MALDI imaging and in-source decay for top-down characterization of glioblastoma

New perspective on central nervous system disorders: focus on mass spectrometry imaging

An abnormally organized brain spatial network is linked to the development of various central nervous system (CNS) disorders, including neurodegenerative diseases and neuropsychiatric disorders. However, the complicated molecular mechanisms of these diseases remain unresolved, making the development of treatment strategies difficult. A novel molecular imaging technique, called mass spectrometry imaging (MSI), captures molecular information on the surface of samples in situ. With MSI, multiple compounds can be simultaneously visualized in a single experiment. The high spatial resolution enables the simultaneous visualization of the spatial distribution and relative content of various compounds. The wide application of MSI in biomedicine has facilitated extensive studies on CNS disorders in recent years. This review provides a concise overview of the processes, applications, advantages, and disadvantages, as well as mechanisms of the main types of MSI. Meanwhile, this review summarizes the main applications of MSI in studying CNS diseases, including Alzheimer's disease (AD), CNS tumors, stroke, depression, Huntington's disease (HD), and Parkinson's disease (PD). Finally, this review comprehensively discusses the synergistic application of MSI with other advanced imaging modalities, its utilization in organoid models, its integration with spatial omics techniques, and provides an outlook on its future potential in single-cell analysis.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation

Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biological processes in health and disease. However, the identification of lipids in MALDI-MSI remains a challenge due to the lack of chromatographic separation or untargeted tandem mass spectrometry. Recent studies have proposed the use of MALDI in-source fragmentation to infer structural information and aid identification. Here we present rMSIfragment, an open-source R package that exploits known adducts and fragmentation pathways to confidently annotate lipids in MALDI-MSI. The annotations are ranked using a novel score that demonstrates an area under the curve of 0.7 in ROC analyses using HPLC-MS and Target-Decoy validations. rMSIfragment applies to multiple MALDI-MSI sample types and experimental setups. Finally, we demonstrate that overlooking in-source fragments increases the number of incorrect annotations. Annotation workflows should consider in-source fragmentation tools such as rMSIfragment to increase annotation confidence and reduce the number of false positives.

MALDI Imaging Mass Spectrometry of High-Grade Gliomas: A Review of Recent Progress and Future Perspective

Glioblastoma (GBM) is the most common malignancy of the brain with a relatively short median survival and high mortality. Advanced age, high socioeconomic status, exposure to ionizing radiation, and other factors have been correlated with an increased incidence of GBM, while female sex hormones, history of allergies, and frequent use of specific drugs might exert protective effects against this disease. However, none of these explain the pathogenesis of GBM. The most recent WHO classification of CNS tumors classifies neoplasms based on their histopathological and molecular characteristics. Modern laboratory techniques, such as matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry, enable the comprehensive metabolic analysis of the tissue sample. MALDI imaging is able to characterize the spatial distribution of a wide array of biomolecules in a sample, in combination with histological features, without sacrificing the tissue integrity. In this review, we first provide an overview of GBM epidemiology, risk, and protective factors, as well as the recent WHO classification of CNS tumors. We then provide an overview of mass spectrometry workflow, with a focus on MALDI imaging, and recent advances in cancer research. Finally, we conclude the review with studies of GBM that utilized MALDI imaging and offer our perspective on future research.

Proteomic Imaging of Vestibular Schwannomas and Normal Nerves. Histopathologic Correlations

OBJECTIVES

Proteomic analysis of vestibular schwannoma (VS), non-vestibular schwannoma (NVS), and normal nerve (NN) using mass spectrometry and imaging of matrix assisted laser desorption ionization-time of flight (MALDI-TOF).

METHODS

Retrospective, qualitative, and descriptive study on VS, NVS, and NN. Samples were provided by our Tumor Bank. They were analyzed histologically then sprayed by acid matrix. The laser beam of MALDI performed desorption-ionization of the sample. A mass spectrogram (MS) was drawn depending on time of flight of ionized peptides, and MALDI-imaging was obtained which is a summation color spectrum depending on sample's peptide content. The slice was reexamined histologically and results compared with MALDI-imaging.

RESULTS

Fifty schwannomas were sampled, of which 27 exploitable: 22 VS (17 Antoni type A and five type B) and five NVS (all Antoni type B). Eleven NN were analyzed. Among the 22 VS, near-total correlation between MALDI-imaging and pathology was found in two cases (9.1%), partial correlation in four (18.2%), and no correlation in 16 (72.7%); correlations were more frequent in VS of the Antoni type B. MS showed a peptide spike at 2,000 m/z in 7 (31.8%) and 5,000 m/z in 21 (95.5%). Among the five NVS, near-total correlation was found in three cases (60%), partial correlation in one (20%), and no correlation in one (20%). MS showed a peptide spike at 2,000 m/z in two (40%) and 5,000 m/z in all (100%). Among the 11 NN, near-total correlation was found in nine cases (81.8%), partial correlation in one (9.1%), and no correlation in one (9.1%). MS showed no peptide spike at 2,000 or 5,000 m/z. Behind homogeneous areas on histology, there was great heterogeneity on MALDI-imaging and MS, regarding VS and NVS, but not NN.

CONCLUSIONS

There was a lack of correlation between MALDI-imaging and pathology in VS (except Antoni type B) as compared with NVS and NN. The lack of correlation in VS of the type A as compared with type B VS and NVS could be attributed to the overexpression of degeneration-associated proteins/peptides in VS of the type B as well as NVS that are better correlated with histologic findings. The two peptide spikes detected in schwannoma and not in NN opens up the prospect of tumor biomarkers identifiable by sequencing. The proteomic polymorphism found in VS and NVS was absent on histology which is a new morphologic characteristic of schwannoma. Further studies should be performed in the future to confirm the benefit and usefulness of the MALDI in the analysis of VS and NVS.

Tumor Heterogeneity in Glioblastomas: From Light Microscopy to Molecular Pathology

One of the main reasons for the aggressive behavior of glioblastoma (GBM) is its intrinsic intra-tumor heterogeneity, characterized by the presence of clonal and subclonal differentiated tumor cell populations, glioma stem cells, and components of the tumor microenvironment, which affect multiple hallmark cellular functions in cancer. "Tumor Heterogeneity" usually encompasses both inter-tumor heterogeneity (population-level differences); and intra-tumor heterogeneity (differences within individual tumors). Tumor heterogeneity may be assessed in a single time point (spatial heterogeneity) or along the clinical evolution of GBM (longitudinal heterogeneity). Molecular methods may detect clonal and subclonal alterations to describe tumor evolution, even when samples from multiple areas are collected in the same time point (spatial-temporal heterogeneity). In GBM, although the inter-tumor mutational landscape is relatively homogeneous, intra-tumor heterogeneity is a striking feature of this tumor. In this review, we will address briefly the inter-tumor heterogeneity of the CNS tumors that yielded the current glioma classification. Next, we will take a deeper dive in the intra-tumor heterogeneity of GBMs, which directly affects prognosis and response to treatment. Our approach aims to follow technological developments, allowing for characterization of intra-tumor heterogeneity, beginning with differences on histomorphology of GBM and ending with molecular alterations observed at single-cell level.

Hierarchical Cluster and Region of Interest Analyses Based on Mass Spectrometry Imaging of Human Brain Tumours

Imaging mass spectrometry (IMS) has been rarely used to examine specimens of human brain tumours. In the current study, high quality brain tumour samples were selected by tissue observation. Further, IMS analysis was combined with a new hierarchical cluster analysis (IMS-HCA) and region of interest analysis (IMS-ROI). IMS-HCA was successful in creating groups consisting of similar signal distribution images of glial fibrillary acidic protein (GFAP) and related multiple proteins in primary brain tumours. This clustering data suggested the relation of GFAP and these identified proteins in the brain tumorigenesis. Also, high levels of histone proteins, haemoglobin subunit α, tubulins, and GFAP were identified in a metastatic brain tumour using IMS-ROI. Our results show that IMS-HCA and IMS-ROI are promising techniques for identifying biomarkers using brain tumour samples.

Novel imaging and related techniques for studies of diseases of the central nervous system: a review

Imaging technologies for the analysis of the central nervous system are rapidly developing. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging, tracer-based magnetic resonance imaging, CLARITY technology and optogenetics can be used to visualize small molecules in brain tissues, the interstitial system of the brain and neuronal circuits in whole-brain samples. These tools serve as powerful technical means to explore the mechanisms underlying disease models and to evaluate the effects of drugs. Here, we review the constituting principles of these imaging techniques and describe their applications in the field of neuroscience.

Whole Cell MALDI Fingerprinting Is a Robust Tool for Differential Profiling of Two-Component Mammalian Cell Mixtures

MALDI fingerprinting was first described two decades ago as a technique to identify microbial cell lines. Microbial fingerprinting has since evolved into an automated platform for microorganism identification and classification, which is now routinely used in clinical and environmental sectors. The extension of fingerprinting to mammalian cells has yet to progress partly due to compartmentalization of eukaryotic cells and overall higher cellular complexity. A number of publications on mammalian whole cell fingerprinting suggest that the method could be useful for classification of different cell types, cell states, and monitoring cell differentiation. We report the optimization of MALDI fingerprinting workflow parameters for mammalian cells and its application for differential profiling of mammalian cell lines and two-component cell line mixtures. Murine fallopian tube cells and high-grade ovarian carcinoma cell lines and their mixtures are used as model mammalian cell lines. Two-component cell mixtures serve to determine the method's feasibility for complex biological samples as the ability to detect cancer cells in a mixed cell population. The level of detection of cancer cells in the two-component mixture by principle component analysis (PCA) starts to deteriorate at 5% but with application of a different statistical approach, Wilcoxon rank sum test, the level of detection was determined to be 1%. The ability to differentiate heterogeneous cell mixtures will help further extend whole cell MALDI fingerprinting to complex biological systems. Graphical Abstract.

Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) enables localization of analytes of interest along with histology. More specifically, MALDI-IMS identifies the distributions of proteins, peptides, small molecules, lipids, and drugs and their metabolites in tissues, with high spatial resolution. This unique capacity to directly analyze tissue samples without the need for lengthy sample preparation reduces technical variability and renders MALDI-IMS ideal for the identification of potential diagnostic and prognostic biomarkers and disease gradation. MALDI-IMS has evolved rapidly over the last decade and has been successfully used in both medical and basic research by scientists worldwide. In this review, we explore the clinical applications of MALDI-IMS, focusing on the major cancer types and neurodegenerative diseases. In particular, we re-emphasize the diagnostic potential of IMS and the challenges that must be confronted when conducting MALDI-IMS in clinical settings. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Droplet-Based Liquid Extraction for Spatially-Resolved Microproteomics Analysis of Tissue Sections

Obtaining information on protein content while keeping their localization on tissue or organ is of importance in different domains to understand pathophysiological processes. There is increasing interest in studying the microenvironment and heterogeneity of tumors, which currently is difficult with existing proteomics techniques. The advent of new techniques, like MALDI Mass Spectrometry Imaging, made a significant progress in the last decade but is characterized by a number of inherent drawbacks. One of these is the limited identification of proteins. New alternative approaches such as spatially-resolved liquid microextraction have recently been proposed to overcome this limitation. In this chapter, we describe strategies using liquid microjunction to perform extraction of previously digested peptides or of intact proteins from tissue section in a localized manner.

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and matrix deposition by micro-spraying. The generated 70μm spatial resolution image datasets were further processed by individual or global segmentation in order to cluster the tissues according to their molecular protein signature. The clustering gives 3 main distinct groups. Within the tissues the ROIs (regions of interest) defined by these groups were used for microproteomics by micro-extraction of the tryptic peptides after on-tissue enzymatic digestion. More than 2500 proteins including 22 alternative proteins (AltProt) are identified by the Shotgun microproteomics. Statistical analysis on the basis of the label free quantification of the proteins shows a similar classification to the MALDI MSI segmentation into 3 groups. Functional analysis performed on each group reveals sub-networks related to neoplasia for group 1, glioma with inflammation for group 2 and neurogenesis for group 3. This demonstrates the interest on these new non-targeted large molecular data combining both MALDI MSI and microproteomics data, for tumor classification. This analysis provides new insights into grade III glioma organization. This specific information could allow a more accurate classification of the biopsies according to the prognosis and the identification of potential new targeted therapeutic options. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

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.

Monitoring therapeutic monoclonal antibodies in brain tumor

Bevacizumab induces normalization of abnormal blood vessels, making them less leaky. By binding to vascular endothelial growth factor, it indirectly attacks the vascular tumor mass. The optimal delivery of targeted therapies including monoclonal antibodies or anti-angiogenesis drugs to the target tissue highly depends on the blood-brain barrier permeability. It is therefore critical to investigate how drugs effectively reach the tumor. In situ investigation of drug distribution could provide a better understanding of pharmacological agent action and optimize chemotherapies for solid tumors. We developed an imaging method coupled to protein identification using matrix-assisted laser desorption/ionization mass spectrometry. This approach monitored bevacizumab distribution within the brain structures, and especially within the tumor, without any labeling.

MALDI mass spectrometry imaging analysis of pituitary adenomas for near-real-time tumor delineation

We present a proof of concept study designed to support the clinical development of mass spectrometry imaging (MSI) for the detection of pituitary tumors during surgery. We analyzed by matrix-assisted laser desorption/ionization (MALDI) MSI six nonpathological (NP) human pituitary glands and 45 hormone secreting and nonsecreting (NS) human pituitary adenomas. We show that the distribution of pituitary hormones such as prolactin (PRL), growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid stimulating hormone (TSH) in both normal and tumor tissues can be assessed by using this approach. The presence of most of the pituitary hormones was confirmed by using MS/MS and pseudo-MS/MS methods, and subtyping of pituitary adenomas was performed by using principal component analysis (PCA) and support vector machine (SVM). Our proof of concept study demonstrates that MALDI MSI could be used to directly detect excessive hormonal production from functional pituitary adenomas and generally classify pituitary adenomas by using statistical and machine learning analyses. The tissue characterization can be completed in fewer than 30 min and could therefore be applied for the near-real-time detection and delineation of pituitary tumors for intraoperative surgical decision-making.

Study of Protein Expression in Peri-Infarct Tissue after Cerebral Ischemia

In this work, we report our study of protein expression in rat peri-infarct tissue, 48 h after the induction of permanent focal cerebral ischemia. Two proteomic approaches, gel electrophoresis with mass spectrometry and combined fractional diagonal chromatography (COFRADIC), were performed using tissue samples from the periphery of the induced cerebral ischemic lesions, using tissue from the contra-lateral hemisphere as a control. Several protein spots (3408) were identified by gel electrophoresis, and 11 showed significant differences in expression between peri-infarct and contra-lateral tissues (at least 3-fold, p < 0.05). Using COFRADIC, 5412 proteins were identified, with 72 showing a difference in expression. Apart from blood-related proteins (such as serum albumin), both techniques showed that the 70 kDa family of heat shock proteins were highly expressed in the peri-infarct tissue. Further studies by 1D and 2D western blotting and immunohistochemistry revealed that only one member of this family (the inducible form, HSP72 or HSP70i) is specifically expressed by the peri-infarct tissue, while the majority of this family (the constitutive form, HSC70 or HSP70c) is expressed in the whole brain. Our data support that HSP72 is a suitable biomarker of peri-infarct tissue in the ischemic brain.

Spatial neuroproteomics using imaging mass spectrometry

The nervous system constitutes arguably the most complicated and least understood cellular network in the human body. This consequently manifests itself in the fact that the molecular bases of neurodegenerative diseases remain unknown. The limited understanding of neurobiological mechanisms relates directly to the lack of appropriate bioanalytical technologies that allow highly resolved, sensitive, specific and comprehensive molecular imaging in complex biological matrices. Imaging mass spectrometry (IMS) is an emerging technique for molecular imaging. The technique is characterized by its high chemical specificity allowing comprehensive, spatial protein and peptide profiling in situ. Imaging MS represents therefore a powerful approach for investigation of spatio-temporal protein and peptide regulations in CNS derived tissue and cells. This review aims to provide a concise overview of major developments and applications concerning imaging mass spectrometry based protein and peptide profiling in neurobiological and biomedical research. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

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.

Oxidative stress, redox regulation and diseases of cellular differentiation

BACKGROUND

Within cells, there is a narrow concentration threshold that governs whether reactive oxygen species (ROS) induce toxicity or act as second messengers.

SCOPE OF REVIEW

We discuss current understanding of how ROS arise, facilitate cell signaling, cause toxicities and disease related to abnormal cell differentiation and those (primarily) sulfur based pathways that provide nucleophilicity to offset these effects.

PRIMARY CONCLUSIONS

Cellular redox homeostasis mediates a plethora of cellular pathways that determine life and death events. For example, ROS intersect with GSH based enzyme pathways to influence cell differentiation, a process integral to normal hematopoiesis, but also affecting a number of diverse cell differentiation related human diseases. Recent attempts to manage such pathologies have focused on intervening in some of these pathways, with the consequence that differentiation therapy targeting redox homeostasis has provided a platform for drug discovery and development.

GENERAL SIGNIFICANCE

The balance between electrophilic oxidative stress and protective biomolecular nucleophiles predisposes the evolution of modern life forms. Imbalances of the two can produce aberrant redox homeostasis with resultant pathologies. Understanding the pathways involved provides opportunities to consider interventional strategies. This article is part of a Special Issue entitled Redox regulation of differentiation and de-differentiation.