Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/121900
Title: Model-driven discovery of long-chain fatty acid metabolic reprogramming in heterogeneous prostate cancer cells.
Author: Marín de Mas, Igor Bartolomé
Aguilar Fadó, Esther
Zodda, Erika
Balcells Nadal, Cristina
Marín Martínez, Silvia
Dallmann, Guido
Thomson, Timothy M.
Papp, Balázs
Cascante i Serratosa, Marta
Keywords: Cèl·lules canceroses
Càncer de pròstata
Metabolisme
Epiteli
Cancer cells
Prostate cancer
Metabolism
Epithelium
Issue Date: 2-Jan-2018
Publisher: Public Library of Science (PLoS)
Abstract: Epithelial-mesenchymal-transition promotes intra-tumoral heterogeneity, by enhancing tumor cell invasiveness and promoting drug resistance. We integrated transcriptomic data for two clonal subpopulations from a prostate cancer cell line (PC-3) into a genome-scale metabolic network model to explore their metabolic differences and potential vulnerabilities. In this dual cell model, PC-3/S cells express Epithelial-mesenchymal-transition markers and display high invasiveness and low metastatic potential, while PC-3/M cells present the opposite phenotype and higher proliferative rate. Model-driven analysis and experimental validations unveiled a marked metabolic reprogramming in long-chain fatty acids metabolism. While PC-3/M cells showed an enhanced entry of long-chain fatty acids into the mitochondria, PC-3/S cells used long-chain fatty acids as precursors of eicosanoid metabolism. We suggest that this metabolic reprogramming endows PC-3/M cells with augmented energy metabolism for fast proliferation and PC-3/S cells with increased eicosanoid production impacting angiogenesis, cell adhesion and invasion. PC-3/S metabolism also promotes the accumulation of docosahexaenoic acid, a long-chain fatty acid with antiproliferative effects. The potential therapeutic significance of our model was supported by a differential sensitivity of PC-3/M cells to etomoxir, an inhibitor of long-chain fatty acid transport to the mitochondria.
Note: Reproducció del document publicat a: https://doi.org/10.1371/journal.pcbi.1005914
It is part of: PLoS Computational Biology, 2018, vol. 14, num. 1, p. e1005914
URI: http://hdl.handle.net/2445/121900
Related resource: https://doi.org/10.1371/journal.pcbi.1005914
ISSN: 1553-734X
Appears in Collections:Articles publicats en revistes (Institut de Biomedicina (IBUB))
Articles publicats en revistes (Bioquímica i Biomedicina Molecular)

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