Breast Cancer Immune Subtypes Linked to Drug Responsiveness

Three distinct immune subtypes of breast cancer were identified through Non-negative Matrix Factorization analysis of transcriptomic profiles from TCGA, GEO, and CCLE. The study, authored by Min Liu, characterizes these subtypes by their immune infiltration, mutational features, and predicted response to immunotherapy. The data, last updated in May 2026, includes computational predictions and in vitro experimental validation of therapeutic sensitivity.

Use Cases

• Predicting immunotherapy response based on identified immune subtype classification.
• Identifying prognostic biomarkers for breast cancer based on immune and molecular features.
• Validating computational drug sensitivity predictions with in vitro experimental data.
• Analyzing co-expression networks to discover subtype-specific hub genes.

Strengths

• Analysis integrates data from three major public repositories: TCGA, GEO, and CCLE.
• Findings are supported by in vitro experimental validation of computational predictions.
• Identifies five hub genes that confirm the stability of the immune stratification system.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the source repositories and analysis timeframe.

Provenance

Source

Transcriptomic profiles from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE).

Collection Method

Non-negative Matrix Factorization (NMF) of Gene Set Variation Analysis enrichment scores, with therapeutic sensitivity assessed via computational algorithms and in vitro experiments.

Freshness

Last updated 2026-05-05 05:28:36; freshness should be verified.