Kinase-Related Gene Prognostic Model for Breast Cancer Survival

A transcriptomics dataset from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) used to develop a prognostic model for breast cancer. The study identified two molecular subtypes and a 7-gene risk signature validated on external datasets. The dataset was authored by Shuanglai Ye and last updated on 2026-05-12.

Use Cases

• Stratifying breast cancer patients into risk groups based on the 7-gene prognostic signature.
• Analyzing differences in immune cell infiltration and tumor mutational burden between identified molecular subtypes.
• Predicting patient drug sensitivity using the pRRophetic algorithm based on the kinase-related gene expression profiles.
• Validating prognostic models for breast cancer survival using independent external datasets from GEO.

Strengths

• Model validated on independent external datasets from the Gene Expression Omnibus (GEO).
• Analysis includes comparative assessment of clinical features, immune infiltration, tumor mutational burden, and drug sensitivity.
• Dataset is 25.6 MB in size and available under a CC-BY-4.0 license.

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 temporal or source bias inherent to the TCGA and GEO repositories.

Provenance

Source

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).

Collection Method

Transcriptome profile analysis of breast cancer tissues.

Freshness

Last updated 2026-05-12 16:29:26; freshness should be verified.