Baregamian, Naira1; Mont, Stacey2; Sekhar, Konjeti R.2; Abumrad, Naji1; Freeman, Michael2
1 Department of Surgery, Division of Surgical Oncology and Endocrine Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
2 Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN, USA
Background/ Purpose: Molecular profiling of thyroid tumors for genetic markers in thyroid cancer diagnostics has only begun to explore our limited understanding of underlying genetic drivers; however, its current limitations suggest that underlying mechanisms beyond genetic drivers are at play. Currently, metabolomic analysis is not a standard diagnostic tool for papillary thyroid carcinoma (PTC), leading to a poor understanding of global metabolic alterations in tumor metabolism and metastatic progression.
Methods: We have performed a pilot global metabolomic profiling of PTC tumors (localized and metastatic, N=20), and normal thyroid (N=8) to assess for target metabolites (Metabolon, NC). Principle Component Analysis (PCA) and Hierarchical Clustering (HC) were used to compare similarities and differences between metabolites in tumors and controls. Paired comparisons were performed between groups (p?0.05, ?2-fold change in metabolite concentrations) for statistical significance.
Results: Global metabolomic profiling of PTC tumors identified 757 metabolites. PCA and HC demonstrated differentiated clustering between normal and PTC samples; significant differences in 172 metabolites were identified between control and PTC groups, 25 metabolite differences were identified within metastatic and localized PTC. Global metabolic shifts revealed enhanced antioxidant activity, overall increase in energy, biosynthetic and transmethylation pathways, and a series of over-represented dipeptides.
Discussion/Conclusion: Our results suggest that PTC tumor metabolic signature is significantly distinct from control, and reveal metabolite differences between localized and metastatic PTC tumors. This study demonstrates, as a proof of principle, that metabolomics can be used for thyroid cancer diagnostics, and possibly, prognostics. Exploiting tumor metabolic vulnerabilities may offer new therapeutic targets for PTC treatment.
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