Comprehensive Analysis of Metabolic Isozyme Targets in Cancer.


Journal

Cancer research
ISSN: 1538-7445
Titre abrégé: Cancer Res
Pays: United States
ID NLM: 2984705R

Informations de publication

Date de publication:
03 05 2022
Historique:
received: 29 12 2021
revised: 07 02 2022
accepted: 21 02 2022
pubmed: 6 3 2022
medline: 6 5 2022
entrez: 5 3 2022
Statut: ppublish

Résumé

Metabolic reprogramming is a hallmark of malignant transformation, and loss of isozyme diversity (LID) contributes to this process. Isozymes are distinct proteins that catalyze the same enzymatic reaction but can have different kinetic characteristics, subcellular localization, and tissue specificity. Cancer-dominant isozymes that catalyze rate-limiting reactions in critical metabolic processes represent potential therapeutic targets. Here, we examined the isozyme expression patterns of 1,319 enzymatic reactions in 14 cancer types and their matching normal tissues using The Cancer Genome Atlas mRNA expression data to identify isozymes that become cancer-dominant. Of the reactions analyzed, 357 demonstrated LID in at least one cancer type. Assessment of the expression patterns in over 600 cell lines in the Cancer Cell Line Encyclopedia showed that these reactions reflect cellular changes instead of differences in tissue composition; 50% of the LID-affected isozymes showed cancer-dominant expression in the corresponding cell lines. The functional importance of the cancer-dominant isozymes was assessed in genome-wide CRISPR and RNAi loss-of-function screens: 17% were critical for cell proliferation, indicating their potential as therapeutic targets. Lists of prioritized novel metabolic targets were developed for 14 cancer types; the most broadly shared and functionally validated target was acetyl-CoA carboxylase 1 (ACC1). Small molecule inhibition of ACC reduced breast cancer viability in vitro and suppressed tumor growth in cell line- and patient-derived xenografts in vivo. Evaluation of the effects of drug treatment revealed significant metabolic and transcriptional perturbations. Overall, this systematic analysis of isozyme expression patterns elucidates an important aspect of cancer metabolic plasticity and reveals putative metabolic vulnerabilities. This study exploits the loss of metabolic isozyme diversity common in cancer and reveals a rich pool of potential therapeutic targets that will allow the repurposing of existing inhibitors for anticancer therapy. See related commentary by Kehinde and Parker, p. 1695.

Identifiants

pubmed: 35247885
pii: 681960
doi: 10.1158/0008-5472.CAN-21-3983
doi:

Substances chimiques

Isoenzymes 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1698-1711

Commentaires et corrections

Type : CommentIn

Informations de copyright

©2022 American Association for Cancer Research.

Auteurs

Michal Marczyk (M)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland.

Vignesh Gunasekharan (V)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

David Casadevall (D)

Cancer Research Program, Hospital del Mar Research Institute (IMIM), Barcelona, Spain.
Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain.

Tao Qing (T)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Julia Foldi (J)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Raghav Sehgal (R)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Naing Lin Shan (NL)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Kim R M Blenman (KRM)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Tess A O'Meara (TA)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Sheila Umlauf (S)

Yale Center for Molecular Discovery, Yale University, West Haven, Connecticut.

Yulia V Surovtseva (YV)

Yale Center for Molecular Discovery, Yale University, West Haven, Connecticut.

Viswanathan Muthusamy (V)

Center for Precision Cancer Modeling, Yale School of Medicine, New Haven, Connecticut.

Jesse Rinehart (J)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Rachel J Perry (RJ)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Richard Kibbey (R)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Christos Hatzis (C)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Lajos Pusztai (L)

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

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Classifications MeSH