Prognosis and tailored treatment prediction based on key genes between polycystic ovary syndrome and uterine corpus endometrial carcinoma

Abstract

Abstract Background Polycystic ovary syndrome (PCOS) is one of the most common risk factors for the development of uterine corpus endometrial carcinoma (UCEC). Despite mounting evidence suggesting that PCOS was strongly associated with the adverse prognosis of UCEC, prognosis prediction and treatment determination remain exceedingly challenging. Results In this study, we constructed a prognostic signature for UCEC and predicted potential therapeutic agents for UCEC patients with high risk score. First, we identified the key genes between PCOS and UCEC, and explored the characteristics with multiple algorithms. Next, the bootstrap method divided samples into TCGA training and testing cohorts. Based on 25 different models, we selected the best and established a twelve-gene signature for UCEC in the training cohort. Then the signature was validated via the TCGA testing and the entire TCGA-UCEC cohorts. Univariate and multivariate analysis verified the independence of the signature. A nomogram was subsequently established to provide a quantitative tool for personalized medicine. Moreover, hallmark pathways and genomic variation analysis were used to explore the mechanism engaged in the unfavourable prognosis. Finally, apicidin has been identified to have potential therapeutic implications in the high-risk UCEC patients. Conclusions A twelve-gene signature that involved in the prognostic significance of UCEC has been constructed. Our result may shed light on personalized prognostication and tailored therapy strategies in UCEC.