Integrating MALDI-MSI and imaging mass cytometry to reveal intratumoral heterogeneity in breast cancer subtypes induced by the tumor microenvironment

Breast cancer (BC) is a global health issue, affecting a high proportion of the female population. Spatial proteomics enables the study of the proteome within tissue context, offering a promising approach to unravel the biological processes contributing to BC heterogeneity that can lead to ineffective therapies. To study this heterogeneity, we use a combination of untargeted MALDI imaging (MSI), bulk tissue LC-MS/MS, and targeted imaging mass cytometry (IMC). This approach aids in identifying diagnostic and prognostic biomarkers masked by tissue heterogeneity and allows precise mapping and quantification of selected biomarkers. The co-registration of these techniques can enhance our ability to correlate molecular and spatial data, leading to comprehensive insights into tumor biology and potential therapeutic targets. We established an optimized protocol for sample preparation of gelatin and paraffin-embedded BC tissue for MALDI imaging, configured a high multiplex IMC-panel, and performed data integration to analyze BC subtypes.

Human BC cell lines (MCF-7, SKBR-3, MDA-MB-231) were inoculated into female athymic BALB/c-nude mice. Excised tumors were embedded in gelatin, paraffin, and liquid nitrogen. For MSI, we optimized pre-analytical and analytical parameters to enhance the signal-to-noise (S/N) ratio and enable protein identification. Following MSI, samples were stained for standard histological evaluation. Adjacent tissue sections were used for IMC. Proteins were also identified by TMT-based LC-MS/MS from homogenized tissue.

Following the establishment of the MSI protocol, peptide signals were analyzed using spatial segmentation and uniform manifold approximation and projection (U-MAP) plots. Segmentation maps based on MSI aligned with expert-based histological assessment were generated. Unsupervised U-MAP plots enabled visualization of multidimensional information, allowing segmentation of different tumor, stroma, and necrotic tissue regions. Molecular BC subtypes were clearly distinguishable by MSI. In the bulk MS analysis ~17 000 proteins were identified, providing a source for confident matching of peptide signals from MSI. Based on the expression analysis of the TMT data and comprehensive literature review, we selected 28 markers for IMC. The targeted analysis revealed distinct marker expression patterns, with some markers predominantly expressed in specific subtypes. This detailed mapping highlighted unique proteomic landscapes across the tumor subtypes, including variations in pathways related to cell proliferation, apoptosis, hypoxia and immune response, thereby advancing our understanding of BC heterogeneity.

Using the established workflow, peptide signatures not only differentiate histologically confirmed tumor regions but also reveal sub-regions that are indistinguishable by standard methods, demonstrating the potential of MSI as a tool for translational BC research.