Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus.

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.See related commentary by Choi and Brown, p. 439

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Refined cut-off for TP53 immunohistochemistry improves prediction of TP53 mutation status in ovarian mucinous tumors: implications for outcome analyses.

TP53 mutations are implicated in the progression of mucinous borderline tumors (MBOT) to mucinous ovarian carcinomas (MOC). Optimized immunohistochemistry (IHC) for TP53 has been established as a proxy for the TP53 mutation status in other ovarian tumor types. We aimed to confirm the ability of TP53 IHC to predict TP53 mutation status in ovarian mucinous tumors and to evaluate the association of TP53 mutation status with survival among patients with MBOT and MOC. Tumor tissue from an initial cohort of 113 women with MBOT/MOC was stained with optimized IHC for TP53 using tissue microarrays (75.2%) or full sections (24.8%) and interpreted using established criteria as normal or abnormal (overexpression, complete absence, or cytoplasmic). Cases were considered concordant if abnormal IHC staining predicted deleterious TP53 mutations. Discordant tissue microarray cases were re-evaluated on full sections and interpretational criteria were refined. The initial cohort was expanded to a total of 165 MBOT and 424 MOC for the examination of the association of survival with TP53 mutation status, assessed either by TP53 IHC and/or sequencing. Initially, 82/113 (72.6%) cases were concordant using the established criteria. Refined criteria for overexpression to account for intratumoral heterogeneity and terminal differentiation improved concordance to 93.8% (106/113). In the expanded cohort, 19.4% (32/165) of MBOT showed evidence for TP53 mutation and this was associated with a higher risk of recurrence, disease-specific death, and all-cause mortality (overall survival: HR = 4.6, 95% CI 1.5-14.3, p = 0.0087). Within MOC, 61.1% (259/424) harbored a TP53 mutation, but this was not associated with survival (overall survival, p = 0.77). TP53 IHC is an accurate proxy for TP53 mutation status with refined interpretation criteria accounting for intratumoral heterogeneity and terminal differentiation in ovarian mucinous tumors. TP53 mutation status is an important biomarker to identify MBOT with a higher risk of mortality.KLG is supported by the Victorian Cancer Agency (MCRF15013) and the Australian National Health and Medical Research Council (APP1045783 and #628434). This study was supported by the Peter MacCallum Cancer Foundation. CS is supported by a University of Melbourne Postgraduate Scholarship. DDB is supported by National Health and Medical Research Council of Australia (NHMRC) grants APP1092856 and APP1117044 and by the US National Cancer Institute U54 programme (U54CA209978-04). ELG and SHK are supported through P50 CA136393-10. The following cohorts that contributed to the GAMuT study were supported as follows: CASCADE: Supported by the Peter MacCallum Cancer Foundation AOCS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID400413 and ID400281). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation. The AOCS also acknowledges the cooperation of the participating institutions in Australia and acknowledges the contribution of the study nurses, research assistants and all clinical and scientific collaborators to the study. The complete AOCS Study Group can be found at www.aocstudy.org. We would like to thank all of the women who participated in these research programs. OVCARE receives core funding from The BC Cancer Foundation and the VGH and UBC Hospital Foundation. The Gynaecological Oncology Biobank at Westmead is a member of the Australasian Biospecimen Network-Oncology group, which was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. COEUR: This study uses resources provided by the Canadian Ovarian Cancer Research Consortium’s - COEUR biobank funded by the Terry Fox Research Institute and managed and supervised by the Centre hospitalier de l’Université de Montréal (CRCHUM). The Consortium acknowledges contributions to its COEUR biobank from Institutions across Canada (for a full list see http://www.tfri.ca/en/research/translational-research/coeur/coeur_biobanks.aspx). The following cohorts that contributed to OTTA were supported as follows: AOV: Canadian Institutes of Health Research (MOP-86727), Cancer Research Society (19319). BAV: ELAN Funds of the University of Erlangen-Nuremberg; DOV: NCI/NIH R01CA168758. Huntsman Cancer Foundation and the National Cancer Institute of the National Institutes of Health under Award Number P30CA042014. HAW: U.S. National 19 Institutes of Health (R01-CA58598, N01-CN-55424 and N01-PC-67001); MAY: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; SEA: SEARCH team: Mitul Shah, Jennifer Alsopp, Mercedes Jiminez-Linan SEARCH funding: Cancer Research UK (C490/A16561), the Cancer Research UK Cambridge Cancer Centre and the National Institute for Health Research Cambridge Biomedical Research Centres. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. JBD: Cancer Research UK Institute Group Award UK A22905 and A15601; STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and årKampMotCancer foundation; TVA: Canadian Institutes of Health Research grant (MOP-86727) and NIH/NCI 1 R01CA160669- 01A1; VAN: M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. The Vancouver study cohort (TVAN) is supported by BC’s Ovarian Cancer Research team (OVCARE), the BC Cancer Foundation and The VGH+UBC Hospital Foundation. WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16

Evaluation of Candidate Stromal Epithelial Cross-Talk Genes Identifies Association between Risk of Serous Ovarian Cancer and TERT, a Cancer Susceptibility “Hot-Spot”

We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n = 675) and controls (n = 1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs—PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616—were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-allele<0.05 in the discovery stage were selected for replication in a subset of five OCAC studies (n = 1,233 serous invasive cases; n = 3,364 controls). The discovery stage associations in PODXL, ITGA6, and MMP3 were attenuated in the larger replication set (adj. Pper-allele≥0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele = 0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04–1.24) p = 0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus

MicroRNA and Target Protein Patterns Reveal Physiopathological Features of Glioma Subtypes

Gliomas such as oligodendrogliomas (ODG) and glioblastomas (GBM) are brain tumours with different clinical outcomes. Histology-based classification of these tumour types is often difficult. Therefore the first aim of this study was to gain microRNA data that can be used as reliable signatures of oligodendrogliomas and glioblastomas. We investigated the levels of 282 microRNAs using membrane-array hybridisation and real-time PCR in ODG, GBM and control brain tissues. In comparison to these control tissues, 26 deregulated microRNAs were identified in tumours and the tissue levels of seven microRNAs (miR-21, miR-128, miR-132, miR-134, miR-155, miR-210 and miR-409-5p) appropriately discriminated oligodendrogliomas from glioblastomas. Genomic, epigenomic and host gene expression studies were conducted to investigate the mechanisms involved in these deregulations. Another aim of this study was to better understand glioma physiopathology looking for targets of deregulated microRNAs. We discovered that some targets of these microRNAs such as STAT3, PTBP1 or SIRT1 are differentially expressed in gliomas consistent with deregulation of microRNA expression. Moreover, MDH1, the target of several deregulated microRNAs, is repressed in glioblastomas, making an intramitochondrial-NAD reduction mediated by the mitochondrial aspartate-malate shuttle unlikely. Understanding the connections between microRNAs and bioenergetic pathways in gliomas may lead to identification of novel therapeutic targets