[Mass spectrometry imaging technology and its application in breast cancer research].

The incidence of breast cancer, one of the most common malignancies affecting women, is increasing significantly worldwide. Given the rapid development of medical technology, early and effective diagnostic methods should be able to improve the survival rate and quality of life of patients suffering from disease. However, although existing treatment options, including chemotherapy and endocrine therapies, have greatly improved the survival of patients, disease recurrence in the long term remains a challenge. Because breast cancer is a heterogeneous and complex disease, which includes several subtypes with different responses to treatment, the continual acquisition of spatial information on related biomolecules is important for accurate tracking of the tumor heterogeneity and microenvironment. At present, prognostic and predictive biomarkers, such as human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), Ki-67, progesterone receptor (PR), and programmed death-ligand 1 (PD-L1), are validated for use in the decision-making over breast cancer therapies. Mass spectrometry imaging (MSI) is a useful technique for acquiring molecular information about biological tissues, including qualitative, quantitative, and spatial distribution information, because it is based on the ion mass-to-charge ratio of the biomolecules and avoids the need for their labeling and staining. MSI can also acquire molecular information on drugs and their metabolites, as well as that on molecules related to endogenous metabolism, such as lipids, peptides, and proteins. Of the various ion sources available for MSI, the most popular are matrix-assisted laser desorption ionization, secondary ion mass spectrometry, and desorption electrospray ionization, and modifications or derivatives of these sources are still emerging. MSI-based techniques provide new ideas and directions for the molecular typing of tumors, as well as knowledge on the metabolism of related antitumor drugs. The process of MSI analysis generally involves tissue acquisition, section preparation, mass spectrometry ionization, map acquisition, and data analysis, with the most crucial step being sample handling to preserve the original chemical and location information of the analytes. The sample preparation steps are sample collection, storage, and slicing, tissue pretreatment, and matrix spraying. This review focuses mainly on the preparation of biological specimens for MSI analysis and the recent progress made in breast cancer research with this technology. With regard to sample preparation, four aspects are discussed: small-molecule samples, macromolecular samples, paraffin-embedded samples, and matrix spraying methods. To solve the difficulties associated with small-molecule sample processing, including the low extraction efficiency for certain lipids and matrix interference in the low-molecular-weight region, the addition of a cationic reagent to the extractant, the use of a new matrix, and tissue derivatization have been used. In the review of macromolecular sample processing, several different washing protocols are summarized. With regard to paraffin-embedded samples, the solutions to several common problems are reviewed. Additionally, the application of MSI to three models associated with breast cancer research is discussed, viz. cell models, animal models, and clinical tumor samples. For these models, MSI technology is used to evaluate the penetration and metabolism of antitumor agents in breast cancer, which can better reflect the malignant transformation of cells and changes in the microenvironment. With regard to lipid molecules, the use of MSI to study differences in their spatial distribution may provide a better understanding of the relationship between lipid metabolism and cancer. This review also provides important information for accurate molecular typing and drug screening in cancer research. Analytically, the tissue preparation method, tissue storage conditions, instrumentation choice, and experimental parameters have all been associated with variability in the imaging and mass-spectral qualities of MSI, thereby affecting the performance of the method. Large-scale studies using diverse sample cohorts are therefore needed to properly evaluate the robustness of MSI molecular markers and workflows for the clinical diagnosis and characterization of breast cancer variants. Our review provides strong evidence that MSI is a reliable, highly reproducible, and rapid technique for the diagnosis of breast cancer biopsies and may be useful in clinical application.