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基于基因表达综合数据库（GEO）数据集的膀胱癌免疫治疗相关基因筛查

Screening of immunotherapy-related genes in bladder cancer based on GEO datasets.

作者信息

Liu Xiaolong, Li Xinxin, Kuang Qihui, Luo Hongbo

机构信息

School of Medicine, Wuhan University of Science and Technology, Wuhan, China.

Department of Urology, Wuhan Third Hospital and Tongren Hospital of Wuhan University, Wuhan, China.

出版信息

Front Oncol. 2023 May 18;13:1176637. doi: 10.3389/fonc.2023.1176637. eCollection 2023.

DOI:10.3389/fonc.2023.1176637
PMID:37274283
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10232963/
Abstract

BACKGROUND

As one of the most prevalent genitourinary cancers, bladder cancer (BLCA) is associated with high morbidity and mortality. Currently, limited indicators are available for early detection and diagnosis of bladder cancer, and there is a lack of specific biomarkers for evaluating the prognosis of BLCA patients. This study aims to identify critical genes that affect bladder cancer immunity to improve the diagnosis and prognosis of bladder cancer and to identify new biomarkers and targets for immunotherapy.

METHODS

Two GEO datasets were used to screen differentially expressed genes (DEGs). The STRING database was used to construct a protein-protein interaction network of DEGs, and plug-in APP CytoHubba in Cytoscape was used to identify critical genes in the network. GO and KEGG analyses explored the functions and pathways of differential gene enrichment. We used GEPIA to validate the expression of differential genes, their impact on patient survival, and their relationship to clinicopathological parameters. Additionally, hub genes were verified using qRT-PCR and Western blotting. Immune infiltration analysis and multiple immunohistochemistry reveal the impact of Hub genes on the tumor microenvironment.

RESULT

We screened out 259 differential genes, and identified 10 key hub genes by the degree algorithm. Four genes (ACTA2, FLNA, TAGLN, and TPM1) were associated with overall or disease-free survival in BLCA patients and were significantly associated with clinical parameters. We experimentally confirmed that the mRNA and protein levels of these four genes were significantly decreased in bladder cancer cells. Immunoassays revealed that these four genes affect immune cell infiltration in the tumor microenvironment; they increased the polarization of M2 macrophages.

CONCLUSION

These four genes affect the tumor microenvironment of bladder cancer, provide a new direction for tumor immunotherapy, and have significant potential in the diagnosis and prognosis of bladder cancer.

摘要

背景

膀胱癌（BLCA）作为最常见的泌尿生殖系统癌症之一，其发病率和死亡率都很高。目前，用于膀胱癌早期检测和诊断的指标有限，且缺乏评估BLCA患者预后的特异性生物标志物。本研究旨在识别影响膀胱癌免疫的关键基因，以改善膀胱癌的诊断和预后，并识别免疫治疗的新生物标志物和靶点。

方法

使用两个GEO数据集筛选差异表达基因（DEG）。利用STRING数据库构建DEG的蛋白质-蛋白质相互作用网络，并使用Cytoscape中的插件APP CytoHubba识别网络中的关键基因。GO和KEGG分析探索差异基因富集的功能和途径。我们使用GEPIA验证差异基因的表达、它们对患者生存的影响以及它们与临床病理参数的关系。此外，通过qRT-PCR和蛋白质印迹法验证枢纽基因。免疫浸润分析和多重免疫组化揭示了枢纽基因对肿瘤微环境的影响。

结果

我们筛选出259个差异基因，并通过度算法确定了10个关键枢纽基因。四个基因（ACTA2、FLNA、TAGLN和TPM1）与BLCA患者的总生存期或无病生存期相关，且与临床参数显著相关。我们通过实验证实，这四个基因在膀胱癌细胞中的mRNA和蛋白质水平显著降低。免疫分析显示，这四个基因影响肿瘤微环境中的免疫细胞浸润；它们增加了M2巨噬细胞的极化。

结论

这四个基因影响膀胱癌的肿瘤微环境，为肿瘤免疫治疗提供了新方向，在膀胱癌的诊断和预后方面具有巨大潜力。

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