Lu Qing, Xi Ping, Xu Suling, Zhang Zhicheng, Gong Binbin, Liu Ji, Zhu Qiqi, Sun Ting, Zhu Shaoxing, Chen Ru
Department of Urology, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian, P.R. China.
Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China.
Aging (Albany NY). 2024 Mar 27;16(7):6118-6134. doi: 10.18632/aging.205691.
Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches.
The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model.
We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells.
We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.
肾透明细胞癌（ccRCC）是最常见的恶性肿瘤之一。然而，其潜在病因、早期诊断技术和治疗方法仍存在诸多障碍。
癌症基因组图谱（TCGA）-肾透明细胞癌（KIRC）队列对来自DrLLPS网站的液-液相分离（LLPS）相关基因进行差异分析。采用单因素和多因素Cox回归分析以及LASSO回归分析构建预后模型。E-MTAB-1980队列用于外部验证。然后，对高风险组和低风险组进行潜在功能、免疫浸润分析和突变图谱分析。最后，通过定量实时聚合酶链反应（qRT-PCR）实验以及单细胞分析验证了模型的关键基因。
我们在ccRCC中筛选出174个LLPS相关基因，并构建了一个由五个基因（CLIC5、MXD3、NUF2、PABPC1L、PLK1）组成的风险特征。发现高风险组在不同亚组中与较差的预后相关。结合年龄和肿瘤分期构建的列线图对ccRCC患者的预后具有很强的预测能力。此外，两组之间在通路富集、免疫细胞浸润和突变图谱方面存在差异。肾癌细胞系和肾癌组织中的qRT-PCR结果与生物特征预测一致。分析了GSE159115、GSE139555和GSE121636的三个单细胞数据，以研究这五个基因在不同细胞中的存在差异。
我们开发了一种基于五个LLPS相关基因构建的风险特征，对ccRCC患者的预后具有较高的预测能力，进一步为临床决策提供了有力支持。
