Newcomb, Polly A.

Background Initiating screening at an earlier age based on cancer family history is one of the primary recommended strategies for the prevention and detection of early‐onset colorectal cancer (EOCRC), but data supporting the effectiveness of this approach are limited. The authors assessed the performance of family history–based guidelines for identifying individuals with EOCRC. Methods The authors conducted a population‐based, case‐control study of individuals aged 40 to 49 years with (2473 individuals) and without (772 individuals) incident CRC in the Colon Cancer Family Registry from 1998 through 2007. They estimated the sensitivity and specificity of family history–based criteria jointly recommended by the American Cancer Society, the US Multi‐Society Task Force on CRC, and the American College of Radiology in 2008 for early screening, and the age at which each participant could have been recommended screening initiation if these criteria had been applied. Results Family history–based early screening criteria were met by approximately 25% of cases (614 of 2473 cases) and 10% of controls (74 of 772 controls), with a sensitivity of 25% and a specificity of 90% for identifying EOCRC cases aged 40 to 49 years. Among 614 individuals meeting early screening criteria, 98.4% could have been recommended screening initiation at an age younger than the observed age of diagnosis. Conclusions Of CRC cases aged 40 to 49 years, 1 in 4 met family history–based early screening criteria, and nearly all cases who met these criteria could have had CRC diagnosed earlier (or possibly even prevented) if earlier screening had been implemented as per family history–based guidelines. Additional strategies are needed to improve the detection and prevention of EOCRC for individuals not meeting family history criteria for early screening.

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.

3526 Background: Prior observational studies have suggested that smoking is associated with poorer overall survival after colon cancer (CC) diagnosis. Using data from N0147, a phase III randomized adjuvant trial of patients with stage III CC, we assessed the relationship between smoking status and cancer outcomes (disease-free survival (DFS) and time to recurrence (TTR)), accounting for possible heterogeneity by patient and tumor characteristics. Methods: Patients completed a risk factor questionnaire at baseline prior to randomization to FOLFOX or FOLFOX+cetuximab (N=1968). Information was collected on smoking and other lifestyle factors, including alcohol consumption, body mass index (BMI), and physical activity. Multivariate Cox models assessed the association between smoking history and the primary trial outcome of DFS, as well TTR, adjusting for other lifestyle and clinical factors. The median follow-up was 3.5 years. Results: Overall, 52% of patients were former or current smokers. Compared to never smokers, ever smokers experienced significantly shorter DFS [3-year DFS: 70% vs 74%, hazard ratio (HR)=1.21, 95% confidence interval (CI): 1.02-1.42]. This association persisted after adjusting for age, sex, tumor subsite, number of nodes involved, T-stage, mismatch repair deficiency, BRAF mutation status, performance score, physical activity, BMI, and alcohol consumption (HR=1.23, 95% CI: 1.02-1.49). There was significant interaction in this association by BRAF mutation status (p=0.02): smoking was associated with shorter DFS in BRAF wildtype CC patients (HR=1.25, 95% CI: 1.04-1.51) but not in BRAF mutant CC patients (HR=0.72, 95% CI: 0.47-1.10). Patterns of association with smoking, overall and by BRAF status, were identical in analyses of TTR. Conclusions: Overall, smoking was significantly associated with shorter DFS and TTR in CC patients. These adverse relationships were most evident in patients with BRAF wildtype CC.

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.

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.