With imaging mass spectrometry we examine the biomolecular make-up of patient tissue samples to identify the biomolecular changes that accompany disease. We combine imaging mass spectrometry with pathology, digital image analysis and statistics for the identification of diagnostic and prognostic biomarkers (see also
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) can generate mass spectral profiles directly from tissue that contain hundreds of distinct biomolecular ions. Spatially-correlated analysis, imaging MS, can reveal how each of these biomolecular ions varies in clinical tissue samples.
One of the most important features of imaging MS is that the tissue’s integrity is not harmed. This allows a microscopic image of the tissue, i.e. its histological image, to be registered with the imaging MS data. This direct comparison enables the molecular profiles from specific histological entities or regions to be extracted, and to assess if further cellular specification may be obtained on the basis of the measured mass spectral information.
There is now ample evidence that imaging MS is having an impact in disease detection, particularly cancer. The differential MS profiles can be used to identify candidate biomarkers, and when combined with clinical outcomes identify MS signatures associated with prognosis or response to therapy.
The figure shows an example of a protein imaging MS analysis of central chondrosarcoma and peripheral chondrosarcoma, histologically identical bone tumors that grow within the medulla cavity or from the bone surface respectively. The imaging MS data shows proteins localized to each specific form of chondrosarcoma, but in each case the proteins are heterogeneously distributed throughout the tissues (
Jones et al., 2013). We recently demonstrated that the biomarkers detected by MSI could be robust to differences in patient series, MSI methodology, MSI tissue preparation method, and measurement location ( Dekker et al., 2014).
30 μm spatial resolution MALDI imaging MS of proteins in atherosclerotic arterial tissue (
Martin-Lorenzo et al., 2014). The mass spectrum is the mean average of all pixels and demonstrates many distinct protein ions were detected. Inset shows example mass spectral images localized to the media (m/z 3568) and intima (m/z 3010). The histological image and Red Alizarin (RA) image are included to contextualize the mass spectral images in terms of the tissue morphology and atherosclerotic (calcified) plaques; M = media; I = intima; P = plaque.
Imaging MS analyses thin tissue sections; by analyzing sequential tissue sections and aligning the resulting datasets we have recorded 3D imaging MS datasets of protein and peptide distributions. In the example shown to the left the protein images were obtained from wild type mouse brains following cortical spreading depression (the electrophysiological correlate of migraine with aura) (
Jones et al., 2012). In this study we used the same technology but different tissue preparation protocols to analyze the metabolite, peptide and protein changes following CSD.
When comparing biomolecular signatures from different animals it is imperative that the tissue sections (analyzed by imaging MS) contain as near identical organs/cells as possible. In collaboration with WP4 we have demonstrated how imaging MS data from rodent models may be automatically registered to curated tissue atlases, thereby automatically placing the MSI results within their correct neurological context (
Abdelmoula et al., 2014). Such developments are key to the wider application of MSI for brain disorders.