Citations

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932

ObjectiveThe Lymphatic Malformation Function (LMF) instrument is a preliminary parent‐report assessment designed to measure outcomes in children with cervicofacial lymphatic malformation (LM). This study aimed to assess the measurement properties of the LMF, refine it, test criterion validity, and evaluate the test‐retest reliability.Study DesignCross‐sectional.SettingTwo pediatric tertiary referral centers.SubjectsParents of 60 children from 6 months to 15 years old with cervicofacial LM.MethodsParents were recruited via mail and online. The LMF was administered on paper or online initially and again within 21 days. Response distributions and interitem correlations were examined for item reduction. Exploratory factor analysis was conducted on retained items. Cronbach’s α, Spearman correlation, and intraclass correlation (ICC) coefficients were calculated to test internal consistency, criterion validity (compared to stage), and test‐retest reliability, respectively.ResultsOne item was removed due to a floor effect. The response scale was collapsed from a 5‐point scale to a 3‐point scale due to skewness. Six items were discarded due to redundancy (interitem correlations >0.7); 2 items were discarded due to factor loadings <0.4. Exploratory factor analysis revealed a 2‐factor structure explaining 84% of variance, and the domains Signs and Impacts had good internal consistency (all Cronbach’s α >0.80 and <0.90), significant association with stage (P <. 05), and good overall test‐retest reliability (ICC, 0.82).ConclusionThe LMF has been refined into a 12‐item, 2‐domain instrument measuring LM‐specific signs and impacts with internal consistency, criterion validity, and test‐retest reliability.

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.