Chaperome networks - Redundancy and implications for cancer treatment Journal Article


Authors: Yan, P.; Wang, T.; Guzman, M. L.; Peter, R. I.; Chiosis, G.
Article Title: Chaperome networks - Redundancy and implications for cancer treatment
Abstract: The chaperome is a large family of proteins composed of chaperones, co-chaperones and a multitude of other factors. Elegant studies in yeast and other organisms have paved the road to how we currently understand the complex organization of this large family into protein networks. The goal of this chapter is to provide an overview of chaperome networks in cancer cells, with a focus on two cellular states defined by chaperome network organization. One state characterized by chaperome networks working in isolation and with little overlap, contains global chaperome networks resembling those of normal, non-transformed, cells. We propose that in this state, redundancy in chaperome networks results in a tumor type unamenable for single-agent chaperome therapy. The second state comprises chaperome networks interconnected in response to cellular stress, such as MYC hyperactivation. This is a state where no redundant pathways can be deployed, and is a state of vulnerability, amenable for chaperome therapy. We conclude by proposing a change in how we discover and implement chaperome inhibitor strategies, and suggest an approach to chaperome therapy where the properties of chaperome networks, rather than genetics or client proteins, are used in chaperome inhibitor implementation.
Keywords: pu-h71; hsp90 inhibitors; anti-cancer therapy; chaperome networks; epichaperome; protein network connectivity; protein network vulnerability
Journal Title: Advances in Experimental Medicine and Biology
Volume: 1243
ISSN: 0065-2598
Publisher: Springer  
Date Published: 2020-01-01
Start Page: 87
End Page: 99
Language: English
DOI: 10.1007/978-3-030-40204-4_6
PUBMED: 32297213
PROVIDER: scopus
PMCID: PMC7279512
DOI/URL:
Notes: Chapter 6 in "HSF1 and Molecular Chaperones in Biology and Cancer" (ISBN: 978-3-030-40203-7) -- Source: Scopus
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  1. Gabriela Chiosis
    279 Chiosis
  2. Pengrong Yan
    24 Yan
  3. Tai   Wang
    19 Wang