Imaging MS in Biomedical Research and Diagnostics
Versatile Potential Applications for the Molecular Analysis of Tissue
- Fig. 1: Principle of MALDI imaging MS.
- Fig. 2: Visualization of various proteins in breast cancer tissue following MALDI imaging. (Reprinted with kind permission of reference . Copyright (2010) American Chemical Society.)
- Fig. 3: Visualization of the distribution of a tyrosine kinase inhibitor in tissue by means of MALDI drug imaging.
- Fig. 4: MALDI metabolomic imaging. (Reprinted by kind permission of reference Miura D. et al.: Anal. Chem. 82, 9789-9796 (2010). Copyright (2010) American Chemical Society.)
Imaging MS (mass spectrometry) allows the molecular composition of tissue samples to be analyzed in their morphological context. This method does not require markers and enables hundreds of analytes to be examined simultaneously within a single measurement. The great potential of imaging MS opens up an expanding range of applications in tissue analysis.
Mass spectrometry methods are a widespread analytical principle in Life Sciences. Imaging MS (Matrix-Assisted Laser Desorption/Ionization imaging - MALDI imaging) extends the applicability of these methods to the molecular analysis of tissues . This method permits the correlation of classic histology and molecular imaging at microscopic level, resulting in a new quality of data in biomedical research and molecular diagnostics. The method allows active substances and their metabolites, as well as a broad range of analytes - proteins and peptides, lipids, components of the metabolism - to be localized in sections of tissue by means of their mass signals. Starting materials are conventional tissue sections which are raster-scanned by the mass spectrometer (for spatial resolution), generating a mass spectrum for each measuring spot. The mass signals detected are then visualized by special software in the form of color signals on the basis of their intensity (Fig. 1). These color signals allow the detection of patterns which represent the distribution in the tissue of proteins and peptides, for example.
The current state of the art permits lateral resolution of up to 20 microns, sufficient for scanning small groups of cells down to individual cells.
From Tissue Section to Spatially Resolved Mass Spectrometry Profile
The primary application for the MALDI imaging technique is currently for frozen tissue and increasingly also in formalin-fixed and paraffin-embedded (FFPE) tissue . FFPE tissue of this kind has to be pre-treated before it can be analyzed. In a similar manner to other in-situ methods, for example, the cross-linked proteins can only be analyzed following the action of heat and/or digestion by enzymes [2,3].
Prior to MALDI imaging, the tissue needs to be prepared in such a way that the analyte molecules can be desorbed and ionized by the laser as in conventional MALDI mass spectrometry.
To this end, a section of tissue is applied to a glass slide coated with indium tin oxide to render it electrically conductive. Following a fixing step in ethanol, a matrix substance (made from cinnamic acid derivatives, for example) is applied. The matrix can be applied by spraying the substance in solution onto the target area in even layers, covering the tissue evenly with small matrix crystals. Following preparation of the sample, the section is raster-scanned by a mass spectrometer (Fig. 1).
Control software applies a virtual raster of measuring spots to the tissue. A mass spectrum is generated above each measuring spot (Fig. 1). Depending on section size, this automatically creates several thousand spectra, each of which is archived on a spatially-correlated basis. Solvents are then used to remove the matrix from the section and this is routinely stained with hematoxylin and eosin (HE). For analysis, the spectra are initially reproduced in color-coded form and a „mass map" is generated. The digital image of the HE-stained section used is superimposed on the virtual mass map to create a direct correlation between the mass spectrometry data and the histology (Fig. 1).
The second evaluation step defines healthy areas of tissue or tumor areas as „regions of interest" (ROIs) on the HE-stained specimen. Spectra generated within these areas are exported for further bioinformatic processing. The spectra can thus be classified on the basis of patterns (e.g. healthy versus tumor). Hierarchical clustering is one example of possible approaches to data analysis.
Applications in Imaging MS
Imaging MS facilitates the search for new disease-specific biomarkers, metabolomic components of the metabolism, or the detection of drugs and their metabolites in tissues [4,5,6].
Identification of Biomarkers
The different protein and peptide signatures obtained by means of MALDI imaging make it possible to identify biomarkers in tissue which may describe, for example, the course of a disease, how patients are responding to therapy or their survival. On a patient collective, MALDI imaging accordingly enabled it to be shown that proteomic markers in tumor tissue are associated with the response to a neoadjuvant therapy with Paclitaxel in breast cancer . In another study, specific biomarkers identified in diseased lymph node tissue were used to distinguish between Hodgkins lymphoma and lymphadenitis . It is also possible to detect protein signatures/patterns reflecting molecular markers, for example predictive ones, which are already known. Two studies have accordingly described a protein profile which predicts HER2 receptor status in carcinomas of the breast and stomach by means of MALDI imaging (Fig. 2) [9,10]. In a recently published study, the use of MALDI imaging facilitated the detection of previously unrecognized defects in the mitochondrial respiratory chain, which lead to individual patient response to cisplatin-based chemotherapy in advanced adenocarcinoma of the esophagus . It is also possible to detect protein modifications, as recently shown for histone modifications in hepatocellular carcinomas .
Pharmacological Active Substances and Their Metabolites
Imaging MS provides a new kind of analysis technique for the development and discovery of new active substances. So-called MALDI drug imaging allows the distribution and quantification of drugs and their metabolites to be detected in tissue . In this way, pharmacological effects of drugs can be explained in their histological context and valuable information obtained about their action (histopharmacology). MALDI drug imaging can make a contribution in the early phases of active substance development.
Conventional methods of visualizing active substances are autoradiography and LC-MS (liquid chromatography-mass spectrometry) analyses from tissue homogenate. In contrast to these methods, MALDI drug imaging does not require (radioactive) marking of the analytes, like autoradiography does, for example, in order to visualize active substances in tissue. Compared to autoradiography, in which typically only one analyte can be detected per experimental setup, MALDI drug imaging permits virtually any number of components to be determined simultaneously. Compared to LC-MS analyses, the strength of MALDI drug imaging is in the spatial visualization of active substances and their metabolites. The possibility of measuring active substances, metabolites, peptides etc. simultaneously means that MALDI drug imaging facilitates parallel tests which can explain how a tissue reacts to administration of an active substance. MALDI drug imaging furthermore makes it possible to see how an active substance becomes distributed in the organism, how certain active substance interactions proceed and how and where transport and metabolization occur. Accordingly it provides an innovative approach to solving a variety of issues in pharmacology and toxicology. As an example, figure 3 shows how a tyrosine kinase inhibitor is distributed in tissue.
Molecules of the Metabolism
The metabolome covers all the small molecules of a cell, tissue or organism which are required for metabolic reactions such as growth or maintenance, for example.
The analysis of endogenous metabolite profiles in tissues following a variety of treatments or under various other influences can lead to a deeper understanding of disease-related mechanisms, diagnostic biomarkers, the mechanisms of action of drugs and also of an organism‘s individual reactions to active substances. As in active substance analyses, the most frequently-used strategy for researching the metabolome in metabolome analysis is the use of mass spectrometry techniques such as LC-MS or GC-MS (gas chromatography-mass spectrometry). Here too, use of these techniques leads to loss of information relating to the localization of the analytes in the tissue. In this case, use of the MALDI metabolome imaging technique led to a new quality of results due to the incorporation of spatially-resolved visualization of analytes.
The first MALDI metabolome imaging studies initially focused on the detection of lipidomic components of the metabolome such as glycerophospholipids, for example . As this technique was developed further, it soon became possible to detect further components of metabolism. In a model for cerebral perfusion disorders, over 30 metabolites (nucleotides, co-factors, phosphorylated sugars, amino acids, lipids, carboxylic acids), as well as their specific individual distribution, were identified in a rat‘s brain (Fig. 4) . A further study on the same disease model reported spatiotemporal changes in energy metabolism in connection with focal ischemia .
The information obtained about spatial distribution of metabolites in tissues allows this information to be considered in direct connection with processes, which manifest themselves histopathologically, thus leading to a deeper understanding of the pathophysiology.
The pioneering technology of imaging MS is in a phase of rapid development. MALDI imaging analyses are easy to perform and require only a little sample material. The correlation between histomorphology and a molecular imaging method leads to a new quality of data for medical research and diagnostics which permits a better understanding of the molecular links between diseases and their treatment. The primary spheres of application for this technology currently include molecular histology, the search for new disease-specific biomarkers and the detection of drugs and their metabolites, as well as examining the metabolome in tissue.
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Further references are available from the authors.