Multiscale profiling of protease activity in cancer

Ava P. Amini, Jesse D. Kirkpatrick, Cathy S. Wang, Alex M. Jaeger, Susan Su, Santiago Naranjo, Qian Zhong, Christina M. Cabana, Tyler Jacks and Sangeeta N. Bhatia ()
Additional contact information
Ava P. Amini: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Jesse D. Kirkpatrick: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Cathy S. Wang: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Alex M. Jaeger: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Susan Su: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Santiago Naranjo: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Qian Zhong: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Christina M. Cabana: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Tyler Jacks: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Sangeeta N. Bhatia: Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology

Nature Communications, 2022, vol. 13, issue 1, 1-16

Abstract: 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.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-022-32988-5 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32988-5

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-32988-5

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().