Hui Yu published a dataset on 2026-03-18 containing a four-gene risk signature for bladder cancer prognosis. The data is derived from the analysis of 359 bladder cancer samples and includes molecular subtypes, risk scores, and gene expression patterns related to fatty acid metabolism. The dataset is stored in a 138.3 KB CSV file under a CC-BY-4.0 license.
Use Cases
- Predicting patient prognosis based on the four-gene FAMR signature (PATZ1, TTC6, AEBP1, MAOA).
- Classifying bladder cancer into molecular subtypes (C1 and C2) for risk stratification.
- Investigating correlations between FAMR scores and clinical features like patient age, sex, and tumor stage.
- Analyzing the relationship between fatty acid metabolism pathways and immune infiltration in bladder cancer.
Strengths
- The prognostic model was validated using internal and external cohorts, as stated in the description.
- Analysis includes single-cell RNA sequencing data to explore cell-type-specific gene expression.
- Findings are supported by in vitro functional experiments on bladder cancer cell lines.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset's 138.3 KB size suggests a limited scope, likely containing summary or signature data rather than raw expression matrices.
Provenance
- Source
- Hui Yu via figshare
- Collection Method
- Analysis of 359 bladder cancer samples, with validation using additional cohorts.
- Freshness
- Last updated 2026-03-18 07:35:20; freshness should be verified.