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基于生物信息学的筛选和分析抗血管生成对髓源抑制细胞影响的关键基因及其对免疫微环境的影响。

Bioinformatics-based screening and analysis of the key genes involved in the influence of antiangiogenesis on myeloid-derived suppressor cells and their effects on the immune microenvironment.

机构信息

Department of Oncology, 5th Medical Center of Chinese, PLA General Hospital, Dongdajie 8th, Fengtai District, Beijing, 100853, China.

Department of Oncology, 6th Medical Center of Chinese, PLA General Hospital, Beijing, China.

出版信息

Med Oncol. 2024 Mar 25;41(5):96. doi: 10.1007/s12032-024-02357-x.

Abstract

This study aimed to screen differentially expressed genes (DEGs) involved in the influence of antiangiogenic therapy on myeloid-derived suppressor cell (MDSC) infiltration and investigate their mechanisms of action. Data on DEGs after the action of antiangiogenic drugs in a pan-cancer context were obtained from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler package in R software. Single-sample gene set enrichment analysis was performed using the gene set variation analysis package to evaluate the levels of immune cells and the activity of immune-related pathways. The relationships of DEGs with the infiltration levels of MDSCs and specific immune cell subpopulations were investigated via gene module analysis. The top 10 key genes were subsequently obtained from PPI network analysis using the cytoHubba plugin of the Cytoscape platform. When the DEGs of the four datasets were intersected, a DEG in the intersection of three datasets and 12 DEGs in the intersection of two datasets were upregulated, and 28 DEGs in the intersection of two datasets were downregulated. GO and KEGG pathway enrichment analyses revealed that the DEGs were associated with multiple important signaling pathways closely related to tumor onset and development, including cell differentiation, cell proliferation, the cell cycle, and immune responses. Most downregulated genes in lung adenocarcinoma (LUAD) were positively correlated with MDSC expression. Only MGP was negatively correlated; the correlation between CACNG6 and MDSC expression was statistically insignificant. In lung squamous cell carcinoma (LUSC), the relationships of PMEPA1, PCDH7, NEURL1B, and CACNG6 with MDSC expression were statistically insignificant; MGP was negatively correlated with MDSC expression. The top 10 key genes with the highest degree scores obtained using the cytoHubba plugin of Cytoscape were AURKB, RRM2, BUB1, NUSAP1, PRC1, TOP2A, NCAPH, CENPA, KIF2C, and CCNA2. Most of these genes were upregulated in LUAD and associated with immune cell infiltration and prognosis in tumors. An analysis of the relationships between DEGs and infiltration by other specific immune cells revealed the presence of consistent patterns in the downregulated genes, which exhibited positive correlations with the levels of Th2 cells, γδ T cells, and CD56dim NK cells, and negative correlations with other infiltrating immune cells. Antiangiogenic therapy may regulate MDSC infiltration through multiple important signaling pathways closely associated with tumor onset and development, such as cell differentiation, cell proliferation, the cell cycle, and immune responses. Antiangiogenic drugs may exert effects by affecting various types of infiltrating cells associated with immune suppression.

摘要

这项研究旨在筛选参与抗血管生成治疗对髓样来源抑制细胞(MDSC)浸润影响的差异表达基因(DEGs),并探讨其作用机制。从基因表达综合数据库(GEO)中获得了泛癌背景下抗血管生成药物作用后 DEGs 的数据。使用 R 软件中的 clusterProfiler 软件包进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路富集分析。使用基因集变异分析(GSVA)软件包进行单样本基因集富集分析,以评估免疫细胞水平和免疫相关途径的活性。通过基因模块分析研究 DEGs 与 MDSC 浸润水平和特定免疫细胞亚群的关系。使用 Cytoscape 平台的 cytoHubba 插件从 PPI 网络分析中获得前 10 个关键基因。当四个数据集的 DEGs 相交时,三个数据集的交集有一个上调的 DEG,两个数据集的交集有 12 个上调的 DEG,两个数据集的交集有 28 个下调的 DEG。GO 和 KEGG 通路富集分析表明,DEGs 与多种与肿瘤发生和发展密切相关的重要信号通路有关,包括细胞分化、细胞增殖、细胞周期和免疫反应。肺腺癌(LUAD)中大多数下调的基因与 MDSC 表达呈正相关。只有 MGP 呈负相关;CACNG6 与 MDSC 表达的相关性无统计学意义。在肺鳞状细胞癌(LUSC)中,PMEPA1、PCDH7、NEURL1B 和 CACNG6 与 MDSC 表达的关系无统计学意义;MGP 与 MDSC 表达呈负相关。使用 Cytoscape 的 cytoHubba 插件获得的具有最高度数得分的前 10 个关键基因是 AURKB、RRM2、BUB1、NUSAP1、PRC1、TOP2A、NCAPH、CENPA、KIF2C 和 CCNA2。这些基因在 LUAD 中大多上调,并与肿瘤中的免疫细胞浸润和预后有关。分析 DEGs 与其他特定免疫细胞浸润之间的关系表明,下调基因存在一致的模式,与 Th2 细胞、γδ T 细胞和 CD56dim NK 细胞的水平呈正相关,与其他浸润免疫细胞呈负相关。抗血管生成治疗可能通过与肿瘤发生和发展密切相关的多个重要信号通路来调节 MDSC 浸润,如细胞分化、细胞增殖、细胞周期和免疫反应。抗血管生成药物可能通过影响与免疫抑制相关的各种类型的浸润细胞来发挥作用。

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