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Updated: Oct 11, 2026
Transmitochondrial Cybrid Generation Using Cancer Cell Lines
Published on: March 17, 2023
Metabolic reprogramming in differentiated thyroid cancer progression: A tumor metabolomics analysis
Joshua D Preston1, Logan D Glosser2, Zachery R Jarrell3
1Medical Scientist Training Program, Emory University School of Medicine, Atlanta, GA; Nutrition and Health Sciences, Laney Graduate School, Emory University, Atlanta, GA; Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA. Electronic address: https://twitter.com/jdpreston30.
Background:
Differentiated thyroid cancers exhibit biologic and clinical heterogeneity not fully explained by conventional staging. Metabolic reprogramming is a hallmark of cancer, and its contribution to differentiated thyroid cancer progression is an ongoing area of study. Metabolomics-the comprehensive analysis of metabolites within biologic systems-may identify stage-specific metabolic signatures.
Methods:
Fifty-five differentiated thyroid cancer specimens underwent untargeted metabolomic profiling using liquid chromatography-mass spectrometry. Stage was assigned per American Joint Committee on Cancer, Eighth Edition criteria. Pathway enrichment analysis was performed, and specific metabolites were evaluated to define metabolic phenotypes of early-stage (I/II; n = 49) versus advanced-stage (III/IV; n = 6) tumors.
Results:
Over 10% of 17,270 metabolic features were significantly (P < .05; |fold change| >1.5) altered in advanced-stage differentiated thyroid cancers. Pathway analysis demonstrated remodeling of fatty acid, linoleate, pyrimidine, and alanine/aspartate metabolism with tumor progression. Advanced-stage tumors accumulated metabolites associated with nucleotide and epigenetic flux (guanosine monophosphate, adenosine monophosphate, S-adenosyl-L-homocysteine, and 1-methylnicotinamide), invasive membrane remodeling (γ-linolenate, oleate), and immune evasion (kynurenine, serotonin) while attenuating markers of oxidative metabolism (α-ketoisocaproate, acetyl phosphate) and adrenergic signaling (adrenaline). Correlation analysis demonstrated internal synchrony among these markers and a counter-regulatory relationship between differentiated function and biosynthetic expansion.
Conclusion:
Locally advanced differentiated thyroid cancers appear to exhibit a metabolic phenotype characterized by adrenergic suppression, immune evasion, invasive membrane remodeling, nucleotide and methylation flux, bioenergetic collapse, and resource shunting, all at the expense of differentiated and homeostatic functions. These hypothesis-generating findings suggest that metabolomic profiling could complement existing risk-stratification frameworks. Prospective validation of metabolic phenotypes as predictors of recurrence and progression is warranted.
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