Rémi Longuespée

MALDI imaging and profiling MS of higher mass proteins from tissue

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 < 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.

Multivariate analyses for biomarkers hunting and validation through on-tissue bottom-up or in-source decay in MALDI-MSI: application to prostate cancer

The large amount of data generated using matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) poses a challenge for data analysis. In fact, generally about 1.108–1.109 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 formalin-fixed paraffin-embedded tissue.

Selected Protein Monitoring in Histological Sections by Targeted MALDI-FTICR in-source decay Imaging.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a rapidly growing method in biomedical research allowing molecular mapping of proteins on histological sections. The images can be analyzed in terms of spectral pattern to define regions of interest. However, the identification and the differential quantitative analysis of proteins require off line or in situ proteomic methods using enzymatic digestion. The rapid identification of biomarkers holds great promise for diagnostic research, but the major obstacle is the absence of a rapid and direct method to detect and identify with a sufficient dynamic range a set of specific biomarkers. In the current work, we present a proof of concept for a method allowing one to identify simultaneously a set of selected biomarkers on histological slices with minimal sample treatment using in-source decay (ISD) MSI and MALDI-Fourier transform ion cyclotron resonance (FTICR). In the proposed method, known biomarkers are spotted next to the tissue of interest, the whole MALDI plate being coated with 1,5-diaminonaphthalene (1,5-DAN) matrix. The latter enhances MALDI radical-induced ISD, providing large tags of the amino acid sequences. Comparative analysis of ISD fragments between the reference spots and the specimen in imaging mode allows for unambiguous identification of the selected biomarker while preserving full spatial resolution. Moreover, the high resolution/high mass accuracy provided by FTICR mass spectrometry allows the identification of proteins. Well-resolved peaks and precise measurements of masses and mass differences allow the construction of reliable sequence tags for protein identification. The method will allow the use of MALDI-FTICR MSI as a method for rapid targeted biomarker detection in complement to classical histology.

MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology.

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.

A laser microdissection-based workflow for FFPE tissue microproteomics: Important considerations for small sample processing

Proteomic methods are today widely applied to formalin-fixed paraffin-embedded (FFPE) tissue samples for several applications in research, especially in molecular pathology. To date, there is an unmet need for the analysis of small tissue samples, such as for early cancerous lesions. Indeed, no method has yet been proposed for the reproducible processing of small FFPE tissue samples to allow biomarker discovery. In this work, we tested several procedures to process laser microdissected tissue pieces bearing less than 3000 cells. Combined with appropriate settings for liquid chromatography mass spectrometry-mass spectrometry (LC-MS/MS) analysis, a citric acid antigen retrieval (CAAR)-based procedure was established, allowing to identify more than 1400 proteins from a single microdissected breast cancer tissue biopsy. This work demonstrates important considerations concerning the handling and processing of laser microdissected tissue samples of extremely limited size, in the process opening new perspectives in molecular pathology. A proof of the proposed method for biomarker discovery, with respect to these specific handling considerations, is illustrated using the differential proteomic analysis of invasive breast carcinoma of no special type and invasive lobular triple-negative breast cancer tissues. This work will be of utmost importance for early biomarker discovery or in support of matrix-assisted laser desorption/ionization (MALDI) imaging for microproteomics from small regions of interest.

A spiked tissue-based approach for quantification of phosphatidylcholines in brain section by MALDI mass spectrometry imaging

AbstractIn the last few years, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has been successfully used to study the distribution of lipids within tissue sections. However, few efforts have been made to acquire reliable quantitative data regarding the localized concentrations of these molecules. Here we propose an approach based on brain homogenates for the quantification of phosphatidylcholines (PCs) in brain section by MALDI MSI. Homogenates were spiked with a range of PC(16:0 d31/18:1) concentrations. Sections from homogenates and intact brain were simultaneously prepared before being analyzed by MALDI MSI using a Fourier transform ion cyclotron resonance (FT-ICR) analyzer. Standard curves were generated from the signal intensity of the different PC(16:0 d31/18:1) ionic species ([M+H]+, [M+Na]+ and [M+K]+) detected from the homogenate sections. Localized quantitative data were finally extracted by correlating the standard curves with the signal intensities of endogenous PC (especially PC(16:0/18:1)) ionic species detected on different areas of the brain section. They were consistent with quantitative values found in the literature. This work introduces a new method to take directly into account biological matrix effects for the quantification of lipids as well as other endogenous compounds, in tissue sections by MALDI MSI. Graphical abstractA spiked tissue-based method for lipids quantification by MALDI mass spectrometry imaging.

Proteomic analyses of serous and endometrioid epithelial ovarian cancers – Cases studies – Molecular insights of a possible histological etiology of serous ovarian cancer

Epithelial ovarian carcinogenesis may occur de novo on the surface of ovarian mesothelial epithelial cells or from cells originating in other organs. Foreign Müllerian cell intrusion into the ovarian environment has been hypothesized to explain the latter scenario. In this study, MALDI MS profiling technology was used to provide molecular insights regarding these potentially different mechanisms.

Implications of Proprotein Convertases in Ovarian Cancer Cell Proliferation and Tumor Progression: Insights for PACE4 as a Therapeutic Target

Proprotein convertases are a family of kexin-like serine proteases that process proteins at single and multiple basic residues. Among the predicted and identified PC substrates, an increasing number of proteins having functions in cancer progression indicate that PCs may be potential targets for antineoplastic drugs. In support of this notion, we identified PACE4 as a vital PC involved in prostate cancer proliferation and progression, contrasting with the other co-expressed PCs. The aim of the present study was to test the importance of PCs in ovarian cancer cell proliferation and tumor progression. Based on tissue-expression profiles, furin, PACE4, PC5/6 and PC7 all displayed increased expression in primary tumor, ascites cells and metastases. These PCs were also expressed in variable levels in three model ovarian cell lines tested, namely SKOV3, CAOV3 and OVCAR3 cells. Since SKOV3 cells closely represented the PC expression profile of ovarian cancer cells, we chose them to test the effects of PC silencing using stable gene-silencing shRNA strategy to generate knockdown SKOV3 cells for each expressed PC. In vitro and in vivo assays confirmed the role of PACE4 in the sustainment of SKOV3 cell proliferation, which was not observed with the other three PCs. We also tested PACE4 peptide inhibitors on all three cell lines and observed consequent reduced cell proliferation which was correlated with PACE4 expression. Overall, these data support a role of PACE4 in promoting cell proliferation in ovarian cancer and provides further evidence for PACE4 as a potential therapeutic target.

Proteomic signatures reveal a dualistic and clinically relevant classification of anal canal carcinoma

Aetiologically linked to HPV infection, malignancies of the anal canal have substantially increased in incidence over the last 20 years. Although most anal squamous cell carcinomas (SCCs) respond well to chemoradiotherapy, about 30% of patients experience a poor outcome, for undetermined reasons. Despite cumulative efforts for discovering independent predictors of overall survival, both nodal status and tumour size are still the only reliable factors predicting patient outcome. Recent efforts have revealed that the biology of HPV‐related lesions in the cervix is strongly linked to the originally infected cell population. To address the hypothesis that topography also influences both gene expression profile and behaviour of anal (pre)neoplastic lesions, we correlated both proteomic signatures and clinicopathological features of tumours arising from two distinct portions of the anal canal: the lower part (squamous zone) and the more proximal anal transitional zone. Although microdissected cancer cells appeared indistinguishable by morphology (squamous phenotype), unsupervised clustering analysis of the whole proteome significantly highlighted the heterogeneity that exists within anal canal tumours. More importantly, two region‐specific subtypes of SCC were revealed. The expression profile (sensitivity/specificity) of several selected biomarkers (keratin filaments) further confirmed the subclassification of anal (pre)cancers based on their cellular origin. Less commonly detected compared to their counterparts located in the squamous mucosa, SCCs originating in the transitional zone more frequently displayed a poor or basaloid differentiation, and were significantly correlated with reduced disease‐free and overall survivals. Taken together, we present direct evidence that anal canal SCC comprises two distinct entities with different cells of origin, proteomic signatures, and survival rates. This study forms the basis for a dualistic classification of anal carcinoma, with implications for management, outcome expectations, and possibly therapy. Copyright

Spectroimmunohistochemistry: A Novel Form of MALDI Mass Spectrometry Imaging Coupled to Immunohistochemistry for Tracking Antibodies

MALDI mass spectrometry imaging (MALDI-MSI) is currently used for clinical applications, such as biomarker identification, particularly for the study of solid tumors. The ability to map specific compounds that have been determined to be biomarkers and therapeutic targets is relevant for the evaluation of the efficacy of targeted therapies. This article describes a new method called Spectro-ImmunoHistoChemistry (SIHC), which combines the use of specific antibodies against markers and mass spectrometric imaging in the MS/MS mode. SIHC is based on direct primary antibody-antigen recognition, trypsin digestion of the antibody overlaying the markers of interest in the tissue section, and MALDI-MSI of the tryptic peptides generated from the antibody. This approach has both clinical and pharmacological applications. First, it can be used as a cross-validation method to monitor the presence specifically of a marker in a tissue section. Second, SIHC could potentially be used as a novel technology for tracking specific antibodies after in vivo injection for anti-cancer treatments. Additionally, SIHC could enable novel clinical applications of MSI, such as monitoring the efficacy of cytotoxic antibody treatments.