Ovarian cancer (OC) is the seventh most commonly diagnosed cancer among women in the world and the tenth most common in China. Epithelial OC is the most predominant pathologic subtype, with five major histotypes that differ in origination, pathogenesis, molecular alterations, risk factors, and prognosis. Genetic susceptibility is manifested by rare inherited mutations with high to moderate penetrance. Genome-wide association studies have additionally identified 29 common susceptibility alleles for OC, including 14 subtype-specific alleles. Several reproductive and hormonal factors may lower risk, including parity, oral contraceptive use, and lactation, while others such as older age at menopause and hormone replacement therapy confer increased risks. These associations differ by histotype, especially for mucinous OC, likely reflecting differences in etiology. Endometrioid and clear cell OC share a similar, unique pattern of associations with increased risks among women with endometriosis and decreased risks associated with tubal ligation. OC risks associated with other gynecological conditions and procedures, such as hysterectomy, pelvic inflammatory disease, and polycystic ovarian syndrome, are less clear. Other possible risk factors include environmental and lifestyle factors such as asbestos and talc powder exposures, and cigarette smoking. The epidemiology provides clues on etiology, primary prevention, early detection, and possibly even therapeutic strategies.

The homeobox A (HOXA) region of protein-coding genes impacts female reproductive system embryogenesis and ovarian carcinogenesis. The 5-prime end of HOXA includes three long non-coding RNAs (lncRNAs) (HOXA10-AS, HOXA11-AS, and HOTTIP) that are underexplored in epithelial ovarian cancer (EOC). We evaluated whether common genetic variants in these lncRNAs are associated with EOC risk and/or have functional roles in EOC development. Using genome-wide association study data from 1,201 serous EOC cases and 2,009 controls, an exonic variant within HOXA11-AS, rs17427875 (A>T), was marginally associated with reduced serous EOC risk (OR = 0.88 (95% CI: 0.78-1.01, p = 0.06). Functional studies of ectopic expression of HOXA11-AS minor allele T in EOC cells showed decreased survival, proliferation, migration, and invasion compared to common allele A expression. Additionally, stable expression of HOXA11-AS minor allele T reduced primary tumor growth in mouse xenograft models to a greater extent than common allele A. Furthermore, HOXA11-AS expression levels were significantly lower in human EOC tumors than normal ovarian tissues (p < 0.05), suggesting that HOXA11-AS has a tumor suppressor function in EOC which may be enhanced by the T allele. These findings demonstrate for the first time a role for HOXA11-AS in EOC with effects that could be modified by germline variants.

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-staged approach to conduct genome-wide association studies for lung, ovary, breast, prostate and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression.

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 -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 < 2.2 × 10, we identified 35 genes, including at 11q14.2 (Z = 5.08, = 3.83 × 10, 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 ( < 1.47 × 10). These data identify one novel locus ) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. .

Background: Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.Methods: CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.Results: Three CNVRs were associated (P < 0.01) with EOC risk: two large ($100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR ¼ 2.57; P ¼ 0.001) and a deletion at CYP2A7 (OR ¼ 1.90; P ¼ 0.007) that were strongly associated with HGSOC risk (OR ¼ 3.02; P ¼ 8.98 Â 10 À5 ). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P ¼ 2.94 Â 10 À47 ). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR ¼ 0.33; P ¼ 9.5 Â 10 À2 ), and somatic deletions correlated with ERBB4 downregulation (P ¼ 7.05 Â 10 À5 ). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR ¼ 0.28; P ¼ 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P ¼ 2.7 Â 10 À7 ), and another at 8p21.2 (OR ¼ 0.52; P ¼ 0.002) that was present somatically where it correlated with lower GNRH1 expression (P ¼ 5.9 Â 10 À5 ).Conclusions: Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.Impact: Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from highdensity arrays.CNVR was defined by overlapping CNV segments across subjects. P values are from logistic regression adjusted for the first principal component. b CNV segments centered on the reported genes, which fell within the SNP-level significance region. Authors' ContributionsConception and design: B.M. Reid, J.B. Permuth, E.L. Goode, T.A. Sellers Development of methodology: B.M. Reid Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J.M. Cunningham, S. Narod, H. Risch, J.M. Schildkraut, T.A. Sellers Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis):

Background: Large-scale genome-wide association studies (GWAS) have identified ~35 loci associated with epithelial ovarian cancer risk. However, these genetic loci together explain only a small portion of the heritability of this malignancy. The large majority of the GWAS-identified variants are located in non-coding regions, thus possible causal genes in these loci remain largely unknown. We performed a transcriptome-wide association study (TWAS) to search for novel genetic loci for ovarian cancer risk and plausible causal genes at GWAS-identified loci. Method: Transcriptome data from normal ovarian tissue samples (n=68) and all tissue samples (n = 369), along with their high-density genotyping data, obtained from only European descendants included in the Genotype-Tissue Expression Project (GTEx), were used to build ovarian linear prediction models and cross-tissue models (to increase statistical power) using the elastic net method. Based on model performance, we evaluated 17,121 genes for their cis-predicted gene expressions in relation to ovarian cancer risk using summary statistics data generated in GWAS of ovarian cancer from 25,509 cases and 40,941 controls. MetaXcan was used to integrate gene expression prediction model with summary statistics. Results: We identified 35 genes with predicted expression levels associated with ovarian cancer risk at P value &lt; 2.2 × 10-6, the Bonferroni corrected significance level for multiple comparisons. Of these, 12 genes at 4 genetic loci are located ≥500kb away from risk SNPs previously reported in GWAS, representing potential novel genetic loci for ovarian cancer risk. The remaining 23 genes at 12 loci are located within known ovarian cancer risk loci. Fifteen of these genes at the 12 loci have not been reported in previous studies. Analyses by ovarian cancer histological subtypes showed that the majority of these 35 genes are associated with serous invasive carcinoma. Several new associations were identified in histological subtype analyses. Conclusion: In this TWAS we identified multiple genes with predicted expressions related to ovarian cancer risk and provide substantial new information to enhance the understanding of ovarian cancer biology and genetics. Citation Format: Yingchang Lu, Joellen M. Schildkraut, Thomas A. Sellers, Lang Wu, Xingyi Guo, Bingshan Li, Y. Ann Chen, Jennifer B. Doherty, Simon Gayther, Ellen L. Goode, Hae Kyung Im, Siddhartha Kar, Kate Lawrenson, Ani W. Manichaikul, Jennifer B. Permuth, Brett M. Reid, Jamie K. Teer, Paul Pharoah, Wei Zheng, Jirong Long. Transcriptome-wide association study among 66,450 women to identify candidate susceptible genes for ovarian cancer risk [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 1308. doi:10.1158/1538-7445.AM2017-1308

Cancer stem cells (CSC) contribute to epithelial ovarian cancer (EOC) progression and therapeutic response. We hypothesized that germline single nucleotide polymorphisms (SNPs) in CSC-related genes may predict an initial therapeutic response for women newly diagnosed with EOC. A nested case–control design was used to study 361 women with advanced-stage serous EOC treated with surgery followed by first-line platinum-based combination therapy at Moffitt Cancer Center or as part of The Cancer Genome Atlas Study. “Cases” included 102 incomplete responders (IRs) and “controls” included 259 complete clinical responders (CRs) to therapy. Using Illumina genotyping arrays and imputation, DNA samples were evaluated for 5,509 SNPs in 24 ovarian CSC-related genes. We also evaluated the overall significance of each CSC gene using the admixture maximum likelihood (AML) test, and correlated genotype with EOC tumor tissue expression. The strongest SNP-level associations with an IR to therapy were identified for correlated (r2 > 0.80) SNPs within signal transducer and activator of transcription 3 (STAT3) [odds ratio (OR), 2.24; 95% confidence interval (CI), 1.32–3.78; p = 0.0027], after adjustment for age, population stratification, grade and residual disease. At the gene level, STAT3 was significantly associated with an IR to therapy (pAML 5 0.006). rs1053004, a STAT3 SNP in a putative miRNA-binding site, was associated with STAT3 expression (p = 0.057). This is the first study to identify germline STAT3 variants as independent predictors of an unfavorable therapeutic response for EOC patients. Findings suggest that STAT3 genotype may identify high-risk women likely to respond more favorably to novel therapeutic combinations that include STAT3 inhibitors.

Adjuvant chemotherapy for solid tumors based on platinum-derived compounds such as cisplatin is the treatment of choice in most cases. Cisplatin triggers signaling pathways that lead to cell death, but it also induces changes in tumor cells that modify the therapeutic response, thereby leading to cisplatin resistance. We have recently reported that microRNA-7 is silenced by DNA methylation and is involved in the resistance to platinum in cancer cells through the action of the musculoaponeurotic fibrosarcoma oncogene family, protein G (MAFG). In the present study, we first confirm the miR-7 epigenetic regulation of MAFG in 44 normal- and/or tumor-paired samples in non-small-cell lung cancer (NSCLC). We also provide translational evidence of the role of MAFG and the clinical outcome in NSCLC by the interrogation of two extensive in silico databases of 2019 patients. Moreover, we propose that MAFG-mediated resistance could be conferred due to lower reactive oxygen species production after cisplatin exposure. We developed specifically selected aptamers against MAFG, with high sensitivity to detect the protein at a nuclear level probed by aptacytochemistry and histochemistry analyses. The inhibition of MAFG activity through the action of the specific aptamer apMAFG6F increased the levels of reactive oxygen species production and the sensitivity to cisplatin. We report first the specific nuclear identification of MAFG as a novel detection method for diagnosis in NSCLC, and then we report that MAFG modulates the redox response and confers cell protection against free radicals generated after platinum administration, thus also being a promising therapeutic target.