CYP17A1 Network Analysis in Ovarian Serous Cystadenocarcinoma for Retrieval of Polycystic ovaries Targets

Abstract

Background/Aims: CYP17A1 is great metabolic switch for androgen overproduction which is hallmark of polycystic ovary syndrome (PCOS)initiation and progression. There is an urgent need to determine CYP17A1 mediated set of metabolic therapeutic targets for PCOS to control androgen synthesis with wide range of molecular options. Methodology: We apply rational in silico approach for determination of PCOS comprehensive set of drug targets. First, we retrieve CYP17A1 network dataset from STRING database (https://string-db.org/) by querying CYP17A1 name that gives us updated 30 nodes containing network with unique options of enrichment analysis and module extraction. The enrichment analysis determines CYP17A1 network involvement in steroidogenesis process with carcinogenesis and drug metabolism. We select ovarian serous cystadenocarcinoma dataset from cBioPortal server (https://www.cbioportal.org/) for CYP17A1 network differential analysis. Results: In this study, several steroid synthesis pathway members showed overexpression including SRD5A1, AKR1C3, CYP11B1, CYP11B2, CYP7A1, AKR1C1, AKR1D1, CYP7B1, CYP21A2, POR and HSD17B8 and are ideal biomarkers that provide cell cycle energy requirements for ovarian carcinoma. Few anti-androgenic members such as HSD17B2, STS, SULT2B1 and CYB5A showed down regulation that predicts the impact of hyper androgenemia on carcinogenesis. Drug metabolism components also showed up regulation which can be potential biomarkers for drug resistance in chemotherapies. Conclusion: Our work suggests androgen and its synthesis pathway paramount in tumorigenesis and is an excellent therapeutic target in ovarian carcinoma. In future, validation of CYP17A1 network as a signature in both ovarian serous cystadenocarcinoma and PCOS dataset may lead to novel shared therapeutic combinations and tremendous syndrome-syndrome molecular linkage for personalized medicine.