Seven-Gene Metastasis-Associated Prognostic Model for Breast Cancer

A seven-gene prognostic signature (IGJ, CXCL14, PTGER3, RTN1, EGOT, TLR10, PANX2) for breast cancer developed by Yuan Yao. The model was constructed using data from TCGA-BRCA, AURORA US Network, SCAN-B, and GEO databases and validated via multiple analyses. The dataset was last updated on 2026-05-10.

Use Cases

• Predicting breast cancer patient survival based on the seven-gene risk score.
• Investigating immune infiltration differences between high-risk and low-risk patient groups.
• Identifying potential novel therapeutic targets, such as RTN1 and TLR10, for tumor progression.
• Analyzing somatic mutation landscapes associated with different prognostic risk groups.
• Characterizing cell type-specific gene expression patterns using single-cell transcriptomics data.

Strengths

• The prognostic model is based on data from multiple established sources including TCGA-BRCA and GEO.
• The model was validated using calibration curves and decision curve analysis (DCA).
• The study identifies two previously under-characterized genes (RTN1 and TLR10) as potential drivers.
• Analysis includes functional enrichment, immune infiltration, 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 primary data file is a 3.6 MB DOCX document, which may not be a standard structured data format.

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 22:02:14; freshness should be verified.