Lindor, Noralane M.

Abstract Background: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. Methods: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. Results: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E = 1.96 × 10−4), KRT16 (PG×E = 2.3 × 10−4), CD14 (PG×E = 9.38 × 10−4), and CYP27A1 (PG×E = 1.44 × 10−3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E = 3.23 × 10−5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR < 0.2. Conclusions: By incorporating functional information, we discovered several novel genes that interacted with NSAID use. Impact: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.

A goal of the 3rd phase of the Electronic Medical Records and Genomics (eMERGE3) Network was to examine the return of results (RoR) of actionable variants in more than 100 genes to consenting participants and their healthcare providers. Each of the 10 eMERGE sites developed plans for three essential elements of the RoR process: Disclosure to the participant, notification of the health care provider, and integration of results into the electronic health record (EHR). Procedures and protocols around these three elements were adapted as appropriate to individual site requirements and limitations. Detailed information about the RoR procedures at each site was obtained through structured telephone interviews and follow-up surveys with the clinical investigator leading or participating in the RoR process at each eMERGE3 institution. Because RoR processes at each of the 10 sites allowed for taking into account differences in population, disease focus and institutional requirements, significant heterogeneity of process was identified, including variability in the order in which patients and clinicians were notified and results were placed in the EHR. This heterogeneity in the process flow for eMERGE3 RoR reflects the “real world” of genomic medicine in which RoR procedures must be shaped by the needs of the patients and institutional environments.

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.

3567 Background: The ability to genotype large numbers of people rapidly and inexpensively for research purposes highlights the need to develop guidelines for providing medically-relevant research results - including unanticipated findings - to study participants. The Colon Cancer Family Registry (C-CFR) is the oldest and largest international colon cancer population-based registry; its experience managing genetic research findings can offer guidance to clinicians and researchers. The C-CFR has enrolled 10,019 cases with colon cancer and 24,708 family members in six registries in the US, Canada, Australia, and New Zealand. Deleterious (“high risk”) germline mutations have been identified in DNA mismatch repair (MMR) genes (MLH1, MSH2, MSH6, PMS2) and the MutYH gene. The aims of this presentation are to: (1) report the uptake of genetic test results by C-CFR participants; (2) systematically compare disclosure protocols and barriers to uptake by registry; (3) make recommendations to guide clinicians and researchers. Methods: Uptake of genetic test results was calculated from data collected by the C-CFR; key investigators (KIs) from each registry completed a survey about disclosure decision-making; KIs also took part in discussions to generate recommendations. Results: Registry-wide molecular testing has identified deleterious MMR germline mutations for at least one member of 424 families (4%) and 48 biallelic MutYH gene carriers. Uptake of test results ranged from 56-86% (n= 1542) across registries. Barriers to disclosure include: (1) lack of pre-existing notification protocols; (2) logistics of re-consent; (3) limited involvement of genetic counselors at some registries; (4) in the US, the requirement that genetic testing be performed in a CLIA approved laboratory; (5) IRBs declining approval; and (6) budget constraints. Conclusions: Based on our international registry’s findings we recommend that researchers generating genetic information establish plans for disclosure at the outset; obtain subject consent a priori; consider subject knowledge and disclosure preferences; provide guidance and budget for clinical follow-up; and involve genetic counselors.

4127 Background: The MMRpredict model, developed at the University of Edinburgh, is a web-based model developed to predict which patients diagnosed with colorectal cancer (CRC) under age 55 years have germline mutations in a DNA mismatch repair (MMR) gene [Barnetson et al., NEngJMed 2006;354:2751–63]. Stage 1 MMRpredict estimates the carrier probability for MMR mutations from clinical parameters (age of diagnosis of colorectal cancer, proximal vs distal site, family history, multiple primary CRCs). We evaluated the performance of Stage 1 of this model in a well characterized cohort of colorectal cancer patients. Methods: Cases with CRC were identified through the Minnesota Cancer Surveillance System (MCSS), a population based registry and Mayo Clinic Rochester, a clinical practice. All were consented participants in the Mayo Colon Cancer Family Registry. Of 342 cases tested for MMR mutations (MLH1, MSH2, MSH6), 45 had insufficient information on colon site and 62 were older than 55 and could not be used in the study. The remaining 235 included 110 females/125 males; 90 cases with proximal site/145 with distal site; 229/235 were self-identified as White. Results: We defined 5 probability risk groups based on output from the MMRpredict web model Stage 1: 1–10%, 11–25%, 26–50%, 51–75%, and 76–100%. In our study, the number of cases in each of these groups was 60, 45, 65, 34, and 31, respectively. The corresponding number of mutations in each group was 1 (1.7%), 4 (8.9%), 9 (13.8%), 3 (8.8%), and 11 (35.5%). Overall, 28/235 patients were found to have mutations (11.9%), compared to predicted range of 62–107 (26–45%). Conclusion: MMRpredict Stage 1 over-estimated the probability of detecting a MMR gene mutation in this study. This may reflect ascertainment issues or genetics of different populations. No significant financial relationships to disclose.

AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast 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 Abstract 4259 Background: Patients with defective DNA repair mechanisms are at higher risk for developing cancer. BRCA1 and BRCA2 are proteins that coordinate DNA repair by homologous-recombination. Mutations in BRCA1 and BRCA2 are associated with an increased risk of cancers, namely breast, ovarian, and pancreatic, thus making these patients more likely to receive chemo- or radiation therapy. Additionally, secondary malignancies can be an unfortunate consequence of treatment with chemo- or radiation therapy. Although tumors with defective DNA repair mechanisms may be more susceptible to therapy, we hypothesized that patients with BRCA mutations that underwent chemotherapy or radiotherapy for treatment of breast or ovarian cancer would be at a higher risk of developing therapy- related myelodysplastic syndrome (t-MDS) or acute myeloid leukemia (t-AML). Methods: We accessed patient data from our institution maintained by the Mayo Clinic Life Sciences System using the Data Discovery and Query Builder. We searched for patients whose notes and diagnoses included the terms BRCA, and breast or ovarian cancer, and myelodysplastic syndrome or acute myeloid leukemia. We searched our records from 1/1/1995–7/15/2011. We cross-referenced our findings to a database of patients who were diagnosed with a BRCA mutation through our department of medical genetics. Secondly, we searched the National Cancer Institute's Surveillance Epidemiology and End Results (SEER) database for female patients who developed AML after the diagnosis or breast or ovarian cancer from the years 1973–2008 using ratio and multiple primaries standardized incidence ratios sessions. Results: We identified 220 patients with a BRCA mutation, of which 73 received chemotherapy. There were two patients with BRCA mutations that developed t-AML following treatment for breast cancer, and one patient with a BRCA mutation who developed t-AML following treatment for ovarian cancer (Table 1). Manual data extraction from the list of patients with BRCA mutations diagnosed at our institution only identified one of these patients, as two obtained their testing through another institution. We did not identify any patients with BRCA mutations who developed t-MDS following treatment for breast or ovarian cancer. The latency between diagnosis of the primary cancer and the diagnosis or t-AML was 24 months for two patients, and 22 years for the other. From our search of the SEER database we found 649 patients who developed AML after a diagnosis of breast cancer, and 98 patients who developed AML after a diagnosis of ovarian cancer. These patients represented 0.1% and 0.2% of evaluable breast and ovarian cases respectively. The latency from time of diagnosis of the primary cancer to that of AML was 58 months (29–113 interquartile range) for breast cancer and 47 months (29–91) for ovarian cancer. The observed number of patients with AML following the diagnosis of breast or ovarian cancer was 1.68 and 4.74 times higher than that expected of the general population, respectively (both p<0.05). We were not able to stratify patients based on the presence of a BRCA mutation due to the limitations of the database. Conclusions: We identified three patients with confirmed BRCA mutations and t-AML at our institution. Although this does not represent a strong association, patients at risk for BRCA mutations do not always undergo testing. Thus, our results may not fully represent whether there is an association with BRCA mutations and t-MDS or t-AML. Using the SEER database, we confirmed that patients who were diagnosed with breast or ovarian cancer subsequently had a higher incidence of AML than the general population, although we were not able to test if patients with BRCA mutations are at higher risk of t-MDS or t-AML. Disclosures: No relevant conflicts of interest to declare.

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.