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利用生物信息学分析,AURKA、CDC20 和 TPX2 的 mRNA 水平升高与吸烟相关肺腺癌的不良预后相关。

Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.

机构信息

Department of Respiratory Medicine, Qilu Hospital of Shandong University, Jinan 250012, China.

出版信息

Int J Med Sci. 2018 Nov 5;15(14):1676-1685. doi: 10.7150/ijms.28728. eCollection 2018.

DOI:10.7150/ijms.28728
PMID:30588191
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6299412/
Abstract

Adenocarcinoma is a very common pathological subtype for lung cancer. We aimed to identify the gene signature associated with the prognosis of smoking related lung adenocarcinoma using bioinformatics analysis. A total of five gene expression profiles (GSE31210, GSE32863, GSE40791, GSE43458 and GSE75037) have been identified from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using GEO2R software and functional and pathway enrichment analysis. Furthermore, the overall survival (OS) and recurrence-free survival (RFS) have been validated using an independent cohort from the Cancer Genome Atlas (TCGA) database. We identified a total of 58 DEGs which mainly enriched in ECM-receptor interaction, platelet activation and PPAR signaling pathway. Then according to the enrichment analysis results, we selected three genes ( and ) for their roles in regulating tumor cell cycle and cell division. The results showed that the hazard ratio (HR) of the mRNA expression of for OS was 1.588 with (1.127-2.237) 95% confidence interval (CI) (P=0.009). The mRNA levels of (HR 1.530, 95% CI 1.086-2.115, P=0.016) and (HR 1.777, 95%CI 1.262-2.503, P=0.001) were also significantly associated with the OS. Expression of these three genes were not associated with RFS, suggesting that there might be many factors affect RFS. The mRNA signature of AURKA, CDC20 and TPX2 were potential biomarkers for predicting poor prognosis of smoking related lung adenocarcinoma.

摘要

腺癌是肺癌中非常常见的一种病理亚型。我们旨在通过生物信息学分析鉴定与吸烟相关的肺腺癌预后相关的基因特征。从基因表达综合数据库(GEO)中确定了五个基因表达谱(GSE31210、GSE32863、GSE40791、GSE43458 和 GSE75037)。使用 GEO2R 软件分析差异表达基因(DEGs),并进行功能和通路富集分析。此外,使用癌症基因组图谱(TCGA)数据库中的独立队列验证总生存期(OS)和无复发生存期(RFS)。我们共鉴定出 58 个 DEGs,这些基因主要富集在 ECM-受体相互作用、血小板激活和 PPAR 信号通路中。然后根据富集分析结果,我们选择了三个基因(和),因为它们在调节肿瘤细胞周期和细胞分裂方面发挥作用。结果表明,OS 中 mRNA 表达的风险比(HR)为 1.588,95%置信区间(CI)为(1.127-2.237)(P=0.009)。mRNA 水平的(HR 1.530,95%CI 1.086-2.115,P=0.016)和(HR 1.777,95%CI 1.262-2.503,P=0.001)也与 OS 显著相关。这三个基因的表达与 RFS 无关,这表明可能有许多因素影响 RFS。AURKA、CDC20 和 TPX2 的 mRNA 特征可能是预测吸烟相关肺腺癌不良预后的潜在生物标志物。

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