Transcriptomic data from TCGA-BRCA and GSE135565 datasets were used to analyze prognostic characteristics in triple-negative breast cancer. Chenyu Zhang constructed a prognostic model based on four T cell-mediated tumor killing-related genes, validated with AUC values above 0.6. The dataset was last updated on April 10, 2026.
Use Cases
- Predicting patient survival risk based on a four-gene prognostic signature.
- Analyzing associations between risk scores and pathological stages.
- Comparing drug sensitivity and immune checkpoint expression among different risk groups.
- Exploring tumor microenvironment differences, such as stromal activation and M2 macrophage polarization.
- Investigating gene associations with transcription factors like SP1, MYC, and CTCF.
Strengths
- The prognostic model was validated with AUC values all above 0.6 in training and validation sets.
- Analysis integrates data from TCGA-BRCA and GSE135565 datasets.
- The model links prognostic genes to specific immune evasion mechanisms and stromal-immune crosstalk.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The dataset is 10.4 KB, indicating a very limited scope.
Provenance
- Source
- figshare
- Collection Method
- Transcriptomic data from TCGA-BRCA and TTKRGs were curated; GSE135565 dataset was used for validation.
- Freshness
- Last updated 2026-04-10 06:02:55; freshness should be verified.