Spatial Multiomics MALDI-MSI Data for Breast Tumor and Normal Tissue Cores

1.5 MB of multiomics data from a proof-of-concept study using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI). The dataset, shared by Seyed M. J. Seyed Golestan on figshare, integrates spatial lipid, glycan, and tryptic peptide layers from a breast cancer tissue microarray. The analysis demonstrates the approach's potential for discriminating between healthy and tumor tissues and capturing molecular differences among breast cancer subtypes.

Use Cases

• Classifying breast tumor subtypes based on integrated spatial lipid, glycan, and peptide signatures.
• Identifying molecular biomarkers for breast cancer using spatially resolved mass spectrometry imaging data.
• Training machine learning models to distinguish between healthy and neoplastic tissue conditions based on proteomic layer information.
• Analyzing the contribution of lipids and glycans to the biological heterogeneity of breast tumors.

Strengths

• Integrates three distinct multiomics layers (lipids, N-glycans, tryptic peptides) from the same tissue section.
• Data is spatially resolved, preserving histological context lost in conventional mass spectrometry.
• File size is 1.5 MB, indicating a focused and likely well-structured dataset for initial analysis.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• Column-level documentation is absent; field semantics must be inferred after download.
• The study is described as a proof-of-concept, suggesting the sample cohort may be limited.

Provenance

Source

figshare

Collection Method

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) on a breast cancer tissue microarray.

Freshness

Last updated 2026-05-06 20:30:03; freshness should be verified.