Folate Metabolism Gene Signature for Head and Neck Cancer Prognosis

An 11-gene prognostic model for head and neck squamous cell carcinoma (HNSCC) developed from TCGA transcriptomic data. The model stratifies patients into distinct survival groups and is associated with immune infiltration and drug response. The dataset was authored by Kai Zhang and last updated in May 2026.

Use Cases

• Predicting patient survival risk based on the folate metabolism–related gene signature (FMRG_score)
• Investigating associations between folate metabolism and anti-tumor immune infiltration
• Predicting chemoresistance potential based on estimated drug IC50 values
• Validating CYP27B1 as a mechanistic target influencing tumor progression and cisplatin sensitivity

Strengths

• Model constructed using LASSO and multivariate Cox regression on TCGA data
• Integrates gene signature with clinical variables in a predictive nomogram
• Includes functional enrichment and immune deconvolution analyses

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment

Provenance

Source

The Cancer Genome Atlas (TCGA)

Collection Method

Transcriptomic data analysis, LASSO regression, multivariate Cox regression

Freshness

Last updated 2026-05-05 05:28:40