Hu Zijian, Zhou Yajie, Xie Lei, Zhang Shuwen, Liu Yijiang, Zhang Wenxiong, Huang Ting
Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
J Cell Mol Med. 2025 Jul;29(14):e70657. doi: 10.1111/jcmm.70657.
Tumour necrosis factor (TNF) plays a critical role in tumour progression, but the specific involvement of mRNA in this process, particularly in kidney renal clear cell carcinoma (KIRC) remains insufficiently understood. Our study aims to develop a TNF-related mRNA (TRmRNA) model to predict prognosis and inform treatment strategies in KIRC. KIRC expression data from The Cancer Genome Atlas (TCGA) and TNF-related genes (TRGs) from the Genecards database were used to construct and validate a TRmRNA prognostic model. A nomogram integrating clinical features with the risk model was also developed to enhance prognostic accuracy. Enrichment analysis, drug sensitivity analysis and RT-qPCR validation were performed to further explore the biological mechanisms and clinical applicability of the model. A prognostic signature consisting of nine TRmRNAs was identified. Kaplan-Meier analysis showed that the high-risk (HRK) group had significantly shorter overall survival (OS) compared to the low-risk (LRG) group (p < 0.001). The nomogram, incorporating the risk model, yielded an area under the curve (AUC) of 0.766, indicating robust prognostic accuracy. Enrichment analysis identified solute sodium symporter and proximal tubule transport pathways enriched in the LRG group, whereas the HRK group exhibited enrichment in CD22-mediated BCR regulation and immunoglobulin complex pathways. The HRK group also showed a higher tumour mutational burden (TMB), correlating with a poorer prognosis. RT-qPCR confirmed the differential expression of mRNAs in KIRC cells. The TRmRNA-based prognostic model holds significant promise for predicting patient outcomes and guiding personalised treatment strategies in KIRC.
肿瘤坏死因子（TNF）在肿瘤进展中起关键作用，但mRNA在此过程中的具体参与情况，尤其是在肾透明细胞癌（KIRC）中的情况，仍未得到充分了解。我们的研究旨在开发一种与TNF相关的mRNA（TRmRNA）模型，以预测KIRC的预后并为治疗策略提供依据。利用来自癌症基因组图谱（TCGA）的KIRC表达数据和来自Genecards数据库的TNF相关基因（TRG）构建并验证了TRmRNA预后模型。还开发了一个将临床特征与风险模型相结合的列线图，以提高预后准确性。进行了富集分析、药物敏感性分析和RT-qPCR验证，以进一步探索该模型的生物学机制和临床适用性。确定了一个由9个TRmRNA组成的预后特征。Kaplan-Meier分析表明，与低风险（LRG）组相比，高风险（HRK）组的总生存期（OS）明显更短（p < 0.001）。纳入风险模型的列线图的曲线下面积（AUC）为0.766，表明预后准确性较强。富集分析确定溶质钠同向转运体和近端小管转运途径在LRG组中富集，而HRK组在CD22介导的BCR调节和免疫球蛋白复合物途径中表现出富集。HRK组还显示出更高的肿瘤突变负担（TMB），与较差的预后相关。RT-qPCR证实了KIRC细胞中mRNA的差异表达。基于TRmRNA的预后模型在预测KIRC患者的预后和指导个性化治疗策略方面具有重要前景。
