Breast Cancer Cell Subtypes Display Different Metabolic Phenotypes That Correlate with Their Clinical Classification.
breast cancer
metabolic profiling
metabolic reprogramming
tumor metabolism
Journal
Biology
ISSN: 2079-7737
Titre abrégé: Biology (Basel)
Pays: Switzerland
ID NLM: 101587988
Informations de publication
Date de publication:
03 Dec 2021
03 Dec 2021
Historique:
received:
11
10
2021
revised:
28
11
2021
accepted:
29
11
2021
entrez:
24
12
2021
pubmed:
25
12
2021
medline:
25
12
2021
Statut:
epublish
Résumé
Metabolic reprogramming of cancer cells represents an orchestrated network of evolving molecular and functional adaptations during oncogenic progression. In particular, how metabolic reprogramming is orchestrated in breast cancer and its decisive role in the oncogenic process and tumor evolving adaptations are well consolidated at the molecular level. Nevertheless, potential correlations between functional metabolic features and breast cancer clinical classification still represent issues that have not been fully studied to date. Accordingly, we aimed to investigate whether breast cancer cell models representative of each clinical subtype might display different metabolic phenotypes that correlate with current clinical classifications. In the present work, functional metabolic profiling was performed for breast cancer cell models representative of each clinical subtype based on the combination of enzyme inhibitors for key metabolic pathways, and isotope-labeled tracing dynamic analysis. The results indicated the main metabolic phenotypes, so-called 'metabophenotypes', in terms of their dependency on glycolytic metabolism or their reliance on mitochondrial oxidative metabolism. The results showed that breast cancer cell subtypes display different metabophenotypes. Importantly, these metabophenotypes are clearly correlated with the current clinical classifications.
Identifiants
pubmed: 34943182
pii: biology10121267
doi: 10.3390/biology10121267
pmc: PMC8698801
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Spanish Ministry of Science and Innovation, European Regional Development Fund
ID : CTQ2017-85658-R
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