ABSTRACT Kidney renal clear cell carcinoma (KIRC) remains a significant challenge worldwide because of its poor prognosis and high mortality rate, and accurate prognostic gene signatures are urgently required for individual therapy. This study aimed to construct and validate a seven-gene signature for predicting overall survival (OS) in patients with KIRC. The mRNA expression profile and clinical data of patients with KIRC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Prognosis-associated genes were identified, and a prognostic gene signature was constructed. Then, the prognostic efficiency of the gene signature was assessed. The results obtained using data from the TCGA were validated using those from the ICGC and other online databases. Gene set enrichment analyses (GSEA) were performed to explore potential molecular mechanisms. A seven-gene signature (PODXL, SLC16A12, ZIC2, ATP2B3, KRT75, C20orf141, and CHGA) was constructed, and it was found to be effective in classifying KIRC patients into high- and low-risk groups, with significantly different survival based on the TCGA and ICGC validation data set. Cox regression analysis revealed that the seven-gene signature had an independent prognostic value. Then, we established a nomogram, including the seven-gene signature, which had a significant clinical net benefit. Interestingly, the seven-gene signature had a good performance in distinguishing KIRC from normal tissues. GSEA revealed that several oncological signatures and GO terms were enriched. This study developed a novel seven-gene signature and nomogram for predicting the OS of patients with KIRC, which may be helpful for clinicians in establishing individualized treatments.

中文翻译：

---

通过综合生物信息学分析预测肾透明细胞癌患者总生存期的七基因特征的构建和验证

摘要 肾肾透明细胞癌 (KIRC) 因其预后差和死亡率高而在世界范围内仍然是一个重大挑战，并且迫切需要准确的预后基因特征用于个体治疗。本研究旨在构建和验证用于预测 KIRC 患者总生存期 (OS) 的七基因特征。KIRC 患者的 mRNA 表达谱和临床数据来自癌症基因组图谱（TCGA）和国际癌症基因组联盟（ICGC）。鉴定了预后相关基因，并构建了预后基因特征。然后，评估基因特征的预后效率。使用来自 TCGA 的数据获得的结果使用来自 ICGC 和其他在线数据库的数据进行验证。进行基因集富集分析（GSEA）以探索潜在的分子机制。构建了一个七基因特征（PODXL、SLC16A12、ZIC2、ATP2B3、KRT75、C20orf141 和 CHGA），发现它可以有效地将 KIRC 患者分为高危组和低危组，根据TCGA 和 ICGC 验证数据集。Cox 回归分析显示七基因特征具有独立的预后价值。然后，我们建立了列线图，包括具有显着临床净收益的七基因特征。有趣的是，七基因特征在区分 KIRC 与正常组织方面表现良好。GSEA 显示，丰富了几个肿瘤学特征和 GO 术语。