Screening of Key Prognosis Genes of Lung Adenocarcinoma Based on Expression Analysis on TCGA Database

作者全名："Shen, Youfeng; Tang, Xiaoqing; Zhou, Xiaoqin; Yi, Yuanxue; Qiu, Yuan; Xu, Jian; Tian, Xingzhong"

作者地址："[Shen, Youfeng; Yi, Yuanxue; Xu, Jian] Chongqing Precis Med Ind Technol Res Inst, Chongqing 400000, Peoples R China; [Tang, Xiaoqing; Zhou, Xiaoqin] Nanan Peoples Hosp, Dept Lab Med, Chongqing 400060, Peoples R China; [Qiu, Yuan] Kaizhou Dist Peoples Hosp, Dept Lab Med, Chongqing 405400, Peoples R China; [Xu, Jian] Chongqing Med Univ, Coll Lab Med, Chongqing 400000, Peoples R China; [Tian, Xingzhong] Fifth Hosp Zhangjiakou, Hebei, Peoples R China"

通信作者："Xu, J (通讯作者)，Chongqing Precis Med Ind Technol Res Inst, Chongqing 400000, Peoples R China.; Xu, J (通讯作者)，Chongqing Med Univ, Coll Lab Med, Chongqing 400000, Peoples R China.; Tian, XZ (通讯作者)，Fifth Hosp Zhangjiakou, Hebei, Peoples R China."

来源：JOURNAL OF ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000910992300001

JCR分区：Q2

影响因子：4.501

年份：2022

卷号：2022

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：　

摘要："Objective. The data of lung adenocarcinoma- (LUAD-) related gene expression profiles were mined from the Cancer Genome Atlas (TCGA) database using bioinformatics methods and potential biomarkers related to the occurrence, development, and prognosis of LUAD were screened out to explore the key prognostic genes and clinical significance. Methods. Following the LUAD gene expression profile data that were initially exported from the TCGA database, R software DESeq2 was employed to analyze the difference between the expression profiles of LUAD and normal tissues. The R package ""clusterProfiler "" was subsequently utilized to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the differential genes. A protein-protein interaction (PPI) network was constructed via the String database, and cytohubba, a plugin of Cytoscape, was applied to screen hub genes using the MCC algorithm. The Gene Expression Profile Data Interactive Analysis (GEPIA) was used to analyze expressions of 10 candidate genes in LUAD samples and healthy lung samples, and the selected genes were employed for survival analysis. Results. A total of 1,598 differential genes were identified through differential analyses and data mining, with 1,394 genes upregulated and 204 downregulated. A total of 10 hub genes CCNA2, CDC20, CCNB2, KIF11, TOP2A, BUB1, BUB1B, CENPF, TPX2, and KIF2C were obtained using the cytohubba plugin. The results of the GEPIA analysis indicated that compared with normal lung tissue, the mRNA expression level of the described hub genes in LUAD tissue was significantly increased (P < 0.05). Survival analysis revealed that these genes had a significant impact on the overall survival time of LUAD patients (P < 0.05). Conclusion. The previously described key genes related to LUAD identified in the TCGA database may be used as potential prognostic biomarkers, which will contribute to further comprehension of the occurrence and development of LUAD and provide references for its diagnosis and treatment."

基金机构：2019 Municipal Science and Technology plan project [1921080D]

基金资助正文：This study is self funded by the 2019 Municipal Science and Technology plan project (1921080D).