Braicu, Elena Ioana

AbstractBackgroundBRCA1 methylation has been associated with homologous recombination deficiency, a biomarker of platinum sensitivity. Studies evaluating BRCA1-methylated tubal and ovarian cancer (OC) do not consistently support improved survival following platinum chemotherapy. We examine the characteristics of BRCA1-methylated OC in a meta-analysis of individual participant data.MethodsData of 2636 participants across 15 studies were analyzed. BRCA1-methylated tumors were defined according to their original study. Associations between BRCA1 methylation and clinicopathological characteristics were evaluated. The effects of methylation on overall survival (OS) and progression-free survival (PFS) were examined using mixed-effects models. All statistical tests were 2-sided.Results430 (16.3%) tumors were BRCA1-methylated. BRCA1 methylation was associated with younger age and advanced-stage, high-grade serous OC. There were no survival differences between BRCA1-methylated and non–BRCA1-methylated OC (median PFS = 20.0 vs 18.5 months, hazard ratio [HR] = 1.01, 95% CI = 0.87 to 1.16; P = .98; median OS = 46.6 vs 48.0 months, HR = 1.02, 95% CI = 0.87 to 1.18; P = .96). Where BRCA1/2 mutations were evaluated (n = 1248), BRCA1 methylation displayed no survival advantage over BRCA1/2-intact (BRCA1/2 wild-type non–BRCA1-methylated) OC. Studies used different methods to define BRCA1 methylation. Where BRCA1 methylation was determined using methylation-specific polymerase chain reaction and gel electrophoresis (n = 834), it was associated with improved survival (PFS: HR = 0.80, 95% CI = 0.66 to 0.97; P = .02; OS: HR = 0.80, 95% CI = 0.63 to 1.00; P = .05) on mixed-effects modeling.ConclusionBRCA1-methylated OC displays similar clinicopathological features to BRCA1-mutated OC but is not associated with survival. Heterogeneity within BRCA1 methylation assays influences associations. Refining these assays may better identify cases with silenced BRCA1 function and improved patient outcomes.

Abstract Purpose: Predicting surgical outcome could improve individualizing treatment strategies for patients with advanced ovarian cancer. It has been suggested earlier that gene expression signatures (GES) might harbor the potential to predict surgical outcome. Experimental Design: Data derived from high-grade serous tumor tissue of FIGO stage IIIC/IV patients of AGO-OVAR11 trial were used to generate a transcriptome profiling. Previously identified molecular signatures were tested. A theoretical model was implemented to evaluate the impact of medically associated factors for residual disease (RD) on the performance of GES that predicts RD status. Results: A total of 266 patients met inclusion criteria, of those, 39.1% underwent complete resection. Previously reported GES did not predict RD in this cohort. Similarly, The Cancer Genome Atlas molecular subtypes, an independent de novo signature and the total gene expression dataset using all 21,000 genes were not able to predict RD status. Medical reasons for RD were identified as potential limiting factors that impact the ability to use GES to predict RD. In a center with high complete resection rates, a GES which would perfectly predict tumor biological RD would have a performance of only AUC 0.83, due to reasons other than tumor biology. Conclusions: Previously identified GES cannot be generalized. Medically associated factors for RD may be the main obstacle to predict surgical outcome in an all-comer population of patients with advanced ovarian cancer. If biomarkers derived from tumor tissue are used to predict outcome of patients with cancer, selection bias should be focused on to prevent overestimation of the power of such a biomarker. See related commentary by Handley and Sood, p. 9