Comprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance

• Published in: Cancers Vol. 13; no. 11; p. 2634
• Main Authors: Soldevilla, Beatriz, López-López, Angeles, Lens-Pardo, Alberto, Carretero-Puche, Carlos, Lopez-Gonzalvez, Angeles, La Salvia, Anna, Gil-Calderon, Beatriz, Riesco-Martinez, Maria C., Espinosa-Olarte, Paula, Sarmentero, Jacinto, Rubio-Cuesta, Beatriz, Rincón, Raúl, Barbas, Coral, Garcia-Carbonero, Rocio
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 27-05-2021; MDPI
• Subjects: Amino acids; Arachidonic acid; Bile acids; Biomarkers; Cancer; Carnitine; Glutathione; Lipids; Medical prognosis; Metabolic networks; Metabolic pathways; Metabolism; Metabolites; Metabolomics; Multivariate analysis; Mutation; Neuroendocrine tumors; NMR; Nuclear magnetic resonance; Plasma; Pyruvic acid; Small intestine; Spectrum analysis; Systems stability; Tricarboxylic acid cycle; Tumorigenesis
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers13112634

Purpose: High-throughput “-omic” technologies have enabled the detailed analysis of metabolic networks in several cancers, but NETs have not been explored to date. We aim to assess the metabolomic profile of NET patients to understand metabolic deregulation in these tumors and identify novel biomarkers with clinical potential. Methods: Plasma samples from 77 NETs and 68 controls were profiled by GC−MS, CE−MS and LC−MS untargeted metabolomics. OPLS-DA was performed to evaluate metabolomic differences. Related pathways were explored using Metaboanalyst 4.0. Finally, ROC and OPLS-DA analyses were performed to select metabolites with biomarker potential. Results: We identified 155 differential compounds between NETs and controls. We have detected an increase of bile acids, sugars, oxidized lipids and oxidized products from arachidonic acid and a decrease of carnitine levels in NETs. MPA/MSEA identified 32 enriched metabolic pathways in NETs related with the TCA cycle and amino acid metabolism. Finally, OPLS-DA and ROC analysis revealed 48 metabolites with diagnostic potential. Conclusions: This study provides, for the first time, a comprehensive metabolic profile of NET patients and identifies a distinctive metabolic signature in plasma of potential clinical use. A reduced set of metabolites of high diagnostic accuracy has been identified. Additionally, new enriched metabolic pathways annotated may open innovative avenues of clinical research.