METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.
RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).
CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.
METHODS: We 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.
RESULTS: We 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.
CONCLUSION: These 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.
METHODS: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.
RESULTS: The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4).
CONCLUSION: These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.
METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients.
RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively).
CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.
METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).
RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.
CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.
IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.
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.