Identification of key candidate genes associated with prognosis of lung adenocarcinoma by integrated bioinformatical analysis

Abstract

Background: Lung adenocarcinoma (LUAD) is the most frequent histologic type of lung cancer and the morbidity of LUAD is increasing rapidly in the worldwide. But the mechanism of LUAD is still largely unknown. Methods: In this study, we analyzed three microarrays of gene expression profiles, containing 196 LUAD samples and 137 normal samples, to explore the potential key candidate genes in LUAD by integrated bioinformatical analysis. Results: A total of 240 shared differentially expressed genes (DEGs) were identified and pathways enrichment were analyzed. DEGs-associated protein-protein interaction (PPI) network was constructed and top 20 hub genes were established by calculating the degree of connectivity. We further validated these genes in TCGA and GTEx projects, and found all of these hub genes were differentially expressed in LUAD patients except TIMP1 and FOS. In these candidate genes, ten genes (TPX2, CENPF, TYMS, PRC1, NEK2, CCNB2, KIAA0101, CDC20, TOP2A and SPP1) were confirmed to associate with the prognosis of LUAD. Out of these ten genes, CENPF had the highest genetic alteration at a rate of 4% in LUAD patients, and the expression of CENPF was significantly increased in different subgroups of all age, gender, race, smoking condition and cancer stage groups of LUAD patients. Conclusions: Our study contributes to comprehend the role of genes in LUAD and provides possible therapeutic targets for further clinical application.