Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Department of Research Management and International Cooperation, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Int Immunopharmacol. 2020 Apr;81:106274. doi: 10.1016/j.intimp.2020.106274. Epub 2020 Feb 7.
Recent studies have demonstrated that immune-associated genes (IAGs) play an important role in the occurrence and progression of clear renal clear cell carcinoma (ccRCC). Novel biomarkers and a reliable prognostic prediction model for ccRCC patients are still limited. The objective of this study was to develop a IAGs signature and validate its prognostic value in ccRCC using bioinformatic methods and publicly database.
In the present study, we identified differentially expressed IAGs in ccRCC based on The Cancer Genome Atlas (TCGA) database. A prognostic IAGs risk model was further developed and its prognostic and predictive value was evaluated by survival analysis and nomogram.
A total of 681 differentially expressed IAGs were identified and seven IAGs (IFI30, WNT5A, IRF9, AGER, PLAUR, TEK, BID) were finally selected in a IAGs signature. Survival analysis revealed that high IAGs risk scores were significantly related to poor survival outcomes. The IAGs signature was demonstrated as an independent prognostic factor and closely related to the metastasis status of ccRCC. A nomogram with clinicopathologic characteristics and IAGs signature was also constructed to superiorly predict prognosis of ccRCC patients.
We identified seven IAGs as a potential signature for reflecting the prognosis of ccRCC based on TCGA database. Further clinical trials are needed to validate our observations and the mechanisms underlying the prognostic value of IAGs signature in ccRCC also deserve further experimental exploration.
最近的研究表明,免疫相关基因(IAGs)在透明细胞肾细胞癌(ccRCC)的发生和发展中起着重要作用。目前仍然缺乏用于 ccRCC 患者的新型生物标志物和可靠的预后预测模型。本研究旨在通过生物信息学方法和公共数据库,开发 IAGs 特征并验证其在 ccRCC 中的预后价值。
本研究基于癌症基因组图谱(TCGA)数据库,鉴定了 ccRCC 中差异表达的 IAGs。进一步开发了一个预后 IAGs 风险模型,并通过生存分析和列线图评估其预后和预测价值。
共鉴定出 681 个差异表达的 IAGs,最终在 IAGs 特征中选择了 7 个 IAGs(IFI30、WNT5A、IRF9、AGER、PLAUR、TEK、BID)。生存分析表明,高 IAGs 风险评分与较差的生存结局显著相关。IAGs 特征被证明是独立的预后因素,与 ccRCC 的转移状态密切相关。还构建了一个包含临床病理特征和 IAGs 特征的列线图,以更好地预测 ccRCC 患者的预后。
我们基于 TCGA 数据库鉴定了 7 个 IAGs,作为反映 ccRCC 预后的潜在特征。需要进一步的临床试验来验证我们的观察结果,并且 IAGs 特征在 ccRCC 中的预后价值的机制也值得进一步的实验探索。