Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease.

Journal: Science (New York, N.Y.)
PMID: 33303684

Abstract

Mapping the gene-regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several outputs at most, biasing discovery and limiting the likelihood of true disease-modifying drug candidates. Here, we developed a machine-learning approach to identify small molecules that broadly correct gene networks dysregulated in a human induced pluripotent stem cell (iPSC) disease model of a common form of heart disease involving the aortic valve (AV). Gene network correction by the most efficacious therapeutic candidate, XCT790, generalized to patient-derived primary AV cells and was sufficient to prevent and treat AV disease in vivo in a mouse model. This strategy, made feasible by human iPSC technology, network analysis, and machine learning, may represent an effective path for drug discovery.

Authors

  • Christina V Theodoris
    Gladstone Institute of Cardiovascular Disease, San Francisco, CA, USA.
  • Ping Zhou
  • Lei Liu
    Department of Science and Technology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Tomohiro Nishino
    Gladstone Institute of Cardiovascular Disease, San Francisco, CA, USA.
  • Yu Huang
    School of Data Science and Software Engineering, Qingdao University, Qingdao 266021, China.
  • Aleksandra Kostina
    Institute of Cytology, Russian Academy of Sciences, Saint Petersburg, Russia.
  • Sanjeev S Ranade
    Gladstone Institute of Cardiovascular Disease, San Francisco, CA, USA.
  • Casey A Gifford
    Gladstone Institute of Cardiovascular Disease, San Francisco, CA, USA.
  • Vladimir Uspenskiy
    Almazov Federal Medical Research Centre, Saint Petersburg, Russia.
  • Anna Malashicheva
    Institute of Cytology, Russian Academy of Sciences, Saint Petersburg, Russia.
  • Sheng Ding
    Gladstone Institute of Cardiovascular Disease, San Francisco, CA, USA.
  • Deepak Srivastava
    Gladstone Institute of Cardiovascular Disease, San Francisco, CA, USA. dsrivastava@gladstone.ucsf.edu.

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