ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for...

Area of Science:

• Oncology
• Bioinformatics
• Genomics

Background:

• Esophageal cancer is a major global health burden, with esophageal squamous cell carcinoma (ESCC) being the predominant subtype.
• The complex molecular mechanisms underlying ESCC progression remain incompletely understood, hindering effective treatment strategies.

Purpose of the Study:

• To develop and present ESCCdb, an integrated database for comprehensive analysis of ESCC molecular alterations.
• To facilitate exploration of gene expression, copy number variations, somatic mutations, and drug-target relationships in ESCC.

Main Methods:

• Integrated 56 datasets from GEO, Xena, and SRA, along with published literature.
• Developed interactive tools for visualizing gene expression, copy number alterations, somatic mutations, and drug-gene interactions.
• Performed survival analysis and whole-genome CRISPR/Cas9 screening analysis.

Main Results:

• Identified 789 consistently differentially expressed genes in ESCC.
• Summarized recurrently mutated genes and genes with significant copy number alterations.
• ESCCdb enables cross-dataset comparisons and exploration of gene correlations and regulatory networks.

Conclusions:

• ESCCdb provides a valuable resource for researchers to explore ESCC molecular data and identify potential biomarkers and therapeutic targets.
• The integrated analysis capabilities of ESCCdb can accelerate basic and clinical research in esophageal squamous cell carcinoma.
• The database facilitates the assessment of clinical relevance and functional inferences for identified genes.