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

IF 4 Q2 Medicine
Tianxue Yang, Ye Yuan, Nianhong Lu, Rui Han, Ziran Xu
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引用次数: 0

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

神经胶质瘤中与免疫景观和生存相关的机械敏感基因特征:多队列分析。
背景:胶质瘤的特点是分子异质性大和临床预后差。新出现的证据表明,机械转导相关途径可能影响肿瘤进展和免疫重塑。然而,机械敏感基因在胶质瘤中的预后相关性尚不清楚。方法:分析TCGA、CGGA-301、CGGA-325和GSE16011队列的rna测序数据和临床信息。从整理的基因集中鉴定出机械敏感基因,并使用LASSO和Cox回归分析构建预后特征。评估免疫浸润、免疫检查点表达、TIDE预测和药物敏感性。在四个独立队列中,风险评分与SPP1表达一致且呈正相关,单细胞分析进一步表明SPP1相关信号可能有助于免疫微环境重塑。选择的基因在胶质瘤细胞系中进行qRT-PCR验证。结果:一项9个基因的机械敏感特征将胶质瘤患者分层为高风险组和低风险组,在多个队列中总生存率显著不同。风险评分与已确定的临床病理因素独立相关,包括WHO分级、IDH突变状态、1p/19q共缺失状态和MGMT启动子甲基化状态。高危肿瘤表现为巨噬细胞和中性粒细胞浸润增加,免疫检查点表达升高,预测免疫逃避电位升高。单细胞分析提示spp1相关信号可能参与免疫微环境重塑。实验验证支持选定基因在胶质瘤细胞中的差异表达。结论:这种机械敏感基因特征与神经胶质瘤的免疫景观异质性和生存有关。该模型可以提供互补的分层信息,并支持进一步研究与机械生物学相关的肿瘤-微环境相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.40
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0.00%
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审稿时长
14 weeks
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