Chenyu Zhang published a prognostic model for triple-negative breast cancer (TNBC) on figshare in April 2026. The model is based on four T cell-mediated tumor killing related genes identified from transcriptomic data from TCGA-BRCA and validated with the GSE135565 dataset. It includes analysis of risk groups, drug sensitivity, immune checkpoint expression, and tumor microenvironment.
Use Cases
- Predicting patient survival outcomes based on the four-gene prognostic signature mentioned in the description
- Analyzing differences in drug sensitivity among patient risk groups
- Investigating immune checkpoint expression patterns within the tumor microenvironment
- Exploring pathways of cell cycle and immune regulation enriched in different risk groups
- Studying associations between prognostic genes and transcription factors like SP1, MYC, and CTCF
Strengths
- The prognostic model was validated using an independent dataset (GSE135565)
- The model's predictive performance had AUC values all above 0.6 in training and validation sets
- Analysis includes multiple dimensions: clinical correlation, drug sensitivity, immune checkpoint, and tumor microenvironment
Limitations
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
- The dataset is 10.4 KB, indicating a very limited scope likely containing summary results rather than raw data
Provenance
- Source
- figshare
- Collection Method
- Transcriptomic data from TCGA-BRCA and TTKRGs were curated to determine prognostic genes and build a model.
- Freshness
- Last updated 2026-04-10 06:02:55