Transcriptomic Profiling of Epigenetic and Metabolic Genes in Human Cholangiocarcinoma

257 epigenetic genes, 96 metabolic genes, and 189 rate-limiting enzymes were examined in transcriptomic data from intrahepatic and extrahepatic cholangiocarcinoma (CCA), normal bile ducts, organoids, and tumoroids. The dataset, created by Amaya Lopez-Pascual and last updated in June 2026, integrates CRISPR-Cas9 screening data and multi-omic profiling from mouse models. It highlights genes linked to poor prognosis and tumor microenvironment subtypes.

Use Cases

• Identify prognostic biomarkers based on the 27 epigenetic and 8 metabolic genes linked to poor survival.
• Characterize tumor microenvironment subtypes based on distinct epigenetic-metabolic signatures described in the results.
• Validate candidate therapeutic targets among epigenetic regulators (e.g., CBX3, SMARCA4) and metabolic enzymes (e.g., TYMS, IDH2) using the provided CRISPR screening data.
• Investigate hypoxia-induced epigenetic programs in cancer cells as described in the methodology.

Strengths

• Integrates data from multiple sources, including human patient samples, organoids, tumoroids, and two mouse CCA models.
• Includes multi-omic profiling (transcriptomic, proteomic, metabolomic) for the TAZ/Akt mouse model.
• Links gene expression data to functional CRISPR-Cas9 DepMap screens evaluating impact on cell viability.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 7.8 MB file size suggests a relatively small dataset.

Provenance

Source

figshare

Collection Method

Transcriptomic analysis of human CCA samples, organoids, tumoroids, and mouse models, combined with CRISPR screening.

Freshness

Last updated 2026-06-04 04:30:50