METABRIC Breast Tumour Microenvironment: Multiplexed Imaging and Single-Cell Data

Esther Danenberg from the University of Cambridge provides multiplexed imaging mass cytometry (IMC) data of breast tumour microenvironments. The dataset includes full-stack TIFF images, five corresponding image masks per acquisition, and processed single-cell and cell-neighbour interaction data. Data can be linked to other public METABRIC studies via patient identifiers.

Use Cases

• Train models to segment cell types and tissue structures based on multiplexed IMC images and associated masks.
• Analyze spatial relationships between cells using the provided cell-cell interaction graph data (CellNeighbours.csv).
• Correlate single-cell protein expression profiles from processed data with clinical outcomes from linked METABRIC studies.

Strengths

• Includes multiple aligned data types per sample: a full-stack image and five distinct image masks (whole cell, nucleus, cytoplasm, tumour, vessel).
• Processed single-cell data is already spillover corrected, reducing a key preprocessing step.
• Data is linkable to the broader public METABRIC cohort via the METABRIC identifier (MB####), enabling multi-modal analysis.

Limitations

• Row count for the processed single-cell and cell-neighbour data is unknown, which may limit suitability assessment.
• Column-level documentation for the processed tabular files is in separate annotation files, requiring manual inspection after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Cambridge

Collection Method

Multiplexed imaging mass cytometry (IMC) on tissue microarray (TMA) cores from the METABRIC cohort.