Abstract
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.
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