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鞘脂相关特征谱揭示 TIMP1 驱动的替莫唑胺耐药并指导胶质母细胞瘤分层治疗

英文原题:Sphingolipid-associated signature unveils TIMP1-driven temozolomide resistance and guides stratified therapy in glioblastoma.

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Sphingolipid-associated signature unveils TIMP1-driven temozolomide resistance and guides stratified therapy in glioblastoma.

PubMed 2026/03/18(内容时间) Front Immunol Q1 · IF 7(JCR 2025)

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研究概要

本研究建立并验证了一个稳健的 GBM 预后模型,将鞘脂相关分子景观与化疗耐药性相整合。它提供了关于鞘脂失调、免疫逃逸、TMZ 耐药性以及 TIMP1 关键功能作用之间相互作用的全面视角。除了能够实现精确的患者分层外,该模型还突出了特定的治疗脆弱性,为开发针对鞘脂调控网络并克服 GBM 化疗耐药性的联合策略提供了转化框架。

研究思路结论见上方概要

胶质母细胞瘤(GBM)仍是最常见且最具侵袭性的原发性中枢神经系统(CNS)恶性肿瘤;然而,首选化疗药物替莫唑胺(TMZ)的临床疗效因固有耐药和获得性耐药而严重受限。鞘脂代谢是GBM细胞命运的关键调控因素,“鞘脂变阻器”失衡与TMZ耐药密切相关。这为开发新型预后模型以指导分层治疗风险策略提供了潜在靶点,同时为TMZ化疗增敏和分层药物联合治疗提供了有前景的切入点。

我们整合了来自TCGA和GEO的单细胞和批量转录组学数据。通过结合加权基因共表达网络分析(WGCNA)、差异表达谱分析、Cox回归和机器学习的多维框架,我们识别了与GBM中鞘脂失调和TMZ敏感性相关的分子景观相关的候选基因,以构建可靠的预后模型。我们分别通过RT-qPCR和组织微阵列(TMA)验证了临床标本中模型基因的mRNA表达和TIMP1的蛋白表达。此外,我们通过在U87细胞中进行慢病毒敲低对核心靶点TIMP1进行了功能表征,采用Transwell、CCK-8和IC50测定来评估其对恶性程度的影响,以及关键地,其调节TMZ化疗增敏的能力。

单细胞分析将GBM样本分层为不同的代谢亚类,揭示了显著的代谢异质性。整合TCGA和GEO图谱与基于WGCNA的多维交集,我们识别出95个候选基因,并通过Cox回归和机器学习精炼为一个有效的六基因模型(MXRA8、TIMP1、TREM1、S100A4、RMI2、IRF7),反映了细胞外基质(ECM)重塑、炎症和DNA修复的关键轴。我们描绘了该模型在塑造免疫排斥性肿瘤微环境(TME)中的作用,其特征为基质重塑、T细胞耗竭和自然杀伤(NK)细胞亚群的功能受损,同时揭示了不同风险亚组的特定治疗脆弱性。实验验证证实了核心靶点在临床标本中的广泛上调。在功能上,TIMP1敲低显著抑制了增殖和侵袭。最重要的是,沉默TIMP1有效恢复了对TMZ的敏感性(化疗增敏)。

展开英文摘要原文

Glioblastoma (GBM) remains the most prevalent and aggressive primary central nervous system (CNS) malignancy; however, the clinical efficacy of the preferred chemotherapeutic agent, Temozolomide (TMZ), is severely compromised by innate and acquired resistance. Sphingolipid metabolism acts as a pivotal regulator of GBM cell fate, and the imbalance of the "sphingolipid rheostat" is intimately linked to TMZ resistance. This provides potential targets for developing novel prognostic models to inform stratified treatment risk strategies, while offering a promising entry point for TMZ chemosensitization and stratified drug combinations.

We integrated single-cell and bulk transcriptomics from TCGA and GEO. Through a multi-dimensional framework combining Weighted Gene Co-expression Network Analysis (WGCNA), differential expression profiling, Cox regression, and machine learning, we identified candidate genes associated with the molecular landscape coupled with sphingolipid dysregulation and TMZ sensitivity in GBM to construct a reliable prognostic model. We verified mRNA expression of model genes and protein expression of TIMP1 in clinical specimens via RT-qPCR and tissue microarrays (TMA), respectively. Furthermore, we functionally characterized the core target, TIMP1, via lentiviral knockdown in U87 cells, employing Transwell, CCK-8, and IC50 assays to evaluate its impact on malignancy and, crucially, its capacity to modulate TMZ chemosensitization.

Single-cell analysis stratified GBM samples into distinct metabolic subclasses, revealing significant metabolic heterogeneity. Integrating TCGA and GEO profiles with WGCNA-based multi-dimensional intersection, we identified 95 candidate genes, refined via Cox regression and machine learning into a potent six-gene model (MXRA8, TIMP1, TREM1, S100A4, RMI2, IRF7) reflecting critical axes of extracellular matrix (ECM) remodeling, inflammation, and DNA repair. We delineated the model's role in shaping an immune-excluded tumor microenvironment (TME) characterized by stromal remodeling, T-cell exhaustion and functional impairment of natural killer (NK) cell subsets, while uncovering specific therapeutic vulnerabilities for distinct risk subgroups. Experimental validation confirmed widespread upregulation of core targets in clinical specimens. Functionally, TIMP1 knockdown significantly suppressed proliferation and invasion. Most importantly, silencing TIMP1 effectively restored sensitivity to TMZ (chemosensitization).

This study establishes and validates a robust GBM prognostic model integrating the sphingolipid-associated molecular landscape with chemotherapy resistance. It provides a comprehensive perspective on the interplay among sphingolipid dysregulation, immune evasion, TMZ resistance, and the critical functional role of TIMP1. Beyond enabling precise patient stratification, this model highlights specific therapeutic vulnerabilities, offering a translational framework for developing combinatorial strategies to target the sphingolipid regulatory network and overcome GBM chemoresistance.

论文信息

作者
Lyu F、Wu J、Qi J、Wang G、Xie L、Wang Z
单位
Department of Radiology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.China
期刊
Frontiers in immunology2026
原文标识
PubMed 41929516 · DOI 10.3389/fimmu.2026.1753274