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通过整合微阵列分析鉴定非小细胞肺癌中的新型生物标志物和候选小分子药物。

Identification of novel biomarkers and candidate small molecule drugs in non-small-cell lung cancer by integrated microarray analysis.

作者信息

Wu Qiong, Zhang Bo, Sun Yidan, Xu Ran, Hu Xinyi, Ren Shiqi, Ma Qianqian, Chen Chen, Shu Jian, Qi Fuwei, He Ting, Wang Wei, Wang Ziheng

机构信息

Medical School of Nantong University, Nantong 226001, People's Republic of China.

The Hand Surgery Research Center, Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong 226001, People's Republic of China.

出版信息

Onco Targets Ther. 2019 May 13;12:3545-3563. doi: 10.2147/OTT.S198621. eCollection 2019.

Abstract

Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC. The microarray datasets of GSE18842, GSE30219, GSE31210, GSE32863 and GSE40791 from Gene Expression Omnibus database were downloaded. The differential expressed genes (DEGs) between NSCLC and normal samples were identified by limma package. The construction of protein-protein interaction (PPI) network, module analysis and enrichment analysis were performed using bioinformatics tools. The expression and prognostic values of hub genes were validated by GEPIA database and real-time quantitative PCR. Based on these DEGs, the candidate small molecules for NSCLC were identified by the CMap database. A total of 408 overlapping DEGs including 109 up-regulated and 296 down-regulated genes were identified; 300 nodes and 1283 interactions were obtained from the PPI network. The most significant biological process and pathway enrichment of DEGs were response to wounding and cell adhesion molecules, respectively. Six DEGs (PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5) which significantly up-regulated in NSCLC tissues, were selected as hub genes according to the results of module analysis. The GEPIA database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. Additionally, CMap predicted the 20 most significant small molecules as potential therapeutic drugs for NSCLC. DL-thiorphan was the most promising small molecule to reverse the NSCLC gene expression. Based on the gene expression profiles of 696 NSCLC samples and 237 normal samples, we first revealed that PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5 could act as the promising novel diagnostic and therapeutic targets for NSCLC. Our work will contribute to clarifying the molecular mechanisms of NSCLC initiation and progression.

摘要

非小细胞肺癌(NSCLC)仍然是全球癌症发病率和死亡率的主要原因。在本研究中,我们鉴定了与NSCLC发病机制相关的新型生物标志物,旨在为NSCLC提供新的诊断和治疗方法。从基因表达综合数据库下载了GSE18842、GSE30219、GSE31210、GSE32863和GSE40791的微阵列数据集。使用limma软件包鉴定NSCLC与正常样本之间的差异表达基因(DEG)。使用生物信息学工具进行蛋白质-蛋白质相互作用(PPI)网络构建、模块分析和富集分析。通过GEPIA数据库和实时定量PCR验证枢纽基因的表达和预后价值。基于这些DEG,通过CMap数据库鉴定NSCLC的候选小分子。共鉴定出408个重叠DEG,包括109个上调基因和296个下调基因;从PPI网络获得300个节点和1283个相互作用。DEG最显著的生物学过程和通路富集分别是对伤口的反应和细胞粘附分子。根据模块分析结果,选择在NSCLC组织中显著上调的6个DEG(PTTG1、TYMS、ECT2、COL1A1、SPP1和CDCA5)作为枢纽基因。GEPIA数据库进一步证实,这些枢纽基因表达水平较高的患者总生存期较短。此外,CMap预测了20个最显著的小分子作为NSCLC的潜在治疗药物。DL-硫代苯丙氨酸是最有希望逆转NSCLC基因表达的小分子。基于696个NSCLC样本和237个正常样本的基因表达谱,我们首次揭示PTTG1、TYMS、ECT2、COL1A1、SPP1和CDCA5可作为NSCLC有前景的新型诊断和治疗靶点。我们的工作将有助于阐明NSCLC发生和发展的分子机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a4c3/6526173/cc28bbf08863/OTT-12-3545-g0001.jpg

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