Systematic characterization of mutations altering protein degradation in human cancers.

Journal: Molecular cell
Published Date: Mar 18, 2021

Abstract

The ubiquitin-proteasome system (UPS) is the primary route for selective protein degradation in human cells. The UPS is an attractive target for novel cancer therapies, but the precise UPS genes and substrates important for cancer growth are incompletely understood. Leveraging multi-omics data across more than 9,000 human tumors and 33 cancer types, we found that over 19% of all cancer driver genes affect UPS function. We implicate transcription factors as important substrates and show that c-Myc stability is modulated by CUL3. Moreover, we developed a deep learning model (deepDegron) to identify mutations that result in degron loss and experimentally validated the prediction that gain-of-function truncating mutations in GATA3 and PPM1D result in increased protein stability. Last, we identified UPS driver genes associated with prognosis and the tumor microenvironment. This study demonstrates the important role of UPS dysregulation in human cancer and underscores the potential therapeutic utility of targeting the UPS.

Authors

  • Collin Tokheim
    Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland.
  • Xiaoqing Wang
    Department of Anesthesiology and Operation, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
  • Richard T Timms
    Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
  • Boning Zhang
    Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
  • Elijah L Mena
    Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
  • Binbin Wang
    Center for Genetics, National Research Institute for Family Planning, Beijing 100081, China Biozy@ict.ac.cn Nicgr@263.net.
  • Cynthia Chen
    Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA.
  • Jun Ge
    Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China. speegejun510@gzhu.edu.cn sspan@gzhu.edu.cn.
  • Jun Chu
    Key Laboratory of Xin'an Medicine, Ministry of Education, Anhui University of Chinese Medicine, Hefei, Anhui 230038, China.
  • Wubing Zhang
    Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China.
  • Stephen J Elledge
    Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. Electronic address: selledge@genetics.med.harvard.edu.
  • Myles Brown
    Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Electronic address: myles_brown@dfci.harvard.edu.
  • X Shirley Liu
    Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address: xsliu@ds.dfci.harvard.edu.

Keywords

External Resources

Popular Topics
Recent Journals