MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice

Analysis of Hashimoto's thyroiditis on fine needle aspiration samples by MALDI-Imaging

Matrix-Assisted Laser Desorption/Ionization (MALDI)-Mass Spectrometry imaging (MSI) has been applied in various diseases aimed to biomarkers discovery. In this study diagnosis and prognosis of Hashimoto Thyroiditis (HT) in cytopathology by MALDI-MSI has been investigated. Specimens from a routine series of subjects who underwent UltraSound-guided thyroid Fine Needle Aspirations (FNAs) were used. The molecular classifier trained in a previous study was modified to include HT as a separate entity in the group of benign lesions, in the diagnostic proteomic triage of thyroid nodules. The statistical analysis confirmed the existence of signals that HT shares with hyperplastic lesions and others that are specific and characterize this subgroup. Statistically relevant HT-related peaks were included in the model. Then, the discriminatory capability of the classifier was tested in a second validation phase, showing a good agreement with cytological diagnoses. The possibility to overlap the molecular signatures of both the lymphocytes and epithelial cells components (ROIs or pixel-by-pixel analysis) confirmed the composite proteomic background of HT. These results open the way to their possible translation as alternative serum biomarkers of this autoimmune condition.

Collagen analysis with mass spectrometry

Mass spectrometry-based techniques can be applied to investigate collagen with respect to identification, quantification, supramolecular organization, and various post-translational modifications. The continuous interest in collagen research has led to a shift from techniques to analyze the physical characteristics of collagen to methods to study collagen abundance and modifications. In this review, we illustrate the potential of mass spectrometry for in-depth analyses of collagen.

Implementation of MALDI Mass Spectrometry Imaging in Cancer Proteomics Research: Applications and Challenges

Studying the proteome–the entire set of proteins in cells, tissues, organs and body fluids—is of great relevance in cancer research, as differential forms of proteins are expressed in response to specific intrinsic and extrinsic signals. Discovering protein signatures/pathways responsible for cancer transformation may lead to a better understanding of tumor biology and to a more effective diagnosis, prognosis, recurrence and response to therapy. Moreover, proteins can act as a biomarker or potential drug targets. Hence, it is of major importance to implement proteomic, particularly mass spectrometric, approaches in cancer research, to provide new crucial insights into tumor biology. Recently, mass spectrometry imaging (MSI) approaches were implemented in cancer research, to provide individual molecular characteristics of each individual tumor while retaining molecular spatial distribution, essential in the context of personalized disease management and medicine.

Mass spectrometry imaging-based metabolomics to visualize the spatially resolved reprogramming of carnitine metabolism in breast cancer

New insights into tumor-associated metabolic reprogramming have provided novel vulnerabilities that can be targeted for cancer therapy. Here, we propose a mass spectrometry imaging (MSI)-based metabolomic strategy to visualize the spatially resolved reprogramming of carnitine metabolism in heterogeneous breast cancer. Methods: A wide carnitine coverage MSI method was developed to investigate the spatial alternations of carnitines in cancer tissues of xenograft mouse models and human samples. Spatial expression of key metabolic enzymes that are closely associated with the altered carnitines was examined in adjacent cancer tissue sections. Results: A total of 17 carnitines, including L-carnitine, 6 short-chain acylcarnitines, 3 middle-chain acylcarnitines, and 7 long-chain acylcarnitines were imaged. L-carnitine and short-chain acylcarnitines are significantly reprogrammed in breast cancer. A classification model based on the carnitine profiles of 170 cancer samples and 128 normal samples enables an accurate identification of breast cancer. CPT 1A, CPT 2, and CRAT, which are extensively involved in carnitine system-mediated fatty acid β-oxidation pathway were also found to be abnormally expressed in breast cancer. Remarkably, the expressions of CPT 2 and CRAT were found for the first time to be altered in breast cancer. Conclusion: These data not only expand our understanding of the complex tumor metabolic reprogramming, but also provide the first evidence that carnitine metabolism is reprogrammed at both the metabolite and enzyme levels in breast cancer.

DIUTHAME enables matrix-free mass spectrometry imaging of frozen tissue sections

RATIONALE

A recently developed matrix-free laser desorption/ionization method, DIUTHAME (desorption ionization using through-hole alumina membrane), was examined for the feasibility of mass spectrometry imaging (MSI) applied to frozen tissue sections. The permeation behavior of DIUTHAME is potentially useful for MSI as positional information may not be distorted during the extraction of analytes from a sample.

METHODS

The through-hole porous alumina membranes used in the DIUTHAME chips were fabricated by wet anodization, were 5 μm thick, and had the desired values of 200 nm through-hole diameter and 50% open aperture ratio. Mouse brain frozen tissue sections on indium tin oxide (ITO)-coated slides were covered using the DIUTHAME chips and were subjected to MSI experiments in commercial time-of-flight mass spectrometers equipped with solid-state UV lasers after thawing and drying without matrix application.

RESULT

Mass spectra and mass images were successfully obtained from the frozen tissue sections using DIUTHAME as the ionization method. The mass spectra contained rich peaks in the phospholipid mass range free from the chemical background owing to there being no matrix-derived peaks in that range. DIUTHAME-MSI delivered high-quality mass images that reflected the anatomy of the brain tissue.

CONCLUSIONS

Analytes can be extracted from frozen tissue by capillary action of the through-holes in DIUTHAME and moisture contained in the tissue without distorting positional information of the analytes. The sample preparation for frozen tissue sections in DIUTHAME-MSI is simple, requiring no specialized skills or dedicated apparatus for matrix application. DIUTHAME can facilitate MSI at a low mass, as there is no interference from matrix-derived peaks, and should provide high-quality, reproducible mass images more easily than MALDI-MSI.

Across the spectrum: integrating multidimensional metal analytics for in situ metallomic imaging

To know how much of a metal species is in a particular location within a biological context at any given time is essential for understanding the intricate roles of metals in biology and is the fundamental question upon which the field of metallomics was born. Simply put, seeing is powerful. With the combination of spectroscopy and microscopy, we can now see metals within complex biological matrices complemented by information about associated molecules and their structures. With the addition of mass spectrometry and particle beam based techniques, the field of view grows to cover greater sensitivities and spatial resolutions, addressing structural, functional and quantitative metallomic questions from the atomic level to whole body processes. In this perspective, I present a paradigm shift in the way we relate to and integrate current and developing metallomic analytics, highlighting both familiar and perhaps less well-known state of the art techniques for in situ metallomic imaging, specific biological applications, and their use in correlative studies. There is a genuine need to abandon scientific silos and, through the establishment of a metallomic scientific platform for further development of multidimensional analytics for in situ metallomic imaging, we have an incredible opportunity to enhance the field of metallomics and demonstrate how discovery research can be done more effectively.

Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence

Spatial metabolomics is an emerging field of omics research that has enabled localizing metabolites, lipids, and drugs in tissue sections, a feat considered impossible just two decades ago. Spatial metabolomics and its enabling technology-imaging mass spectrometry-generate big hyper-spectral imaging data that have motivated the development of tailored computational methods at the intersection of computational metabolomics and image analysis. Experimental and computational developments have recently opened doors to applications of spatial metabolomics in life sciences and biomedicine. At the same time, these advances have coincided with a rapid evolution in machine learning, deep learning, and artificial intelligence, which are transforming our everyday life and promise to revolutionize biology and healthcare. Here, we introduce spatial metabolomics through the eyes of a computational scientist, review the outstanding challenges, provide a look into the future, and discuss opportunities granted by the ongoing convergence of human and artificial intelligence.

MALDI imaging directed laser ablation tissue microsampling for data independent acquisition proteomics

A multimodal workflow for mass spectrometry imaging was developed that combines MALDI imaging with protein identification and quantification by liquid chromatography tandem mass spectrometry (LC-MS/MS). Thin tissue sections were analyzed by MALDI imaging, and the regions of interest (ROI) were identified using a smoothing and edge detection procedure. A midinfrared laser at 3-μm wavelength was used to remove the ROI from the brain tissue section after MALDI mass spectrometry imaging (MALDI MSI). The captured material was processed using a single-pot solid-phase-enhanced sample preparation (SP3) method and analyzed by LC-MS/MS using ion mobility (IM) enhanced data independent acquisition (DIA) to identify and quantify proteins; more than 600 proteins were identified. Using a modified database that included isoform and the post-translational modifications chain, loss of the initial methionine, and acetylation, 14 MALDI MSI peaks were identified. Comparison of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the identified proteins was achieved through an evolutionary relationships classification system.

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.

In situ analysis of oxytetracycline tablets based on matrix-assisted laser desorption/ionization mass spectrometry imaging

RATIONALE

A thorough understanding of the content and distribution of active ingredients in pharmaceuticals is essential for drug efficacy and safety. Technological advancements in mass spectrometry imaging present an opportunity for methodological innovation by providing qualification and quantification analysis, as well as spatial information, in the same assay, which has great potential for applications in the rapid analysis and quality control of drugs.

METHODS

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was employed to directly analyze oxytetracycline tablets in order to map the distribution of the active constituent within the whole tablet. Quantitative analysis was capable of differentiating tablets containing various doses of the active pharmaceutical ingredient.

RESULTS

To establish the methodology, detailed factors that influence matrix spraying and spatial resolution during sample preparation and the data acquisition process were optimized systematically. Quantitative analysis could differentiate the tablets containing various doses of the active compound. The proposed method was successfully applied to analyze real commercial tablets.

CONCLUSIONS

The developed method could successfully achieve the spatial location of oxytetracycline in actual tablet samples. These results could contribute to pharmaceutical tracing technology, especially the formulation process of tablets, which is helpful for monitoring the quality of pharmaceutical products and guaranteeing drug security.

Differentiation of lymphocytic-plasmacytic enteropathy and small cell lymphoma in cats using histology-guided mass spectrometry

BACKGROUND

Differentiation of lymphocytic-plasmacytic enteropathy (LPE) from small cell lymphoma (SCL) in cats can be challenging.

HYPOTHESIS/OBJECTIVE

Histology-guided mass spectrometry (HGMS) is a suitable method for the differentiation of LPE from SCL in cats.

ANIMALS

Forty-one cats with LPE and 52 cats with SCL.

METHODS

This is a retrospective clinicopathologic study. Duodenal tissue samples of 17 cats with LPE and 22 cats with SCL were subjected to HGMS, and the acquired data were used to develop a linear discriminate analysis (LDA) machine learning algorithm. The algorithm was subsequently validated using a separate set of 24 cats with LPE and 30 cats with SCL. Cases were classified as LPE or SCL based on a consensus by an expert panel consisting of 5-7 board-certified veterinary specialists. Histopathology, immunohistochemistry, and clonality testing were available for all cats. The panel consensus classification served as a reference for the calculation of test performance parameters.

RESULTS

Relative sensitivity, specificity, and accuracy of HGMS were 86.7% (95% confidence interval [CI]: 74.5%-98.8%), 91.7% (95% CI: 80.6%-100%), and 88.9% (95% CI: 80.5%-97.3%), respectively. Comparatively, the clonality testing had a sensitivity, specificity, and accuracy of 85.7% (95% CI: 72.8%-98.7%), 33.3% (95% CI: 14.5%-52.2%), and 61.5% (95% CI: 48.3%-74.8%) relative to the panel decision.

CONCLUSIONS AND CLINICAL IMPORTANCE

Histology-guided mass spectrometry was a reliable technique for the differentiation of LPE from SCL in duodenal formalin-fixed paraffin-embedded samples of cats and might have advantages over tests currently considered state of the art.

Profiling embryonic stem cell differentiation by MALDI TOF mass spectrometry: development of a reproducible and robust sample preparation workflow

MALDI TOF mass spectrometry (MS) is widely used to characterise and biotype bacterial samples, but a complementary method for profiling of mammalian cells is still underdeveloped. Current approaches vary dramatically in their sample preparation methods and are not suitable for high-throughput studies. In this work, we present a universal workflow for mammalian cell MALDI TOF MS analysis and apply it to distinguish ground-state naïve and differentiating mouse embryonic stem cells (mESCs), which can be used as a model for drug discovery. We employed a systematic approach testing many parameters to evaluate how efficiently and reproducibly each method extracted unique mass features from four different human cell lines. These data enabled us to develop a unique mammalian cell MALDI TOF workflow involving a freeze-thaw cycle, methanol fixing and a CHCA matrix to generate spectra that robustly phenotype different cell lines and are highly reproducible in peak identification across replicate spectra. We applied our optimised workflow to distinguish naïve and differentiating populations using multivariate analysis and reproducibly identify unique features. We were also able to demonstrate the compatibility of our optimised method for current automated liquid handling technologies. Consequently, our MALDI TOF MS profiling method enables identification of unique features and robust phenotyping of mESC differentiation in under 1 hour from culture to analysis, which is significantly faster and cheaper when compared with conventional methods such as qPCR. This method has the potential to be automated and can in the future be applied to profile other cell types and expanded towards cellular MALDI TOF MS screening assays.

Enhancement of On-tissue Chemical Derivatization by Laser-Assisted Tissue Transfer for MALDI MS Imaging

The development of on-tissue chemical derivatization methods for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) of small endogenous metabolites in tissues has attracted great attention for their advantages in improving detection sensitivity and ionization efficiency of poorly ionized and low abundant metabolites. Herein, a laser-assisted tissue transfer (LATT) technique was developed to enhance on-tissue derivatization of small molecules. Using a focused blue laser, a thin-layer tissue film (∼1 μm) was transferred to an acceptor slide from a 6 μm dry tissue section preliminarily coated with derivatization and matrix reagents. The acceptor slide with its ablated constituents was then imaged by MALDI MS. On-tissue chemical derivatization with amino-specific derivatization reagent 4-hydroxy-3-methoxycinnamaldehyde (CA) was carried out on LATT system. 20-235 folds increase in signal intensity for CA derivatized metabolites such as amino acids, neurotransmitters, and dipeptides were observed from rat brain tissues in comparison with conventional incubation-based derivatization. This technique was further extended to derivatize steroids with Girard reagent T (GirT). The remarkable derivatization efficiency can mainly be attributed to the minimization of ion suppression effects due to the reduced thickness of tissue section and endogenous components. Additionally, shorter derivatization time with no obvious metabolite delocalization was achieved using LATT method. These results demonstrate the advantages of LATT in the enhancement of on-tissue derivatization for the more specific and sensitive imaging of small metabolites in tissues with MALDI MS.

Molecular Heterogeneity of Papillary Thyroid Cancer: Comparison of Primary Tumors and Synchronous Metastases in Regional Lymph Nodes by Mass Spectrometry Imaging

Intra-tumor heterogeneity results from both genetic heterogeneity of cancer (sub)clones and phenotypic plasticity of cancer cells that could be induced by different local microenvironments. Here, we used mass spectrometry imaging (MSI) to compare molecular profiles of primary tumors located in the thyroid gland and their synchronous metastases in regional lymph nodes to analyze phenotypic heterogeneity in papillary thyroid cancer. Two types of cancerous (primary tumor and metastasis) and two types of not cancerous (thyroid gland and lymph node) regions of interest (ROIs) were delineated in postoperative material from 11 patients, then the distribution of tryptic peptides (spectral components) was analyzed by MSI in all tissue regions. Moreover, tryptic peptides identified by shotgun proteomics in corresponding tissue lysates were matched to components detected by MSI to enable their hypothetical protein annotation. Unsupervised segmentation of all cancer ROIs revealed that different clusters dominated in tumor ROIs and metastasis ROIs. The intra-patient similarity between thyroid and tumor ROIs was higher than the intra-patient similarity between tumor and metastasis ROIs. Moreover, the similarity between tumor and its metastasis from the same patients was lower than similarities among tumors and among metastases from different patients (inter-patient similarity was higher for metastasis ROIs than for tumor ROIs). Components differentiating between tumor and its metastases were annotated as proteins involved in the organization of the cytoskeleton and chromatin, as well as proteins involved in immunity-related functions. We concluded that phenotypical heterogeneity between primary tumor and lymph node metastases from the same patient was higher than inter-tumor heterogeneity between primary tumors from different patients.

Tunneling nanotubes: A bridge for heterogeneity in glioblastoma and a new therapeutic target?

BACKGROUND

The concept of tumour heterogeneity is not novel but is fast becoming a paradigm by which to explain part of the highly recalcitrant nature of aggressive malignant tumours. Glioblastoma is a prime example of such difficult-to-treat, invasive, and incurable malignancies. With the advent of the post-genomic age and increased access to next-generation sequencing technologies, numerous publications have described the presence and extent of intratumoural and intertumoural heterogeneity present in glioblastoma. Moreover, there have been numerous reports more directly correlating the heterogeneity of glioblastoma to its refractory, reoccurring, and inevitably terminal nature. It is therefore prudent to consider the different forms of heterogeneity seen in glioblastoma and how to harness this understanding to better strategize novel therapeutic approaches. One of the most central questions of tumour heterogeneity is how these numerous different cell types (both tumour and non-tumour) in the tumour mass communicate.

RECENT FINDINGS

This chapter provides a brief review on the variable heterogeneity of glioblastoma, with a focus on cellular heterogeneity and on modalities of communication that can induce further molecular diversity within the complex and ever-evolving tumour microenvironment. We provide particular emphasis on the emerging role of actin-based cellular conduits called tunnelling nanotubes (TNTs) and tumour microtubes (TMs) and outline the perceived current problems in the field that need to be resolved before pharmacological targeting of TNTs can become a reality.

CONCLUSIONS

We conclude that TNTs and TMs provide a new and exciting avenue for the therapeutic targeting of glioblastoma and that numerous inroads have already made into TNT and TM biology. However, to target TMs and TNTs, several advances must be made before this aim can become a reality.

Deciphering Metabolic Heterogeneity by Single-Cell Analysis

Single-cell analysis provides insights into cellular heterogeneity and dynamics of individual cells. This Feature highlights recent developments in key analytical techniques suited for single-cell metabolic analysis with a special focus on mass spectrometry-based analytical platforms and RNA-seq as well as imaging techniques that reveal stochasticity in metabolism.

Proteomic Biomarkers for the Detection of Endometrial Cancer

Endometrial cancer is the leading gynaecological malignancy in the western world and its incidence is rising in tandem with the global epidemic of obesity. Early diagnosis is key to improving survival, which at 5 years is less than 20% in advanced disease and over 90% in early-stage disease. As yet, there are no validated biological markers for its early detection. Advances in high-throughput technologies and machine learning techniques now offer unique and promising perspectives for biomarker discovery, especially through the integration of genomic, transcriptomic, proteomic, metabolomic and imaging data. Because the proteome closely mirrors the dynamic state of cells, tissues and organisms, proteomics has great potential to deliver clinically relevant biomarkers for cancer diagnosis. In this review, we present the current progress in endometrial cancer diagnostic biomarker discovery using proteomics. We describe the various mass spectrometry-based approaches and highlight the challenges inherent in biomarker discovery studies. We suggest novel strategies for endometrial cancer detection exploiting biologically important protein biomarkers and set the scene for future directions in endometrial cancer biomarker research.

Improvement of Sensitivity and Reproducibility for Imaging of Endogenous Metabolites by Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry

Matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) is a powerful technique to visualize the distributions of biomolecules without any labeling. In MALDI-MSI experiments, the choice of matrix deposition method is important for acquiring favorable MSI data with high sensitivity and high reproducibility. Generally, manual or automated spray-coating and automated sublimation methods are used, but these methods have some drawbacks with respect to detection sensitivity, spatial resolution, and data reproducibility. Herein, we present an optimized matrix deposition method of sublimation coupled with recrystallization using 9-aminoacridine (9-AA) as a matrix capable of ionizing endogenous metabolites. The matrix recrystallization process after sublimation was optimized for the solvent concentration and reaction temperature for matrix-metabolite co-crystallization. This optimized method showed excellent reproducibility and spatial resolution compared to the automatic spray-coating method. Furthermore, the recrystallization step after sublimation remarkably improved the detectability of metabolites, including amino acids, nucleotide derivatives, and lipids, compared with the conventional sublimation method. To date, there have been no other reports of 9-AA-based sublimation combined with recrystallization. The present method provides an easy, sensitive, and reproducible matrix deposition method for MALDI-MSI of endogenous metabolites. Graphical Abstract.

Unsupervised segmentation of mass spectrometric ion images characterizes morphology of tissues

MOTIVATION

Mass spectrometry imaging (MSI) characterizes the spatial distribution of ions in complex biological samples such as tissues. Since many tissues have complex morphology, treatments and conditions often affect the spatial distribution of the ions in morphology-specific ways. Evaluating the selectivity and the specificity of ion localization and regulation across morphology types is biologically important. However, MSI lacks algorithms for segmenting images at both single-ion and spatial resolution.

RESULTS

This article contributes spatial-Dirichlet Gaussian mixture model (DGMM), an algorithm and a workflow for the analyses of MSI experiments, that detects components of single-ion images with homogeneous spatial composition. The approach extends DGMMs to account for the spatial structure of MSI. Evaluations on simulated and experimental datasets with diverse MSI workflows demonstrated that spatial-DGMM accurately segments ion images, and can distinguish ions with homogeneous and heterogeneous spatial distribution. We also demonstrated that the extracted spatial information is useful for downstream analyses, such as detecting morphology-specific ions, finding groups of ions with similar spatial patterns, and detecting changes in chemical composition of tissues between conditions.

AVAILABILITY AND IMPLEMENTATION

The data and code are available at https://github.com/Vitek-Lab/IonSpattern.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MALDI imaging in Fabry nephropathy: a multicenter study

BACKGROUND

The current study evaluates the application of histology and in situ proteomics (MALDI-MSI) in Fabry nephropathy (FN), showing investigative and classification role for this coupled approach.

METHODS

A retrospective series of 14 formalin fixed paraffin embedded (FFPE) renal biopsies with diagnosis of FN and 1 biopsy from a patient bearing a galactosidase-α (GLA) genetic variant of unknown significance (GVUS, c.376A>G) have been classified for clinical characteristics. Groups were compared for histological differences (following the ISGFN scoring system). Moreover, renal biopsies from these cases have been analyzed with MALDI-MSI as previously described to find proteomic signatures among different mutations and phenotypes.

RESULTS

Comparison of clinical features revealed lower mean 24 h proteinuria in females (225 mg/24 h) than in males (1477.5 mg/24 h, p = 0.006). As for clinical characteristics, females significantly differed from males only for lower arterial sclerosis, with a mean value of 0.82 vs. 1.05 (p = 0.001). Proteomic analysis demonstrated specific signatures in different subgroups of FN patients. Moreover, MALDI correctly classified cases with undetermined mutation or GVUS.

CONCLUSIONS

The present study demonstrated the feasible application of MALDI-MSI in the analysis of FN FFPE renal biopsies, allowing the detection of putative signatures for phenotypic distinction and demonstrating genetic classification capabilities.

MALDI Mass Spectrometry Imaging Linked with Top-Down Proteomics as a Tool to Study the Non-Small-Cell Lung Cancer Tumor Microenvironment

Advanced non-small-cell lung cancer (NSCLC) is generally linked with a poor prognosis and is one of the leading causes of cancer-related deaths worldwide. Since only a minority of the patients respond well to chemotherapy and/or targeted therapies, immunotherapy might be a valid alternative in the lung cancer treatment field, as immunotherapy attempts to strengthen the body’s own immune response to recognize and eliminate malignant tumor cells. However, positive response patterns to immunotherapy remain unclear. In this study, we demonstrate how immune-related factors could be visualized from single NSCLC tissue sections (Biobank@UZA) while retaining their spatial information by using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), in order to unravel the molecular profile of NSCLC patients. In this way, different regions in lung cancerous tissues could be discriminated based on the molecular composition. In addition, we linked visualization (MALDI MSI) and identification (based on liquid chromatography higher resolution mass spectrometry) of the molecules of interest for the correct biological interpretation of the observed molecular differences within the area in which these molecules are detected. This is of major importance to fully understand the underlying molecular profile of the NSCLC tumor microenvironment.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

Therapeutic targeting of glutaminolysis as an essential strategy to combat cancer

Metabolic reprogramming in cancer targets glutamine metabolism as a key mechanism to provide energy, biosynthetic precursors and redox requirements to allow the massive proliferation of tumor cells. Glutamine is also a signaling molecule involved in essential pathways regulated by oncogenes and tumor suppressor factors. Glutaminase isoenzymes are critical proteins to control glutaminolysis, a key metabolic pathway for cell proliferation and survival that directs neoplasms' fate. Adaptive glutamine metabolism can be altered by different metabolic therapies, including the use of specific allosteric inhibitors of glutaminase that can evoke synergistic effects for the therapy of cancer patients. We also review other clinical applications of in vivo assessment of glutaminolysis by metabolomic approaches, including diagnosis and monitoring of cancer.

A new optimization strategy for MALDI FTICR MS tissue analysis for untargeted metabolomics using experimental design and data modeling

Ultra-high-resolution imaging mass spectrometry using matrix-assisted laser desorption ionization (MALDI) MS coupled to a Fourier transform ion cyclotron resonance (FTICR) mass analyzer is a powerful technique for the visualization of small molecule distribution within biological tissues. The FTICR MS provides ultra-high resolving power and mass accuracy that allows large molecular coverage and molecular formula assignments, both essential for untargeted metabolomics analysis. These performances require fine optimizations of the MALDI FTICR parameters. In this context, this study proposes a new strategy, using experimental design, for the optimization of ion transmission voltages and MALDI parameters, for tissue untargeted metabolomics analysis, in both positive and negative ionization modes. These experiments were conducted by assessing the effects of nine factors for ion transmission voltages and four factors for MALDI on the number of peaks, the weighted resolution, and the mean error within m/z 150-1000 mass range. For this purpose, fractional factorial designs were used with multiple linear regression (MLR) to evaluate factor effects and to optimize parameter values. The optimized values of ion transmission voltages (RF amplitude TOF, RF amplitude octopole, frequency transfer optic, RF frequency octopole, deflector plate, funnel 1, skimmer, funnel RF amplitude, time-of-flight, capillary exit), MALDI parameters (laser fluence, number of laser shots), and detection parameters (data size, number of scans) led to an increase of 32% and 18% of the number of peaks, an increase of 8% and 39% of the resolution, and a decrease of 56% and 34% of the mean error in positive and negative ionization modes, respectively. Graphical abstract.

How many human proteoforms are there?

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

Beyond tissue concentrations: antifungal penetration at the site of infection

Despite advances in antifungal therapy, invasive fungal infections remain a significant cause of morbidity and mortality worldwide. One important factor contributing to the relative ineffectiveness of existing antifungal drugs is insufficient drug exposure at the site of infection. Despite the importance of this aspect of antifungal therapy, we generally lack a full appreciation of how antifungal drugs distribute, penetrate, and interact with their target organisms in different tissue subcompartments. A better understanding of drug distribution will be critical to guide appropriate use of currently available antifungal drugs, as well as to aid development of new agents. Herein we briefly review current perspectives of antifungal drug exposure at the site of infection and describe a new technique, matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging, which has the potential to greatly expand our understanding of drug penetration.

Rapid Identification of Ischemic Injury in Renal Tissue by Mass-Spectrometry Imaging

The increasing analytical speed of mass-spectrometry imaging (MSI) has led to growing interest in the medical field. Acute kidney injury is a severe disease with high morbidity and mortality. No reliable cut-offs are known to estimate the severity of acute kidney injury. Thus, there is a need for new tools to rapidly and accurately assess acute ischemia, which is of clinical importance in intensive care and in kidney transplantation. We investigated the value of MSI to assess acute ischemic kidney tissue in a porcine model. A perfusion model was developed where paired kidneys received warm (severe) or cold (minor) ischemia ( n = 8 per group). First, ischemic tissue damage was systematically assessed by two blinded pathologists. Second, MALDI-MSI of kidney tissues was performed to study the spatial distributions and compositions of lipids in the tissues. Histopathological examination revealed no significant difference between kidneys, whereas MALDI-MSI was capable of a detailed discrimination of severe and mild ischemia by differential expression of characteristic lipid-degradation products throughout the tissue within 2 h. In particular, lysolipids, including lysocardiolipins, lysophosphatidylcholines, and lysophosphatidylinositol, were dramatically elevated after severe ischemia. This study demonstrates the significant potential of MSI to differentiate and identify molecular patterns of early ischemic injury in a clinically acceptable time frame. The observed changes highlight the underlying biochemical processes of acute ischemic kidney injury and provide a molecular classification tool that can be deployed in assessment of acute ischemic kidney injury.

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

While mass spectrometry (MS)-based quantification of small molecules has been successfully used for decades, targeted MS has only recently been used by the proteomics community to investigate clinical questions such as biomarker verification and validation. Targeted MS holds the promise of a paradigm shift in the quantitative determination of proteins. Nevertheless, targeted quantitative proteomics requires improvisation in making sample processing, instruments, and data analysis more accessible. In the backdrop of the genomic era reaching its zenith, certain questions arise: is the proteomic era about to come? If we are at the beginning of a new future for protein quantification, are we prepared to incorporate targeted proteomics at the benchside for basic research and at the bedside for the good of patients? Here, an overview of the knowledge required to perform targeted proteomics as well as its applications is provided. A special emphasis is placed on upcoming areas such as peptidomics, proteoform research, and mass spectrometry imaging, where the utilization of targeted proteomics is expected to bring forth new avenues. The limitations associated with the acceptance of this technique for mainstream usage are also highlighted. Also see the video abstract here https://youtu.be/mieB47B8gZw.

Single-Cell Screening of Tamoxifen Abundance and Effect Using Mass Spectrometry and Raman-Spectroscopy

Monitoring drug uptake, its metabolism, and response on the single-cell level is invaluable for sustaining drug discovery efforts. In this study, we show the possibility of accessing the information about the aforementioned processes at the single-cell level by monitoring the anticancer drug tamoxifen using live single-cell mass spectrometry (LSC-MS) and Raman spectroscopy. First, we explored whether Raman spectroscopy could be used as a label-free and nondestructive screening technique to identify and predict the drug response at the single-cell level. Then, a subset of the screened cells was isolated and analyzed by LSC-MS to measure tamoxifen and its metabolite, 4-Hydroxytamoxifen (4-OHT) in a highly selective, sensitive, and semiquantitative manner. Our results show the Raman spectral signature changed in response to tamoxifen treatment which allowed us to identify and predict the drug response. Tamoxifen and 4-OHT abundances quantified by LSC-MS suggested some heterogeneity among single-cells. A similar phenomenon was observed in the ratio of metabolized to unmetabolized tamoxifen across single-cells. Moreover, a correlation was found between tamoxifen and its metabolite, suggesting that the drug was up taken and metabolized by the cell. Finally, we found some potential correlations between Raman spectral intensities and tamoxifen abundance, or its metabolism, suggesting a possible relationship between the two signals. This study demonstrates for the first time the potential of using Raman spectroscopy and LSC-MS to investigate pharmacokinetics at the single-cell level.

Imaging mass spectrometry of gold nanoparticles in a tissue section as an immunohistochemical staining mass probe

For analysis of low abundance peptides in a tissue section, immunohistochemical staining through antibody-antigen interaction is a usual technique. The antibody is conjugated with a probe moiety that aids in highly sensitive detection. Gold nanoparticles, which show excellent chemical stability and variation of surface modifications, are expected to act as a sensitive mass probe to desorb gold ions (Au⁺ , Au₂ ⁺ , Au₃ ⁺ ) that are distinguishable from fragment ions from organic molecules. Here, green fluorescent proteins (GFP) in a tissue section of a transgenic zebrafish were detected by the gold mass probe conjugated with antibodies. Due to the efficient ionization and desorption of gold ions, imaging mass spectrometry of Au₂ ⁺ ions indicated the distribution of gold nanoparticles stained in a tissue section, and the mass signal distribution was consistent with the area where the GFP-expressing cells were distributed. Conventional immunofluorescence techniques showed intense autofluorescence that come from intrinsic fluorophores in the tissue section. In contrast, the gold nanoparticles acted as an immunostaining mass probe that displayed significantly lower background signals.

An Overview of Mass Spectrometry-Based Methods for Functional Proteomics

The mechanism underlying many biological phenotypes remains unknown despite the increasing availability of whole genome and transcriptome sequencing. Direct measurement of changes in protein expression is an attractive alternative and has the potential to reveal novel processes. Mass spectrometry has become the standard method for proteomics, allowing both the confident identification and quantification of thousands of proteins from biological samples. In this review, mass spectrometry-based proteomic methods and their applications are described.

Spatial Distribution of Endogenous Tissue Protease Activity in Gastric Carcinoma Mapped by MALDI Mass Spectrometry Imaging

Aberrant protease activity has been implicated in the etiology of various prevalent diseases including neurodegeneration and cancer, in particular metastasis. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has recently been established as a key technology for bioanalysis of multiple biomolecular classes such as proteins, lipids, and glycans. However, it has not yet been systematically explored for investigation of a tissue's endogenous protease activity. In this study, we demonstrate that different tissues, spray-coated with substance P as a tracer, digest this peptide with different time-course profiles. Furthermore, we reveal that distinct cleavage products originating from substance P are generated transiently and that proteolysis can be attenuated by protease inhibitors in a concentration-dependent manner. To show the translational potential of the method, we analyzed protease activity of gastric carcinoma in mice. Our MSI and quantitative proteomics results reveal differential distribution of protease activity - with strongest activity being observed in mouse tumor tissue, suggesting the general applicability of the workflow in animal pharmacology and clinical studies.

Deep learning for tumor classification in imaging mass spectrometry

Motivation

Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification.

Results

Methodologically, we propose an adapted architecture based on deep convolutional networks to handle the characteristics of mass spectrometry data, as well as a strategy to interpret the learned model in the spectral domain based on a sensitivity analysis. The proposed methods are evaluated on two algorithmically challenging tumor classification tasks and compared to a baseline approach. Competitiveness of the proposed methods is shown on both tasks by studying the performance via cross-validation. Moreover, the learned models are analyzed by the proposed sensitivity analysis revealing biologically plausible effects as well as confounding factors of the considered tasks. Thus, this study may serve as a starting point for further development of deep learning approaches in IMS classification tasks.

Availability and implementation

https://gitlab.informatik.uni-bremen.de/digipath/Deep_Learning_for_Tumor_Classification_in_IMS.

Contact

jbehrmann@uni-bremen.de or christianetmann@uni-bremen.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

Clinical Proteomics in Colorectal Cancer, a Promising Tool for Improving Personalised Medicine

Colorectal cancer is the third most common and the fourth most lethal cancer worldwide. In most of cases, patients are diagnosed at an advanced or even metastatic stage, thus explaining the high mortality. The lack of proper clinical tests and the complicated procedures currently used for detecting this cancer, as well as for predicting the response to treatment and the outcome of a patient's resistance in guiding clinical practice, are key elements driving the search for biomarkers. In the present overview, the different biomarkers (diagnostic, prognostic, treatment resistance) discovered through proteomics studies in various colorectal cancer study models (blood, stool, biopsies), including the different proteomic techniques used for the discovery of these biomarkers, are reviewed, as well as the various tests used in clinical practice and those currently in clinical phase. These studies define the limits and perspectives related to proteomic biomarker research for personalised medicine in colorectal cancer.

Simultaneous quantification of atropine and scopolamine in infusions of herbal tea and Solanaceae plant material by matrix-assisted laser desorption/ionization time-of-flight (tandem) mass spectrometry

RATIONALE

Atropine (Atr) and scopolamine (Scp) are toxic secondary plant metabolites of species within the Solanaceae genus that can accidentally or intentionally reach the food store chain by inaccurate harvesting of any plant material, e.g. for herbal tea infusions. Ingestion may cause severe anticholinergic poisoning thus requiring risk-oriented determination in food and beverages. The suitability of matrix-assisted laser desorption/ionization time-of-flight (tandem) mass spectrometry, MALDI-TOF MS(/MS), should be characterized for simultaneous analysis.

METHODS

We herein present the first MALDI-TOF MS(/MS) procedure for quantitative determination of both alkaloids in herbal tea infusions and Solanaceae plant material. A standard additions procedure using triply deuterated Atr as internal standard was developed and validated.

RESULTS

Tropane alkaloids were detected without interferences and the standard additions procedure allowed reliable quantification. Intraday and interday precision were less than 17% and corresponding accuracies were between 77% and 112%. Limits of detection in the spotting solution were found at 5 ng/mL (Atr) and 0.5 ng/mL (Scp). The assay was applied to diverse tea infusions as well as to berries and leaves of deadly nightshade and angel's trumpet.

CONCLUSIONS

The usefulness of MALDI-TOF MS(/MS) for investigations of plant-derived samples to prove contaminations by small basic compounds was demonstrated. The elaborate procedure is reliable but quite laborious to obtain quantitative results, but MALDI-TOF MS(/MS) was also shown to be a valuable tool for rapid qualitative screening for Atr and Scp in plant extracts.

Identification of Proteomic Markers in Head and Neck Cancer Using MALDI-MS Imaging, LC-MS/MS, and Immunohistochemistry

PURPOSE

The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level.

EXPERIMENTAL DESIGN

MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC).

RESULTS

In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC.

CONCLUSIONS AND CLINICAL RELEVANCE

The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.

Feasibility Study for the MALDI-MSI Analysis of Thyroid Fine Needle Aspiration Biopsies: Evaluating the Morphological and Proteomic Stability Over Time

PURPOSE

MALDI-MS imaging (MALDI-MSI) is an emerging technology that enables the spatial distribution of biomolecules within tissue to be combined with the traditional morphological information familiar to clinicians. Thus, for diagnostic or prognostic purposes, along with predicting response to therapeutic treatment, it is important to properly collect and handle biological specimens in order to avoid degradation or the formation of artifacts in the morphological structure and proteomic profile.

EXPERIMENTAL DESIGN

In this work, the morphological and proteomic stability of thyroid fine needle aspiration biopsies in PreservCyt (up to 14 days) and CytoLyt (up to 7 days) solutions at 4 °C has been verified, by MALDI-MSI analysis. Moreover, a new measure has been introduced in order to assess the similarity of the obtained MALDI-MSI spectra, by equally taking into account the number of signals (fit and retrofit), and their intensities (Spearman's correlation and spectra overlap).

RESULTS

Results show no degradation of the cellular morphology and a good stability of the samples up to 14 days in PreservCyt solution.

CONCLUSIONS AND CLINICAL RELEVANCE

Moreover, this protocol can be easily implemented in pathological units, allowing simple sample collection and shipment to be used not only for the proteomic MALDI-MSI analysis of thyroid FNABs but also for other biological liquid based specimens.

Molecular imaging mass spectrometry for probing protein dynamics in neurodegenerative disease pathology

Recent advances in the understanding of basic pathological mechanisms in various neurological diseases depend directly on the development of novel bioanalytical technologies that allow sensitive and specific chemical imaging at high resolution in cells and tissues. Mass spectrometry-based molecular imaging (IMS) has gained increasing popularity in biomedical research for mapping the spatial distribution of molecular species in situ. The technology allows for comprehensive, untargeted delineation of in situ distribution profiles of metabolites, lipids, peptides and proteins. A major advantage of IMS over conventional histochemical techniques is its superior molecular specificity. Imaging mass spectrometry has therefore great potential for probing molecular regulations in CNS-derived tissues and cells for understanding neurodegenerative disease mechanism. The goal of this review is to familiarize the reader with the experimental workflow, instrumental developments and methodological challenges as well as to give a concise overview of the major advances and recent developments and applications of IMS-based protein and peptide profiling with particular focus on neurodegenerative diseases. This article is part of the Special Issue "Proteomics".

Discrimination of normal oral mucosa from oral cancer by mass spectrometry imaging of proteins and lipids

Identification of biomarkers for molecular classification of cancer and for differentiation between cancerous and normal epithelium remains a vital issue in the field of head and neck cancer. Here we aimed to compare the ability of proteome and lipidome components to discriminate oral cancer from normal mucosa. Tissue specimens including squamous cell cancer and normal epithelium were analyzed by MALDI mass spectrometry imaging. Two molecular domains of tissue components were imaged in serial sections-peptides (resulting from trypsin-processed proteins) and lipids (primarily zwitterionic phospholipids), then regions of interest corresponding to cancer and normal epithelium were compared. Heterogeneity of cancer regions was higher than the heterogeneity of normal epithelium, and the distribution of peptide components was more heterogeneous than the distribution of lipid components. Moreover, there were more peptide components than lipid components that showed significantly different abundance between cancer and normal epithelium (median of the Cohen's effect was 0.49 and 0.31 in case of peptide and lipid components, respectively). Multicomponent cancer classifier was tested (vs. normal epithelium) using tissue specimens from three patients and then validated with a tissue specimen from the fourth patient. Peptide-based signature and lipid-based signature allowed cancer classification with a weighted accuracy of 0.85 and 0.69, respectively. Nevertheless, both classifiers had very high precision (0.98 and 0.94, respectively). We concluded that though molecular differences between cancerous and normal mucosa were higher in the proteome domain than in the analyzed lipidome subdomain, imaging of lipidome components also enabled discrimination of oral cancer and normal epithelium. Therefore, both cancer proteome and lipidome are promising sources of biomarkers of oral malignancies.

Biological and Ecological Roles of External Fish Mucus: A Review

Fish mucus layers are the main surface of exchange between fish and the environment, and they possess important biological and ecological functions. Fish mucus research is increasing rapidly, along with the development of high-throughput techniques, which allow the simultaneous study of numerous genes and molecules, enabling a deeper understanding of the fish mucus composition and its functions. Fish mucus plays a major role against fish infections, and research has mostly focused on the study of fish mucus bioactive molecules (e.g., antimicrobial peptides and immune-related molecules) and associated microbiota due to their potential in aquaculture and human medicine. However, external fish mucus surfaces also play important roles in social relationships between conspecifics (fish shoaling, spawning synchronisation, suitable habitat finding, or alarm signals) and in interspecific interactions such as prey-predator relationships, parasite–host interactions, and symbiosis. This article reviews the biological and ecological roles of external (gills and skin) fish mucus, discussing its importance in fish protection against pathogens and in intra and interspecific interactions. We also discuss the advances that “omics” sciences are bringing into the fish mucus research and their importance in studying the fish mucus composition and functions.

Novel vacuum stable ketone-based matrices for high spatial resolution MALDI imaging mass spectrometry

We describe the use of aromatic ketones and cinnamyl ketones that have high vacuum stability for analyzing tissue sections using matrix-assisted laser desorption/ionization imaging mass spectrometry. Specifically, the matrix, (E)-4-(2,5-dihydroxyphenyl)but-3-en-2-one (2,5-cDHA) provides high sensitivity and high vacuum stability while producing small size crystals (1-2 μm). A high throughput and highly reproducible sample preparation method was developed for these matrices that first involves using an organic spray solution for small matrix crystal seeding followed by spraying of the matrix in a 30% acetonitrile/70% water solution on the tissue surface to obtain a homogeneous coating of small crystals, suitable for high spatial resolution imaging.

Mass spectrometry imaging: How will it affect clinical research in the future?

INTRODUCTION

Mass spectrometry imaging (MSI) is a label free, multiplex imaging technology able to simultaneously record the distributions of 100's to 1000's of species, and which may be configured to study metabolites, lipids, glycans, peptides, and proteins simply by changing the tissue preparation protocol. Areas covered: The capability of MSI to complement established histopathological practice through the identification of biomarkers for differential diagnosis, patient prognosis, and response to therapy; the capability of MSI to annotate tissues on the basis of each pixel's mass spectral signature; the development of reproducible MSI through multicenter studies. Expert commentary: We discuss how MSI can be combined with microsampling/microdissection technologies in order to investigate, with more depth of coverage, the molecular changes uncovered by MSI.