Zou Xiong, Chen Xi, Yang Jianjun, Li Yanfeng
Department of Urology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Front Mol Biosci. 2025 Aug 20;12:1630250. doi: 10.3389/fmolb.2025.1630250. eCollection 2025.
Kidney renal clear cell carcinoma (KIRC) prognosis exhibits substantial heterogeneity even among patients with identical clinicopathological staging, reflecting the limitations of current classification systems. Therefore, the development of reliable prognostic tools may improve clinical evaluation of KIRC outcomes and facilitate personalized therapy optimization.
The KIRC data of GSE40435 and GSE46699 in the GEO database were immunologically grouped based on 29 immune gene sets through R language. At the same time, RNA sequencing data, clinical information and tumor mutation data of KIRC patients in the TCGA database were jointly processed to explore methods that facilitate clinicians to judge the prognosis of KIRC patients. Quantitative real-time PCR (qPCR) was performed to validate the expression of key prognostic related genes (PRGs) in KIRC and paired adjacent normal tissues.
There were significant differences in the immune microenvironment and genetic composition of different immune subtypes of KIRC. A number of high-risk genes related to KIRC prognosis were screened out, and these genes were mainly involved in immune-related functions such as lymphocyte migration. At the same time, we combined TCGA and GEO to find four genes (BASP1, CCL8, FCGR1B, FKBP11) for determining the risk stratification of KIRC, and constructed a model for clinicians to assess KIRC prognosis based on gene expression and clinical information. qPCR confirmed that BASP1, FCGR1B, and FKBP11 were significantly upregulated in KIRC compared to adjacent normal tissues, whereas CCL8 showed no significant differential expression between KIRC and paracancerous tissues.
Our study has the potential to assist clinicians assess KIRC prognosis and modify more appropriate personalized treatment for KIRC patients in a timely manner.
肾透明细胞癌（KIRC）的预后即使在临床病理分期相同的患者中也存在很大异质性，这反映了当前分类系统的局限性。因此，开发可靠的预后工具可能会改善KIRC预后的临床评估，并有助于优化个性化治疗。
通过R语言，基于29个免疫基因集对GEO数据库中GSE40435和GSE46699的KIRC数据进行免疫分组。同时，联合处理TCGA数据库中KIRC患者的RNA测序数据、临床信息和肿瘤突变数据，以探索有助于临床医生判断KIRC患者预后的方法。进行定量实时PCR（qPCR）以验证关键预后相关基因（PRG）在KIRC及配对的相邻正常组织中的表达。
KIRC不同免疫亚型的免疫微环境和基因组成存在显著差异。筛选出了一些与KIRC预后相关的高危基因，这些基因主要参与淋巴细胞迁移等免疫相关功能。同时，我们结合TCGA和GEO发现了四个用于确定KIRC风险分层的基因（BASP1、CCL8、FCGR1B、FKBP11），并构建了一个基于基因表达和临床信息的模型，供临床医生评估KIRC预后。qPCR证实，与相邻正常组织相比，BASP1、FCGR1B和FKBP11在KIRC中显著上调，而CCL8在KIRC与癌旁组织之间无显著差异表达。
我们的研究有潜力协助临床医生评估KIRC预后，并及时为KIRC患者调整更合适的个性化治疗方案。
