Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy

Gliomas exhibit high heterogeneity and poor prognosis. Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. In this study, we perform proteomic profiling of gliomas using 343 formalin-fixed and paraffin-embedded tumor samples and 53 normal-appearing brain samples from 188 patients, integrating these data with genomic panel information and clinical outcomes. The proteomic analysis uncovers two distinct subgroups: Subgroup 1, the metabolic neural subgroup, enriched in metabolic enzymes and neurotransmitter receptor proteins, and Subgroup 2, the immune subgroup, marked by upregulation of immune and inflammatory proteins. These proteomic subgroups show significant differences in prognosis, tumorigenesis, microenvironment dysregulation, and potential therapeutics, highlighting the critical roles of metabolic and immune processes in glioma biology and patient outcomes. Through a detailed investigation of metabolic pathways guided by our proteomic findings, dihydropyrimidine dehydrogenase (DPYD) and thymidine phosphorylase (TYMP) emerge as potential prognostic biomarkers linked to the reprogramming of nucleotide metabolism. Functional validation in patient-derived glioma stem cells and animal models highlights nucleotide metabolism as a promising therapy target for gliomas. This integrated multi-omics analysis introduces a proteomic classification for gliomas and identifies DPYD and TYMP as key metabolic biomarkers, offering insights into glioma pathogenesis and potential treatment strategies.

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Publication Details

Journal
Nature Communications
Published
2024-11-19
DOI
https://doi.org/10.1038/s41467-024-54352-5
Citations
17
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
7.45

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article

Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy

Tiannan Guo, Chaxian Liu, Zunguo Du, Tianming Qiu et al.
17 citations
Nature Communications
Glioma Diagnosis and Treatment
7.45
article

Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy

Tiannan Guo, Chaxian Liu, Zunguo Du, Tianming Qiu, Jinsen Zhang, Yu Yao, Yuan Feng, Yi Zhang, Hui Yang, Dongxiao Zhuang, Wei Zhu, Ying Liu, Peter Jih Cheng Wong, Wei Hua, Minjie Fu, Rui Sun, Zhiyong Qin, Yingying Lyu, Ying Mao
article en
17 citations

Abstract

Gliomas exhibit high heterogeneity and poor prognosis. Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. In this study, we perform proteomic profiling of gliomas using 343 formalin-fixed and paraffin-embedded tumor samples and 53 normal-appearing brain samples from 188 patients, integrating these data with genomic panel information and clinical outcomes. The proteomic analysis uncovers two distinct subgroups: Subgroup 1, the metabolic neural subgroup, enriched in metabolic enzymes and neurotransmitter receptor proteins, and Subgroup 2, the immune subgroup, marked by upregulation of immune and inflammatory proteins. These proteomic subgroups show significant differences in prognosis, tumorigenesis, microenvironment dysregulation, and potential therapeutics, highlighting the critical roles of metabolic and immune processes in glioma biology and patient outcomes. Through a detailed investigation of metabolic pathways guided by our proteomic findings, dihydropyrimidine dehydrogenase (DPYD) and thymidine phosphorylase (TYMP) emerge as potential prognostic biomarkers linked to the reprogramming of nucleotide metabolism. Functional validation in patient-derived glioma stem cells and animal models highlights nucleotide metabolism as a promising therapy target for gliomas. This integrated multi-omics analysis introduces a proteomic classification for gliomas and identifies DPYD and TYMP as key metabolic biomarkers, offering insights into glioma pathogenesis and potential treatment strategies.

Nature CommunicationsVol. 15(1)
Shanghai Medical College of Fudan University (CN), Fudan University (CN), Westlake University (CN), Shanghai Public Health Clinical Center (CN), National Center for Spinal Disorders (HU), Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN), Hongzhiwei Technology (China) (CN), Shanghai Clinical Research Center (CN), Neurological Surgery (US), Huashan Hospital (CN), Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Zero hunger
Openalex Percentile: Top 2%
Glioma Diagnosis and Treatment
7.45
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