A mechanosensitive gene signature associated with immune landscape and survival in glioma: a multi-cohort analysis.

Authors

Tianxue Yang, Ye Yuan, Nianhong Lu, Rui Han, Ziran Xu

Published in

Neurological research and practice. Volume 8. Issue 1. Aug 07, 2026. Epub Aug 07, 2026.

Abstract

Glioma is characterized by substantial molecular heterogeneity and poor clinical outcomes. Emerging evidence suggests that mechanotransduction-related pathways may influence tumor progression and immune remodeling. However, the prognostic relevance of mechanosensitive genes in glioma remains unclear.
RNA-sequencing data and clinical information from the TCGA, CGGA-301, CGGA-325, and GSE16011 cohorts were analyzed. Mechanosensitive genes were identified from curated gene sets, and a prognostic signature was constructed using LASSO and Cox regression analyses. Immune infiltration, immune checkpoint expression, TIDE predictions, and drug sensitivity were evaluated. The risk score was consistently and positively correlated with SPP1 expression across four independent cohorts, and single‑cell analysis further suggested that SPP1‑related signaling may contribute to immune microenvironment remodeling. Selected genes were validated by qRT-PCR in glioma cell lines.
A nine-gene mechanosensitive signature stratified glioma patients into high- and low-risk groups with significantly different overall survival across multiple cohorts. The risk score was independently associated with established clinicopathological factors, including WHO grade, IDH mutation status, 1p/19q co-deletion status, and MGMT promoter methylation status. High-risk tumors exhibited increased macrophage and neutrophil infiltration, elevated immune checkpoint expression, and higher predicted immune evasion potential. Single-cell analysis suggested that SPP1-related signaling may contribute to immune microenvironment remodeling. Experimental validation supported differential expression of selected genes in glioma cells.
This mechanosensitive gene signature is associated with immune landscape heterogeneity and survival in glioma. The model may provide complementary stratification information and support further investigation of mechanobiology-related tumor-microenvironment interactions.

PMID:
42568087
Bibliographic data and abstract were imported from PubMed on 08 Aug 2026.

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