Abstract #0602

Insight in metabolic changes of early and late stage glioma revealed by both downfield MRS and Non-targeted Metabolomics

Xinyi Zhu¹, Yang Cao¹, Yufan Zhou¹, Ke Zhou¹, Dingyi Lin¹, Shiyang You¹, Zhongyi He¹, Sheng Chen², Chunli Cai³, Yi-Cheng Hsu⁴, and Min Wang^1,5

¹Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China, ²Department of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China, ³Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, China, ⁴MR Collaboration, Siemens Healthcare Ltd, Shanghai, China, ⁵School of Medicine, Sir Run Run Shaw Hospital, Department of Endocrinology, Zhejiang University, Hangzhou, China

Synopsis

Keywords: Spectroscopy, Metabolism

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.

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