Seven-Gene Metastasis-Associated Prognostic Model for Breast Cancer

A prognostic risk model based on seven metastasis- and cancer-associated genes (IGJ, CXCL14, PTGER3, RTN1, EGOT, TLR10, PANX2) for breast cancer. The model was developed and validated using data from TCGA-BRCA, AURORA US Network, SCAN-B, and GEO databases. It was authored by Yuan Yao and last updated on May 10, 2026.

Use Cases

• Predicting patient survival outcomes based on the seven-gene risk score.
• Investigating immune infiltration phenotypes (e.g., 'hot' vs. T-cell exclusion) associated with risk groups.
• Identifying potential novel therapeutic targets like RTN1 and TLR10 for breast cancer progression.
• Analyzing somatic mutation landscapes and metabolic pathway enrichment differences between prognostic groups.
• Validating gene expression patterns in breast cancer cell lines versus normal mammary epithelial cells.

Strengths

• Model validated across multiple independent datasets (TCGA-BRCA, AURORA US Network, SCAN-B, GEO).
• Identifies two previously under-characterized genes (RTN1 and TLR10) as potential drivers of tumor progression.
• Analysis includes multiple validation methods: calibration curves, decision curve analysis, and single-cell transcriptomics.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 2.7 MB file size suggests a small dataset, likely containing the model description and results rather than the full underlying data.

Provenance

Source

Data were acquired from the TCGA-BRCA, AURORA US Network, SCAN-B, and GEO databases.

Collection Method

M-CA-DEGs were identified, and a prognostic risk model was constructed via univariate Cox and LASSO regression analyses.

Freshness

Last updated 2026-05-10 22:02:13; freshness should be verified.