Liu Yufeng, Wu Dali, Chen Haiping, Yan Lingfei, Xiang Qi, Li Qing, Wang Tao
Department of Urology, The Fifth Affiliated Hospital, Southern Medical University, Guangzhou, China.
Front Genet. 2023 Jan 20;14:1107294. doi: 10.3389/fgene.2023.1107294. eCollection 2023.
Currently, there are no useful biomarkers or prognostic risk markers for the diagnosis of kidney renal clear cell carcinoma (KIRC), although recent research has shown that both, the onset and progression of KIRC, are substantially influenced by immune-associated genes (IAGs). This work aims to create and verify the prognostic value of an immune risk score signature (IRSS) based on IAGs for KIRC using bioinformatics and public databases. Differentially expressed genes (DEGs) related to the immune systems (IAGs) in KIRC tissues were identified from The Cancer Genome Atlas (TCGA) databases. The DEGs between the tumor and normal tissues were identified using gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, a prognostic IRSS model was constructed and its prognostic and predictive performance was analyzed using survival analyses and nomograms. Kidney renal papillary cell carcinoma (KIRP) sets were utilized to further validate this model. Six independent immunity-related genes (PAEP, PI3, SAA2, SAA1, IL20RB, and IFI30) correlated with prognosis were identified and used to construct an IRSS model. According to the Kaplan-Meier curve, patients in the high-risk group had significantly poorer prognoses than those of patients in the low-risk group in both, the verification set ( <0.049; HR = 1.84; 95% CI = 1.02-3.32) and the training set ( < 0.001; HR = 3.12, 95% CI = 2.23-4.37). The numbers of regulatory T cells (Tregs) were significantly positively correlated with the six immunity-related genes identified, with correlation coefficients were 0.385, 0.415, 0.399, 0.451, 0.485, and 0.333, respectively ( <0.001). This work investigated the association between immune infiltration, immunity-related gene expression, and severity of KIRC to construct and verify a prognostic risk model for KIRC and KIRP.
目前，对于肾透明细胞癌（KIRC）的诊断，尚无有效的生物标志物或预后风险标志物，尽管最近的研究表明，KIRC的发生和进展均受到免疫相关基因（IAG）的显著影响。这项工作旨在利用生物信息学和公共数据库，创建并验证基于IAG的KIRC免疫风险评分特征（IRSS）的预后价值。从癌症基因组图谱（TCGA）数据库中识别出KIRC组织中与免疫系统相关的差异表达基因（DEG）。使用基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析来识别肿瘤组织与正常组织之间的DEG。此外，构建了一个预后IRSS模型，并使用生存分析和列线图分析其预后和预测性能。利用肾乳头状细胞癌（KIRP）数据集进一步验证该模型。识别出六个与预后相关的独立免疫相关基因（PAEP、PI3、SAA2、SAA1、IL20RB和IFI30），并用于构建IRSS模型。根据Kaplan-Meier曲线，在验证集（<0.049；HR = 1.84；95% CI = 1.02 - 3.32）和训练集（< 0.001；HR = 3.12，95% CI = 2.23 - 4.37）中，高风险组患者的预后均显著差于低风险组患者。调节性T细胞（Treg）的数量与所识别的六个免疫相关基因显著正相关，相关系数分别为0.385、0.415、0.399、0.451、0.485和0.333（<0.001）。这项工作研究了免疫浸润、免疫相关基因表达与KIRC严重程度之间的关联，以构建并验证KIRC和KIRP的预后风险模型。
