The high molecular heterogeneity of breast cancer (BC) poses a significant challenge for its classification and biological characterization. Despite numerous efforts, conventional immunohistochemical techniques and traditional mass spectrometry (MS) have failed to provide an exhaustive characterization of tumor subtypes. This limitation is likely due to the loss of spatial information, which significantly impacts the interpretation of the results. In this study, we present a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) approach that spatially integrates three multiomics layers, including lipids, N-glycans, and tryptic peptides, on the same tissue microarray (TMA) section with BC and normal tissue cores. The analysis of individual layers and their integration demonstrates the potential of multiomics MALDI-MSI in discriminating between healthy and tumor tissues and in capturing molecular differences associated with different subtypes of BC. Specifically, the approach adopted highlighted the significant contribution of lipids and glycans to characterizing breast tumor subtypes. The proteomic layer provides complementary information on the proliferative state and biological heterogeneity of the tumors, clearly distinguishing between the healthy and neoplastic conditions. Overall, this proof-of-concept study demonstrates the potential of spatial multiomics MALDI-MSI as a tool for a more in-depth characterization of BC subtypes, laying the groundwork for future applications on larger sample cohorts.
Golestan et al. (Wed,) studied this question.