ER+/HER2- Breast Cancer Molecular Subtypes with Clinical and Genomic Data

A meta-dataset of 5,342 clinically defined ER+/HER2- breast cancer samples, analyzed by François Bertucci. It aggregates gene-expression, DNA copy number, mutational, and proteomic data from 36 public datasets to compare therapeutic responses between basal and luminal molecular subtypes. The supporting data includes histo-clinical and molecular tumor classifications.

Use Cases

• Classifying breast cancer molecular subtypes based on aggregated gene-expression and clinical data mentioned in the description.
• Evaluating potential vulnerabilities to hormone treatment and other systemic therapies for ER+/HER2- cancers.
• Comparing basal versus luminal breast cancer subtypes using multi-omics data from a large patient cohort.

Strengths

• Includes data from 5,342 clinically defined ER+/HER2- breast cancer samples.
• Aggregates multi-omics data types (gene expression, DNA copy number, mutational, proteomic) from 36 public datasets.
• Focuses on a specific, clinically relevant breast cancer subtype (ER+/HER2-).

Limitations

• Row count for the primary classification dataset is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

François Bertucci via paperswithcode and figshare repository.

Collection Method

In-silico analysis of a meta-dataset pooling 36 publicly available gene-expression and genomic datasets.