Wang Luyao, Li Shicheng, Wang Yuanyong, Tang Zhenxue, Liu Chaolong, Jiao Wenjie, Liu Jia
Department of Pharmacology, School of Pharmacy, Qingdao University, Qingdao, Shandong 266000, P.R. China.
Department of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China.
Exp Ther Med. 2020 Feb;19(2):1103-1111. doi: 10.3892/etm.2019.8300. Epub 2019 Dec 6.
Lung adenocarcinoma accounts for a high proportion of lung cancers. Though efforts have been made to develop new and effective treatments for this disease, the mortality rate remains high. Gene expression microarrays facilitate the study of lung cancer at the molecular level. The present study aimed to detect differentially expressed protein-coding genes to identify novel biomarkers and therapeutic targets for lung adenocarcinoma. Aberrations in gene expression in lung adenocarcinoma were determined by analysis of mRNA microarray datasets from the Gene Expression Omnibus database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) networks and statistical analysis were used to identify the biological functions of the differentially expressed genes (DEGs). The results of the bioinformatics analysis were subsequently validated using reverse transcription-quantitative PCR. A total of 303 DEGs were identified in lung adenocarcinomas, and they were enriched in a number of cancer-associated GO terms and KEGG pathways. DNA topoisomerase 2α (TOP2A), cell division cycle protein homolog 20 (CDC20), mitotic checkpoint serine/threonine protein kinase BUB1 (BUB1) and mitotic spindle assembly checkpoint protein MAD2A (MAD2L1) exhibited the highest degree of interaction in the PPI network. Survival analysis performed using Kaplan-Meier curves and Cox regression indicated that these four genes were all significantly associated with the survival of patients with lung adenocarcinomas. In conclusion, TOP2A, CDC20, BUB1 and MAD2L1 may be key protein-coding genes that may serve as biomarkers and therapeutic targets in lung adenocarcinomas.
肺腺癌在肺癌中占比很高。尽管人们已努力开发针对该疾病的新型有效治疗方法，但死亡率仍然很高。基因表达微阵列有助于在分子水平上研究肺癌。本研究旨在检测差异表达的蛋白质编码基因，以鉴定肺腺癌的新型生物标志物和治疗靶点。通过分析来自基因表达综合数据库的mRNA微阵列数据集，确定肺腺癌中的基因表达异常。使用基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析、蛋白质-蛋白质相互作用（PPI）网络和统计分析来鉴定差异表达基因（DEG）的生物学功能。随后使用逆转录定量PCR对生物信息学分析结果进行验证。在肺腺癌中总共鉴定出303个DEG，它们在许多与癌症相关的GO术语和KEGG通路中富集。DNA拓扑异构酶2α（TOP2A）、细胞分裂周期蛋白同源物20（CDC20）、有丝分裂检查点丝氨酸/苏氨酸蛋白激酶BUB1（BUB1）和有丝分裂纺锤体组装检查点蛋白MAD2A（MAD2L1）在PPI网络中表现出最高程度的相互作用。使用Kaplan-Meier曲线和Cox回归进行的生存分析表明，这四个基因均与肺腺癌患者的生存显著相关。总之，TOP2A、CDC20、BUB1和MAD2L1可能是关键的蛋白质编码基因，可作为肺腺癌的生物标志物和治疗靶点。
