Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database

An-Yi Song; Lan Mu; Xiao-Yong Dai; Li-Jun Wang; Lai-Qiang Huang

doi:10.24920/004148

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Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database

Chinese Medical Sciences Journal Vol. 38, Issue 1, Pages: 20-28(2023)

Original Article | Updated：2024-03-30

- Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database
- Affiliations：
  
  1. 1The Shenzhen Key Laboratory of Gene and Antibody Therapy, State Key Laboratory of Chemical Oncogenomics, Tsinghua-Berkeley Shenzhen Institute (TBSI), Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, Guangdong Province, China
  2. 2Department of Chemistry, Tsinghua University, Beijing 100084, China
- Author bio：
- Funds：
- DOI：10.24920/004148
  CLC：
- Received：01 August 2022，
  
  Accepted：2023-1-28，
  
  Published Online：01 March 2023，
  
  Published：31 March 2023
- Accepted：
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An-Yi Song, Lan Mu, Xiao-Yong Dai, et al. Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database[J]. Chinese medical sciences journal, 2023, 38(1): 20-28.
DOI：

An-Yi Song, Lan Mu, Xiao-Yong Dai, et al. Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database[J]. Chinese medical sciences journal, 2023, 38(1): 20-28. DOI： 10.24920/004148.

摘要

目的

基于GEO数据库，通过分析癌症组织的高表达基因，筛选用于免疫治疗的抗原靶点，并通过富集分析、PPI网络和生存分析等方法，探讨癌症相关的关键通路和分子机制。

方法

通过筛选高表达基因，借助于TMHMM和IEDB平台，分析蛋白质的跨膜域和抗原表位。基于富集分析、PPI网络和生存分析的方法，对癌症发展相关的基因和信号通路进行分析。分析和绘图涉及的软件和平台包括Prism 8、R语言、Cytoscape、DAVID、STRING和GEPIA网站等。

结果

MUC13

和

EPCAM

基因在食管癌组织中高表达，并具有多个抗原识别位点。根据富集分析的结果，一系列基因与角质化过程相关。生存分析结果表明，基因

ALDH3A1

、

SLC6A1

和

ZBTB7C

的生存曲线具有显著差异性。

结论

MUC13

和

EPCAM

可能作为食管癌免疫治疗的抗原靶点和生物标志物。角质化过程可能在食管癌的发生发展过程中发挥重要作用。基因ALDH3A1

SLC6A1和ZBTB7C可能与食管癌患者生存周期密切相关。

Abstract

Objective

To screen antigen targets for immunotherapy by analyzing over-expressed genes

and to identify significant pathways and molecular mechanisms in esophageal cancer by using bioinformatic methods such as enrichment analysis

protein-protein interaction (PPI) network

and survival analysis based on the Gene Expression Omnibus (GEO) database.

Methods

By screening with highly expressed genes

we mainly analyzed proteins MUC13 and EPCAM with transmembrane domain and antigen epitope from TMHMM and IEDB websites. Significant genes and pathways associated with the pathogenesis of esophageal cancer were identified using enrichment analysis

PPI network

and survival analysis. Several software and platforms including Prism 8

R langu

age

Cytoscape

DAVID

STRING

and GEPIA platform were used in the search and/or figure creation.

Results

Genes

MUC13

and

EPCAM

were over-expressed with several antigen epitopes in esophageal squamous cell carcinoma (ESCC) tissue. Enrichment analysis revealed that the process of keratinization was focused and a series of genes were related with the development of esophageal cancer. Four genes including

ALDH3A1

SLC6A1

and

ZBTB7C

were screened with significant

value of survival curve.

Conclusions

Genes

MUC13

and

EPCAM

may be promising antigen targets or biomarkers for esophageal cancer. Keratinization may greatly impact the pathogenesis of esophageal cancer. Genes

ALDH3A1

SLC6A1

and

ZBTB7C

may play important roles in the development of esophageal cancer.

关键词

Keywords

references

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