Li Wanzhen, Liu Shiqing, Su Shihong, Chen Yang, Sun Gengyun
Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha, China.
PeerJ. 2021 Jan 8;9:e10470. doi: 10.7717/peerj.10470. eCollection 2021.
MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In brief, the miRNA expression profiles and clinicopathological factors of 499 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier (K-M) survival analysis showed significant correlations between differentially expressed miRNAs and LUAD survival outcomes. Afterward, 1,000 resample LUAD training matrices based on the training set was applied to identify the potential prognostic miRNAs. The least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to constructed a six-miRNA based prognostic signature for LUAD patients. Samples with different risk scores displayed distinct OS in K-M analysis, indicating considerable predictive accuracy of this signature in both training and validation sets. Furthermore, time-dependent receiver operating characteristic (ROC) analysis demonstrated the nomogram achieved higher predictive accuracy than any other clinical variables after incorporating the clinical information (age, sex, stage, and recurrence). In the stratification analysis, the prognostic value of this classifier in LUAD patients was validated to be independent of other clinicopathological variables, such as age, gender, tumor recurrence, and early stage. Gene set annotation analyses were also conducted through the Hallmark gene set and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating target genes of the six miRNAs were positively related to various molecular pathways of cancer, such as hallmark UV response, Wnt signaling pathway and mTOR signaling pathway. In addition, fresh cancer tissue samples and matched adjacent tissue samples from 12 LUAD patients were collected to verify the expression of miR-582's target genes in the model, further revealing the potential relationship between SOX9, RASA1, CEP55, MAP4K4 and LUAD tumorigenesis, and validating the predictive value of the model. Taken together, the present study identified a robust signature for the OS prediction of LUAD patients, which could potentially aid in the individualized selection of therapeutic approaches for LUAD patients.
据报道，微小RNA（miRNA，miR）与肺癌（LC）的广泛生物学过程高度相关，正常样本与LC样本之间差异表达miRNA的鉴定已广泛用于发现总生存期（OS）的预后因素和对治疗的反应。本研究旨在开发和评估一种基于miRNA的特征，用于预测肺腺癌（LUAD）患者的OS，LUAD是LC的一种常见组织学亚型。简而言之，从癌症基因组图谱（TCGA）数据库收集了499例LUAD患者的miRNA表达谱和临床病理因素。Kaplan-Meier（K-M）生存分析显示差异表达的miRNA与LUAD生存结果之间存在显著相关性。随后，基于训练集应用1000个重采样的LUAD训练矩阵来识别潜在的预后miRNA。使用最小绝对收缩和选择算子（LASSO）cox回归分析为LUAD患者构建了基于六个miRNA的预后特征。在K-M分析中，具有不同风险评分的样本显示出不同的OS，表明该特征在训练集和验证集中均具有相当高的预测准确性。此外，时间依赖性受试者工作特征（ROC）分析表明，在纳入临床信息（年龄、性别、分期和复发）后，列线图的预测准确性高于任何其他临床变量。在分层分析中，该分类器在LUAD患者中的预后价值被验证独立于其他临床病理变量，如年龄、性别、肿瘤复发和早期阶段。还通过标志性基因集和京都基因与基因组百科全书（KEGG）途径进行了基因集注释分析，表明这六个miRNA的靶基因与癌症的各种分子途径呈正相关，如标志性紫外线反应、Wnt信号通路和mTOR信号通路。此外，收集了12例LUAD患者的新鲜癌组织样本和匹配的相邻组织样本，以验证模型中miR-582靶基因的表达，进一步揭示SOX9、RASA1、CEP55、MAP4K4与LUAD肿瘤发生之间的潜在关系，并验证模型的预测价值。综上所述，本研究确定了一种用于预测LUAD患者OS的可靠特征，这可能有助于为LUAD患者个体化选择治疗方法。
