Determination of metabolomic profiles related to pathogenesis, prognosis, and recurrence in differentiated thyroid tumors: A non-targeted metabolomic analysis of tumor tissues

Differentiated thyroid cancer (DTC) is characterized by its biological heterogeneity and variability in clinical outcomes. This is the most common malignant endocrine neoplasm and constitutes 1-2% of all cancers, with a high variability of recurrence risk according to pathological and clinical characteristics, however, the diagnostic classification tools are still invasive and late. Objective: In this study, we propose to identify metabolites that discriminate between the different prognostic and recurrence classifications of DTC by using metabolomic analysis. Results: In order to explore the metabolic pathways involved in the prognosis and recurrence risk, we applied gas chromatography coupled mass spectrometry (GC-MS) in tumor tissue with different prognoses (low, moderate, high) by risk of recurrence according to the American Thyroid Association Classification (ATA) (low, moderate, high) (n = 29). Evidenced by partial least squares discriminant analysis (PLSDA), 62 candidate metabolites, of which 23 are significantly altered in the model that compares high risk with moderate risk (FDR < 0.05 Benjamini-Hochberg). Among which are Amino acids, carboxylic acids, Fatty Acids, Hydroxy acids, Keto acids, Organic phosphoric acids, Organooxygen compounds, Purines and pyridines, metabolites that help to establish differences between the various risks of recurrence and other types of characteristics clinics. Conclusions: Metabolomics represents a promising tool for the identification of patients at high risk of recurrence in patients with DTC who are deficient in post-surgical adjuvant therapy.