Prognostic Relevance of BRCA1 Expression in Survival of Patients With Cervical Cancer - Paik, E Sun; Chang, Chi-Son; Chae, Ye Lin; Oh, So Young; Byeon, Sun-Ju; Kim, Chul Jung; Lee, Yoo-Young; Kim, Tae-Joong; Lee, Jeong-Won; Kim, Byoung-Gie; Choi, Chel Hun (Frontiers in Oncology, 2021)
Objective BRCA1 expression can be lost by a variety of mechanisms including germline or somatic mutation and promotor hypermethylation. Given the potential importance of BRCA1 loss as a predictive and prognostic biomarker in several cancers, the objective of this study was to investigate BRCA1 expression using immunohistochemistry (IHC) in cervical cancer and its possible prognostic relevance. Methods Seventy patients with cervical cancer were enrolled in this study. Samples from each tumor were stained for BRCA1 and reviewed independently by gynecologic pathologists blinded to the BRCA status. Kaplan–Meier methods were used to estimate overall survival according to BRCA1 expression. Differentially expressed genes (DEGs) by BRCA1 expression were selected using GSE44001 dataset, which included 300 samples treated with radical hysterectomy. In addition, cox regression analysis with backward elimination was performed to select independent prognostic markers. Gene set enrichment analysis (GSEA) was done using these DEGs. Results BRCA1 IHC was positive in 62.9% (44/70) of cases. Patients with BRCA1 expression showed better overall survival (100% vs. 76.2%, HR 0.20, 95% CI 0.04 – 0.99, p = 0.028) than those without BRCA1 expression. Analysis of gene expression profiles according to BRCA1 expression identified 321 differentially expressed mRNAs. Gene set enrichment analysis results showed two dysregulated pathways (VEGF_A_UP.V1_DN and E2F1_UP.V1_UP). Of these DEGs, alterations of 20 gene signatures were found to be independently associated with survival outcomes of patients. Conclusions BRCA1 expression in cervical cancer tissue is associated with survival. In addition, the identification of specific gene alterations associated with BRCA1 expression could help to provide individualized prediction in these patients.