STAT3 polymorphisms may predict an unfavorable response to first-line platinum-based therapy for women with advanced serous epithelial ovarian cancer

Abstract

Cancer stem cells (CSC) contribute to epithelial ovarian cancer (EOC) progression and therapeutic response. We hypothesized that germline single nucleotide polymorphisms (SNPs) in CSC-related genes may predict an initial therapeutic response for women newly diagnosed with EOC. A nested case-control design was used to study 361 women with advanced-stage serous EOC treated with surgery followed by first-line platinum-based combination therapy at Moffitt Cancer Center or as part of The Cancer Genome Atlas Study. "Cases" included 102 incomplete responders (IRs) and "controls" included 259 complete clinical responders (CRs) to therapy. Using Illumina genotyping arrays and imputation, DNA samples were evaluated for 5,509 SNPs in 24 ovarian CSC-related genes. We also evaluated the overall significance of each CSC gene using the admixture maximum likelihood (AML) test, and correlated genotype with EOC tumor tissue expression. The strongest SNP-level associations with an IR to therapy were identified for correlated (r2 > 0.80) SNPs within signal transducer and activator of transcription 3 (STAT3) [odds ratio (OR), 2.24; 95% confidence interval (CI), 1.32-3.78; p = 0.0027], after adjustment for age, population stratification, grade and residual disease. At the gene level, STAT3 was significantly associated with an IR to therapy (pAML = 0.006). rs1053004, a STAT3 SNP in a putative miRNA-binding site, was associated with STAT3 expression (p = 0.057). This is the first study to identify germline STAT3 variants as independent predictors of an unfavorable therapeutic response for EOC patients. Findings suggest that STAT3 genotype may identify high-risk women likely to respond more favorably to novel therapeutic combinations that include STAT3 inhibitors. What's new? This study identified genomic biomarkers that may predict a woman's response to ovarian cancer treatment. Self-renewing cancer stem cells are key to ovarian cancer's development and spread, and the authors tested more than 5,500 SNPs in 24 ovarian cancer stem cell-related genes and compared the relationship between genotype and the patient's response to first-line ovarian cancer treatment. They identified variants in the STAT3 gene as predicting an unfavorable response to treatment, suggesting that testing this gene could help identify patients who may respond more favorably to combination therapy, possibly including STAT3 inhibitors.