HNCDB

HNCDB aggregates curated gene, drug, and expression data for head and neck cancer to enable integrative analysis of molecular associations and potential therapeutic candidates.

Key Features:

• Data scope: Aggregates information from over 2,564 gene-related publications and over 2,032 drug-related publications relevant to head and neck cancer.
• HNC GENE: Provides manually curated details for 1,173 genes associated with head and neck cancer.
• Connectivity Map: Contains manually curated interactions between HNC-related genes and a set of 176 drugs to explore potential influences on gene expression.
• ANALYSIS: Offers analytical modules for correlation studies, differential expression analysis, and survival analysis on high-throughput gene expression data.
• Dataset coverage: Supports analysis across 2,403 samples from 78 distinct head and neck cancer gene expression datasets.
• Curation methods: Integrates text mining with manual curation to extract and validate gene and drug associations from the literature.

Scientific Applications:

• Therapeutic prioritization: Prioritizes candidate drugs and gene–drug interactions for further experimental validation in head and neck cancer.
• Biomarker discovery: Identifies potential diagnostic, prognostic, or predictive biomarkers through differential expression and survival analyses.
• Mechanistic investigation: Enables investigation of molecular relationships and co-expression patterns among HNC-associated genes across multiple datasets.

Methodology:

Integration of text mining and manual curation of literature (over 2,564 gene-related and over 2,032 drug-related publications); manual curation to derive gene–drug connections; and provision of correlation, differential expression, and survival analyses on 2,403 samples from 78 HNC gene expression datasets.