摘要：SummaryClear cell renal cell carcinoma (ccRCC) is the most common histological type of kidney cancer and has high heterogeneity. Stratification of ccRCC is important since distinct subtypes differ in prognosis and treatment. Here, we applied a systems biology approach to stratify ccRCC into three molecular subtypes with different mRNA expression patterns and prognosis of patients. Further, we developed a set of biomarkers that could robustly classify the patients into each of the three subtypes and predict the prognosis of patients. Then, we reconstructed subtype-specific metabolic models and performed essential gene analysis to identify the potential drug targets. We identified four drug targets, includingSOAT1,CRLS1, and ACACB,essential in all the three subtypes andGPD2, exclusively essential to subtype 1. Finally, we repositioned mitotane, an FDA-approvedSOAT1inhibitor, to treat ccRCC and showed that it decreased tumor cell viability and inhibited tumor cell growth based onin vitroexperiments.Graphical abstractDisplay OmittedHighlights•Three consistent molecular ccRCC subtypes were found to guide patients' prognoses•REOs-based biomarker was developed to robustly classify patients at individual level•SOAT1is identified as a common drug target for all ccRCC subtypes•Mitotane was repositioned treatment of ccRCC via inhibitingSOAT1Bioinformatics; Systems biology; Cancer systems biology; Omics
