Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China.
Clin Transl Gastroenterol. 2023 Jun 1;14(6):e00582. doi: 10.14309/ctg.0000000000000582.
This study aims to identify the oxidative stress-related genes (OSRGs) with prognostic value and develop a riskscore model for prognosis evaluation in colon cancer.
The transcriptome data and corresponding clinical information about colon cancer were extracted from The Cancer Genome Atlas database. Differentially expressed OSRGs and transcription factors (TFs) were identified between the normal and tumor samples. A riskscore model was established with OSRGs filtered from Cox regression analysis. This riskscore model was appraised by Kaplan-Meier plot, receiver operating characteristic curve, and Cox regression analysis. The clinical relevance of riskscore and its association with immune cell infiltration were also evaluated.
A total of 307 differentially expressed OSRGs and 64 differential TFs were identified. A TF-OSRG regulatory network was constructed in Cytoscape software. A riskscore model was established based on 17 OSRGs with independent prognostic value. This riskscore model could separate the patients into low-risk and high-risk groups. It also had good predictive ability, with an area under the curve = 0.8. In multivariate Cox regression analysis, age, T stage, and riskscore were identified as independent risk factors in colon cancer. Riskscore was significantly correlated with T stage, N stage, and immune cell infiltration.
We established a useful riskscore model with 17 OSRGs for prognosticating the overall survival in patients with colon cancer. This study provides a new insight into the clinical utility of OSRG-based riskscore model, which will hopefully facilitate the prognosis evaluation of patients with colon cancer.
本研究旨在鉴定具有预后价值的氧化应激相关基因（OSRGs），并为结肠癌的预后评估开发风险评分模型。
从癌症基因组图谱数据库中提取了结肠癌的转录组数据和相应的临床信息。在正常和肿瘤样本之间鉴定出差异表达的 OSRGs 和转录因子（TFs）。通过 Cox 回归分析筛选出 OSRGs，建立风险评分模型。通过 Kaplan-Meier 图、接收者操作特征曲线和 Cox 回归分析评估该风险评分模型。还评估了风险评分的临床相关性及其与免疫细胞浸润的关联。
鉴定出 307 个差异表达的 OSRGs 和 64 个差异 TF。在 Cytoscape 软件中构建了 TF-OSRG 调控网络。基于具有独立预后价值的 17 个 OSRGs 建立了风险评分模型。该风险评分模型能够将患者分为低风险和高风险组。它还具有良好的预测能力，曲线下面积为 0.8。在多变量 Cox 回归分析中，年龄、T 分期和风险评分被确定为结肠癌的独立危险因素。风险评分与 T 分期、N 分期和免疫细胞浸润显著相关。
我们建立了一个包含 17 个 OSRGs 的有用风险评分模型，用于预测结肠癌患者的总生存率。本研究为基于 OSRG 的风险评分模型的临床应用提供了新的见解，有望促进结肠癌患者的预后评估。
