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鉴定促进 CD8 T 细胞浸润并具有葡萄膜黑色素瘤预后价值的共表达基因网络。

Identification of co-expressed gene networks promoting CD8 T cell infiltration and having prognostic value in uveal melanoma.

机构信息

Department of ophthalmology, West China Hospital, Sichuan University, Sichuan Province, 610041, Chengdu, China.

出版信息

BMC Ophthalmol. 2023 Aug 10;23(1):354. doi: 10.1186/s12886-023-03098-7.

Abstract

Current immunotherapies are unsatisfactory against uveal melanoma (UM); however, elevated CD8 T cell infiltration level indicates poor prognosis in UM. Here, we aimed to identify co-expressed gene networks promoting CD8 T cell infiltration in UM and created a prognostic hazard model based on the identified hub genes. Raw data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Stromal-immune comprehensive score (ESTIMATE) was used to evaluate the immune-infiltration landscape of the tumor microenvironment. Single-Sample Gene Set Enrichment Analysis (ssGSEA) and Weighted Correlation Network Analysis (WGCNA) were used to quantify CD8 T cell infiltration level and identify hub genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to analyze the biological processes. Least absolute shrinkage and selection operator (LASSO) Cox regression were used to establish a prognostic model, which was further validated. Finally, pan-cancer analysis evaluated these genes to be associated with CD8 T cell infiltration in other tumors. In conclusion, the proposed four-gene (PTPN12, IDH2, P2RX4, and KDELR2) prognostic hazard model had satisfactory prognostic ability. These hub genes may promote CD8 T cell infiltration in UM through antigen presentation, and CD8 T cell possibly function as Treg, resulting in poor prognosis. These findings might facilitate the development of novel immunotherapies.

摘要

目前针对葡萄膜黑色素瘤(UM)的免疫疗法并不令人满意;然而,CD8 T 细胞浸润水平升高预示着 UM 预后不良。在这里,我们旨在鉴定促进 UM 中 CD8 T 细胞浸润的共表达基因网络,并基于鉴定出的枢纽基因构建一个预后风险模型。从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)下载原始数据和临床信息。基质-免疫综合评分(ESTIMATE)用于评估肿瘤微环境的免疫浸润景观。单样本基因集富集分析(ssGSEA)和加权相关网络分析(WGCNA)用于量化 CD8 T 细胞浸润水平和鉴定枢纽基因。进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析以分析生物学过程。最小绝对收缩和选择算子(LASSO)Cox 回归用于建立预后模型,并进一步进行验证。最后,泛癌分析评估了这些基因与其他肿瘤中 CD8 T 细胞浸润的相关性。总之,所提出的四基因(PTPN12、IDH2、P2RX4 和 KDELR2)预后风险模型具有令人满意的预后能力。这些枢纽基因可能通过抗原呈递促进 UM 中 CD8 T 细胞的浸润,而 CD8 T 细胞可能作为 Treg 发挥作用,导致预后不良。这些发现可能有助于开发新的免疫疗法。

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