Integrated multi-omics analysis identifies a machine learning-derived signature for predicting prognosis and therapeutic vulnerability in clear cell renal cell carcinoma.

Abstract

Authors

• Shengqiang Chi
  Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou Zhejiang Province, China.
• Jing Ma
  Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.
• Yiming Ding
  From the Department of Radiology and Biomedical Imaging (Y.D., J.H.S., H.T., R.H., N.W.J., T.P.C., M.S.A., C.M.A., S.C.B., R.R.F., S.Y.H., Y.S., R.A.H., M.H.P., B.L.F.) and Institute for Computational Health Sciences (J.H.S., M.G.K., H.T., D.L., K.A.Z., D.H.), University of California, San Francisco, 550 Parnassus Ave, San Francisco, CA 94143; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, Calif (Y.D.); and Department of Radiology, University of California, Davis, Sacramento, Calif (L.N.).
• Zeyi Lu
  Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
• Zhenwei Zhou
  Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
• Mingchao Wang
  Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
• Gonghui Li
  Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang, China. 3193119@zju.edu.cn.
• Yuanlei Chen
  Department of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China. Electronic address: yuanlei0926@zju.edu.cn.

Keywords

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