Stig Bojesen, Georgia Chenevix-Trench, Alison Dunning and colleagues report common variants at the TERT-CLPTM1L locus associated with mean telomere length measured in whole blood. They also identify associations at this locus to breast or ovarian cancer susceptibility and report functional studies in breast and ovarian cancer tissue and cell lines. TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 × 10−7), lower risks for estrogen receptor (ER)-negative (P = 1.0 × 10−8) and BRCA1 mutation carrier (P = 1.1 × 10−5) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 × 10−14), higher risk of low-malignant-potential ovarian cancer (P = 1.3 × 10−15) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 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 splice variant.

Paul Pharoah, Joellen Schildkraut, Thomas Sellers and colleagues report a meta-analysis of genome-wide association studies for epithelial ovarian cancer and genotyping using the iCOGS array in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. They identify three new ovarian cancer susceptibility loci, including one specific to the serous subtype, and their integrated molecular analysis of genes and regulatory regions at these loci suggests disease mechanisms. Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly 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 and implicated CHMP4C in the pathogenesis of ovarian cancer.

Georgia Chenevix-Trench and colleagues report meta-analyses of genome-wide association studies identifying six loci newly associated with epithelial ovarian cancer (EOC). They also test variants at the 12 known and 6 new EOC susceptibility loci for association in BRCA1 and BRCA2 mutation carriers. Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10−8. Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.

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.

Ovarian tumors from two patients, compatible by histological and immunohistochemical criteria with small cell carcinoma of hypercalcemic type (SCCHT) (WT1+, EMA dispersed+, synaptophysin+ or dispersed+), were extensively sampled in order to find clues to their histogenesis. Subsequently, small...

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients treatment; however, the results of such studies are poorly reproducible, and critical analyses of these methods are rare. In this study we examined gene expression in 97 ovarian cancer samples. Validation of results by quantitative RT-PCR was performed also on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients prognosis. Histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints (tumor response to chemotherapy, overall survival, disease-free survival, DFS) brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found as important for DFS in the independent group, while in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worth of further testing. Our results confirm that histological tumor type is a strong confounding factor and gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Relatively small and unequal patients groups, may be a reason of poor reproducibility of statistical results, as well as the fact that the patients were treated with different chemotherapies. In addition, clinical endpoints may depend on subtle changes in many alternative molecular pathways, and this may be difficult to demonstrate by the methods applied. Also, arbitrarily performed division of samples may not reflect their true biological diversity