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鉴定和验证用于预测肾透明细胞癌患者生存的双基因代谢特征。

Identification and validation of a two-gene metabolic signature for survival prediction in patients with kidney renal clear cell carcinoma.

机构信息

Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China.

Department of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong, China.

出版信息

Aging (Albany NY). 2021 Mar 3;13(6):8276-8289. doi: 10.18632/aging.202636.

Abstract

Metabolic reprogramming contributes to the high mortality of advanced stage kidney renal clear cell carcinoma (KIRC), the most common renal cancer subtype. This study aimed to identify a metabolism-related gene (MRG) signature to improve survival prediction in KIRC patients. We downloaded RNA sequencing data and corresponding clinical information for KIRC and control samples from The Cancer Genome Atlas database and identified, based on an MRG dataset in the Molecular Signatures Database, 123 MRGs with differential expression in KIRC. Following Cox regression analysis and least absolute shrinkage and selection operator selection, RRM2 and ALDH6A1 were identified as prognosis-related genes and used to construct a prognostic signature with independent prognostic significance. After risk score-based patient separation, stratified survival analysis indicated that high-risk patients showed poorer overall survival than low-risk patients. We then constructed a clinical nomogram that showed a concordance index of 0.774 and good performance based upon calibration curves. Gene set enrichment analysis revealed several metabolic pathways significantly enriched in the target genes. The two-gene metabolic signature identified herein may represent a highly valuable tool for KIRC prognosis prediction, and might also help identify new metabolism-related biomarkers and therapeutic targets for KIRC.

摘要

代谢重编程导致晚期肾透明细胞癌 (KIRC) 患者死亡率居高不下,KIRC 是最常见的肾癌亚型。本研究旨在鉴定一个与代谢相关的基因 (MRG) 特征,以改善 KIRC 患者的生存预测。我们从癌症基因组图谱 (TCGA) 数据库下载了 KIRC 和对照样本的 RNA 测序数据和相应的临床信息,并基于分子特征数据库中的一个 MRG 数据集,鉴定出 123 个在 KIRC 中差异表达的 MRG。经过 Cox 回归分析和最小绝对收缩和选择算子选择,确定 RRM2 和 ALDH6A1 为与预后相关的基因,并用于构建具有独立预后意义的预后特征。基于风险评分的患者分组后,分层生存分析表明,高风险患者的总体生存率低于低风险患者。然后,我们构建了一个临床列线图,根据校准曲线显示其一致性指数为 0.774,性能良好。基因集富集分析显示,在目标基因中存在几个显著富集的代谢途径。本文鉴定的两基因代谢特征可能代表 KIRC 预后预测的一个非常有价值的工具,也可能有助于鉴定 KIRC 新的代谢相关生物标志物和治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64ae/8034923/8665c1d1c377/aging-13-202636-g001.jpg

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