Downfield magnetic resonance signals serve as endogenous imaging biomarkers of nucleotide metabolism in glioma
Gliomas, the most common primary brain tumors, exhibit profound metabolic alterations that can be non-invasively probed using magnetic resonance spectroscopy (MRS). Compared to upfield signals in traditional MRS, downfield signals exhibit complex composition with limited understanding of their metabolite origins. Correlating high-throughput metabolic profiles provided by untargeted metabolomics with MRS signals can help elucidate the origins of metabolites in MRS. In this study, upfield and downfield MRS spectra are obtained from control and glioma-bearing male Wistar rats, followed by correlation analysis with untargeted metabolomics from corresponding brain tissues. Here, we show that multiple downfield MRS peaks are significantly elevated in glioma rats and correlate with metabolomic features. Notably, downfield MRS demonstrate the capability of capturing adenosine triphosphate (ATP)-associated nucleotide metabolism. Furthermore, MRS signatures exhibit predictive potential for tumor growth parameters. This work establishes an integrated MRS-metabolomics framework, providing a basis for non-invasively monitoring dynamic metabolic reprogramming and predicting glioma progression.
Authors
- Jiaqiang Zhou (ORCID: https://orcid.org/0000-0001-8372-0940)
- M C Wang
- Yibo Liu
- Y.Y. Liu
- Xuetao Zhu (ORCID: https://orcid.org/0000-0002-7563-1603)
- Yang Cao
- Sheng Chen
- Ke Zhou
Institutions
- Ministry of Education (NZ)
- Sir Run Run Shaw Hospital (CN)
- Shandong Provincial Hospital (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Communications Biology
- Published
- 2026-03-03
- DOI
- https://doi.org/10.1038/s42003-026-09780-y
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Natural Science Foundation of Zhejiang Province