Bladder Cancer Amino Acid Metabolism Genes and Prognostic Model

Data Sheet 3_A systematic characterization of amino acid metabolism–related genes reveals molecular subtypes and a prognostic signature in bladder cancer.xlsx contains results from a multi-cohort bioinformatics study. The dataset includes 144 dysregulated amino acid metabolism–related genes, two defined metabolic subtypes, and a validated 16-gene prognostic signature. It was authored by Junrui He and last updated on March 18, 2026.

Use Cases

• Training prognostic models for bladder cancer survival based on the 16-gene metabolic signature.
• Identifying bladder cancer molecular subtypes based on amino acid metabolism gene expression patterns.
• Correlating metabolic gene expression with immune infiltration features and drug sensitivity predictions.
• Validating the role of specific genes like PSPH in bladder cancer cell proliferation and invasion.

Strengths

• Analysis integrates transcriptomic and clinical data from three major cohorts: TCGA-BLCA, GSE13507, and GSE32894.
• Prognostic signature was validated across multiple independent datasets, suggesting stable performance.
• Includes single-cell data (GSE222315) to trace cellular origin of model genes.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific cohorts and platforms used.

Provenance

Source

figshare, authored by Junrui He.

Collection Method

Transcriptomic and clinical data integrated from TCGA-BLCA, GSE13507, and GSE32894 cohorts using differential analysis, consensus clustering, and model optimization via the MIME platform.

Freshness

Last updated 2026-03-18 07:35:02; freshness should be verified.