Spatial Proteomics for the Molecular Characterization of Breast Cancer

Abstract

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Keywords: MALDI imaging; breast cancer; mass spectrometry imaging; proteomics.

Figure 1

Overview of spatial proteomics approaches in breast cancer. (a) Tumor microenvironment in breast cancer. The tumor consists of tumor cells and stromal cells, including cancer-associated fibroblasts, mesenchymal cells, and immune cells, surrounded by an extracellular matrix. Interactions between these components within the tumor contribute to the optimal conditions for tumor cell proliferation, progression, and survival. To study these processes, a spatial approach is used to determine cellular heterogeneity within tissues. (b) Schematic outline of a typical workflow for fresh frozen (FF) or formalin-fixed paraffin-embedded (FFPE) tissue samples. Sample processing includes sectioning and mounting a tissue section on a target. (c) For untargeted methods, such as mass spectrometry imaging, a matrix solution is homogenously sprayed, the tissue surface is irradiated by the laser and ion images are generated. Small areas of tissue or cells isolated by laser capture microdissection (LCM) can be analyzed by highly sensitive liquid chromatography coupled to mass spectrometry (LC-MS). (d) For targeted methods, typically antibodies labeled with fluorophores or mass tags are applied for multiplex data acquisition. As the number of markers that can be analyzed increases, the spatial resolution substantially declines. (e) As all these methods produce data-rich outputs, computational analysis, such as dimension reduction, clustering, or network analysis, is applied to visually represent and calculate statistical information.