FAMR: A Four-Gene Fatty Acid Metabolism Risk Signature for Bladder Cancer Prognosis

A study by Hui Yu, published on figshare in March 2026, developed a prognostic model for bladder cancer based on fatty acid metabolism. The analysis used 359 bladder cancer samples to construct a four-gene risk signature (PATZ1, TTC6, AEBP1, MAOA) and classify molecular subtypes. The model was validated with internal and external cohorts and investigated through functional enrichment, immune infiltration, and single-cell RNA sequencing analyses.

Use Cases

• Predicting patient prognosis in bladder cancer based on the four-gene FAMR signature.
• Classifying bladder cancer into molecular subtypes (C1 and C2) for risk stratification.
• Investigating correlations between risk scores and clinical features like patient age, sex, and tumor stage.
• Exploring biological mechanisms linking fatty acid metabolism, immune infiltration, and cancer progression.
• Validating MAOA as a potential tumor suppressor gene through in silico analysis of expression data.

Strengths

• Model validated using internal and external patient cohorts.
• Analysis integrates bulk RNA-seq, single-cell RNA-seq, and in vitro functional assays.
• Signature is based on a specific biological pathway (fatty acid metabolism).

Limitations

• Dataset size is very small at 1.0 KB; row and column counts are unknown.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect bias inherent to the specific patient cohorts analyzed.

Provenance

Source

figshare, author Hui Yu.

Collection Method

Analysis of 359 bladder cancer samples from unspecified cohorts; includes single-cell RNA-seq and in vitro experiments.

Freshness

Last updated 2026-03-18 07:35:18.