Receptor tyrosine kinases (RTKs) are key regulatory signaling proteins governing cancer cell growth and metastasis. During the last two decades, several molecules targeting RTKs were used in oncology as a first or second line therapy in different types of cancer. However, their effectiveness is limited by the appearance of resistance or adverse effects. In this review, we summarize the main features of RTKs and their inhibitors (RTKIs), their current use in oncology, and mechanisms of resistance. We also describe the technological advances of artificial intelligence, chemoproteomics, and microfluidics in elaborating powerful strategies that could be used in providing more efficient and selective small molecules inhibitors of RTKs. Finally, we discuss the interest of therapeutic combination of different RTKIs or with other molecules for personalized treatments, and the challenge for effective combination with less toxic and off-target effects.

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phaseenhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

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Purpose To facilitate the transition of MALDI–MS Imaging (MALDI–MSI) from basic science to clinical application, it is necessary to analyze formalin‐fixed paraffin‐embedded (FFPE) tissues. The aim is to improve in situ tryptic digestion for MALDI–MSI of FFPE samples and determine if similar results would be reproducible if obtained from different sites. Experimental Design FFPE tissues (mouse intestine, human ovarian teratoma, tissue microarray of tumor entities sampled from three different sites) are prepared for MALDI–MSI. Samples are coated with trypsin using an automated sprayer then incubated using deliquescence to maintain a stable humid environment. After digestion, samples are sprayed with CHCA using the same spraying device and analyzed with a rapifleX MALDI Tissuetyper at 50 µm spatial resolution. Data are analyzed using flexImaging, SCiLS, and R. Results Trypsin application and digestion are identified as sources of variation and loss of spatial resolution in the MALDI–MSI of FFPE samples. Using the described workflow, it is possible to discriminate discrete histological features in different tissues and enabled different sites to generate images of similar quality when assessed by spatial segmentation and PCA. Conclusions and Clinical Relevance Spatial resolution and site‐to‐site reproducibility can be maintained by adhering to a standardized MALDI–MSI workflow.

MALDI imaging and profiling mass spectrometry of proteins typically leads to the detection of a large number of peptides and small proteins but is much less successful for larger proteins: most ion signals correspond to proteins of m/z Ͻ 25,000. This is a severe limitation as many proteins, including cytokines, growth factors, enzymes, and receptors have molecular weights exceeding 25 kDa. The detector technology typically used for protein imaging, a microchannel plate, is not well suited to the detection of high m/z ions and is prone to detector saturation when analyzing complex mixtures. Here we report increased sensitivity for higher mass proteins by using the CovalX high mass HM1 detector (Zurich, Switzerland), which has been specifically designed for the detection of high mass ions and which is much less prone to detector saturation. The results demonstrate that a range of different sample preparation strategies enable higher mass proteins to be analyzed if the detector technology maintains high detection efficiency throughout the mass range. The detector enables proteins up to 70 kDa to be imaged, and proteins up to 110 kDa to be detected, directly from tissue, and indicates new directions by which the mass range amenable to MALDI imaging MS and MALDI profiling MS may be extended. (J Am Soc Mass Spectrom 2010, 21, 1922-1929) © 2010 American Society for Mass Spectrometry S ince its inception ϳ10 y ago, MALDI imaging mass spectrometry (imaging MS) has developed into a powerful and versatile tool for biomedical research [1,2]. It is now routinely used for analyzing peptides and small proteins up to 25 kDa [3-6], administered drugs and their metabolites [7], and recently major improvements have been reported for lipids [8]. Despite this success, proteins exceeding 25 kDa are not routinely detected. Proteins larger than 25 kDa include many proteins with important biological activities, such as most cytokines, growth factors, enzymes, receptors, proproteins, and neuropeptide precursors. Increasing the mass range of proteins amenable to MALDI imaging MS might enable these biologically crucial proteins to be included in current applications, e.g., biomarker discovery.The most common technique currently used to access larger proteins in MALDI imaging MS analyses is based on proteolytic digestion of the tissue's proteins followed by MALDI imaging MS of their tryptic peptides. Note on-tissue digestion has the additional advantage that it can be applied to formalin fixed tissues as proteolytic peptides can be generated that are not bound within the cross-linked protein matrix. For example, Djidja et al. used on-tissue digestion to determine that the 78 kDa protein GRP78 may be a new candidate protein biomarker of pancreatic adenocarcinoma [9]. In principal, this 'bottom-up' strategy could enable proteins of any mass to be detected. In practice the large increase in complexity associated with proteolysing the entire tissue's protein content will cause many tryptic peptides to have identical nominal mass [1], thus under...

The large amount of data generated using matrixassisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) poses a challenge for data analysis. In fact, generally about 1.10 8 -1.10 9 values (m/z, I) are stored after a single MALDI-MSI experiment. This imposes processing techniques using dedicated informatics tools to be used since manual data interpretation is excluded. This work proposes and summarizes an approach that utilizes a multivariable analysis of MSI data. The multivariate analysis, such as principal component analysis-symbolic discriminant analysis, can remove and highlight specific m/z from the spectra in a specific region of interest. This approach facilitates data processing and provides better reproducibility, and thus, broadband acquisition for MALDI-MSI should be considered an effective tool to highlight biomarkers of interest. Additionally, we demonstrate the importance of the hierarchical classification of biomarkers by analyzing studies of clusters obtained either from digested or undigested tissues and using bottom-up and in-source decay strategies for in-tissue protein identification. This provides the possibility for the rapid identification of specific markers from different histological samples and their direct localization in tissues. We present an example from a prostate cancer study using formalinfixed paraffin-embedded tissue.

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Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.