Transcriptomic Profiling of Epigenetic and Metabolic Genes in Human Cholangiocarcinoma

Amaya Lopez-Pascual's dataset contains transcriptomic profiling data for epigenetic and metabolic genes in cholangiocarcinoma (CCA). It includes expression data for 257 epigenetic genes, 96 metabolic genes, and 189 rate-limiting enzymes from human iCCA, eCCA, normal bile ducts, organoids, and tumoroids, alongside CRISPR-Cas9 DepMap data. The dataset 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.
• Analyze tumor microenvironment subtypes based on distinct epigenetic-metabolic signatures described in the results.
• Investigate hypoxia-induced epigenetic programs in cancer cells using the described HuCCT-1 cell line data.
• Validate essential genes for cancer cell viability using the CRISPR screen results highlighting 50 epigenetic and 23 metabolic genes.

Strengths

• Includes data on a specific set of 257 epigenetic genes, 96 metabolic genes, and 189 rate-limiting enzymes.
• Integrates multiple data sources, including human transcriptomic data, CRISPR-Cas9 DepMap screens, and multi-omic profiling from mouse models.
• Links gene expression changes to clinical outcomes, identifying 35 genes whose overexpression predicts poor survival.

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 (465.3 KB), suggesting it contains processed summary data rather than raw sequencing reads.

Provenance

Source

figshare

Collection Method

Transcriptomic analysis of human CCA samples, organoids, tumoroids, and mouse models, combined with CRISPR-Cas9 functional screens.

Freshness

Last updated 2026-06-04 04:30:48; freshness should be verified.