Edwards, Todd

Abstract Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

AbstractProblemPrevious studies identified circulating CD14+HLA‐DRlo/− monocytic cells as an immune suppressive subset in solid malignancies, such as prostate, renal cell carcinoma, and pancreatic cancer. Such monocytic cells have been implicated not only in tumour progression but also as a potential barrier for immunotherapy. This study examined the relationship between the frequency of circulating monocytic cells and epithelial ovarian cancer (EOC) progression pre‐ and post‐frontline chemotherapy, defined by disease stage, which is a leading prognostic factor for this malignancy.Method of studyIncident cases of 236 women with EOC were recruited and comprehensive flow cytometry was utilized to assess the frequency of peripheral blood CD33+CD11b+HLA‐DR−/lowCD14+CD15− monocytic cells, henceforth termed CD14+HLA‐DRlo/− monocytic cells, prior to and after completion of frontline chemotherapy. Multivariable odds ratios (OR) were used to estimate the association between CD14+HLA‐DRlo/− monocytic cell percentages and disease stage. Wilcoxon signed‐rank tests evaluated changes in these monocytic cell levels pre‐ and post‐chemotherapy in a patient subset (n = 70).ResultsPatients with elevated frequencies of circulating CD14+HLA‐DRlo/− monocytic cells at diagnosis were at 3.33‐fold greater odds of having advanced stage (III/IV) EOC (CI: 1.04‐10.64), with a significant trend in increasing CD14+HLA‐DRlo/−monocytic cell levels (P = .04). There was a 2.02% median decrease of these monocytic cells post‐chemotherapy among a subset of patients with advanced stage disease (P < .0001).ConclusionThese findings support the potential clinical relevance of CD14+HLA‐DRlo/−monocytic cells in EOC for prognosis and may indicate a non‐invasive biomarker to measure disease progression.

AbstractWe aimed to validate the prognostic association of p16 expression in ovarian high‐grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical‐grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis‐associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47–2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30–2.75, p = 0.004), while absence was associated with shorter OS in low‐grade serous carcinomas (HR: 2.95, 95% CI 1.61–5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype‐specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low‐grade serous carcinoma justifies CDK4 inhibition.

Abstract Background: Ovarian carcinoma is composed of five major histologic types, which associate with outcome and predict therapeutic response. Our aim was to evaluate histologic type assessments across the centers participating in the Ovarian Tumor Tissue Analysis (OTTA) consortium using an immunohistochemical (IHC) prediction model. Methods: Tissue microarrays (TMA) and clinical data were available for 524 pathologically confirmed ovarian carcinomas. Centralized IHC was conducted for ARID1A, CDKN2A, DKK1, HNF1B, MDM2, PGR, TP53, TFF3, VIM, and WT1, and three histologic type assessments were compared: the original pathologic type, an IHC-based calculated type (termed TB_COSPv2), and a WT1-assisted TMA core review. Results: The concordance between TB_COSPv2 type and original type was 73%. Applying WT1-assisted core review, the remaining 27% discordant cases subdivided into unclassifiable (6%), TB_COSPv2 error (6%), and original type error (15%). The largest discordant subgroup was classified as endometrioid carcinoma by original type and as high-grade serous carcinoma (HGSC) by TB_COSPv2. When TB_COSPv2 classification was used, the difference in overall survival of endometrioid carcinoma compared with HGSC became significant [RR 0.60; 95% confidence interval (CI), 0.37–0.93; P = 0.021], consistent with previous reports. In addition, 71 cases with unclear original type could be histologically classified by TB_COSPv2. Conclusions: Research cohorts, particularly those across different centers within consortia, show significant variability in original histologic type diagnosis. Our IHC-based reclassification produced more homogeneous types with respect to outcome than original type. Impact: Biomarker-based classification of ovarian carcinomas is feasible, improves comparability of results across research studies, and can reclassify cases which lack reliable original pathology. Cancer Epidemiol Biomarkers Prev; 22(10); 1677–86. ©2013 AACR.