To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3, 9q31.1) and one for endometrioid EOC (5q12.3). We then meta-analysed the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified an additional three loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a novel susceptibility gene for low grade/borderline serous EOC.

We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study (TWAS) of gene expression and splice junction usage in HGSOC-relevant tissue types (N = 2,169) and the largest GWAS available for HGSOC (N = 13,037 cases/40,941 controls). We identified 25 TWAS significant genes, 7 at the junction level only, including LRRC46 at 19q21.32, (P = 1 × 10−9), CHMP4C at 8q21 (P = 2 × 10−11), and a PRC1 junction at 15q26 (P = 7 × 10−9). In vitro assays for CHMP4C showed the associated variant induces allele specific exon inclusion (P = 0.0024). Functional screens in HGSOC cell lines found evidence of essentiality for three of the novel genes we identified: HAUS6, KANSL1 and PRC1, with the latter comparable to CMYC. Our study implicated at least one target gene for 6/13 distinct GWAS regions, identifying 23 novel candidate susceptibility genes for HGSOC.

Purpose: BRCA1 pathogenic variant heterozygotes are at a substantially increased risk for breast and ovarian cancer. The widespread uptake of testing has led to a significant increase in the detection of missense variants in BRCA1, the vast majority of which are variants of uncertain clinical significance (VUS), posing a challenge to genetic counseling. Here, we harness a wealth of functional data for thousands of variants to aid in variant classification. Methods: We have collected, curated, and harmonized functional data for 2701 missense variants representing 24.5% of possible missense variants in BRCA1. Results were harmonized across studies by converting data into binary categorical variables (functional impact versus no functional impact). Using a panel of reference variants we identified a subset of assays with high sensitivity and specificity (≥80%) and apply the American College of Medical Genetics and Genomics/ Association for Molecular Pathology (ACMG/AMP) variant interpretation guidelines to assign evidence criteria for classification. Results: Integration of data from validated assays provided ACMG/ AMP evidence criteria in favor of pathogenicity for 297 variants or against pathogenicity for 2058 representing 96.2% of current VUS functionally assessed. We also explore discordant results and identify limitations in the approach. Conclusion: High quality functional data are available for BRCA1 missense variants and provide evidence for classification of 2355 VUS according to their pathogenicity.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer.Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. 12 16,915,387-16,915,739 NOTE: LD (r 2 ! 0.3) to rs3814113 based on 1000GP data v3. rs2153271 is reported in dbSNP as the reverse orientation to the genome. SNPs in bold represent the final five SNPs remaining at the end of the functional analysis. SNP in bold and underline indicates the only SNP that is common to the two analytic approaches. Abbreviations: MAF, minor allele frequency; NA, not available.Buckley et al.

Purpose: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS). Experimental Design: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes. Results: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE. Conclusions: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways.

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Nitrogen mustards were the first clinically useful anticancer agents [1] and its derivatives, such as cyclophosphamide, are still among the most widely used antitumor drugs [2]. Cyclophosphamide is a derivative of nitrogen mustards with a modified chemical structure that confers it a greater specificity for cancer cells [3]. The rational on developing cyclophosphamide was that cancer cells express higher levels of phosphamidase, which is able to cleave the phosphorus-nitrogen (P-N) bond, releasing the nitrogen mustard within the cancer cell [4]; this premise was later proven inaccurate [5]. The first clinical trials with cyclophosphamide occurred in 1958, when this drug was found to be the most effective anticancer compound against 33 cancer types on a 1,000 compounds screening trial [6]. In 1959, cyclophosphamide was approved by the Food and Drug Administration (FDA) as a cytotoxic anticancer compound, and up until now, over 50 years of its approval, it is still one of the most successful anticancer drugs [5]. Cyclophosphamide is used for the treatment of lymphoma, leukemias, breast and ovary cancers [7-10]. Cyclophosphamide is administered as a prodrug which is highly stable and requires hepatic mixed function oxidase system to be metabolically activated. Hepatic cytochrome P-450 systems are responsible for generating 4-hydroxycyclophosphamide by the hydroxylation of Cancer Treatment-Conventional and Innovative Approaches 4

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