Zhang Quncheng, Wu Xuan, Sun Ya, Yang Li, Wang Ziqi, Yang Yuanjian, Zhao Xingru, Zhang Xiaoju
Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital China.
Henan Provincial People's Hospital Zhengzhou, China.
Am J Transl Res. 2022 Oct 15;14(10):7308-7323. eCollection 2022.
Lung adenocarcinoma (LUAD) remains the most common type of lung cancer and is associated with distant metastasis and poor prognosis. Epithelial-mesenchymal transition (EMT) plays crucial roles in carcinogenesis, embryogenesis, and wound healing. EMT-related molecules may be adopted for early diagnosis and prognosis of cancer and targeting them may constitute an attractive strategy for treatment. This study aims to identify the EMT-related long non-coding RNAs (lncRNAs) and develop a risk signature to accurately predict the prognosis of LUAD patients.
The RNA-seq data and corresponding clinical profiles were obtained from LUAD cohort of The Cancer Genome Atlas (TCGA) database. EMT-related lncRNAs significantly associated with prognosis were identified by Pearson correlation analysis and univariate regression analysis. Subsequently, an EMT-related prognostic risk signature was developed through LASSO and multivariate regression analyses. Kaplan Meier and receiver operating characteristic curve analysis were implemented to assess the predictive performance of the signature. The nomogram was constructed to predict the 1-year, 3-year, and 5-year overall survival of LUAD patients. Additionally, enrichment analyses were carried out to identify probable biologic processes and cellular pathways involved in the signature. The correlation of immune cell infiltration and risk score was also evaluated by CIBERSORT algorithm. Finally, we constructed a ceRNA network to further study possible downstream targets and molecular mechanisms of EMT-related lncRNAs in LUAD.
Eight EMT-related lncRNAs were identified to develop a prognostic risk signature in LUAD. Patients with high-risk scores had worse survival outcomes than those with low-risk scores. The signature showed robust predictive potential, and was verified to be an independent prognostic factor. Moreover, the risk score based on the signature was significantly correlated with immune cell infiltration in LUAD.
We established and validated a prognostic signature that reflects the tumor microenvironment characteristics and predicts the outcomes for LUAD.
肺腺癌（LUAD）仍然是最常见的肺癌类型，与远处转移和不良预后相关。上皮-间质转化（EMT）在肿瘤发生、胚胎发育和伤口愈合中起关键作用。EMT相关分子可用于癌症的早期诊断和预后评估，针对这些分子可能构成一种有吸引力的治疗策略。本研究旨在鉴定与EMT相关的长链非编码RNA（lncRNA），并开发一种风险特征以准确预测LUAD患者的预后。
从癌症基因组图谱（TCGA）数据库的LUAD队列中获取RNA测序数据和相应的临床资料。通过Pearson相关分析和单因素回归分析鉴定与预后显著相关的EMT相关lncRNA。随后，通过LASSO和多因素回归分析开发了一种与EMT相关的预后风险特征。采用Kaplan-Meier法和受试者工作特征曲线分析来评估该特征的预测性能。构建列线图以预测LUAD患者1年、3年和5年的总生存率。此外，进行富集分析以确定该特征可能涉及的生物学过程和细胞途径。还通过CIBERSORT算法评估免疫细胞浸润与风险评分的相关性。最后，构建ceRNA网络以进一步研究LUAD中EMT相关lncRNA可能的下游靶点和分子机制。
鉴定出8个与EMT相关的lncRNA，用于构建LUAD的预后风险特征。高风险评分患者的生存结果比低风险评分患者更差。该特征显示出强大的预测潜力，并被验证为独立的预后因素。此外，基于该特征的风险评分与LUAD中的免疫细胞浸润显著相关。
我们建立并验证了一种反映肿瘤微环境特征并预测LUAD患者预后的预后特征。
