Evidence map›Paper›PMID 42740387›Full record

ArticleChemical biology & drug design2026

Integrated Multi-Omics and Radiogenomic Analysis Identifies S100B and ITGB5 as Complementary Candidate Biomarkers of Glioblastoma Heterogeneity.

Xuhang Yang, Yusong Zhang, Yutuo Zheng, Jian Lin

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Article in Chemical biology & drug design, 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

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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5 · Who and what money

Authors and funding

4 authors.

Xuhang YangWenzhou Medical University, Wenzhou, China.ORCID https://orcid.org/0009-0004-1852-642X
Yusong ZhangWenzhou Medical University, Wenzhou, China.
Yutuo ZhengWenzhou Medical University, Wenzhou, China.
Jian LinWenzhou Medical University, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma (GBM) is characterized by marked intratumoral heterogeneity, diffuse invasion, and a profoundly immunosuppressive tumor microenvironment. In this study, we applied an integrative multi-omics and radiogenomic framework to identify candidate biomarkers reflecting complementary dimensions of GBM heterogeneity. Public bulk transcriptomic datasets were integrated to define GBM-related differentially expressed genes, which were intersected with curated microbiota-associated gene sets as a hypothesis-generating screening strategy. Machine-learning models with SHAP interpretation were used for candidate-gene prioritization, followed by survival-association analysis, pan-cancer comparison, Human Protein Atlas immunohistochemistry, CPTAC proteomics, immune infiltration analysis, single-cell transcriptomics, spatial transcriptomics, in silico perturbation analysis, and MRI-based radiogenomics. GBM samples showed enrichment of extracellular matrix organization, proliferative programs, immune-related signaling, and vascular or endothelial pathways, with relative reductions in neural, synaptic, and myelin-associated signatures. S100B and ITGB5 emerged as survival-associated candidate markers with different biological contexts. Multi-omics analyses suggested that S100B may reflect broadly distributed glial-lineage and malignant-state programs, whereas ITGB5 was more closely associated with focal extracellular matrix remodeling, stromal-vascular interactions, and immunoregulatory niches. Radiogenomic analysis further suggested distinct MRI-derived associations for the two genes, with the ITGB5-related model retaining a broader radiomic signature and showing a more heterogeneous habitat pattern than the S100B-related model. These exploratory findings support S100B and ITGB5 as complementary candidate biomarkers of GBM heterogeneity and provide a basis for future experimental, multicenter, and prospective validation.

Indexed as

Biomarkers, TumorBrain NeoplasmsGlioblastomaS100 Calcium Binding Protein beta SubunitHumansMachine LearningMagnetic Resonance ImagingMultiomicsRadiomicsSpatial TranscriptomicsTumor MicroenvironmentBiomarkers, TumorS100B protein, humanS100 Calcium Binding Protein beta SubunitglioblastomaheterogeneityITGB5microbiota‐associated genesmulti‐omicsradiogenomicsS100Bsingle‐cell transcriptomicsspatial transcriptomicstumor microenvironment

Identifiers

PMID42740387
PMCPMC13575307

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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.