Purpose: The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Experimental Design: Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Results: Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Conclusion: Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

The pan-cancer analysis of whole genomes The expansion of whole-genome sequencing studies from individual ICGC and TCGA working groups presented the opportunity to undertake a meta-analysis of genomic features across tumour types. To achieve this, the PCAWG Consortium was established. A Technical Working Group implemented the informatics analyses by aggregating the raw sequencing data from different working groups that studied individual tumour types, aligning the sequences to the human genome and delivering a set of high-quality somatic mutation calls for downstream analysis (Extended Data Fig. 1). Given the recent meta-analysis

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.

Purpose: A significant number of women with serous ovarian cancer are intrinsically refractory to platinum-based treatment. We analyzed somatic DNA copy number variation and gene expression data to identify key mechanisms associated with primary resistance in advancedstage serous cancers. Experimental Design: Genome-wide copy number variation was measured in 118 ovarian tumors using high-resolution oligonucleotide microarrays. A well-defined subset of 85 advanced-stage serous tumors was then used to relate copy number variation to primary resistance to treatment. The discovery-based approach was complemented by quantitative-PCR copy number analysis of 12 candidate genes as independent validation of previously reported associations with clinical outcome. Likely copy number variation targets and tumor molecular subtypes were further characterized by gene expression profiling. Results: Amplification of 19q12, containing cyclin E (CCNE1), and 20q11.22-q13.12, mapping immediately adjacent to the steroid receptor coactivator NCOA3, was significantly associated with poor response to primary treatment. Other genes previously associated with copy number variation and clinical outcome in ovarian cancer were not associated with primary treatment resistance. Chemoresistant tumors with high CCNE1 copy number and protein expression were associated with increased cellular proliferation but so too was a subset of treatment-responsive patients, suggesting a cell-cycle independent role for CCNE1 in modulating chemoresponse. Patients with a poor clinical outcome without CCNE1 amplification overexpressed genes involved in extracellular matrix deposition. Conclusions: We have identified two distinct mechanisms of primary treatment failure in serous ovarian cancer, involving CCNE1 amplification and enhanced extracellular matrix deposition. CCNE1 copy number is validated as a dominant marker of patient outcome in ovarian cancer.Standard of care for women with advanced-stage ovarian cancer involves primary cytoreductive surgery followed by adjuvant chemotherapy with a platinum-based agent, often regarded as the most active component, and a taxane (1). Although response rates to first-line treatment are high, 20% to 25% of cases relapse during or soon after the cessation of primary therapy (2). The ability to predict treatment response and the development of therapies to counter primary chemoresistance are key goals of ovarian cancer research. Known platinum-resistance mechanisms include reduced drug delivery

Low grade serous ovarian tumours are a rare and under-characterised histological subtype of epithelial ovarian tumours, with little known of the molecular drivers and facilitators of tumorigenesis beyond classic oncogenic RAS/RAF mutations. With a move towards targeted therapies due to the chemoresistant nature of this subtype, it is pertinent to more fully characterise the genetic events driving this tumour type, some of which may influence response to therapy and/or development of drug resistance. We performed genome-wide high-resolution genomic copy number analysis (Affymetrix SNP6.0) and mutation hotspot screening (KRAS, BRAF, NRAS, HRAS, ERBB2 and TP53) to compare a large cohort of ovarian serous borderline tumours (SBTs, n = 57) with low grade serous carcinomas (LGSCs, n = 19). Whole exome sequencing was performed for 13 SBTs, nine LGSCs and one mixed low/high grade carcinoma. Copy number aberrations were detected in 61% (35/57) of SBTs, compared to 100% (19/19) of LGSCs. Oncogenic RAS/RAF/ERBB2 mutations were detected in 82.5% (47/57) of SBTs compared to 63% (12/19) of LGSCs, with NRAS mutations detected only in LGSC. Some copy number aberrations appeared to be enriched in LGSC, most significantly loss of 9p and homozygous deletions of the CDKN2A/2B locus. Exome sequencing identified BRAF, KRAS, NRAS, USP9X and EIF1AX as the most frequently mutated genes. We have identified markers of progression from borderline to LGSC and novel drivers of LGSC. USP9X and EIF1AX have both been linked to regulation of mTOR, suggesting that mTOR inhibitors may be a key companion treatment for targeted therapy trials of MEK and RAF inhibitors.