Ma Nan, Si Lu, Yang Meiling, Li Meihua, He Zhiyi
Department of Respiratory Medicine, The First Affiliated Hospital of GuangXi Medical University, Nanning, 530021, GuangXi, People's Republic of China.
Sci Rep. 2021 Mar 12;11(1):5855. doi: 10.1038/s41598-021-85246-x.
There is an urgent need to identify novel biomarkers that predict the prognosis of patients with NSCLC. In this study,we aim to find out mRNA signature closely related to the prognosis of NSCLC by new algorithm of bioinformatics. Identification of highly expressed mRNA in stage I/II patients with NSCLC was performed with the "Limma" package of R software. Survival analysis of patients with different mRNA expression levels was subsequently calculated by Cox regression analysis, and a multi-RNA signature was obtained by using the training set. Kaplan-Meier estimator, log-rank test and receiver operating characteristic (ROC) curves were used to analyse the predictive ability of the multi-RNA signature. RT-PCR used to verify the expression of the multi-RNA signature, and Westernblot used to verify the expression of proteins related to the multi-RNA signature. We identified fifteen survival-related mRNAs in the training set and classified the patients as high risk or low risk. NSCLC patients with low risk scores had longer disease-free survival than patients with high risk scores. The fifteen-mRNA signature was an independent prognostic factor, as shown by the ROC curve. ROC curve also showed that the combined model of the fifteen-mRNA signature and tumour stage had higher precision than stage alone. The expression of fifteen mRNAs and related proteins were higher in stage II NSCLC than in stage I NSCLC. Multi-gene expression profiles provide a moderate prognostic tool for NSCLC patients with stage I/II disease.
迫切需要鉴定能够预测非小细胞肺癌（NSCLC）患者预后的新型生物标志物。在本研究中，我们旨在通过生物信息学新算法找出与NSCLC预后密切相关的mRNA特征。使用R软件的“Limma”包对I/II期NSCLC患者中高表达的mRNA进行鉴定。随后通过Cox回归分析计算不同mRNA表达水平患者的生存分析，并使用训练集获得多RNA特征。采用Kaplan-Meier估计法、对数秩检验和受试者工作特征（ROC）曲线分析多RNA特征的预测能力。使用RT-PCR验证多RNA特征的表达，并使用蛋白质印迹法验证与多RNA特征相关的蛋白质的表达。我们在训练集中鉴定出15个与生存相关的mRNA，并将患者分为高风险或低风险。低风险评分的NSCLC患者的无病生存期比高风险评分的患者更长。如ROC曲线所示，15-mRNA特征是一个独立的预后因素。ROC曲线还表明，15-mRNA特征与肿瘤分期的联合模型比单独分期具有更高的准确性。15种mRNA和相关蛋白质在II期NSCLC中的表达高于I期NSCLC。多基因表达谱为I/II期疾病的NSCLC患者提供了一种适度的预后工具。
