Abstract
In this study, metastatic melanoma, breast, and prostate cancer cell lines were analyzed using a 1H-NMR-based approach in order to investigate common features and differences of aggressive cancers metabolomes. For that purpose, 1H-NMR spectra of both cellular extracts and culture media were combined with multivariate data analysis, bringing to light no less than 20 discriminant metabolites able to separate the metastatic metabolomes. The supervised approach succeeded in classifying the metastatic cell lines depending on their glucose metabolism, more glycolysis-oriented in the BRAF proto-oncogene mutated cell lines compared to the others. Other adaptive metabolic features also contributed to the classification, such as the increased total choline content (tCho), UDP-GlcNAc detection, and various changes in the glucose-related metabolites tree, giving additional information about the metastatic metabolome status and direction. Finally, common metabolic features detected via 1H-NMR in the studied cancer cell lines are discussed, identifying the glycolytic pathway, Kennedy’s pathway, and the glutaminolysis as potential and common targets in metastasis, opening up new avenues to cure cancer.
Highlights
Cancer is a genetic or epigenetic disease resulting in altered metabolic activities compared to normal cells, including biological hallmarks such as the Warburg effect [1,2], the oxidative phosphorylation (OXPHOS) [3], and the glutaminolysis [4,5]
The binned spectra (0.04 ppm stepwise) generated from the cellular extracts of melanoma (D10, 451-Lu, M229), prostate cancer (LNCaP, PC-3), and breast cancer (MCF-7, MDA-MB-231) were integrated, and the numerical values exported to an Excel table
Phosphocreatine (PCr) is synthesized from creatine (Cr) by creatine kinase (CK) [27], a shuttle system identified in cancer cells to store phosphate groups from ATP and enabling its restitution in
Summary
Cancer is a genetic or epigenetic disease resulting in altered metabolic activities compared to normal cells, including biological hallmarks such as the Warburg effect [1,2], the oxidative phosphorylation (OXPHOS) [3], and the glutaminolysis [4,5]. Due to several mutations in key oncogenes and tumor suppressor genes, cancer cells become highly demanding from a metabolic point of view, using larger amounts of carbohydrates, amino acids, and fats as energy resources to sustain rapid growth [6,7]. This results in a higher turnover of metabolites production, corresponding to intermediates or end-products of biological pathways, detectable by spectroscopic-based metabonomics approaches such as Nuclear Magnetic Resonance (NMR) or mass spectrometry (MS).
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