Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
Comput Math Methods Med. 2020 Nov 18;2020:7103412. doi: 10.1155/2020/7103412. eCollection 2020.
Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. The purpose of this study is to search for genes related to the prognosis of LUAD through methylation based on a linear mixed model (LMM).
Gene expression, methylation, and survival data of LUAD patients were downloaded from the TCGA database. Based on the LMM model, the GEMMA algorithm was used to screen the predictive genes related to LUAD survival. The Cox model was used to further screen the predicted genes, and then, protein-protein interaction (PPI) network was constructed. Through the software plugin Cytoscape MCODE 3.8.0, the most closely related genes in the PPI network module were selected for in-depth biological function analysis to further explore the interaction and correlation between genes.
We screened out 97 predictive genes from 18,834 genes and eliminated one gene associated with lung squamous cell carcinoma from previous studies, leaving 96 genes. The MCODE and the Kaplan-Meier curve analysis were used to finally identify two genes and that are related to the prognosis of LUAD.
The newly identified two genes associated with the prognosis of LUAD may provide a basis for the treatment of patients.
肺腺癌（LUAD）是肺癌最常见的病理类型。本研究旨在通过线性混合模型（LMM）基于甲基化来寻找与 LUAD 预后相关的基因。
从 TCGA 数据库中下载 LUAD 患者的基因表达、甲基化和生存数据。基于 LMM 模型，使用 GEMMA 算法筛选与 LUAD 生存相关的预测基因。使用 Cox 模型进一步筛选预测基因，然后构建蛋白质-蛋白质相互作用（PPI）网络。通过软件插件 Cytoscape MCODE 3.8.0，选择 PPI 网络模块中最密切相关的基因进行深入的生物学功能分析，以进一步探讨基因之间的相互作用和相关性。
我们从 18834 个基因中筛选出 97 个预测基因，并从先前的研究中消除了一个与肺鳞癌相关的基因，留下 96 个基因。使用 MCODE 和 Kaplan-Meier 曲线分析最终确定了与 LUAD 预后相关的两个基因 和 。
新鉴定的两个与 LUAD 预后相关的基因可能为患者的治疗提供依据。
