Gapstur, Susan M.

Investigating the most likely causal variants identified by fine‐mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine‐scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR‐rs7558475 and current smoking (ORint = 0.77, 95% CI: 0.67–0.88, pint = 1.8 × 10−4). The interaction with the strongest statistical evidence was found between 5q14‐rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16–1.59, pint = 1.9 × 10−5) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21‐rs6796502 and age at menarche (ORint = 1.26, 95% CI: 1.12–1.43, pint =1.8 × 10−4) and between 8q23‐rs13267382 and age at first full‐term pregnancy (ORint = 0.89, 95% CI: 0.83–0.95, pint = 5.2 × 10−4). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P &lt; 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P &lt; 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932

Abstract Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). Results: We observed no significant association between genetic variants and prostate cancer survival. Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study. Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev; 24(11); 1796–800. ©2015 AACR.

Abstract Background: To better understand colorectal cancer etiology and prognosis, archived surgical tissues were collected from Cancer Prevention Study II (CPS-II) Nutrition Cohort participants who were diagnosed with colorectal cancer. Herein, the methodology for this collection is described to help inform other efforts to collect tissues. Methods: The main components to accruing tissue were: (i) obtaining consent from participants or next-of-kin; (ii) contacting hospitals to request materials; and (iii) pathology review and laboratory processing. Results: In CPS-II, we identified 3,643 participants diagnosed with colorectal cancer between 1992/1993 and 2009. Of these, tissue could not be sought from cases verified through state cancer registry linkage (N = 1,622), because of insufficient information on tissue location. We sought tissue from the 2,021 cases verified using medical records, and received tissue from 882. When hospitals were contacted within 10 years of diagnosis, we received 87% of tissue materials; beyond that 10-year mark, we received 32%. Compared with the 2,761 colorectal cancer cases without tissue, the 882 cases with tissue were more likely to be alive, diagnosed more recently during follow-up, and had less-advanced staged disease. Cases with and without tissues were similar with respect to age at diagnosis, smoking, body mass index, physical activity, and other epidemiologic factors. Conclusions: Some of the most important elements in forming a tissue repository included having the cases' hospital contact and surgical accession information as well as contacting patients/next-of-kin and hospitals within 10 years of surgery. Impact: This tissue repository will serve as an important resource for colorectal cancer studies. See all the articles in this CEBP Focus section, “Biomarkers, Biospecimens, and New Technologies in Molecular Epidemiology.” Cancer Epidemiol Biomarkers Prev; 23(12); 2694–702. ©2014 AACR.