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  3. Multiscale profiling of protease activity in cancer

Multiscale profiling of protease activity in cancer

  • Nat Commun. 2022 Oct 3;13(1):5745. doi: 10.1038/s41467-022-32988-5.
Ava P Amini  # 1 2 3 4,  Jesse D Kirkpatrick  # 1 2,  Cathy S Wang 1 5,  Alex M Jaeger 1,  Susan Su 1 6,  Santiago Naranjo 1 7,  Qian Zhong 1,  Christina M Cabana 1 7,  Tyler Jacks 1 7,  Sangeeta N Bhatia 8 9 10 11 12 13 14
Affiliations

Affiliations

  • 1 Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • 2 Harvard MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • 3 Program in Biophysics, Harvard University, Boston, MA, USA.
  • 4 Microsoft Research New England, Cambridge, MA, USA.
  • 5 Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • 6 Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • 7 Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • 8 Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. sbhatia@mit.edu.
  • 9 Harvard MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA. sbhatia@mit.edu.
  • 10 Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. sbhatia@mit.edu.
  • 11 Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. sbhatia@mit.edu.
  • 12 Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA. sbhatia@mit.edu.
  • 13 Wyss Institute at Harvard University, Boston, MA, USA. sbhatia@mit.edu.
  • 14 Howard Hughes Medical Institute, Cambridge, MA, USA. sbhatia@mit.edu.
  • # Contributed equally.
PMID: 36192379 DOI: 10.1038/s41467-022-32988-5
Abstract

Diverse processes in Cancer are mediated by Enzymes, which most proximally exert their function through their activity. High-fidelity methods to profile Enzyme activity are therefore critical to understanding and targeting the pathological roles of Enzymes in Cancer. Here, we present an integrated set of methods for measuring specific protease activities across scales, and deploy these methods to study treatment response in an autochthonous model of Alk-mutant lung Cancer. We leverage multiplexed nanosensors and machine learning to analyze in vivo protease activity dynamics in lung Cancer, identifying significant dysregulation that includes enhanced cleavage of a peptide, S1, which rapidly returns to healthy levels with targeted therapy. Through direct on-tissue localization of protease activity, we pinpoint S1 cleavage to the tumor vasculature. To link protease activity to cellular function, we design a high-throughput method to isolate and characterize proteolytically active cells, uncovering a pro-angiogenic phenotype in S1-cleaving cells. These methods provide a framework for functional, multiscale characterization of protease dysregulation in Cancer.

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