Metabolic Changes in Blood-derived Extracellular Vesicles of Malnourished Breast Cancer Patients.

Malnutrition cancer patients large extracellular vesicles metabolomics profiling

Journal

Anticancer research
ISSN: 1791-7530
Titre abrégé: Anticancer Res
Pays: Greece
ID NLM: 8102988

Informations de publication

Date de publication:
Jun 2023
Historique:
received: 21 03 2023
revised: 02 04 2023
accepted: 03 04 2023
medline: 31 5 2023
pubmed: 30 5 2023
entrez: 29 5 2023
Statut: ppublish

Résumé

Cancer cachexia describes a multifactorial wasting syndrome marked by a metabolic imbalance leading to the loss of muscle and fat tissue. Extracellular vesicles (EV) provide unique insights into their parental cells' metabolism. The value of these vesicles as diagnostic tools in cancer cachexia has not been investigated so far. A previously analyzed metabolomics dataset on large EV from breast cancer patients was used for analyzing the metabolomic changes in patients with malnutrition. Follow-up time was 6 months. The data were analyzed using fold change analysis, volcano plotting, receiver operator characteristic (ROC) analysis, pathway analysis, and survival analysis. In patients with weight loss, statistical analysis revealed an increase in lysophosphatidylcholines (lysoPC a C16:0, lysoPC a C18:0, lysoPC a C18:1, lysoPC a C18:2, lysoPC a C20:4), sphingomyelins (SM (OH) C22:2 and SM C18:1), and phosphatidylcholines (PC aa C24:0, PC ae C34:3). When combined, these metabolites are a good predictor for cachexia in ROC curve analysis (AUC of 0.970; 95%CI=0.920-1.000; p<0.0001). Pathway analysis revealed an involvement of metabolites in "choline metabolism in cancer" and "glycerophospholipid metabolism". Large EV reflect metabolic changes in cancer patients suffering from cancer cachexia. Metabolic changes at the time of drawing blood were associated with the weight status (stable vs. weight loss) six months later and thereby could have a predictive impact.

Sections du résumé

BACKGROUND/AIM OBJECTIVE
Cancer cachexia describes a multifactorial wasting syndrome marked by a metabolic imbalance leading to the loss of muscle and fat tissue. Extracellular vesicles (EV) provide unique insights into their parental cells' metabolism. The value of these vesicles as diagnostic tools in cancer cachexia has not been investigated so far.
PATIENTS AND METHODS METHODS
A previously analyzed metabolomics dataset on large EV from breast cancer patients was used for analyzing the metabolomic changes in patients with malnutrition. Follow-up time was 6 months. The data were analyzed using fold change analysis, volcano plotting, receiver operator characteristic (ROC) analysis, pathway analysis, and survival analysis.
RESULTS RESULTS
In patients with weight loss, statistical analysis revealed an increase in lysophosphatidylcholines (lysoPC a C16:0, lysoPC a C18:0, lysoPC a C18:1, lysoPC a C18:2, lysoPC a C20:4), sphingomyelins (SM (OH) C22:2 and SM C18:1), and phosphatidylcholines (PC aa C24:0, PC ae C34:3). When combined, these metabolites are a good predictor for cachexia in ROC curve analysis (AUC of 0.970; 95%CI=0.920-1.000; p<0.0001). Pathway analysis revealed an involvement of metabolites in "choline metabolism in cancer" and "glycerophospholipid metabolism".
CONCLUSION CONCLUSIONS
Large EV reflect metabolic changes in cancer patients suffering from cancer cachexia. Metabolic changes at the time of drawing blood were associated with the weight status (stable vs. weight loss) six months later and thereby could have a predictive impact.

Identifiants

pubmed: 37247938
pii: 43/6/2593
doi: 10.21873/anticanres.16426
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2593-2599

Informations de copyright

Copyright © 2023 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Auteurs

Judith Buentzel (J)

Department of Hematology and Medical Oncology, University Medical Center Goettingen, Goettingen, Germany; judith.buentzel@med.uni-goettingen.de.

Matthias Schulz (M)

Department of Hematology and Medical Oncology, University Medical Center Goettingen, Goettingen, Germany.

Lena Aperdannier (L)

Department of Hematology and Medical Oncology, University Medical Center Goettingen, Goettingen, Germany.

Annalen Bleckmann (A)

Department of Medicine A (Hematology, Oncology, Hemostaseology and Pulmonology), University Hospital Muenster, Muenster, Germany.

Claudia Binder (C)

Department of Hematology and Medical Oncology, University Medical Center Goettingen, Goettingen, Germany.

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Classifications MeSH