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

TERT-locus single nucleotide polymorphisms (SNPs) and leucocyte telomere measures are reportedly associated with risks of multiple cancers. Using the iCOGs chip, we analysed ~480 TERT-locus SNPs in breast (n=103,991), ovarian (n=39,774) and BRCA1 mutation carrier (11,705) cancer cases and controls. 53,724 participants have leucocyte telomere measures. Most associations cluster into three independent peaks. Peak 1 SNP rs2736108 minor allele associates with longer telomeres (P=5.8×10 −7 ), reduced estrogen receptor negative (ER-negative) (P=1.0×10 −8 ) and BRCA1 mutation carrier (P=1.1×10 −5 ) breast cancer risks, and altered promoter-assay signal. Peak 2 SNP rs7705526 minor allele associates with longer telomeres (P=2.3×10 −14 ), increased low malignant potential ovarian cancer risk (P=1.3×10 −15 ) and increased promoter activity. Peak 3 SNPs rs10069690 and rs2242652 minor alleles increase ER-negative (P=1.2×10 −12 ) and BRCA1 mutation carrier (P=1.6×10 −14 ) breast and invasive ovarian (P=1.3×10 −11 ) cancer risks, but not via altered telomere length. The cancer-risk alleles of rs2242652 and rs10069690 respectively increase silencing and generate a truncated TERT splicevariant.

Genome wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC) with another two loci being close to genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the United Kingdom. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. Follow-up genotyping was carried out in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 previously near genome-wide significance and identified three novel loci associated with risk; two loci associated with all EOC subtypes, at 8q21 (rs11782652, P=5.5×10-9) and 10p12 (rs1243180; P=1.8×10-8), and another locus specific to the serous subtype at 17q12 (rs757210; P=8.1×10-10). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility that implicates CHMP4C in the pathogenesis of ovarian cancer.

Summary We performed genomic, epigenomic, transcriptomic and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7 and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest amongst all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy number alterations in genes that are therapeutic targets were identified.

Molecular classification of high-grade serous ovarian cancer (HGSOC) using transcriptional profiling has proven to be complex and difficult to validate across studies. We determined gene expression profiles of 174 well-annotated HGSOCs and demonstrate prognostic significance of the prespecified TCGA Network gene signatures. Furthermore, we confirm the presence of four HGSOC transcriptional subtypes using a de novo classification. Survival differed statistically significantly between de novo subtypes (log rank, P = .006) and was the best for the immunoreactive-like subtype, but statistically significantly worse for the proliferative- or mesenchymal-like subtypes (adjusted hazard ratio = 1.89, 95% confidence interval = 1.18 to 3.02, P = .008, and adjusted hazard ratio = 2.45, 95% confidence interval = 1.43 to 4.18, P = .001, respectively). More prognostic information was provided by the de novo than the TCGA classification (Likelihood Ratio tests, P = .003 and P = .04, respectively). All statistical tests were two-sided. These findings were replicated in an external data set of 185 HGSOCs and confirm the presence of four prognostically relevant molecular subtypes that have the potential to guide therapy decisions.

To our knowledge, L1CAM has been shown to be the best-ever published prognostic factor in FIGO stage I, type I endometrial cancers and shows clear superiority over the standardly used multifactor risk score. L1CAM expression in type I cancers indicates the need for adjuvant treatment. This adhesion molecule might serve as a treatment target for the fully humanized anti-L1CAM antibody currently under development for clinical use.

Purpose PD-0332991 is a selective inhibitor of the CDK4/6 kinases with the ability to block retinoblastoma (Rb) phosphorylation in the low nanomolar range. Here we investigate the role of CDK4/6 inhibition in human ovarian cancer. Experimental Design We examined the effects of PD-0332991 on proliferation, cell-cycle, apoptosis, and Rb phosphorylation using a panel of 40 established human ovarian cancer cell lines. Molecular markers for response prediction, including p16 and Rb, were studied using gene expression profiling, Western blot, and array CGH. Multiple drug effect analysis was used to study interactions with chemotherapeutic drugs. Expression of p16 and Rb was studied using immunohistochemistry in a large clinical cohort of ovarian cancer patients. Results Concentration-dependent antiproliferative effects of PD-0332991 were seen in all ovarian cancer cell lines, but varied significantly between individual lines. Rb-proficient cell lines with low p16 expression were most responsive to CDK4/6 inhibition. Copy number variations of CDKN2A, RB, CCNE1, and CCND1 were associated with response to PD-0332991. CDK4/6 inhibition induced G0/G1 cell cycle arrest, blocked Rb phosphorylation in a concentration-and time-dependent manner, and enhanced the effects of chemotherapy. Rb-proficiency with low p16 expression was seen in 97/262 (37%) of ovarian cancer patients and was independently associated with poor progression-free survival (adjusted relative risk 1.49, 95% CI 1.00 –2.24, P = 0.052). Conclusions PD-0332991 shows promising biologic activity in ovarian cancer cell lines. Assessment of Rb and p16 expression may help select patients most likely to benefit from CDK4/6 inhibition in ovarian cancer.

HNF1B is overexpressed in clear cell epithelial ovarian cancer, and we observed epigenetic silencing in serous epithelial ovarian cancer, leading us to hypothesize that variation in this gene differentially associates with epithelial ovarian cancer risk according to histological subtype. Here we comprehensively map variation in HNF1B with respect to epithelial ovarian cancer risk and analyse DNA methylation and expression profiles across histological subtypes. Different single-nucleotide polymorphisms associate with invasive serous (rs7405776 odds ratio (OR) = 1.13, P = 3.1 × 10−10) and clear cell (rs11651755 OR = 0.77, P = 1.6 × 10−8) epithelial ovarian cancer. Risk alleles for the serous subtype associate with higher HNF1B-promoter methylation in these tumours. Unmethylated, expressed HNF1B, primarily present in clear cell tumours, coincides with a CpG island methylator phenotype affecting numerous other promoters throughout the genome. Different variants in HNF1B associate with risk of serous and clear cell epithelial ovarian cancer; DNA methylation and expression patterns are also notably distinct between these subtypes. These findings underscore distinct mechanisms driving different epithelial ovarian cancer histological subtypes.