Citations

Objective An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. Design To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. Results We identified 13 loci that reached genome-wide significance (p<5×10 −8 ) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. Conclusion Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.

Abstract Background: Inherited susceptibility is an important contributor to colorectal cancer risk, and rare variants in key genes or pathways could account in part for the missing proportion of colorectal cancer heritability. Methods: We conducted an exome-wide association study including 2,327 cases and 2,966 controls of European ancestry from three large epidemiologic studies. Single variant associations were tested using logistic regression models, adjusting for appropriate study-specific covariates. In addition, we examined the aggregate effects of rare coding variation at the gene and pathway levels using Bayesian model uncertainty techniques. Results: In an exome-wide gene-level analysis, we identified ST6GALNAC2 as the top associated gene based on the Bayesian risk index (BRI) method [summary Bayes factor (BF)BRI = 2604.23]. A rare coding variant in this gene, rs139401613, was the top associated variant (P = 1.01 × 10–6) in an exome-wide single variant analysis. Pathway-level association analyses based on the integrative BRI (iBRI) method found extreme evidence of association with the DNA repair pathway (BFiBRI = 17852.4), specifically with the nonhomologous end joining (BFiBRI = 437.95) and nucleotide excision repair (BFiBRI = 36.96) subpathways. The iBRI method also identified RPA2, PRKDC, ERCC5, and ERCC8 as the top associated DNA repair genes (summary BFiBRI ≥ 10), with rs28988897, rs8178232, rs141369732, and rs201642761 being the most likely associated variants in these genes, respectively. Conclusions: We identified novel variants and genes associated with colorectal cancer risk and provided additional evidence for a role of DNA repair in colorectal cancer tumorigenesis. Impact: This study provides new insights into the genetic predisposition to colorectal cancer, which has potential for translation into improved risk prediction.

Abstract Background: Evidence for aspirin's chemopreventative properties on colorectal cancer (CRC) is substantial, but its mechanism of action is not well-understood. We combined a proteomic approach with Mendelian randomization (MR) to identify possible new aspirin targets that decrease CRC risk. Methods: Human colorectal adenoma cells (RG/C2) were treated with aspirin (24 hours) and a stable isotope labeling with amino acids in cell culture (SILAC) based proteomics approach identified altered protein expression. Protein quantitative trait loci (pQTLs) from INTERVAL (N = 3,301) and expression QTLs (eQTLs) from the eQTLGen Consortium (N = 31,684) were used as genetic proxies for protein and mRNA expression levels. Two-sample MR of mRNA/protein expression on CRC risk was performed using eQTL/pQTL data combined with CRC genetic summary data from the Colon Cancer Family Registry (CCFR), Colorectal Transdisciplinary (CORECT), Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia and UK Biobank (55,168 cases and 65,160 controls). Results: Altered expression was detected for 125/5886 proteins. Of these, aspirin decreased MCM6, RRM2, and ARFIP2 expression, and MR analysis showed that a standard deviation increase in mRNA/protein expression was associated with increased CRC risk (OR: 1.08, 95% CI, 1.03–1.13; OR: 3.33, 95% CI, 2.46–4.50; and OR: 1.15, 95% CI, 1.02–1.29, respectively). Conclusions: MCM6 and RRM2 are involved in DNA repair whereby reduced expression may lead to increased DNA aberrations and ultimately cancer cell death, whereas ARFIP2 is involved in actin cytoskeletal regulation, indicating a possible role in aspirin's reduction of metastasis. Impact: Our approach has shown how laboratory experiments and population-based approaches can combine to identify aspirin-targeted proteins possibly affecting CRC risk.

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 &lt; 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.

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 The purpose of this study was to estimate precise age-specific tubo-ovarian carcinoma (TOC) and breast cancer (BC) risks for carriers of pathogenic variants in RAD51C and RAD51D. Methods We analyzed data from 6178 families, 125 with pathogenic variants in RAD51C, and 6690 families, 60 with pathogenic variants in RAD51D. TOC and BC relative and cumulative risks were estimated using complex segregation analysis to model the cancer inheritance patterns in families while adjusting for the mode of ascertainment of each family. All statistical tests were two-sided. Results Pathogenic variants in both RAD51C and RAD51D were associated with TOC (RAD51C: relative risk [RR] = 7.55, 95% confidence interval [CI] = 5.60 to 10.19; P = 5 × 10-40; RAD51D: RR = 7.60, 95% CI = 5.61 to 10.30; P = 5 × 10-39) and BC (RAD51C: RR = 1.99, 95% CI = 1.39 to 2.85; P = 1.55 × 10-4; RAD51D: RR = 1.83, 95% CI = 1.24 to 2.72; P = .002). For both RAD51C and RAD51D, there was a suggestion that the TOC relative risks increased with age until around age 60 years and decreased thereafter. The estimated cumulative risks of developing TOC to age 80 years were 11% (95% CI = 6% to 21%) for RAD51C and 13% (95% CI = 7% to 23%) for RAD51D pathogenic variant carriers. The estimated cumulative risks of developing BC to 80 years were 21% (95% CI = 15% to 29%) for RAD51C and 20% (95% CI = 14% to 28%) for RAD51D pathogenic variant carriers. Both TOC and BC risks for RAD51C and RAD51D pathogenic variant carriers varied by cancer family history and could be as high as 32–36% for TOC, for carriers with two first-degree relatives diagnosed with TOC, or 44–46% for BC, for carriers with two first-degree relatives diagnosed with BC. Conclusions These estimates will facilitate the genetic counseling of RAD51C and RAD51D pathogenic variant carriers and justify the incorporation of RAD51C and RAD51D into cancer risk prediction models.

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.

PURPOSETo estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized.METHODSWe analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes.RESULTSWe found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10−76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10−3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10−3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 × 10−2). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age ( P for trend = 2.0 × 10−3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies ( P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer.CONCLUSIONThese results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.

Abstract INTRODUCTION AND OBJECTIVES: Patient responses to cancer immunotherapy such as checkpoint inhibitor drugs vary greatly between patients and there remains no biomarker to predict sensitivity to these drugs. We describe a patient derived xenograft (PDX) avatar system that predicts cancer immunotherapy responses in the context of tumor heterogeneity within 8-10 days. This avatar model preserves the original tumor microenvironment and tumor infiltrating lymphocytes (TILs) at a high tumor take rate for evaluation of various immunotherapy drugs. This prediction model also involves tumor infiltrating lymphocyte isolation and primary cell generation for confirming the immunotherapy response in vitro. This PDX avatar platform generates rapid actionable information and readily identifies patients that would maximally benefit from checkpoint inhibitor therapies in a phenotype-based manner. METHODS: Tissue from patients that underwent a nephrectomy for RCC or metastasectomy were engrafted into the chorioallantoic membrane of avian embryos with a portion used for TIL isolation and primary cell generation. PD-1 and PD-L1 checkpoint inhibitors were intravenously injected and high frequency ultrasound imaging and immunophenotyping was used to quantitate changes in tumor volume, vascularity, and TIL expansion in all treatment groups. Isolated TILs were expanded and co-cultured with respective primary cells to confirm and examine immunotherapy response at a molecular level. RESULTS: Patient PDXs demonstrated heterogeneous responses to immunotherapy that relates to presence and expansion of TILs after checkpoint inhibitor injection. Patient #1 demonstrated the greatest response with a &gt;50% reduction in tumor volume and 4X expansion of T-cells over 8 days of treatment. Patient #2 demonstrated intratumoral heterogeneities in terms of tumor volume change after checkpoint inhibitors treatment despite TIL expansion in all treatment groups. Patient #3 showed no response that correlated to lack of TILs in the PDX. In vitro expansion of TILs and co-culture with primary cell line demonstrated a specific immune response via INF-gamma release and changes in immunomodulatory molecules. CONCLUSIONS: This PDX system preserves TILs and permits rapid large scale prediction of tumor specimens to various systemic therapy agents such as checkpoint inhibitors without the need for humanized models. This avatar system is a useful tool to rapidly predict and examine response to checkpoint inhibitors on a per-patient basis to improve the assignment of cancer immunotherapies to specific RCC patients. Citation Format: Mario Cepeda, Matthew Lowerison, Cindy Liu, Yarolslav Fedyshyn, Vidhu Joshi, Paras Shah, John Cheville, R. Houston Thompson, Boorjian Stephen, Bradley Leibovich, Haidong Dong, Hon S. Leong. Rapid patient derived xenograft avatars that consider tumor heterogeneity for prediction of cancer immunotherapy responses in metastatic renal cell carcinoma patients [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 LB-155.

Abstract Background Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10−8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. Methods We conducted a GWAS in European descent CRC cases and control subjects using a discovery–replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10−8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. Results The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10−8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. Conclusions This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.