Evidence map›Paper›PMID 40257572›Full record

ArticleJournal of molecular neuroscience : MN2025

SERPINH1 and CTSZ are Key Markers of Glioma Angiogenesis.

Haotian Wei, Xinlong Li, Peng Feng, Zhaohui He

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Article in Journal of molecular neuroscience : MN, 2025. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Haotian Wei *Department of Neurosurgery, First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Xinlong Li *Lanzhou University Second Hospital, The Second Medical College of Lanzhou University, Lanzhou, 730030, China.
Peng FengLanzhou University Second Hospital, The Second Medical College of Lanzhou University, Lanzhou, 730030, China.
Zhaohui HeDepartment of Neurosurgery, First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China. geno_he@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioma, as one of the most complex and prognostically variable malignant tumors of the central nervous system, poses a significant challenge to clinical decision-making due to its molecular heterogeneity. This study aims to deepen our understanding of glioma molecular subtypes and explore key gene markers with prognostic and diagnostic value. We utilized an angiogenesis-related gene set and employed the Non-negative Matrix Factorization (NMF) algorithm to successfully identify two distinct prognostic subtypes, with subtype one exhibiting more unfavorable prognostic characteristics. To further elucidate the biological functional differences between these two subtypes, we conducted Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Gene Set Enrichment Analysis (GSEA). Building on this, we integrated differentially expressed genes between subtypes with core genes revealed by Weighted Gene Co-expression Network Analysis (WGCNA) through intersection analysis to pinpoint a series of key candidate genes. Subsequently, we constructed a Protein-Protein Interaction (PPI) network to identify genes occupying central nodes within the network. To screen markers with high specificity and sensitivity for prognosis and diagnosis, we adopted a dual-track strategy: on the one hand, we utilized machine learning algorithms such as Lasso regression, Support Vector Machine (SVM), and Random Forest (RF) to select core genes, identifying markers that can accurately predict the subtype with a poor prognosis; on the other hand, we employed a comprehensive evaluation system incorporating 101 machine learning ensemble algorithms to further validate and screen prognosis-related genes. Through cross-validation using these two strategies, we ultimately determined SERPINH1 and CTSZ as dual prognostic and diagnostic markers for glioma. This study not only provides a new perspective and tool for the molecular subclassification of glioma but also, through a rigorous multi-algorithm, multi-dimensional screening process, uncovers SERPINH1 and CTSZ as markers with potential clinical translational value. These findings are expected to offer more precise biomarker support for the early diagnosis and prognostic assessment of glioma, potentially paving new avenues for the development of personalized treatment strategies and improving patient outcomes. This has far-reaching implications for the clinical management of glioma in the field of neurosurgery.

Indexed as

Biomarkers, TumorBrain NeoplasmsGliomaNeovascularization, PathologicSerpinsAngiogenesisHumansProtein Interaction MapsBiomarkers, TumorSerpinsAngiogenesisGliomaMachine LearningNMFWCGNA

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Registered trials

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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.