TRPM4 in Bladder Cancer: Prognostic Gene Risk Model and Drug Sensitivity

A 22.8 KB Excel file by Qi Zhao, last updated April 13, 2026, containing bioinformatics analysis results for bladder cancer. The dataset includes a risk model built from six prognostic genes and lists 220 candidate genes, 12 immune cell types, and 112 drugs with differential sensitivity identified through integrated single-cell and transcriptome analyses.

Use Cases

• Validate the six-gene prognostic risk model (UNC93B1, FAM193B, POGLUT3, FBN1, MAP1B, RUNX2) for bladder cancer patient stratification.
• Analyze candidate gene lists (220 genes from intersection analysis) for functional studies in bladder cancer.
• Investigate associations between TRPM4 expression and immune infiltration based on the 12 identified immune cell types.
• Screen for drug sensitivity using the list of 112 drugs with differential responses, such as WZ3105.

Strengths

• Includes a validated six-gene prognostic risk model for bladder cancer.
• Lists 220 candidate genes, 12 immune cell types, and 112 drugs from a structured bioinformatics pipeline.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The 22.8 KB file size suggests a limited, summary-level dataset rather than raw expression data.
• Data may reflect analytical bias inherent to the specific study's methodology and source data.

Provenance

Source

figshare, author Qi Zhao.

Collection Method

Integrated analysis of single-cell and whole-genome transcriptomic data.

Time Range

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Freshness

Last updated 2026-04-13 05:21:44.

Geography

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