Abstract:Abstract: To analyze the microarray data to screen its potential pathogenesis at the molecular level, and explore the potential biomarkers of lung adenocarcinoma (LUAD). The expression data of GSE63459, GSE27262 and GSE75037 were downloaded from the Gene Expression Omnibus (GEO), and the differentially expressed genes were obtained from three microarray datasets, including 82 up-regulated genes and 273 down-regulated genes. The function and pathway enrichment of these differential genes were analyzed by DAVID data mining platform. Gene ontology (GO) enrichment analysis showed that the gene products were closely related to collagen catabolism, angiogenesis, cell adhesion and other biological processes, mainly involved in the composition of extracellular matrix, extracellular region, extracellular body, collagen trimer and other cellular components, and mainly played a role in regulating the activity of metalloendopeptidase, heparin binding, regulation of receptor activity and other molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis mainly involves extracellular matrix-receptor signal pathway, adhesion spot signal pathway, TGF-βsignal pathway, PI3K-Akt signal pathway and other related pathways. Then the protein-protein interaction (PPI) network was constructed by using STRING online database and Cytoscape software, and the most important gene modules and 10 key genes were screened. Then the prognosis was analyzed by Kaplan-Meier plotter, and the relationship between key genes and prognosis was verified and analyzed by GEPIA and THPA online database from gene and protein level. Finally, four key genes of lung adenocarcinoma (LUAD) were screened : SPP1, TIMP1, MMP9 and COL1A1. These four genes may become potential biomarkers of prognosis of lung adenocarcinoma, and may become therapeutic targets and diagnostic targets, which have certain value for clinical diagnosis and treatment of LUAD.
Key words: lung adenocarcinoma; bioinformatics; gene expression; prognosis
引用本文:
刘少博,黄 波. 基于生物信息学分析的肺腺癌诊断及预后相关基因筛选[J]. 激光生物学报, 2020, 29(5): 413-423.
LIU Shaobo, HUANG Bo. Screening of Genes Related to Diagnosis and Prognosis of Lung Adenocarcinoma Based on Bioinformatics Analysis. journal1, 2020, 29(5): 413-423.