TY - JOUR
T1 - Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness
AU - Galai, Geut
AU - He, Xie
AU - Rotblat, Barak
AU - Pilosof, Shai
N1 - Funding Information: We thank Prof. Peter Mucha for valuable suggestions on the stochastic block models analysis. We thank Dr. Liron Levin for help with data preparation. This work was supported by research grants from the ISF (Israel Science Foundation): 1281/20 to S.P. and 1436/19 to B.R. B.R. also acknowledges support from The Israel Cancer Association. X.H. was supported by the joint NIH-NSF-NIFA Ecology and Evolution of Infectious Disease award R01-TW011493. Publisher Copyright: © 2023, Springer Nature Limited.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones’ ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.
AB - Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones’ ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.
UR - http://www.scopus.com/inward/record.url?scp=85173519543&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/s41467-023-41906-2
DO - https://doi.org/10.1038/s41467-023-41906-2
M3 - Article
C2 - 37805501
SN - 2041-1723
VL - 14
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 6277
ER -