dogrusoz U, et al. Integrative Analysis of Complex

Cancer Genomics and Clinical Profiles Using the CBioPortal InTRODUcTiOn

EQUiPMenT InSTRUcTiOnS Querying Individual Cancer Studies Viewing and

Interpreting the Results Performing Cross-Cancer Queries Viewing Cancer Study

Summary Data Viewing Genomic Alterations in a Single Tumor: Patient View

Programmatic Access NOTeS anD ReMaRKS Complementary Data Sources and

Analysis Options Future Directions Downloaded From. Vol 6.; 2013.

http://stke.sciencemag.org/. Accessed April 7, 2019.

216. Cerami E, Gao J, Dogrusoz U, et al. The cBio Cancer Genomics Portal: An Open

Platform for exploring Multidimensional Cancer Genomics Data. CANCER Discov

|. 2012;401. doi:10.1158/2159-8290.CD-12-0095

217. Wang C, Zhan X, Bragg-Gresham J, et al. Ancestry estimation and control of

population stratification for sequence-based association studies. Nat Genet.

2014;46(4):409-415. doi:10.1038/ng.2924

218. The 1000 Genomes Project Consortium. A global reference for human genetic

variation The 1000 Genomes Project Consortium*. Nature. 2015;526:68-74.

doi:10.1038/nature15393

219. Shinbrot E, Henninger EE, Weinhold N, et al. Exonuclease mutations in DNA

polymerase epsilon reveal replication strand specific mutation patterns and human

origins of replication. doi:10.1101/gr.174789.114

220. Qin J, Xie Y, Wang B, et al. Upregulation of PIP3-dependent Rac exchanger 1 (P-

235

Mechanisms of Tumorigenesis in African American CRC References

Rex1) promotes prostate cancer metastasis. Oncogene. 2009;28:1853-1863.

doi:10.1038/onc.2009.30

221. Lindsay CR, Lawn S, Campbell AD, et al. P-Rex1 is required for efficient

melanoblast migration and melanoma metastasis. Nat Commun. 2011;2.

doi:10.1038/ncomms1560

222. Lucato CM, Halls ML, Ooms LM, et al. The Phosphatidylinositol (3,4,5)-

Trisphosphate-dependent Rac Exchanger 1Ras-related C3 Botulinum Toxin

Substrate 1 (P-Rex1Rac1) Complex Reveals the Basis of Rac1 Activation in

Breast Cancer Cells *. 2015. doi:10.1074/jbc.M115.660456

223. Shyr C, Tarailo-Graovac M, Gottlieb M, Lee JJ, van Karnebeek C, Wasserman

WW. FLAGS, Frequently Mutated Genes in Public Exomes.; 2014.

doi:10.1186/s12920-014-0064-y

224. Berger BM, Robison L, Glickman J. Colon Cancer-Associated DNA Mutations:

Marker Selection for the Detection of Proximal Colon Cancer. Diagnostic Mol

Pathol. 2003;12(4):187-192. doi:10.1097/00019606-200312000-00002

225. Chang S-C, Lin P-C, Lin J-K, et al. Mutation Spectra of Common Cancer-

Associated Genes in Different Phenotypes of Colorectal Carcinoma Without

Distant Metastasis. Oncol. 2016;23:849-855. doi:10.1245/s10434-015-4899-z

226. L• Uchtenborg M, Weijenberg MP, Roemen GMJM, et al. APC mutations in

sporadic colorectal carcinomas from The Netherlands Cohort Study.

doi:10.1093/carcin/bgh117

227. Ernst J, Kellis M. Large-scale imputation of epigenomic datasets for systematic

annotation of diverse human tissues. Nat Biotechnol. 2015;33(4):364-376.

236

Mechanisms of Tumorigenesis in African American CRC References

doi:10.1038/nbt.3157

228. Hahn MA, Li AX, Wu X, et al. Tumor and Stem Cell Biology Loss of the

Polycomb Mark from Bivalent Promoters Leads to Activation of Cancer-

Promoting Genes in Colorectal Tumors. 2014. doi:10.1158/0008-5472.CAN-13-

3147

229. De La Roche M, Worm J, Bienz M. The function of BCL9 in Wnt/β-catenin

signaling and colorectal cancer cells. 2008. doi:10.1186/1471-2407-8-199

230. Deka J, Wiedemann N, Anderle P, et al. Tumor and Stem Cell Biology Bcl9/Bcl9l

Are Critical for Wnt-Mediated Regulation of Stem Cell Traits in Colon Epithelium

and Adenocarcinomas. 2010. doi:10.1158/0008-5472.CAN-10-0148

231. Giannakis M, Mu J, Shukla SA, et al. Correction Genomic Correlates of Immune-

Cell Infiltrates in Colorectal Carcinoma. Cell Rep. 2016;17:857-865.

doi:10.1016/j.celrep.2016.10.009

232. O’Connell JB, Maggard MA, Liu JH, Etzioni DA, Livingston EH, Ko C. Rates of

colon and rectal cancers are increasing in young adults. In: American Surgeon. Vol

69. ; 2003:866-872. doi:10.2144/05384CI01

233. You YN, Xing Y, Feig B, Chang GJ, Cormier JN. Young-Onset Colorectal

Cancer: Is It Time to Pay Attention? Arch Intern Med. 2012;172(3):287-289.

doi:10.1001/archinternmed.2011.602

234. Siegel RL, Fedewa SA, Miller KD, et al. Cancer statistics for Hispanics/Latinos,

2015. CA Cancer J Clin. 2015;65(6):457-480. doi:10.3322/caac.21314

235. Chang DT, Pai RKRKRK, Rybicki LA, et al. Clinicopathologic and molecular

features of sporadic early-onset colorectal adenocarcinoma: an adenocarcinoma

237

Mechanisms of Tumorigenesis in African American CRC References

with frequent signet ring cell differentiation, rectal and sigmoid involvement, and

adverse morphologic features. Mod Pathol. 2012;25(8):1128-1139.

doi:10.1038/modpathol.2012.61

236. Yantiss RK, Goodarzi M, Zhou XK, et al. Clinical, pathologic, and molecular

features of early-onset colorectal carcinoma. Am J Surg Pathol. 2009;33(4):572-

582. doi:10.1097/PAS.0b013e31818afd6b

237. Stigliano V, Sanchez-Mete L, Martayan A, Anti M. Early-onset colorectal cancer:

A sporadic or inherited disease? World J Gastroenterol. 2014;20(35):12420-

12430. doi:10.3748/wjg.v20.i35.12420

238. Chan TL, Curtis LC, Leung SY, et al. Early-onset colorectal cancer with stable

microsatellite DNA and near-diploid chromosomes. Oncogene. 2001;20(35):4871-

4876. doi:10.1038/sj.onc.1204653

239. Osorio Silla I, Rueda D, Rodríguez Y, et al. Early-onset colorectal cancer: A

separate subset of colorectal cancer. World J Gastroenterol. 2014;20(46):17288-

17296. doi:10.3748/wjg.v20.i46.17288

240. Perea J, Rueda D, Canal A, et al. Age at Onset Should Be a Major Criterion for

Subclassification of Colorectal Cancer. J Mol Diagnostics. 2014;16:116-126.

doi:10.1016/j.jmoldx.2013.07.010

241. Baba Y, Huttenhower C, Nosho K, et al. Open Access RESEARCH Epigenomic

Diversity of Colorectal Cancer Indicated by LINE-1 Methylation in a Database of

869 Tumors. Vol 9.; 2010. http://www.molecular-cancer.com/content/9/1/125.

Accessed April 7, 2019.

242. Kirzin S, Marisa L, Guimbaud R, et al. Sporadic early-onset colorectal cancer is a

238

Mechanisms of Tumorigenesis in African American CRC References

specific sub-type of cancer: A morphological, molecular and genetics study. PLoS

One. 2014;9(8). doi:10.1371/journal.pone.0103159

243. Berg M, Agesen TH, Thiis-Evensen E, et al. Distinct high resolution genome

profiles of early onset and late onset colorectal cancer integrated with gene

expression data identify candidate susceptibility loci. Mol Cancer. 2010;9:100.

doi:10.1186/1476-4598-9-100

244. Jandova J, Xu W, Nfonsam V. Association for Academic Surgery Sporadic early-

onset colon cancer expresses unique molecular features. 2016.

doi:10.1016/j.jss.2016.04.068

245. Matheu A, Collado M, Wise C, et al. Oncogenicity of the Developmental

Transcription Factor Sox9. Tumor Stem Cell Biol. 2012;72(5):1301-1315.

doi:10.1158/0008-5472.CAN-11-3660

246. Ma F, Ye H, He HH, et al. SOX9 drives WNT pathway activation in prostate

cancer. J Clin Invest. 2016;126(5):1745-1758. doi:10.1172/JCI78815

247. Whissell G, Montagni E, Martinelli P, et al. The transcription factor GATA6

enables self-renewal of colon adenoma stem cells by repressing BMP gene

expression. Nat Cell Biol. 2014;16(7):695-707. doi:10.1038/ncb2992

248. Vadnais C, Shooshtarizadeh P, Rajadurai C V, et al. Autocrine Activation of the

Wnt/b-Catenin Pathway by CUX1 and GLIS1 in Breast Cancers.

doi:10.1242/bio.20148193

249. Neri F, Dettori D, Incarnato D, et al. TET1 is a tumour suppressor that inhibits

colon cancer growth by derepressing inhibitors of the WNT pathway. Oncogene.

2015;34(32):4168-4176. doi:10.1038/onc.2014.356

239

Mechanisms of Tumorigenesis in African American CRC References

250. Morris LGT, Kaufman AM, Gong Y, et al. Recurrent somatic mutation of FAT1 in

multiple human cancers leads to aberrant Wnt activation. Nat Genet.

2013;45(3):253-261. doi:10.1038/ng.2538

251. Augustus GJ, Roe DJ, Jacobs ET, Lance P, Ellis NA. Is increased colorectal

screening effective in preventing distant disease? PLoS One.

2018;13(7):e0200462. doi:10.1371/journal.pone.0200462

252. Melcher R, Hartmann E, Zopf W, et al. LOH and copy neutral LOH (cnLOH) act

as alternative mechanism in sporadic colorectal cancers with chromosomal and

microsatellite instability. Carcinogenesis. 2011;32(4):636-642.

doi:10.1093/carcin/bgr011

253. Cheung K-JJ, Delaney A, Ben-Neriah S, et al. High Resolution Analysis of

Follicular Lymphoma Genomes Reveals Somatic Recurrent Sites of Copy-Neutral

Loss of Heterozygosity and Copy Number Alterations that Target Single Genes.

Genes Chromosomes Cancer. 2010;49(March):669-681. doi:10.1002/gcc.20780

254. O’Keefe C, McDevitt MA, Maciejewski JP. Copy neutral loss of heterozygosity: a

novel chromosomal lesion in myeloid malignancies. Blood. 2010;115(14):2731-

2739. doi:10.1182/blood-2009-10-201848

255. Pemberton TJ, Absher D, Feldman MW, Myers RM, Rosenberg NA, Li JZ.

Genomic patterns of homozygosity in worldwide human populations. Am J Hum

Genet. 2012;91(2):275-292. doi:10.1016/j.ajhg.2012.06.014

256. Wang J-C, Ross L, Mahon LW, et al. Regions of homozygosity identified by

oligonucleotide SNP arrays: evaluating the incidence and clinical utility. Eur J

Hum Genet. 2015;23(5):663-671. doi:10.1038/ejhg.2014.153

240

Mechanisms of Tumorigenesis in African American CRC References

257. Kearney HM, Kearney JB, Conlin LK. Diagnostic Implications of Excessive

Homozygosity Detected by SNP-Based Microarrays: Consanguinity, Uniparental

Disomy, and Recessive Single-Gene Mutations. CLL. 2011;31:595-613.

doi:10.1016/j.cll.2011.08.003

258. Costantino L, Sotiriou SK, Rantala JK, et al. Break-Induced Replication Repair of

Damaged Forks Induces Genomic Duplications in Human Cells.

http://science.sciencemag.org/. Accessed March 13, 2019.

259. Bhowmick R, Minocherhomji S, Hickson ID, Hickson Correspondence ID.

RAD52 Facilitates Mitotic DNA Synthesis Following Replication Stress. Mol Cell.

2016;64(6):1117-1126. http://dx.doi.org/10.1016/j.molcel.2016.10.037. Accessed

March 13, 2019.

260. Sotiriou SK, Kamileri I, Lugli N, et al. Mammalian RAD52 Functions in Break-

Induced Replication Repair of Collapsed DNA Replication Forks.

2016;64(6):1127-1134. doi:10.1016/j.molcel.2016.10.038

241