Analysis of core genes and pathways in esophageal adenocarcinoma by bioinformatics

Li Changbo

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Analysis of core genes and pathways in esophageal adenocarcinoma by bioinformatics

更新时间：2023-04-16

- Analysis of core genes and pathways in esophageal adenocarcinoma by bioinformatics
- Journal of Chongqing Medical University Vol. 47, Issue 12, Pages: 1490-1495(2022)
- 作者机构：
  
  广西医科大学第七附属医院心胸外科,梧州,543000
- 作者简介：
- 基金信息：
- DOI：
  CLC： R735.1
- Published：2022，
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Li Changbo. Analysis of core genes and pathways in esophageal adenocarcinoma by bioinformatics. [J]. Journal of Chongqing Medical University 47(12):1490-1495(2022)
DOI：

Li Changbo. Analysis of core genes and pathways in esophageal adenocarcinoma by bioinformatics. [J]. Journal of Chongqing Medical University 47(12):1490-1495(2022) DOI：

摘要

目的：探讨食管腺癌（esophageal adenocarcinoma，EAC）的核心基因及通路。方法：结合GEO数据库分析EAC与正常食管组织间的差异表达基因。利用多种在线分析软件对中枢基因进行功能富集、通路分析、构建蛋白质互作网络及挑选核心基因。结合TCGA、Oncomine肿瘤数据库对核心基因进行验证以及绘制受试者工作特征（receiver operating characteristic，ROC）曲线、计算曲线下面积（area under the curve，AUC）。结果： 4个GEO数据集分析得出中枢基因共141个，富集在细胞外基质中，主要通过糖酵解、糖异生通路和酪氨酸、组氨酸、苯丙氨酸、β-丙氨酸代谢通路。筛选出3个核心基因，COL1A2的AUC为0.707~0.954；TIMP1的AUC为0.795~0.984；MMP1的AUC为0.896~1.000。结论：利用生物信息学方法筛选出与EAC相关的核心基因及通路，有助于EAC的早期分子诊断与基因靶向治疗。

Abstract

Objective: To explore the core genes and pathways of esophageal adenocarcinoma (EAC). Methods: The differentially expressed genes between EAC tissue and normal esophageal tissue were analyzed with GEO database. A variety of online analysis software were used for functional enrichment

pathway analysis

construction of protein-protein interaction network

and selection of core genes. Combined with TCGA and Oncomine database

the core genes were verified

the ROC curves were drawn and the area under the curve (AUC) was calculated. Results: A total of 141 core genes were obtained from 4 GEO datasets

which were mainly enriched in the extracellular matrix

mainly in glycolysis/gluconeogenesis pathways

and tyrosine

histidine

phenylalanine and β-alanine metabolic pathways. COL1A2

TIMP1 and MMP1 were screened out in TCGA and Oncomine databases. The AUC of COL1A2 was 0.707-0.954

that of TIMP1 was 0.795-0.984

and that of MMP1 is 0.896-1.000. Conclusion: Screening out core genes and pathways related to EAC by bioinformatics is helpful for early molecular diagnosis and gene targeted therapy of EAC.

关键词

食管腺癌生物信息学差异表达基因诊断

Keywords

esophageal adenocarcinomabioinformaticsdifferentially expressed genediagnosis

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Related Institution

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