Data Sheet 3_Interrogation of macrophage-related prognostic signatures reveals a potential immune-mediated therapy strategy by histone deacetylase inhibition in glioma.csv

BackgroundGlioma-associated macrophages (GAMs) originate from intracranially resident microglia and myeloid-derived macrophages. In the glioma microenvironment, these two types of macrophages tend to adopt a specialized activation state known as type 2 or M2 macrophages and play crucial roles in the progression of glioma.
MethodsTo identify genes associated with GAMs, we intersected genes identified from single-cell RNA sequencing (scRNA-seq) data (specific to GAMs) with M2 macrophage module genes derived from weighted gene coexpression network analysis (WGCNA). Prognostic genes were screened using univariate Cox regression, multivariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analysis. These genes were used to construct and validate prognostic signatures and to delineate the immune landscape. During drug screening, Vorinostat exhibited the highest risk score and the lowest half-maximal inhibitory concentration (IC50). The expression of the 14 prognostic genes was further investigated using a glioma cell-macrophage co-culture model.
ResultsFourteen prognostic genes (TREM2, GAL3ST4, AP1B1, SLA, CYBB, CD53, SLC37A2, ABI3, RIN3, SCIN, SIGLEC10, C3, PLEKHO2, and PLXDC2) were identified. The prognostic model constructed from these genes demonstrated robust predictive efficacy. Based on this model, Vorinostat was prioritized as a candidate therapeutic agent, and subsequent validation confirmed its significant inhibitory effects on the glioma microenvironment.
ConclusionThese findings elucidate the molecular mechanisms of GAMs in glioma, uncover the immunological landscape of the tumor microenvironment, and identify potential therapeutic targets and drug action mechanisms.

研究背景
胶质瘤相关巨噬细胞（Glioma-associated macrophages，GAMs）起源于颅内常驻小胶质细胞及髓系来源巨噬细胞。在胶质瘤微环境中，这两类巨噬细胞多倾向于分化为一种被称为2型（M2型）巨噬细胞的特异性活化表型，并在胶质瘤进展过程中发挥关键作用。

研究方法
为筛选与胶质瘤相关巨噬细胞相关的基因，本研究将从胶质瘤相关巨噬细胞特异性单细胞RNA测序（single-cell RNA sequencing，scRNA-seq）数据中鉴定得到的基因，与通过加权基因共表达网络分析（weighted gene coexpression network analysis，WGCNA）获取的M2型巨噬细胞模块基因取交集。随后通过单因素Cox回归、多因素Cox回归及最小绝对收缩和选择算子（least absolute shrinkage and selection operator，LASSO）回归分析筛选预后相关基因。利用上述筛选得到的基因构建并验证预后特征模型，并描绘肿瘤免疫微环境图谱。在药物筛选环节，伏立诺他（Vorinostat）展现出最高的风险评分与最低的半数抑制浓度（half-maximal inhibitory concentration，IC50）。本研究进一步通过胶质瘤细胞-巨噬细胞共培养模型，验证了这14个预后基因的表达情况。

研究结果
本研究共鉴定得到14个预后相关基因（TREM2、GAL3ST4、AP1B1、SLA、CYBB、CD53、SLC37A2、ABI3、RIN3、SCIN、SIGLEC10、C3、PLEKHO2及PLXDC2）。基于上述基因构建的预后模型展现出优异的预测效能。基于该模型，伏立诺他被优先推荐为潜在治疗药物，后续验证实验证实其可显著抑制胶质瘤微环境的功能。

研究结论
本研究阐明了胶质瘤相关巨噬细胞在胶质瘤发生发展中的分子机制，揭示了肿瘤微环境的免疫图谱，并筛选得到潜在治疗靶点与药物作用机制。