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通过生物信息学分析鉴定与肺癌相关的基因。

Identification of genes associated with lung cancer by bioinformatics analysis.

作者信息

Li J, Yu H, Ma Y-F, Zhao M, Tang J

机构信息

Department of Thoracic Surgery, General Hospital of People's Liberation Army, Beijing, China.

出版信息

Eur Rev Med Pharmacol Sci. 2017 May;21(10):2397-2404.

PMID:28617549
Abstract

OBJECTIVE

This study was aimed to explore the underlying genes associated with lung cancer (LC) by bioinformatics analysis.

DATA AND METHODS

Gene expression profile GSE2514 was downloaded from the Gene Expression Omnibus database. Twenty lung and nineteen para-carcinoma tissue samples were used to identify the differentially expressed genes (DEGs) by paired t-test. Pathway enrichment analysis of DEGs was performed, followed by the construction of protein-protein interaction (PPI) network. Functional enrichment analysis of the module identified from PPI network was performed, and the enriched term with the highest enrichment scores was selected for pathway enrichment analysis.

RESULTS

Total 257 DEGs including 179 up-regulated DEGs such as monoamine oxidase A (MAOA) and intercellular adhesion molecule 2 (ICAM2), and 78 down-regulated DEGs such as thrombospondin-2 (THBS2) were identified. Up-regulated DEGs were enriched in 7 pathways, such as drug metabolism, tyrosine metabolism and cell adhesion molecules (CAMs). Down-regulated DEGs were enriched in extracellular cell matrix receptor interaction and focal adhesion pathways. In the PPI network, interleukin-6 (IL6) had the highest connectivity degree of 39. Module 1 with the highest functional enrichment scores of 5.457 containing 13 hub genes such as KIAA0101.

CONCLUSIONS

DEGs of LC were mainly enriched in the pathways related to metabolism and cell adhesion. The DEGs such as MAOA, ICAM2, IL6, THBS2 and KIAA0101 may be the potential targets for LC diagnosis and treatment.

摘要

目的

本研究旨在通过生物信息学分析探索与肺癌(LC)相关的潜在基因。

数据与方法

从基因表达综合数据库下载基因表达谱GSE2514。使用20个肺组织样本和19个癌旁组织样本,通过配对t检验鉴定差异表达基因(DEG)。对DEG进行通路富集分析,随后构建蛋白质-蛋白质相互作用(PPI)网络。对从PPI网络中识别出的模块进行功能富集分析,并选择富集分数最高的富集术语进行通路富集分析。

结果

共鉴定出257个DEG,其中包括179个上调的DEG,如单胺氧化酶A(MAOA)和细胞间粘附分子2(ICAM2),以及78个下调的DEG,如血小板反应蛋白2(THBS2)。上调的DEG富集于7条通路,如药物代谢、酪氨酸代谢和细胞粘附分子(CAM)。下调的DEG富集于细胞外细胞基质受体相互作用和粘着斑通路。在PPI网络中,白细胞介素-6(IL6)的连接度最高,为39。模块1的功能富集分数最高,为5.457,包含13个中心基因,如KIAA0101。

结论

LC的DEG主要富集于与代谢和细胞粘附相关的通路。MAOA、ICAM2、IL6、THBS2和KIAA0101等DEG可能是LC诊断和治疗的潜在靶点。

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