Berchuck, Andrew

AbstractWe aimed to validate the prognostic association of p16 expression in ovarian high‐grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical‐grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis‐associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47–2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30–2.75, p = 0.004), while absence was associated with shorter OS in low‐grade serous carcinomas (HR: 2.95, 95% CI 1.61–5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype‐specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low‐grade serous carcinoma justifies CDK4 inhibition.

Abstract Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P &lt; 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P &lt; 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.

Abstract Epithelial ovarian cancer (EOC) is a rare but deadly disease for which there is notably poorer survival in women of African Ancestry (AA) compared to women of European Ancestry (EA). Previous EA-based genome-wide association studies (GWAS) have identified 30 common, low penetrant EOC susceptibility alleles. Using the custom-designed 533,631 SNP Illumina OncoArray and imputation to ~12 million genetic variants in the 1000 Genomes Phase 3, we conducted a GWAS in 755 AA EOC cases, including 537 high-grade serous ovarian cancer (HGSOC) cases, and 1,235 AA controls from the Ovarian Cancer Association Consortium (OCAC). We identified novel susceptibility loci with suggestive evidence of association with EOC, based on a threshold of P&lt;1x10-6, at three distinct loci including 10p15.1 (lead SNP rs4525119, intronic to AKR1C3, P=4.9 x 10-7, minor allele frequency [MAF]=0.33), 3p25.3 (lead SNP rs7643459, intronic to LOC101927394, P=8.4 x 10-7, MAF=0.36), and 4q13.3 (lead SNP rs4286604, 15 kb 3’ of UGT2A1, P=8.5x10-7, MAF=0.27). In analysis of HGSOC, we identified suggestive evidence of association at six distinct loci including 5q11.2 (lead SNP rs37792, 132 kb 5’ of FST, P=6.0x10-8, MAF=0.34), Xq27.2 (lead SNP rs57403204, 81 kb 3' of MAGEC1, P=1.7x10-7, MAF=0.06), 10p15.1 (lead SNP rs79079890, LOC105376360 intronic, P=3.0x10-7, MAF=0.03), 17p25.1 (lead SNP rs66459581, 5 kb 5’ of PRPSAP1, P=5.1x10-7, MAF=0.23), 15p12 (lead SNP rs116046250, GABRG3 intronic, P=8.7x10-7, MAF=0.05), and 4q21.21 (lead SNP rs192876988, 30 kb 3’ of GK2, P=9.2x10-7, MAF=0.05). These SNPs showed no evidence of association with risk in the OCAC EA GWAS including up to 23,543 EOC cases and 29,444 controls. Of the SNPs identified with suggestive evidence of association in our GWAS, two are located near genes known to regulate hormones and previously reported in relation to diseases of the ovary (AKR1C3 and FST), two have been linked to cancer (AKR1C3 and MAGEC1) and one represents testis-specific expression (GK2). Of the 30 SNPs identified previously in a EA EOC GWAS, we observed nominally significant associations (P&lt;0.05) with consistent direction of effect for eight SNPs in AA women. Our investigation presents evidence of (1) variants for EOC shared among EA and AA women and (2) novel EOC risk loci of importance for AA women. Citation Format: Ani Manichaikul, Lauren C. Peres, Xin-Qun Wang, Kate Lawrenson, Sarah Abbott, Ann G. Schwartz, Anna H. Wu, Edward Peters, Patricia G. Moorman, Michele L. Cote, Melissa Bondy, Linda Kelemen, Ellen L. Goode, Jill Barnholtz-Sloan, Simon A. Gather, Andrew Berchuck, Jennifer A. Doherty, Paul Pharoah, Joellen Schildkraut. Identification of novel epithelial ovarian cancer loci in women of African ancestry from the Ovarian Cancer Association Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1307. doi:10.1158/1538-7445.AM2017-1307

Abstract In this review, we summarize current progress in the genetic epidemiology of epithelial ovarian cancer (EOC), focusing exclusively on elucidating the role of common germline genetic variation in conferring susceptibility to EOC. We provide an overview of the more than 30 EOC risk loci identified to date by genome-wide association studies (GWAS) and describe the contribution of large-scale, cross-cancer type, custom genotyping projects, such as the OncoArray and the Collaborative Oncological Gene-Environment Study, to locus discovery and replication. We discuss the histotype-specific nature of these EOC risk loci, pleiotropy, or overlapping genetic effects between EOC and other hormone-related cancer types, and the application of findings to polygenic risk prediction for EOC. The second part of the article offers a concise review of primarily laboratory-based studies that have led to the identification of several putative EOC susceptibility genes using common variants at the known EOC risk loci as starting points. More global biological insights emerging from network- and pathway-based analyses of GWAS for EOC susceptibility are also highlighted. Finally, we delve into potential future directions, including the need to identify EOC risk loci in non-European populations and the next generation of GWAS functional studies that are likely to involve genome editing to establish the cell type–specific carcinogenic effects of EOC risk variants Cancer Epidemiol Biomarkers Prev; 27(4); 395–404. ©2018 AACR. See all articles in this CEBP Focus section, “Genome-Wide Association Studies in Cancer.”

Abstract Background: Genome-wide association studies (GWAS) have identified multiple loci associated with epithelial ovarian cancer (EOC) susceptibility, but further progress requires integration of epidemiology and biology to illuminate true risk loci below genome-wide significance levels (P &lt; 5 × 10−8). Most risk SNPs lie within non–protein-encoding regions, and we hypothesize that long noncoding RNA (lncRNA) genes are enriched at EOC risk regions and represent biologically relevant functional targets. Methods: Using imputed GWAS data from about 18,000 invasive EOC cases and 34,000 controls of European ancestry, the GENCODE (v19) lncRNA database was used to annotate SNPs from 13,442 lncRNAs for permutation-based enrichment analysis. Tumor expression quantitative trait locus (eQTL) analysis was performed for sub-genome-wide regions (1 × 10−5 &gt; P &gt; 5 × 10−8) overlapping lncRNAs. Results: Of 5,294 EOC-associated SNPs (P &lt; 1.0 × 10−5), 1,464 (28%) mapped within 53 unique lncRNAs and an additional 3,484 (66%) SNPs were correlated (r2 &gt; 0.2) with SNPs within 115 lncRNAs. EOC-associated SNPs comprised 130 independent regions, of which 72 (55%) overlapped with lncRNAs, representing a significant enrichment (P = 5.0 × 10−4) that was more pronounced among a subset of 5,401 lncRNAs with active epigenetic regulation in normal ovarian tissue. EOC-associated lncRNAs and their putative promoters and transcription factors were enriched for biologically relevant pathways and eQTL analysis identified five novel putative risk regions with allele-specific effects on lncRNA gene expression. Conclusions: lncRNAs are significantly enriched at EOC risk regions, suggesting a mechanistic role for lncRNAs in driving predisposition to EOC. Impact: lncRNAs represent key candidates for integrative epidemiologic and functional studies. Further research on their biologic role in ovarian cancer is indicated. Cancer Epidemiol Biomarkers Prev; 26(1); 116–25. ©2016 AACR.

Abstract Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.