MALDI mass spectrometric imaging meets "omics": recent advances in the fruitful marriage.

Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI MSI) is a method that allows the investigation of the molecular content of surfaces, in particular, tissues, within its morphological context. The applications of MALDI MSI in the field of large-scale mass spectrometric studies, which are typically denoted by the suffix "omics", are steadily increasing. This is because, on the one hand, technical advances regarding sample collection and preparation, matrix application, instrumentation, and data processing have enhanced the molecular specificity and sensitivity of MALDI MSI; on the other hand, the focus of the "omics" community has moved from establishing an inventory of certain compound classes to exploring their spatial distribution to gain novel insights. Thus, the aim of this mini-review is twofold, to display the state-of-the-art in terms of technical aspects in MALDI MSI and to highlight selected applications in the last two years, which either have significantly advanced a certain "omics" field or have introduced a new one through pioneering efforts.

MALDI imaging-based classification of hepatocellular carcinoma and non-malignant lesions in fibrotic liver tissue.

Histopathologic differentiation of nodular lesions in cirrhotic liver is difficult even for experienced hepatopathologists especially regarding diagnosis of hepatocellular carcinoma (HCC) in biopsies. For this reason, new tissue markers are needed to reinforce histopathologic decision-making. With advances in molecular techniques, proteomic analysis may help to confirm the diagnosis of HCC. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful technology which allows to determine and to localize proteins directly in tissue sections. Using MALDI IMS proteomic patterns of cryosections with lesions of HCC (n = 15) and non-malignant fibrotic liver tissue (n = 11) were investigated to establish a classification model of HCC, which was validated in an independent set of tissue to distinguish HCC (n = 10) from regenerative nodules (n = 8). By correlating generated mass spectrometric images with the histology of the tissue sections we found that the expression of 4 proteins as indicated by m/z 6274, m/z 6647, m/z 6222 and m/z 6853 was significantly higher in HCC tissue than in non-tumorous liver tissue. The generated classification model based on the most significant 3 differentially expressed proteins allowed a reliable prediction of benign and malignant lesions in fibrotic liver tissue with a sensitivity and specificity of 90 % in the validation set. The identified MALDI IMS proteomic signature can be diagnostically helpful to allow simplifying the diagnostic process and minimize the risks of delays in establishing the objective final diagnosis and initiating treatment of patients with HCC.

Deeper understanding of biological tissue: quantitative correlation of MALDI-TOF and Raman imaging.

In order to achieve a comprehensive description of biological tissue, spectral information about proteins, lipids, nucleic acids, and other biochemical components need to be obtained concurrently. Different analytical techniques may be combined to record complementary information of the same sample. Established techniques, which can be utilized to elucidate the biochemistry of tissue samples are, for instance, MALDI-TOF-MS and Raman microscopic imaging. With this contribution, we combine these two techniques for the first time. The combination of both techniques allows the utilization and interpretation of complementary information (i.e., the information about the protein composition derived from the Raman spectra with data of the lipids analyzed by the MALDI-TOF measurements). Furthermore, we demonstrate how spectral information from MALDI-TOF experiments can be utilized to interpret Raman spectra.