Data Sheet 1_Multi-omics integration and experimental validation reveal the mechanism of b

A research dataset containing 182 common targets of berberine and triple-negative breast cancer (TNBC), with 12 identified hub genes including SRC, STAT3, and EGFR. The data was generated by Ying Zhang and integrates network pharmacology, transcriptomic analysis from GEO and TCGA, molecular docking, dynamics simulation, and in vitro cellular experiments. It was last updated on May 28, 2026.

Use Cases

• Identify potential drug targets for natural compounds based on the 182 common targets identified between berberine and TNBC.
• Validate molecular docking predictions using the reported binding affinity of -8.8 kcal/mol for BBR with SRC.
• Analyze tumor microenvironment characteristics based on the immune infiltration and single-cell sequencing data described in the study.
• Investigate pathways involved in cancer cell proliferation and stemness based on the downregulation of p-PI3K/p-AKT and p-SRC/p-STAT3 pathways mentioned.

Strengths

• Identifies 182 common targets and 12 hub genes, providing a specific multi-target profile.
• Integrates multiple analysis methods including network pharmacology, transcriptomics, molecular docking, and in vitro validation.
• Includes specific experimental results such as a molecular docking score of -8.8 kcal/mol for BBR-SRC interaction.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small in size (310.6 KB), suggesting limited scope or summary-level data.

Provenance

Source

Ying Zhang via figshare.

Collection Method

Integrated strategy combining network pharmacology, transcriptomic analysis (GEO, TCGA), molecular docking, dynamics simulation, and in vitro experiments.

Freshness

Last updated 2026-05-28 08:14:03; freshness should be verified.