Transcriptomic Profiling of Epigenetic and Metabolic Genes in Human Cholangiocarcinoma

A transcriptomic dataset profiling 257 epigenetic genes, 96 metabolic genes, and 189 rate-limiting enzymes in human cholangiocarcinoma (iCCA, eCCA) and normal tissues. The data, authored by Amaya Lopez-Pascual and shared on figshare under CC-BY-4.0, includes CRISPR-Cas9 DepMap viability screens and analyses of tumor microenvironment subtypes. It was last updated on June 4, 2026.

Use Cases

• Identify prognostic biomarkers based on the 27 epigenetic and 8 metabolic genes linked to poor survival.
• Investigate tumor microenvironment subtypes using transcriptomic deconvolution of epigenetic-metabolic signatures.
• Validate essential genes for cancer cell viability using CRISPR-Cas9 DepMap screening data on 50 epigenetic and 23 metabolic genes.
• Study hypoxia-induced epigenetic programs in cancer cells based on experiments with HuCCT-1 cells.
• Analyze multi-omic pathway rewiring (nucleotide, one-carbon, lipid, mitochondrial) using integrated mouse model data.

Strengths

• Profiles a defined set of 257 epigenetic genes, 96 metabolic genes, and 189 rate-limiting enzymes.
• Integrates data from multiple sources including human patient samples, organoids, tumoroids, CRISPR screens, and mouse models.
• Includes functional validation data from CRISPR-Cas9 DepMap screens assessing gene essentiality.

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 18.1 MB DOCX document, which may require format conversion for computational analysis.

Provenance

Source

figshare

Collection Method

Transcriptomic analysis of human cholangiocarcinoma samples, organoids, tumoroids, and mouse models, supplemented by CRISPR-Cas9 DepMap screens.

Freshness

Last updated 2026-06-04 04:30:51; freshness should be verified.