Molecular tissue profiling by MALDI imaging: recent progress and applications in cancer research

Matrix-assisted laser desorption/ionization matrix incorporation evaluation algorithm for improved peak coverage and signal-to-noise ratio in mass spectrometry imaging

RATIONALE

Despite decades of implementation, the selection of optimal sample preparation conditions for matrix-assisted laser desorption/ionization (MALDI) imaging is still ambiguous due to the lack of a universal and comprehensive evaluation methodology. Thus, numerous experiments with different matrix application conditions accompany a translation of the method to novel sample types and matrices.

METHODS

Mouse brain tissues were covered with 9-aminoacridine through sublimation, followed by recrystallization in vapors of 5% (v/v) methanol solution in water. The samples were analyzed by MALDI time-of-flight mass spectrometry, and the efficiency of lipid and small-molecule ionization was evaluated with different metrics.

RESULTS

We first investigate the dependency of matrix density and recrystallization conditions on the thickness of an analyte-empty matrix layer to roughly evaluate the laser shot number required to obtain an intense signal with minimal noise. Then, we introduce metrics for the analysis of small imaging datasets (small sample regions) of model samples based on median quantity of peaks in spectra (medQP) and weighted median signal-to-noise ratio (wmSNR). The evaluation of small regions and taking median values for metrics help overcome the sample heterogeneity and allow for the simultaneous comparison of different acquisition parameters.

CONCLUSIONS

Here, we propose a methodology based on gradual laser ablation of small regions of sample and further implementation of weighted signal-to-noise ratio to assess various matrix application conditions. The proposed approach helps reduce the number of test samples required to determine optimal sample preparation conditions and improve the overall quality of images.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Single-cell proteomics by mass spectrometry: Advances and implications in cancer research

Cancer harbours extensive proteomic heterogeneity. Inspired by the prior success of single-cell RNA sequencing (scRNA-seq) in characterizing minute transcriptomics heterogeneity in cancer, researchers are now actively searching for information regarding the proteomics counterpart. Therefore recently, single-cell proteomics by mass spectrometry (SCP) has rapidly developed into state-of-the-art technology to cater the need. This review aims to summarize application of SCP in cancer research, while revealing current development progress of SCP technology. The review also aims to contribute ideas into research gaps and future directions, ultimately promoting the application of SCP in cancer research.

Cutaneous squamous cell carcinoma characterized by MALDI mass spectrometry imaging in combination with machine learning

Cutaneous squamous cell carcinoma (SCC) is an increasingly prevalent global health concern. Current diagnostic and surgical methods are reliable, but they require considerable resources and do not provide metabolomic insight. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables detailed, spatially resolved metabolomic analysis of tissue samples. Integrated with machine learning, MALDI-MSI could yield detailed information pertaining to the metabolic alterations characteristic for SCC. These insights have the potential to enhance SCC diagnosis and therapy, improving patient outcomes while tackling the growing disease burden. This study employs MALDI-MSI data, labelled according to histology, to train a supervised machine learning model (logistic regression) for the recognition and delineation of SCC. The model, based on data acquired from discrete tumor sections (n = 25) from a mouse model of SCC, achieved a predictive accuracy of 92.3% during cross-validation on the labelled data. A pathologist unacquainted with the dataset and tasked with evaluating the predictive power of the model in the unlabelled regions, agreed with the model prediction for over 99% of the tissue areas. These findings highlight the potential value of integrating MALDI-MSI with machine learning to characterize and delineate SCC, suggesting a promising direction for the advancement of mass spectrometry techniques in the clinical diagnosis of SCC and related keratinocyte carcinomas.

Mass spectrometry imaging methods for visualizing tumor heterogeneity

Profiling spatial distributions of lipids, metabolites, and proteins in tumors can reveal unique cellular microenvironments and provide molecular evidence for cancer cell dysfunction and proliferation. Mass spectrometry imaging (MSI) is a label-free technique that can be used to map biomolecules in tumors in situ. Here, we discuss current progress in applying MSI to uncover molecular heterogeneity in tumors. First, the analytical strategies to profile small molecules and proteins are outlined, and current methods for multimodal imaging to maximize biological information are highlighted. Second, we present and summarize biological insights obtained by MSI of tumor tissue. Finally, we discuss important considerations for designing MSI experiments and several current analytical challenges.

EtOH-LN cryoembedding workflow to minimize freezing artifact in frozen tissues: A pilot study in preparing tissues compatible with mass spectrometry-based spatial proteomics application

Coolant-assisted liquid nitrogen (LN) flash freezing of frozen tissues has been widely adopted to preserve tissue morphology for histopathological annotations in mass spectrometry-based spatial proteomics techniques. However, existing coolants pose health risks upon inhalation and are expensive. To overcome this challenge, we present our pilot study by introducing the EtOH-LN workflow, which demonstrates the feasibility of using 95 % ethanol as a safer and easily accessible alternative to existing coolants for LN-based cryoembedding of frozen tissues. Our study reveals that both the EtOH-LN and LN-only cryoembedding workflows exhibit significantly reduced freezing artifacts compared to cryoembedding in cryostat (p < 0.005), while EtOH-LN (SD = 0.56) generates more consistent results compared to LN-only (SD = 1.29). We have modified a previously reported morphology restoration method to incorporate the EtOH-LN workflow, which successfully restored the tissue architecture from freezing artifacts (p < 0.05). Additional studies are required to validate the impact of the EtOH-LN workflow on the molecular profiles of tissues.

Metabolic heterogeneity in cancer

Cancer cells rewire their metabolism to survive during cancer progression. In this context, tumour metabolic heterogeneity arises and develops in response to diverse environmental factors. This metabolic heterogeneity contributes to cancer aggressiveness and impacts therapeutic opportunities. In recent years, technical advances allowed direct characterisation of metabolic heterogeneity in tumours. In addition to the metabolic heterogeneity observed in primary tumours, metabolic heterogeneity temporally evolves along with tumour progression. In this Review, we summarize the mechanisms of environment-induced metabolic heterogeneity. In addition, we discuss how cancer metabolism and the key metabolites and enzymes temporally and functionally evolve during the metastatic cascade and treatment.

Spatial metabolomics principles and application to cancer research

Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.

High-Throughput Deconvolution of Native Protein Mass Spectrometry Imaging Data Sets for Mass Domain Analysis

Protein mass spectrometry imaging (MSI) with electrospray-based ambient ionization techniques, such as nanospray desorption electrospray ionization (nano-DESI), generates data sets in which each pixel corresponds to a mass spectrum populated by peaks corresponding to multiply charged protein ions. Importantly, the signal associated with each protein is split among multiple charge states. These peaks can be transformed into the mass domain by spectral deconvolution. When proteins are imaged under native/non-denaturing conditions to retain non-covalent interactions, deconvolution is particularly valuable in helping interpret the data. To improve the acquisition speed, signal-to-noise ratio, and sensitivity, native MSI is usually performed using mass resolving powers that do not provide isotopic resolution, and conventional algorithms for deconvolution of lower-resolution data are not suitable for these large data sets. UniDec was originally developed to enable rapid deconvolution of complex protein mass spectra. Here, we developed an updated feature set harnessing the high-throughput module, MetaUniDec, to deconvolve each pixel of native MSI data sets and transform m/z-domain image files to the mass domain. New tools enable the reading, processing, and output of open format .imzML files for downstream analysis. Transformation of data into the mass domain also provides greater accessibility, with mass information readily interpretable by users of established protein biology tools such as sodium dodecyl sulfate polyacrylamide gel electrophoresis.

Promise of spatially resolved omics for tumor research

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.

Desorption electrospray ionization and matrix-assisted laser desorption/ionization as imaging approaches for biological samples analysis

The imaging of biological tissues can offer valuable information about the sample composition, which improves the understanding of analyte distribution in such complex samples. Different approaches using mass spectrometry imaging (MSI), also known as imaging mass spectrometry (IMS), enabled the visualization of the distribution of numerous metabolites, drugs, lipids, and glycans in biological samples. The high sensitivity and multiple analyte evaluation/visualization in a single sample provided by MSI methods lead to various advantages and overcome drawbacks of classical microscopy techniques. In this context, the application of MSI methods, such as desorption electrospray ionization-MSI (DESI-MSI) and matrix-assisted laser desorption/ionization-MSI (MALDI-MSI), has significantly contributed to this field. This review discusses the evaluation of exogenous and endogenous molecules in biological samples using DESI and MALDI imaging. It offers rare technical insights not commonly found in the literature (scanning speed and geometric parameters), making it a comprehensive guide for applying these techniques step-by-step. Furthermore, we provide an in-depth discussion of recent research findings on using these methods to study biological tissues.

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

A Five-Year Update on Matrix Compounds for MALDI-MS Analysis of Lipids

Matrix-assisted laser desorption and ionization (MALDI) is a widely used soft-ionization technique of modern mass spectrometry (MS). MALDI enables the analysis of nearly all chemical compounds—including polar and apolar (phospho)lipids—with a minimum extent of fragmentation. MALDI has some particular advantages (such as the possibility to acquire spatially-resolved spectra) and is competitive with the simultaneously developed ESI (electrospray ionization) MS. Although there are still some methodological aspects that need to be elucidated in more detail, it is obvious that the careful selection of an appropriate matrix plays the most important role in (lipid) analysis. Some lipid classes can be detected exclusively if the optimum matrix is used, and the matrix determines the sensitivity by which a particular lipid is detected within a mixture. Since the matrix is, thus, crucial for optimum results, we provide here an update on the progress in the field since our original review in this journal in 2018. Thus, only the development during the last five years is considered, and lipids are sorted according to increasing complexity, starting with free fatty acids and ending with cardiolipins and phosphoinositides.

Spatial profiling technologies illuminate the tumor microenvironment

The tumor microenvironment (TME) is composed of many different cellular and acellular components that together drive tumor growth, invasion, metastasis, and response to therapies. Increasing realization of the significance of the TME in cancer biology has shifted cancer research from a cancer-centric model to one that considers the TME as a whole. Recent technological advancements in spatial profiling methodologies provide a systematic view and illuminate the physical localization of the components of the TME. In this review, we provide an overview of major spatial profiling technologies. We present the types of information that can be extracted from these data and describe their applications, findings and challenges in cancer research. Finally, we provide a future perspective of how spatial profiling could be integrated into cancer research to improve patient diagnosis, prognosis, stratification to treatment and development of novel therapeutics.

A Multimodal Desorption Electrospray Ionisation Workflow Enabling Visualisation of Lipids and Biologically Relevant Elements in a Single Tissue Section

The colocation of elemental species with host biomolecules such as lipids and metabolites may shed new light on the dysregulation of metabolic pathways and how these affect disease pathogeneses. Alkali metals have been the subject of extensive research, are implicated in various neurodegenerative and infectious diseases and are known to disrupt lipid metabolism. Desorption electrospray ionisation (DESI) is a widely used approach for molecular imaging, but previous work has shown that DESI delocalises ions such as potassium (K) and chlorine (Cl), precluding the subsequent elemental analysis of the same section of tissue. The solvent typically used for the DESI electrospray is a combination of methanol and water. Here we show that a novel solvent system, (50:50 (%v/v) MeOH:EtOH) does not delocalise elemental species and thus enables elemental mapping to be performed on the same tissue section post-DESI. Benchmarking the MeOH:EtOH electrospray solvent against the widely used MeOH:H₂O electrospray solvent revealed that the MeOH:EtOH solvent yielded increased signal-to-noise ratios for selected lipids. The developed multimodal imaging workflow was applied to a lung tissue section containing a tuberculosis granuloma, showcasing its applicability to elementally rich samples displaying defined structural information.

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.

Spatially resolved proteomics via tissue expansion

Spatially resolved proteomics is an emerging approach for mapping proteome heterogeneity of biological samples, however, it remains technically challenging due to the complexity of the tissue microsampling techniques and mass spectrometry analysis of nanoscale specimen volumes. Here, we describe a spatially resolved proteomics method based on the combination of tissue expansion with mass spectrometry-based proteomics, which we call Expansion Proteomics (ProteomEx). ProteomEx enables quantitative profiling of the spatial variability of the proteome in mammalian tissues at ~160 µm lateral resolution, equivalent to the tissue volume of 0.61 nL, using manual microsampling without the need for custom or special equipment. We validated and demonstrated the utility of ProteomEx for streamlined large-scale proteomics profiling of biological tissues including brain, liver, and breast cancer. We further applied ProteomEx for identifying proteins associated with Alzheimer's disease in a mouse model by comparative proteomic analysis of brain subregions.

Advances in mass spectrometry imaging for toxicological analysis and safety evaluation of pharmaceuticals

Safety issues caused by pharmaceuticals have frequently occurred worldwide, posing a tremendous threat to human health. As an essential part of drug development, the toxicological analysis and safety evaluation is of great significance. In addition, the risk of pharmaceuticals accumulation in the environment and the monitoring of the toxicity from natural medicines have also received ongoing concerns. Due to a lack of spatial distribution information provided by common analytical methods, analyses that provide spatial dimensions could serve as complementary safety evaluation methods for better prediction and evaluation of drug toxicity. With advances in technical solutions and software algorithms, mass spectrometry imaging (MSI) has received increasing attention as a popular analytical tool that enables the simultaneous implementation of qualitative, quantitative, and localization without complex sample pretreatment and labeling steps. In recent years, MSI has become more attractive, powerful, and sensitive and has been applied in several scientific fields that can meet the safety assessment requirements. This review aims to cover a detailed summary of the various MSI technologies utilized in the biomedical and pharmaceutical area, including technical principles, advantages, current status, and future trends. Representative applications and developments in the safety-related issues of different pharmaceuticals and natural medicines are also described to provide a reference for pharmaceutical research, improve rational clinical medicine use, and ensure public safety.

Nanostructured Layer of Silver for Detection of Small Biomolecules in Surface-Assisted Laser Desorption Ionization Mass Spectrometry

A facile approach for the synthesis of a silver nanostructured layer for application in surface-assisted laser desorption/ionization mass spectrometry of low-molecular-weight biomolecules was developed using electrochemical deposition. The deposition was carried out using the following silver salts: trifluoroacetate, acetate and nitrate, varying the voltage and time. The plate based on trifluoroacetate at 10 V for 15 min showed intense SALDI-MS responses for standards of various classes of compounds: fatty acids, cyclitols, saccharides and lipids at a concentration of 1 nmol/spot, with values of the signal-to-noise ratio ≥50. The values of the limit of detection were 0.71 µM for adonitol, 2.08 µM for glucose and 0.39 µM for palmitic acid per spot. SEM analysis of the plate showed anisotropic flower-like microstructures with nanostructures on their surface. The reduced chemical background in the low-mass region can probably be explained by the absence of stabilizers and reducing agents during the synthesis. The plate synthesized with the developed approach showed potential for future use in the analysis of low-molecular-weight compounds of biological relevance. The absence of the need for the utilization of sophisticated equipment and the synthesis time (10 min) may benefit large-scale applications of the layer for the detection of various types of small biomolecules.

MALDI-TOF/MS Analysis of Non-Invasive Human Urine and Saliva Samples for the Identification of New Cancer Biomarkers

Cancer represents a group of heterogeneous diseases that are a leading global cause of death. Even though mortality has decreased in the past thirty years for different reasons, most patients are still diagnosed at the advanced stage, with limited therapeutic choices and poor outcomes. Moreover, the majority of cancers are detected using invasive painful methods, such as endoscopic biopsy, making the development of non-invasive or minimally invasive methods for the discovery and fast detection of specific biomarkers a crucial need. Among body fluids, a valuable non-invasive alternative to tissue biopsy, the most accessible and least invasive are undoubtedly urine and saliva. They are easily retrievable complex fluids containing a large variety of endogenous compounds that may provide information on the physiological condition of the body. The combined analysis of these fluids with matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF/MS), a reliable and easy-to-use instrumentation that provides information with relatively simple sample pretreatments, could represent the ideal option to rapidly achieve fast early stage diagnosis of tumors and their real-time monitoring. On this basis, the present review summarizes the recently reported applications relevant to the MALDI analysis of human urine and saliva samples.

Enhancing Metabolomic Coverage in Positive Ionization Mode Using Dicationic Reagents by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization

Mass spectrometry imaging is a powerful tool to analyze a large number of metabolites with their spatial coordinates collected throughout the sample. However, the significant differences in ionization efficiency pose a big challenge to metabolomic mass spectrometry imaging. To solve the challenge and obtain a complete data profile, researchers typically perform experiments in both positive and negative ionization modes, which is time-consuming. In this work, we evaluated the use of the dicationic reagent, 1,5-pentanediyl-bis(1-butylpyrrolidinium) difluoride (abbreviated to [C5(bpyr)2]F2) to detect a broad range of metabolites in the positive ionization mode by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI). [C5(bpyr)2]F2 at 10 µM was doped in 50% MeOH/H2O (v/v) electrospray solvent to form +1 charged adducted ions with anionic species (-1 charged) through post-electrospray ionization. This method was demonstrated with sectioned rat liver and hen ovary. A total of 73 deprotonated metabolites from rat liver tissue sections were successfully adducted with [C5(bpyr)2]2+ and putatively identified in the adducted positive ionization polarity, along with 164 positively charged metabolite ions commonly seen in positive ionization mode, which resulted in 44% increased molecular coverage. In addition, we were able to generate images of hen ovary sections showing their morphological features. Following-up tandem mass spectrometry (MS/MS) indicated that this dicationic reagent [C5(bpyr)2]2+ could form ionic bonds with the headgroup of glycerophospholipid ions. The addition of the dicationic reagent [C5(bpyr)2]2+ in the electrospray solvent provides a rapid and effective way to enhance the detection of metabolites in positive ionization mode.

Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns

Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.