Metabolomic profiling of blood plasma of patients with lung cancer and malignant tumors with metastasis in the lungs showed similar features and promising statistical discrimination against controls

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Abstract

Targeting metabolomic pathways is a promising strategy for cancer treatment. Alterations in the metabolomic state have also an epigenetic impact, making the metabolomic studies even more interesting. We explored metabolomic changes in the blood plasma of patients with primary and secondary lung cancer and tried to explore their origin. We also applied a discrimination algorithm to the data. In the study, blood samples from 132 patients with primary lung cancer, 47 with secondary lung cancer, and 77 subjectively healthy subjects without any cancer history were used. The samples were measured by NMR spectroscopy. PCA and PLS-DA analyses did not distinguish between patients with primary and secondary lung tumors. Accordingly, no significantly changed levels of plasmatic metabolites were found between these groups. When comparing with healthy controls, significantly increased glucose, citrate, acetate, 3-hydroxybutyrate, and creatinine balanced with decreased pyruvate, lactate, alanine, tyrosine, and tryptophan were found as a common feature of both groups. Metabolomic analysis of blood plasma showed considerable proximity of patients with primary and secondary lung cancer. The changes observed can be partially explained as cancer-derived and also as changes showing ischemic nature. Random Forrest discrimination based on the relative concentration of metabolites in blood plasma performed very promising with AUC of 0.95 against controls; however noticeable parts of differencing metabolites are overlapping with those observed after ischemic injury in other studies.

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Sarlinova, M., Baranovicova, E., Skalicanova, M., Dzian, A., Petras, M., Lehotsky, J., … Halasova, E. (2021). Metabolomic profiling of blood plasma of patients with lung cancer and malignant tumors with metastasis in the lungs showed similar features and promising statistical discrimination against controls. Neoplasma, 68(4), 852–860. https://doi.org/10.4149/neo_2021_210103N3

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