Guo Xuyang, Zhou Shaolong, Yang Zhuo, Li Zi-An, Hu Weihua, Dai Lirui, Liang Wulong, Wang Xinjun
Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Henan International Joint Laboratory of Glioma Metabolism and Microenvironment Research, Zhengzhou, China.
Front Oncol. 2022 May 12;12:896433. doi: 10.3389/fonc.2022.896433. eCollection 2022.
Metabolic reprogramming is a hallmark of glioma, and is an essential target for metabolic therapy. However, the prognostic value of and its association with immune infiltration has not been fully elucidated. Using RNA-seq and clinical data of glioma patients from The Cancer Genome Atlas (TCGA), was found to be correlated with poor prognosis in glioma and the advanced malignancy of clinicopathological characteristics. Next, the correlation between expression and tumor-infiltrating immune cells was performed using the single-sample GSEA algorithm, gene expression profiling interactive analysis (GEPIA), and tumor immune estimation resource version 2 (TIMER2.0); it was found that expression was positively correlated with multiple tumor-infiltrating immune cells. To further verify these results, immunofluorescence was conducted on paraffin-embedded glioma specimens, and a positive trend of the correlation between expression and Treg infiltration was observed in this cohort. Finally, differentially expressed gene analysis, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to explore the biological processes and signaling pathways that may be involved in during glioma pathogenesis. A protein-protein interaction network was established, and co-expression analysis was conducted to investigate the regulatory mechanism of in glioma. To the best of our knowledge, this is the first comprehensive study reporting that may serve as a novel prognostic biomarker associated with immune infiltrates, providing a novel perspective for glioma metabolic therapy.
代谢重编程是胶质瘤的一个标志，也是代谢治疗的一个重要靶点。然而，其预后价值及其与免疫浸润的关联尚未完全阐明。利用来自癌症基因组图谱（TCGA）的胶质瘤患者的RNA测序和临床数据，发现其与胶质瘤的不良预后及临床病理特征的高级别恶性相关。接下来，使用单样本基因集富集分析（GSEA）算法、基因表达谱交互分析（GEPIA）和肿瘤免疫评估资源版本2（TIMER2.0）进行了表达与肿瘤浸润免疫细胞之间的相关性分析；发现表达与多种肿瘤浸润免疫细胞呈正相关。为了进一步验证这些结果，对石蜡包埋的胶质瘤标本进行了免疫荧光检测，在该队列中观察到表达与调节性T细胞（Treg）浸润之间的相关性呈阳性趋势。最后，进行差异表达基因分析、基因本体论（Gene Ontology）和京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes）分析，以探索在胶质瘤发病机制中可能涉及的生物学过程和信号通路。建立了蛋白质-蛋白质相互作用网络，并进行了共表达分析，以研究其在胶质瘤中的调控机制。据我们所知，这是第一项综合研究报告，表明其可能作为一种与免疫浸润相关的新型预后生物标志物，为胶质瘤代谢治疗提供了新的视角。
