Observational analysis reveals correlations between MRS data and metabolomics in glioma, suggesting novel biomarkers.
Motivation: Downfield MRS data is interpreted based primarily on theoretical conjecture and past experience which limits its application in precise diagnosis and treatment. Goal(s): We aimed find out correlations between metabolomics and MRS downfield spectra, to further clarify the signal sources. Approach: MRS spectra were collected from normal and glioma rat models using our optimized downfield MRS protocol. Brain and tumor tissues was dissected for non-targeted metabolomics analysis. Correlation between MRS data and the metabolomics data was analyzed. Results: Significant differences exist in downfield spectra and non-targeted metabolomics between norm and gliomas at early/late-stage. Strong correlation was found between several downfield peaks and nucleotides. Impact: Downfield MRS signal differences between normal and tumor tissues at different stages enhance tumor metabolism diagnosis. Correlations with nucleotides and other metabolic pathways suggest these non-conventional peaks as potential novel biomarkers for cancer metabolism.
No takes yet. Share an insight, caveat, or question.
Zhu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: