Abstract
Background 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). Methods 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. Results 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 ASB16 and NEDD4 that are related to the prognosis of LUAD. Conclusions The newly identified two genes associated with the prognosis of LUAD may provide a basis for the treatment of patients.
Highlights
Global cancer data show that the incidence and mortality rates of lung cancer again top the list [1]
Lung adenocarcinoma (LUAD) refers to the mucus-secreting epithelial cells that originate from the smaller bronchial mucosa, so most adenocarcinomas are located in the peripheral part of the lung in a spherical mass close to the pleura
By analyzing the GO and KEGG pathways of genes related to LUAD in GWAS, the results showed that gene enrichment molecule functions were mainly identical protein binding, and the biological processes were mainly positive regulation of transcription from RNA polymerase II promoters, and the components mainly included integral
Summary
Global cancer data show that the incidence and mortality rates of lung cancer again top the list [1]. Different types of cancer cells originate from different sites in the lung. Some prognostic genes related to LUAD have been found, which provide an effective criterion for early molecular diagnosis of LUAD and greatly promote the treatment of patients. The new predictive gene screening model and bioinformatics analysis are used to identify the driver genes associated with LUAD survival and to provide an effective criterion for early molecular diagnosis of LUAD. 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). Based on the LMM model, the GEMMA algorithm was used to screen the predictive genes related to LUAD survival. The newly identified two genes associated with the prognosis of LUAD may provide a basis for the treatment of patients
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