Lipid Metabolism at the Nexus of Diet and Tumor Microenvironment.


Journal

Trends in cancer
ISSN: 2405-8025
Titre abrégé: Trends Cancer
Pays: United States
ID NLM: 101665956

Informations de publication

Date de publication:
11 2019
Historique:
received: 02 07 2019
revised: 24 09 2019
accepted: 26 09 2019
entrez: 19 11 2019
pubmed: 19 11 2019
medline: 17 7 2020
Statut: ppublish

Résumé

Obesity is a leading contributing factor to cancer development worldwide. Epidemiological evidence suggests that diet affects cancer risk and also substantially alters therapeutic outcome. Therefore, studying the impact of diet in the development and treatment of cancer should be a clinical priority. In this Review, we set out the evidence supporting the role of lipid metabolism in shaping the tumor microenvironment (TME) and cancer cell phenotype. We will discuss how dietary lipids can impact phenotype thereby affecting disease trajectory and treatment response. Finally, we will posit potential strategies on how this knowledge can be exploited to increase treatment efficacy and patient survival.

Identifiants

pubmed: 31735288
pii: S2405-8033(19)30190-6
doi: 10.1016/j.trecan.2019.09.007
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

693-703

Subventions

Organisme : Cancer Research UK
ID : C16420/A18066
Pays : United Kingdom

Informations de copyright

Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Barrie Peck (B)

Translational Cancer Metabolism Team, Centre for Tumour Biology, Barts Cancer Institute, Cancer Research UK Centre of Excellence, Queen Mary University of London, Charterhouse Square, London, EC1 6BQ, UK; The Institute of Cancer Research, London, SW7 3RP, UK. Electronic address: b.peck@qmul.ac.uk.

Almut Schulze (A)

Theodor-Boveri-Institute, Biocenter, Am Hubland, 97074 Würzburg, Germany; Comprehensive Cancer Center Mainfranken, Josef-Schneider-Str.6, 97080, Würzburg, Germany.

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Classifications MeSH