Abstract：ObjectiveTo explore the potential key genes of lung adenocarcinoma (LUAD) and their diagnostic and prognostic value. MethodsWe downloaded the ChIP data (GSE10072,GSE32867,GSE43458) from the GEO database, and analyzed these data using online tool GEO2R to obtain the differentially expressed genes (DEGs) between cancer tissues and normal tissues. These DEGs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We used the STRING database to build a protein-protein interaction (PPI) network, then ranked the genes by the descending order of the links between proteins, finally the top 8 genes were considered as the key genes. The expression profile, prognosis, and the tumor mutation burden (TMB) were analyzed using R (4.0.0). ResultsA total of 240 genes differentially expressed among three ChIP data were screened out, and the GO outcome showed that these DEGs mainly concentrated in cell adhesion and drug resistance. Cytological components were mainly located in cytoplasm, cell membrane, and extracellular exosome. The molecular function was enriched in calcium ion binding. KEGG signaling pathway analysis showed that the DEGs were mainly involved in PI3K/AKT/MAPK pathway. The 8 genes all expressed differentially between tumor and normal tissues, and patients with higher expression of CDC20, TIMP1, CCNB2, KIAA0101 and TOP2A had worse overall surviver (OS) than the patients with lower expression (all P＜0.01). What's more, the key genes also affect the immune infiltration in the tumor, and the expression levels of CCNB2 （r=0.43）, CDC20（r=0.46）, GNG11（r=-0.11）, KIAA0101（r=0.32）, TIMP1（r=-0.10）, TOP2A（r=0.43） were associated with the TMB (all P＜0.05). ConclusionThere are DEGs in patients with LUAD, a part of these key genes may be involved in the occurrence, development, metastasis, invasion, and drug resistance of LUAD cells and other biological functions, and are expected to become potential markers for individualized diagnosis and prognostic evaluation of LUAD.
汪昕 周燕斌 陈思民 邱艳丽 王帅帅 邓佳婷. 基于生物信息学筛选肺腺癌诊断与预后的关键基因[J]. 中华诊断学电子杂志, 2021, 9(2): 114-120.
Wang Xin, Zhou Yanbin, Chen Simin, Qiu Yanli, Wang Shuaishuai. Identification of key genes for diagnosis and prognosis of lung adenocarcinoma based on bioinformatics. zhzdx, 2021, 9(2): 114-120.
