Wu Yuxi, Peng Zesheng, Wang Haofei, Xiang Wei
Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Brain Sci. 2022 Jun 19;12(6):805. doi: 10.3390/brainsci12060805.
Glioma peritumoral brain edema (GPTBE) is a frequent complication in patients with glioma. The severity of peritumoral edema endangers patients' life and prognosis. However, there are still questions concerning the process of GPTBE formation and evolution. In this study, the patients were split into two groups based on edema scoring findings in the cancer imaging archive (TCIA) comprising 186 TCGA-LGG patients. Using mRNA sequencing data, differential gene (DEG) expression analysis was performed, comparing the two groups to find the key genes affecting GPTBE. A functional enrichment analysis of differentially expressed genes was performed. Then, a protein-protein interaction (PPI) network was established, and important genes were screened. Gene set variation analysis (GSVA) scores were calculated for major gene sets and comparatively correlated with immune cell infiltration. Overall survival (OS) was analyzed using the Kaplan-Meier curve. A total of 59 DEGs were found, with 10 of them appearing as important genes. DEGs were shown to be closely linked to inflammatory reactions. According to the network score, IL10 was in the middle of the network. The presence of the IL10 protein in glioma tissues was verified using the human protein atlas (HPA). Furthermore, the gene sets' GSVA scores were favorably linked with immune infiltration, particularly, with macrophages. The high-edema group had higher GSVA scores than the low-edema group. Finally, Kaplan-Meier analysis revealed no differences in OS between the two groups, and eight genes were found to be related to prognosis, whereas two genes were not. GPTBE is linked to the expression of inflammatory genes.
胶质瘤瘤周脑水肿（GPTBE）是胶质瘤患者常见的并发症。瘤周水肿的严重程度危及患者的生命和预后。然而，关于GPTBE的形成和演变过程仍存在一些问题。在本研究中，根据癌症影像存档（TCIA）中的水肿评分结果，将186例TCGA-LGG患者分为两组。利用mRNA测序数据，进行差异基因（DEG）表达分析，比较两组以找出影响GPTBE的关键基因。对差异表达基因进行功能富集分析。然后，建立蛋白质-蛋白质相互作用（PPI）网络，并筛选重要基因。计算主要基因集的基因集变异分析（GSVA）分数，并与免疫细胞浸润进行比较相关分析。使用Kaplan-Meier曲线分析总生存期（OS）。共发现59个差异表达基因，其中10个为重要基因。差异表达基因显示与炎症反应密切相关。根据网络评分，IL10位于网络中心。利用人类蛋白质图谱（HPA）验证了胶质瘤组织中IL10蛋白的存在。此外，基因集的GSVA分数与免疫浸润呈正相关，尤其是与巨噬细胞。高水肿组的GSVA分数高于低水肿组。最后，Kaplan-Meier分析显示两组患者的总生存期无差异，发现8个基因与预后相关，而2个基因与预后无关。GPTBE与炎症基因的表达有关。
