Evidence map›Paper›PMID 41807981›Full record

ArticleHuman genomics2026

Leveraging proteomics and machine learning for mechanism and biomarker discovery on glioma progression and transformation: from LGG to GBM.

Qinhong Huang, Hui Liang, Jie Liu, Shenbao Shi, Xinlin Sun, Yiquan Ke, Taoliang Chen

Abstract read
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In one paragraph

Article in Human genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Qinhong Huang *The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
Hui Liang *The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
Jie Liu *The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
Shenbao ShiThe National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
Xinlin SunThe National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
Yiquan KeThe National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China. kyquan@smu.edu.cn.
Taoliang ChenThe National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory On Brain Function Repair and Regeneration, Department of Neuro-oncological Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China. 1073758862@qq.com.

Funding

Guangzhou Science and Technology Planning Project No. 2024A04J4878Guangzhou Science and Technology Planning Project No. 2024A04J9993Natural Science Foundation of China No. 82103668President Foundation of Zhujiang Hospital, Southern Medical University No. yzjj2022qn11
6 · The paper itself

Abstract

backgroundGlioma was the most common malignant tumor of the central nervous system in adults. Low-grade gliomas (LGGs) have a potential of grade progression and histological transformation, and the relevant mechanisms of this malignant evolution were still unclear.

methodsIn this study, we used 61 primary-recurrent paired glioma samples from 28 patients for proteomics analysis based upon DIA-NN approach.

resultsOur results indicated that the Ras/p38-MAPK pathways were hub signaling pathways driving grade progression and histological transformation in LGG. The activation of non-MGMT dependent unspecific DNA damage repair system mediated by Replication Factor C (RFC) can be an important reason for the treatment resistance. Moreover, metabolic reprogramming was widely involved in the regulation of LGG grade progression and histological transformation. The enhanced synthesis of unsaturated fatty acids and the significantly activated peroxisomal fatty acid beta-oxidation pathways were metabolic characteristics of LGG after histological transformation. Last, we constructed a reliable LGG progression prediction model consisted of 2 proteins, which can be monitor biomarkers for LGG progression, with potential clinical translation value.

conclusionsIn summary, glioma grade progression and histological transformation were complex biological processes, which involved the abnormal up-regulation of Ras/p38-MAPK signalings, enhanced non-MGMT dependent unspecific DNA damage repair system regulated by RFC complex and metabolic reprogramming based on HK1-PFKP-ENO2 mediated glycolysis and peroxisomal FA beta oxidation. This study filled the gap in relevant research on the grade progression and histological transformation of LGG, providing novel and unique insights into the biological mechanisms of glioma progression.

Indexed as

Biomarkers, TumorBrain NeoplasmsGlioblastomaGliomaMachine LearningProteomicsAdultCell Transformation, NeoplasticDisease ProgressionFemaleHumansMaleMetabolic ReprogrammingSignal TransductionBiomarkers, TumorGrade progressionHistological transformationLGGMetabolic reprogrammingProteomics

Identifiers

PMID41807981
PMCPMC13088795

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.