Qiu Chongrong, Zhou Yuming, Xiao Xiaoliu, Song Tianjun, Zeng Dongyun, Peng Jingliang
Department of Emergency, The Affiliated Ganzhou Hospital of Nanchang University, Ganzhou, China.
Department of Emergency, Ganzhou People's Hospital, Ganzhou, China.
Cancer Biother Radiopharm. 2025 Jan;40(1):11-21. doi: 10.1089/cbr.2024.0094. Epub 2024 Jul 1.
Lung adenocarcinoma (LUAD) remains heterogeneous in the prognosis of patients; oxidative stress (OS) has been widely linked to cancer progression. Therefore, it is necessary to explore the prognostic value of the OS-associated genes in LUAD. An OS-associated prognostic signature was developed using the Cox regression and random forest model in The Cancer Genome Atlas-LUAD dataset. Kaplan-Meier survival curve and time-dependent receiver operating characteristic (tROC) curves were applied to evaluate and validate the predictive accuracy of this signature among the training and testing cohorts. A nomogram was constructed and also verified by the concordance index (C-index), calibration curves, and tROC curves, respectively. ESTIMATE algorithm and CIBERSORT algorithms were conducted to explore the signature's immune characteristics. Core target genes of the prognostic signature were identified in the protein-protein interaction network. A six OS-associated prognostic gene signature () was developed. The tROC and K-M survival curves in the training and testing cohorts revealed that the signature had good and robust predictive capability to predict the overall survival of LUAD patients. Meanwhile, the risk score was an independent prognostic factor influencing patients' overall survival. The results of the C-index (0.714), calibration curves, and the 1-, 2-, and 3-year tROC curves (area under the curve = 0.703, 0.737, and 0.723, respectively) suggested that the nomogram had good predictive efficacy and prognostic value for LUAD. Then, the authors found that the high-risk group may be depletion or loss of antitumor function of immune cells. Finally, 10 core genes of the signature were predicted. Their study may provide a novel understanding for the identification of prognostic stratification in LUAD patients, as well as the regulation of OS-associated genes in LUAD progression.
肺腺癌(LUAD)患者的预后仍然存在异质性;氧化应激(OS)与癌症进展密切相关。因此,有必要探索OS相关基因在LUAD中的预后价值。利用Cox回归和随机森林模型在癌症基因组图谱-LUAD数据集中开发了一种OS相关的预后特征。应用Kaplan-Meier生存曲线和时间依赖性受试者工作特征(tROC)曲线来评估和验证该特征在训练和测试队列中的预测准确性。构建了列线图,并分别通过一致性指数(C指数)、校准曲线和tROC曲线进行验证。采用ESTIMATE算法和CIBERSORT算法来探索该特征的免疫特性。在蛋白质-蛋白质相互作用网络中鉴定出预后特征的核心靶基因。开发了一种由六个OS相关的预后基因组成的特征。训练和测试队列中的tROC和K-M生存曲线显示,该特征对预测LUAD患者的总生存期具有良好且稳健的预测能力。同时,风险评分是影响患者总生存期的独立预后因素。C指数(0.714)、校准曲线以及1年、2年和3年tROC曲线(曲线下面积分别为0.703、0.737和0.723)的结果表明,列线图对LUAD具有良好的预测效能和预后价值。然后,作者发现高风险组可能存在免疫细胞抗肿瘤功能的耗竭或丧失。最后,预测了该特征的10个核心基因。他们的研究可能为LUAD患者预后分层的识别以及LUAD进展中OS相关基因的调控提供新的认识。