Han Rui, Chi Guangfan, Sun Dongjie, Xu Ziran, Zhou Liangfu, Xu Kan
Department of Neurovascular Surgery, The First Hospital of Jilin University, No. 71, Xinmin Street, Chaoyang District, Changchun City, Jilin Province, 130021, People's Republic of China.
The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, 130012, China.
BMC Cancer. 2025 Nov 22;25(1):1901. doi: 10.1186/s12885-025-15291-6.
Glioblastoma (GBM) is the most aggressive adult brain tumor, marked by intratumoral heterogeneity and therapy resistance. Metabolic reprogramming through histone lactylation has been linked to tumor progression and immune suppression. However, the spatial and single-cell landscape of lactylation in GBM and its prognostic significance remain poorly understood.
We employed a multi-omics approach integrating bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to investigate lactylation-related signatures in GBM. Differential expression and pathway analyses were performed using GEO and TCGA datasets. Cell clustering, SCENIC transcriptional network inference, CellChat intercellular communication modeling, and pseudotime analysis were conducted. A prognostic risk model was constructed using LASSO-Cox regression based on lactylation-associated genes. Experimental validation was performed using western blotting, immunohistochemistry, and functional assays in GBM cell lines.
Lactylation-related genes were significantly upregulated in GBM and associated with poor prognosis and immunosuppressive tumor microenvironments. Single-cell analysis revealed high-lactylation malignant subpopulations enriched in hypoxic tumor cores, exhibiting metabolic reprogramming and enhanced immune evasion. Spatial transcriptomics confirmed the localization of S100A6-high-lactylation GBM cells in aggressive tumor regions. A nine-gene lactylation-based risk model stratified patients into high- and low-risk groups with significantly different survival outcomes (AUC: 0.77-0.87). Experimental knockdown of S100A6 reduced GBM cell proliferation, migration, and invasion.
Lactylation defines distinct tumor cell clusters in GBM that are spatially localized, metabolically reprogrammed, and immunosuppressive. The S100A6-associated lactylation signature serves as a robust prognostic biomarker and potential therapeutic target in GBM.
胶质母细胞瘤(GBM)是最具侵袭性的成人脑肿瘤,其特征为肿瘤内异质性和治疗抗性。通过组蛋白乳酰化进行的代谢重编程与肿瘤进展和免疫抑制有关。然而,GBM中乳酰化的空间和单细胞图谱及其预后意义仍知之甚少。
我们采用了一种多组学方法,整合了批量RNA测序、单细胞RNA测序(scRNA-seq)和空间转录组学,以研究GBM中与乳酰化相关的特征。使用GEO和TCGA数据集进行差异表达和通路分析。进行了细胞聚类、SCENIC转录网络推断、CellChat细胞间通讯建模和伪时间分析。基于与乳酰化相关的基因,使用LASSO-Cox回归构建了预后风险模型。在GBM细胞系中使用蛋白质免疫印迹、免疫组织化学和功能测定进行了实验验证。
与乳酰化相关的基因在GBM中显著上调,与预后不良和免疫抑制性肿瘤微环境相关。单细胞分析揭示了富含缺氧肿瘤核心的高乳酰化恶性亚群,表现出代谢重编程和增强的免疫逃逸。空间转录组学证实了S100A6高乳酰化GBM细胞在侵袭性肿瘤区域的定位。基于乳酰化的九基因风险模型将患者分为高风险和低风险组,生存结果有显著差异(AUC:0.77-0.87)。实验性敲低S100A6可降低GBM细胞的增殖、迁移和侵袭。
乳酰化在GBM中定义了不同的肿瘤细胞簇,这些细胞簇在空间上定位、进行代谢重编程并具有免疫抑制作用。与S100A6相关的乳酰化特征是GBM中一种强大的预后生物标志物和潜在的治疗靶点。