Wang Lin-Jian, Lv Peipei, Lou Yongli
Advanced Medical Research Center of Zhengzhou University, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Department of Neurosurgery, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Front Oncol. 2022 Apr 27;12:862723. doi: 10.3389/fonc.2022.862723. eCollection 2022.
The composition and abundance of immune and stromal cells in the tumor microenvironment (TME) dramatically affect prognosis. Infiltration of immunosuppressive tumor-associated fibroblasts (TAFs) is a hallmark of glioma. However, the mechanisms regulating TAF infiltration and the prognostic value of TAF-related genes in glioma remain unclear. In this study, we analyzed TAF infiltration by Estimating the Proportion of Immune and Cancer cells (EPIC) algorithm based on multiple glioma databases, including Glioblastoma and low-grade glioma merged cohort from The Cancer Genome Atlas (TCGA GBMLGG) cohort, the Chinese Glioma Genome Atlas (CGGA) #325 cohort, and the CGGA #693 cohort. TAF infiltration was increased in glioblastoma (GBM), and elevated TAF infiltration predicted poorer survival in gliomas. Gene enrichment analyses revealed that differentially expressed genes (DEGs) between low-grade glioma (LGG) and GBM were significantly enriched in the extracellular matrix (ECM) remodeling-related signaling, which may contribute to immune escape and resistance to immune checkpoint blockers (ICBs). To identify co-expression modules and candidate hub genes that may be associated with TAF infiltration, we performed weighted correlation network analysis (WGCNA) of DEGs. Afterward, univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses were performed to screen the positive prognostic hub genes. Finally, a high-efficacy prediction signature was constructed based on the expression of , and . The signature correlated with the abundance of TAF infiltration in glioma and was an independent risk factor for glioma. In conclusion, our findings suggested that the TAF-related signature was a valuable prognostic biomarker in glioma and provided potential targets for integrative therapy of gliomas.
肿瘤微环境（TME）中免疫细胞和基质细胞的组成与丰度对预后有显著影响。免疫抑制性肿瘤相关成纤维细胞（TAFs）的浸润是胶质瘤的一个标志。然而，调节TAF浸润的机制以及TAF相关基因在胶质瘤中的预后价值仍不清楚。在本研究中，我们基于多个胶质瘤数据库，包括来自癌症基因组图谱（TCGA GBMLGG）队列的胶质母细胞瘤和低级别胶质瘤合并队列、中国胶质瘤基因组图谱（CGGA）#325队列以及CGGA #693队列，通过估计免疫细胞和癌细胞比例（EPIC）算法分析TAF浸润情况。胶质母细胞瘤（GBM）中TAF浸润增加，TAF浸润升高预示着胶质瘤患者预后较差。基因富集分析显示，低级别胶质瘤（LGG）和GBM之间的差异表达基因（DEGs）在细胞外基质（ECM）重塑相关信号通路中显著富集，这可能有助于免疫逃逸和对免疫检查点阻断剂（ICBs）的耐药性。为了识别可能与TAF浸润相关的共表达模块和候选枢纽基因，我们对DEGs进行了加权基因共表达网络分析（WGCNA）。随后，进行单变量Cox回归、最小绝对收缩和选择算子（LASSO）回归以及多变量Cox回归分析，以筛选出阳性预后枢纽基因。最后，基于 、 和 的表达构建了一个高效预测特征。该特征与胶质瘤中TAF浸润的丰度相关，是胶质瘤的一个独立危险因素。总之，我们的研究结果表明，TAF相关特征是胶质瘤中一个有价值的预后生物标志物，并为胶质瘤的综合治疗提供了潜在靶点。
