Supplementary File 1: HCC Transcriptomics and Drug Discovery Analysis

Pan Li authored a dataset supporting a study on hepatocellular carcinoma (HCC) biomarkers and therapeutic targets, last updated on 2026-05-07. The data underpins a comparative transcriptomic analysis of 724 HCC samples from four international cohorts. It includes results from differential expression, survival analysis, and computational drug screening targeting the ASPM gene.

Use Cases

• Identifying prognostic biomarkers for hepatocellular carcinoma based on multi-cohort transcriptomic analysis.
• Conducting computational drug discovery and molecular docking studies targeting the ASPM calponin domain.
• Performing functional enrichment analysis to explore biological roles of overexpressed genes in cancer pathways.
• Validating potential therapeutic compounds through in silico ADMET and pharmacokinetic property profiling.

Strengths

• Data is derived from 724 HCC samples across four independent international cohorts.
• Analysis includes 100-ns molecular dynamics simulations and MM-GBSA binding energy calculations.
• Dataset is openly shared under a CC-BY-4.0 license.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary data file is a 3.1 MB DOCX document, which may require parsing to extract structured data.

Provenance

Source

figshare, author Pan Li.

Collection Method

Comparative transcriptomic analysis and computational drug discovery.

Freshness

Last updated 2026-05-07 04:47:18; freshness should be verified.

Geography

Samples from cohorts in the United States, South Korea, France, and Taiwan.