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Related Experiment Video

Updated: Jan 13, 2026

Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

751

Integrated bioinformatics analysis of differences between EAC and ESCC.

Qi Lyu1, Yanfei Chai2,3, Wei Chen1

  • 1Hunan Normal University Health Science Center, Changsha, China.

BMC Cancer
|October 30, 2025
PubMed
Summary
This summary is machine-generated.

This study identified distinct genes for esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC). These findings offer potential biomarkers and therapeutic targets for these major esophageal cancer subtypes.

Keywords:
EACESCCImmune microenvironmentPrognosis

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Esophageal cancer (EC) comprises distinct subtypes: esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC).
  • These subtypes differ in etiology, epidemiology, tumor biology, and prognosis.
  • Identifying subtype-specific genes is crucial for targeted therapies.

Purpose of the Study:

  • To identify differentially expressed genes (DEGs) specific to EAC and ESCC.
  • To explore potential biomarkers and therapeutic targets for each subtype.
  • To analyze molecular differences between EAC and ESCC, including immune infiltration and mutations.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) for DEG identification.
  • Applied Weighted Gene Co-expression Network Analysis (WGCNA) to find subtype-associated genes.
  • Conducted Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Protein-Protein Interaction (PPI) network analysis.
  • Employed LASSO Cox regression for prognostic gene identification and analyzed immune, mutational, and drug sensitivity differences.

Main Results:

  • Identified 131 EAC-specific DEGs and 49 ESCC-specific DEGs.
  • ESCC associated with extracellular matrix (ECM), cell cycle, epithelial-mesenchymal transition (EMT), and hypoxia pathways.
  • EAC linked to metabolic alterations, particularly glycolysis and gluconeogenesis.
  • Developed a prognostic model for EAC (RHOV, SYTL1, MT1X, PRRG4, KCNK5, CCL20) and identified TUSC3 as an ESCC prognostic biomarker.
  • Revealed distinct immune, mutation, copy number variation (CNV), and drug sensitivity profiles between EAC and ESCC.

Conclusions:

  • Successfully identified pathologically specific genes for EAC and ESCC.
  • These subtype-specific genes provide insights into molecular mechanisms.
  • The findings highlight potential novel biomarkers and therapeutic targets for distinct esophageal cancer subtypes.