Citations

AbstractBackgroundBody mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology.MethodsTo improve statistical power and interpretation for gene‐environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype‐Tissue Expression Project for all genes with heritability ≥1%. We used a mixed‐effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI‐CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2.ResultsAmong 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10−5), PSMC5 (P = 4.51 × 10−4) and CD33 (P = 2.71 × 10−4) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10−5) and SCN1B (P = 2.76 × 10−4) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10−5).ConclusionsAggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

Abstract Background: Results from epidemiologic studies examining polyunsaturated fatty acids (PUFA) and colorectal cancer risk are inconsistent. Mendelian randomization may strengthen causal inference from observational studies. Given their shared metabolic pathway, examining the combined effects of aspirin/NSAID use with PUFAs could help elucidate an association between PUFAs and colorectal cancer risk. Methods: Information was leveraged from genome-wide association studies (GWAS) regarding PUFA-associated SNPs to create weighted genetic scores (wGS) representing genetically predicted circulating blood PUFAs for 11,016 non-Hispanic white colorectal cancer cases and 13,732 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Associations per SD increase in the wGS were estimated using unconditional logistic regression. Interactions between PUFA wGSs and aspirin/NSAID use on colorectal cancer risk were also examined. Results: Modest colorectal cancer risk reductions were observed per SD increase in circulating linoleic acid [ORLA = 0.96; 95% confidence interval (CI) = 0.93–0.98; P = 5.2 × 10−4] and α-linolenic acid (ORALA = 0.95; 95% CI = 0.92–0.97; P = 5.4 × 10−5), whereas modest increased risks were observed for arachidonic (ORAA = 1.06; 95% CI = 1.03–1.08; P = 3.3 × 10−5), eicosapentaenoic (OREPA = 1.04; 95% CI = 1.01–1.07; P = 2.5 × 10−3), and docosapentaenoic acids (ORDPA = 1.03; 95% CI = 1.01–1.06; P = 1.2 × 10−2). Each of these effects was stronger among aspirin/NSAID nonusers in the stratified analyses. Conclusions: Our study suggests that higher circulating shorter-chain PUFAs (i.e., LA and ALA) were associated with reduced colorectal cancer risk, whereas longer-chain PUFAs (i.e., AA, EPA, and DPA) were associated with an increased colorectal cancer risk. Impact: The interaction of PUFAs with aspirin/NSAID use indicates a shared colorectal cancer inflammatory pathway. Future research should continue to improve PUFA genetic instruments to elucidate the independent effects of PUFAs on colorectal cancer.

Abstract Purpose: Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention. Methods: A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases (N = 4,445) and controls (N = 3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). Model validation used CCFRC follow-up data for population-based (N = 12,052) and clinic-based (N = 5,584) relatives with no cancer history at recruitment to assess model calibration [expected/observed rate ratio (E/O)] and discrimination [area under the receiver-operating-characteristic curve (AUC)]. Results: The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74–1.45) for men and 0.86 (0.64–1.20) for women, and for clinic-based relatives were 1.15 (0.87–1.58) for men and 1.04 (0.76–1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60–0.78) for men and 0.70 (0.62–0.77) for women, and for clinic-based relatives were 0.77 (0.69–0.84) for men and 0.68 (0.60–0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01–0.15) for men and 0.10 (0.04–0.16) for women, and for clinic-based relatives were 0.11 (0.05–0.17) for men and 0.11 (0.06–0.17) for women. Conclusions: Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model. Impact: Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

Abstract Background: Smoking has been associated with colorectal cancer (CRC) risk; but limited evidence has shown the association between smoking and molecular subtypes of CRC. Methods: We analyzed 9,422 CRC cases and 9,950 controls from 10 observational studies. Multinomial logistic regression analysis was performed to assess the association between sex-study-specific quartiles of pack years of smoking and risk of CRC molecular subtypes, using non-smokers as reference group, adjusting for age, sex, and study. Known oncogenic mutations in four somatic colorectal tumor markers were assessed individually and in combination, including BRAF mutations, KRAS mutations, CpG island methylator phenotype (CIMP), and microsatellite instability (MSI) status. Case-only analysis was also performed to estimate heterogeneity in risk of molecular subtypes of CRC. Results: Compared with controls, higher pack years of smoking were statistically significantly associated with increased CRC risk when stratified, individually, by all four markers, and the associations got stronger with higher quartiles pack years (p-trend&lt;0.001). Associations between smoking and CRC risk also differed significantly among molecular subtypes. Compared to nonsmokers, the risk of BRAFmut CRC was 83% higher for smokers within the highest quartile of pack-years (OR=1.83; 95% CI: 1.50, 2.25), and 29% higher for BRAFwt CRC (OR=1.29; 95% CI: 1.17, 1.43; Ratio of ORs (ROR)=1.45; 95% CI: 1.18, 1.17; p=3.45x10-4). Similarly, heavy pack-years of smoking was associated with almost two times higher risk of CIMP-high CRC (OR=1.93; 95% CI: 1.60, 2.31), but only 33% higher risk of CIMP-low/negative CRC (OR=1.33; 95% CI: 1.19, 1.48; ROR=1.49; 95% CI: 1.24, 1.79; p=1.72x10-5). The association between smoking and CRC was also stronger in MSI-high tumors (ORMSI-H=1.65; 95% CI: 1.36, 2.00; ORMSI-L/MSS=1.37; 95% CI: 1.23, 1.52; ROR=1.22; 95% CI: 1.00, 1.48; p=0.046). In contrast, the association between smoking and CRC risk was stronger for KRASwt (OR=1.43; 95% CI: 1.27, 1.60), than KRASmut tumors (OR=1.18; 95% CI: 1.02, 1.37; ROR=0.83; 95% CI: 0.71, 0.97; p =0.016). When combining tumor markers, smoking was found to be significantly associated with higher risk of colorectal tumors from the serrated pathway. Conclusion: In this largest study with a total of 19,372 subjects, we found that heavier pack years of smoking was associated with increased risk of all CRC molecular subtypes. Smokers with heavier pack-years of smoking had particularly higher risk of CRC subtypes with BRAF mutation and CIMP-high, suggesting smoking may be particularly involved in the development of these subtypes of colorectal tumor. Citation Format: Xiaoliang Wang, Efrat Amitay, Barbara L. Banbury, Hermann Brenner, Daniel D. Buchanan, Peter T. Campbell, Jenny Chang-Claude, Steven J. Gallinger, Graham G. Giles, Tabitha A. Harrison, John L. Hopper, Mark A. Jenkins, Yi Lin, Reiko Nishihara, Polly A. Newcomb, Shuji Ogino, Lori C. Sakoda, Robert E. Schoen, Martha L. Slattery, Steven N. Thibodeau, Bethany Van Guelpen, Michael O. Woods, Li Hsu, Michael Hoffmeister, Ulrike Peters. Smoking is associated with risks of molecular subtypes of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 630.

Interindividual differences in DNA repair systems may play a role in modulating the individual risk of developing colorectal cancer. To better ascertain the role of DNA repair gene polymorphisms on colon and rectal cancer risk individually, we evaluated 15,419 single nucleotide polymorphisms (SNPs) within 185 DNA repair genes using GWAS data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), which included 8,178 colon cancer, 2,936 rectum cancer cases and 14,659 controls. Rs1800734 (in MLH1 gene) was associated with colon cancer risk (p‐value = 3.5 × 10−6) and rs2189517 (in RAD51B) with rectal cancer risk (p‐value = 5.7 × 10−6). The results had statistical significance close to the Bonferroni corrected p‐value of 5.8 × 10−6. Ninety‐four SNPs were significantly associated with colorectal cancer risk after Binomial Sequential Goodness of Fit (BSGoF) procedure and confirmed the relevance of DNA mismatch repair (MMR) and homologous recombination pathways for colon and rectum cancer, respectively. Defects in MMR genes are known to be crucial for familial form of colorectal cancer but our findings suggest that specific genetic variations in MLH1 are important also in the individual predisposition to sporadic colon cancer. Other SNPs associated with the risk of colon cancer (e.g., rs16906252 in MGMT) were found to affect mRNA expression levels in colon transverse and therefore working as possible cis‐eQTL suggesting possible mechanisms of carcinogenesis.

e13145 Background: A multiplexed biomarker panel was developed for detection of MSI that is more sensitive than currently available systems. Preliminary data showed an increased MSI sensitivity for colon polyps, endometrial (EC) and skin cancers. This study expands that finding to 14 different types of cancer. Methods: Selection of the best microsatellite markers was done using a cohort of 160 patients ≤55 years with ≥1 colon polyp and 100 EC patients ≤ 50 years. To validate the new panel, a cohort of 100 Lynch syndrome CRC, 100 sporadic MSI-High CRC, 100 sporadic MSI stable CRC and 219 extra-colonic cancers from the Colon Cancer Family Registry were tested for MSI. Samples were screened using a new 8-marker panel and Promega’s MSI Analysis System. Mismatch repair (MMR) gene mutation status and expression were determined. To compare the relative sensitivity of the 8-marker panel across all cancer types we developed a quantitative “MSI-score” for each cancer type. Results: Considerable differences in MSI phenotypes were observed between cancer types and a new approach to scoring MSI in extra-colonic cancers is proposed. Relative intensity of the MSI phenotype was characterized by MSI-Scores ranging from high of 66 (small intestine) to 6 (brain). The mutations in MSI samples were significantly more common and allele size shifts larger with the new biomarkers, making MSI classification more accurate and robost. MSI, IHC and MMR gene mutation status were highly correlated. Conclusions: The MSI sensitivity of the new biomarker panel for most cancer types was significantly higher than currently available PCR-based MSI systems. Development of the new pan-cancer PCR-based MSI system allows laboratories to leverage established equipment and known analysis techniques to keep turnaround time and costs, quick and affordable compared with emerging NGS-based technologies.

Abstract Aim: We aimed to develop a comprehensive Colorectal cancer Risk Prediction Tool (CRiPT). To achieve this, it is necessary to incorporate germline mutations in the DNA mismatch repair genes and MUTYH to account for a proportion of the familial aggregation of colorectal cancer. Population prevalence of these mutations and the genetic and environmental causes of the remaining familial aggregation, however, are not known. Methods: We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the USA, Canada and Australia, and screened probands for mutations in the mismatch repair genes MLH1, MSH2, MSH6, and PMS2, and MUTYH. We fitted modified segregation analysis models to the cancer history of first-degree relatives, conditional on the age at diagnosis of the proband, using the software MENDEL. We determined the genetic model that best explained the familial aggregation of colorectal cancer by estimating the prevalence of mutations in the known susceptibility genes, the prevalence of and hazard ratio for unmeasured high-risk gene mutations, and the variance of the unmeasured polygenic component, using a χ2 goodness-of-fit test. Results: The best fitting model was a mixed dominant model with the polygenic standard deviation varying by age. Under that model, we estimated 1 in 279 of the population carry mutations in the mismatch repair genes (MLH = 1 in 1946, MSH2 = 1 in 2841, MSH6 = 1 in 758, PMS2 = 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations in unknown major gene(s) which are associated with on average a 31-fold increased risk of colorectal cancer. The estimated variance of the polygenic component decreased from 1.8 for age &lt;40 years to 0.7 for age ≥70 years (equivalent to a sibling relative risk of 5.1 and 1.3, respectively). There was good internal consistency in the best fitting model; i.e., predicted and observed numbers were close. Conclusion: CRiPT is a comprehensive prediction model that incorporates both known and unknown major genes and polygenes. CRiPT can provide the probabilities of having a mutation in a DNA mismatch repair gene or MUTYH as well as estimate future risk (e.g., 5-year risk) of developing colorectal cancer. This model is similar to the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) that calculates for women the probabilities of carrying a BRCA1 or BRCA2 mutation and their future risk of developing breast and ovarian cancer based on their family history. Further work will include measured environmental factors and genetic variants to CRiPT, and it will be useful for genetic counselling and targeted colorectal cancer screening in clinical practices. This abstract is also being presented as Poster B04. Citation Format: Aung Ko Win, Mark A. Jenkins, James G. Dowty, Antonis C. Antoniou, Andrew Lee, Yingye Zheng, Noralane M. Lindor, Polly A. Newcomb, John L. Hopper, Robert J. MacInnis. Development of a comprehensive colorectal cancer risk prediction tool (CRiPT) incorporating known and unknown major genes and polygenes. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR10.

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR10) of the Conference Proceedings. Citation Format: Aung Ko Win, Mark A. Jenkins, James G. Dowty, Antonis C. Antoniou, Andrew Lee, Yingye Zheng, Noralane M. Lindor, Polly A. Newcomb, John L. Hopper, Robert J. MacInnis. Development of a comprehensive colorectal cancer risk prediction tool (CRiPT) incorporating known and unknown major genes and polygenes. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B04.

Abstract Background The risk of cancers is well characterized in Lynch syndrome (LS) families but has been less studied in familial colorectal cancer type X (FCCTX) families. Methods In this article, we compare the risk estimates of first and second colorectal cancers (CRCs) in 168 FCTTX and 780 LS families recruited through the Colon Cancer Family Registry as well as the risk of cancer-related deaths and disease-free survival (DFS) after a first CRC. Our methodology is based on a survival analysis approach, developed specifically to model the occurrence of successive cancers (ie, first and second CRCs) in the presence of competing risk events (ie, death from any causes). Results We found an excess risk of first and second CRC in individuals with LS compared to FCCTX family members. However, for an average age at first CRC of 60 years in FCCTX families and 50 years in LS families, the DFS rates were comparable in men but lower in women from FCCTX vs LS families, eg , 75.1% (95% confidence interval [CI] = 69.0% to 80.9%) vs 78.9% (95% CI = 76.3% to 81.3%) for the 10-year DFS. The 10-year risk of cancer-related death was higher in FCCTX families vs LS families, eg, 15.4% in men (95% CI = 10.9% to 19.8%) and 19.3% in women (95% CI = 13.6% to 24.7%) vs 8.9% (95% CI = 7.5% to 11.4%) and 8.7% (95% CI = 7.1% to 10.8%), respectively. Conclusions Individuals with CRCs arising in the context of FCCTX do not experience the same improved DFS and overall survival of those with LS, and that difference may be relevant in management decisions.

Abstract Genome-wide association studies of colorectal cancer (CRC) have identified over 50 susceptibility loci. These variants represent only a small fraction of total heritability for CRC. Gene-environment (GxE) interaction studies may help identify novel loci and biological interactions that give insight to the pathogenesis of CRC. Previous genome-wide GxE studies with dietary factors have identified interactions between loci and processed meat consumption and alcohol; however, limited statistical power remains a primary concern. Set-based SNP testing has the potential to increase statistical power to detect GxE interactions by aggregating functionally relevant SNPs. In this large pooled analysis using 14 case-control and nested case-control studies, we incorporated functional information from the transcriptome prediction tool, PrediXcan, into a novel set-based approach for testing GxE interactions. We used variant weights from the PrediXcan models of tissue-specific gene expression in the transverse colon as a priori variant information for a set-based GxE approach. We restricted our analysis to variants in the PrediXcan transverse colon gene models (n = 4,842). This discovery phase included 10,360 CRC and advanced adenoma cases, and 11,183 controls of European ancestry from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colon Cancer Family Registry. All 14 studies were analyzed together in a pooled data set using the Mixed Effects Score Tests for interactions. We tested for gene interactions with sex- and study- specific quartiles of dietary intake of red meat (servings/day), processed meat (servings/day), vegetables (servings/day), fruits (servings/day), and fiber (g/day). We detected two genes with suggestive interactions (false discovery rate (FDR) &lt; 0.2) with intake of red meat and risk of CRC: Superoxide Dismutase 2 (SOD2) and Ubiquitin Conjugating Enzyme E2 H (UBE2H). No interactions at FDR &lt; 0.2 were observed for processed meat, vegetables, fruits, or fiber. The SOD2 gene, which encodes an enzyme important in apoptotic signaling and clearing of reactive oxygen species, may regulate response to colonic exposure to heme iron or increased bile acid from high-fat content in red meat. UBE2H is part of the ubiquitin-proteasome system that has a role in Wnt signaling, which can be mediated by heme iron in red meat and is commonly found dysregulated in cancer. These findings highlight the efficacy of integrating functional information and set-based testing for novel discovery of genes interacting with known dietary risk factors of CRC. We plan to replicate these findings in additional studies. Citation Format: Paneen S. Petersen, Yu-Ru Su, Sonja I. Berndt, Stephanie A. Bien, Hermann Brenner, Graham Casey, Andrew T. Chan, Jenny Chang-Claude, Jane C. Figueiredo, Steven J. Gallinger, Robert W. Haile, Tabitha A. Harrison, Michael Hoffmeister, Mark A. Jenkins, Amit D. Joshi, Sébastien Küry, Loic Le Marchand, Yi Lin, Noralane M. Lindor, Polly A. Newcomb, John D. Potter, Robert Schoen, Martha L. Slattery, Stephen N. Thibodeau, Emily White, Li Hsu, Ulrike Peters, CCFR, GECCO. Interactions between genetic predictors of gene expression and dietary factors associated with risk of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5268.