Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci.

BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

DNA methylation and transcriptomic features are preserved throughout disease recurrence and chemoresistance in high grade serous ovarian cancers.

BACKGROUND: Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). METHODS: We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations. RESULTS: Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers. CONCLUSION: These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC.

Evidence of disrupted rhombic lip development in the pathogenesis of Dandy-Walker malformation.

Dandy-Walker malformation (DWM) and Cerebellar vermis hypoplasia (CVH) are commonly recognized human cerebellar malformations diagnosed following ultrasound and antenatal or postnatal MRI. Specific radiological criteria are used to distinguish them, yet little is known about their differential developmental disease mechanisms. We acquired prenatal cases diagnosed as DWM and CVH and studied cerebellar morphobiometry followed by histological and immunohistochemical analyses. This was supplemented by laser capture microdissection and RNA-sequencing of the cerebellar rhombic lip, a transient progenitor zone, to assess the altered transcriptome of DWM vs control samples. Our radiological findings confirm that the cases studied fall within the accepted biometric range of DWM. Our histopathological analysis points to reduced foliation and inferior vermian hypoplasia as common features in all examined DWM cases. We also find that the rhombic lip, a dorsal stem cell zone that drives the growth and maintenance of the posterior vermis is specifically disrupted in DWM, with reduced proliferation and self-renewal of the progenitor pool, and altered vasculature, all confirmed by transcriptomics analysis. We propose a unified model for the developmental pathogenesis of DWM. We hypothesize that rhombic lip development is disrupted through either aberrant vascularization and/or direct insult which causes reduced proliferation and failed expansion of the rhombic lip progenitor pool leading to disproportionate hypoplasia and dysplasia of the inferior vermis. Timing of insult to the developing rhombic lip (before or after 14 PCW) dictates the extent of hypoplasia and distinguishes DWM from CVH.

GENAVi: a shiny web application for gene expression normalization, analysis and visualization.

BACKGROUND: The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. RESULTS: We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. CONCLUSION: The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Genetic variation in insulin pathway genes and distal colorectal adenoma risk.

BACKGROUND: Insulin, glucose, and other insulin-related proteins that mediate insulin signaling are associated with colorectal neoplasia risk, but associations with common genetic variation in insulin axis genes are less clear. In this study, we used a comprehensive tag single-nucleotide polymorphisms (SNPs) approach to define genetic variation in six insulin axis genes (IGF1, IGF2, IGFBP1, IGFBP3, IRS1, and IRS2) and three genes associated with estrogen signaling (ESR1, ESR2, and PGR). METHODS: We assessed associations between SNPs and distal colorectal adenoma (CRA) risk in a case-control study of 1,351 subjects. Cases were individuals with one or more adenomas diagnosed during sigmoidoscopy, and controls were individuals with no adenomas at the sigmoidoscopy exam. We used unconditional logistic regression assuming an additive model to assess SNP-specific risks adjusting for multiple comparisons with P (act). RESULTS: Distal adenoma risk was significantly increased for one SNP in IGF2 [per minor allele OR = 1.41; 95 % confidence interval (CI) = 1.16, 1.67; P (act) = 0.005] and decreased for an ESR2 SNP (per minor allele OR = 0.78; 95 % CI = 0.66, 0.91; P (act) = 0.041). There was no statistically significant heterogeneity of these associations by race, sex, BMI, physical activity, or, in women, hormone replacement therapy use. Risk estimates did not differ in the colon versus rectum or for smaller (<1 cm) versus larger (>1 cm) adenomas. CONCLUSIONS: These data suggest that selected genetic variability in IGF2 and ESR2 may be modifiers of CRA risk.

Variation in folate pathway genes and distal colorectal adenoma risk: a sigmoidoscopy-based case-control study.

BACKGROUND: Folate-associated one-carbon metabolism (FOCM) is an important pathway in colorectal neoplasia risk but data on genetic variation in this pathway are largely limited to studies of single SNPs in selected genes. METHODS: We used a comprehensive tagSNP approach to study the association between genetic variation in 11 genes in the FOCM pathway and risk of incident distal colorectal adenomas in a sigmoidoscopy-based case-control study. We included 655 cases (one or more adenomas) and 695 controls (no adenomas) recruited from one of two Kaiser Permanente clinics between 1991 and 1995. We assessed a total of 159 tagSNPs selected using Haploview Tagger as well as selected non-synonymous SNPs. We used unconditional logistic regression to model the association between SNPs and risk of distal adenomas, assuming a log-additive model. RESULTS: Five SNPs in the SLC19A1 (RFC1) gene: rs1051266 (G80A), rs283895, rs2236484, rs12482346, and rs2838958 were associated with adenoma risk after correction for multiple testing (all corrected p values ≤ 0.043). The non-synonymous SLC19A1 SNP G80A interacted significantly with the MTHFR C677T genotype (interaction p value = 0.018). CONCLUSION: Our data suggest that genetic variation in SLC19A1 may modify the risk of distal colorectal adenoma.