Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI MSI) for Monitoring of Drug Response in Primary Cancer Spheroids

Exploiting Differential Signal Filtering (DSF) and Image Structure Filtering (ISF) Methods for Untargeted Mass Spectrometry Imaging of Bacterial Metabolites

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a label-free technique, producing images where pixels contain mass spectra. The technique allows the visualization of the spatial distribution of (bio)molecules from metabolites to proteins, on surfaces such as tissues sections or bacteria culture media. One particularly exciting example of MALDI-MSI use rests on its potential to localize ionized compounds produced during microbial interactions and chemical communication, offering a molecular snapshot of metabolomes at a given time. The huge size and the complexity of generated MSI data make the processing of the data challenging, which requires the use of computational methods. Despite recent advances, currently available commercial software relies mainly on statistical tools to identify patterns, similarities, and differences within data sets. However, grouping m/z values unique to a given data set according to microbiological contexts, such as coculture experiments, still requires tedious manual analysis. Here we propose a nontargeted method exploiting the differential signals between negative controls and tested experimental conditions, i.e., differential signal filtering (DSF), and a scoring of the ion images using image structure filtering (ISF) coupled with a fold change score between the controls and the conditions of interest. These methods were first applied to coculture experiments involving Escherichia coli and Streptomyces coelicolor, revealing specific MS signals during bacterial interaction. Two case studies were also investigated: (i) cellobiose-mediated induction for the pathogenicity of Streptomyces scabiei, the causative agent of common scab on root and tuber crops, and (ii) iron-repressed production of siderophores of S. scabiei. This report proposes guidelines for MALDI-MSI data treatment applied in the case of microbiology contexts, with enhanced ion peak annotation in specific culture conditions. The strengths and weaknesses of the methods are discussed.

DISC-3D: dual-hydrogel system enhances optical imaging and enables correlative mass spectrometry imaging of invading multicellular tumor spheroids

Multicellular tumor spheroids embedded in collagen I matrices are common in vitro systems for the study of solid tumors that reflect the physiological environment and complexities of the in vivo environment. While collagen I environments are physiologically relevant and permissive of cell invasion, studying spheroids in such hydrogels presents challenges to key analytical assays and to a wide array of imaging modalities. While this is largely due to the thickness of the 3D hydrogels that in other samples can typically be overcome by sectioning, because of their highly porous nature, collagen I hydrogels are very challenging to section, especially in a manner that preserves the hydrogel network including cell invasion patterns. Here, we describe a novel method for preparing and cryosectioning invasive spheroids in a two-component (collagen I and gelatin) matrix, a technique we term dual-hydrogel in vitro spheroid cryosectioning of three-dimensional samples (DISC-3D). DISC-3D does not require cell fixation, preserves the architecture of invasive spheroids and their surroundings, eliminates imaging challenges, and allows for use of techniques that have infrequently been applied in three-dimensional spheroid analysis, including super-resolution microscopy and mass spectrometry imaging.

Pharmacological Inhibition of Membrane Signaling Mechanisms Reduces the Invasiveness of U87-MG and U251-MG Glioblastoma Cells In Vitro

Impairing the motility of glioblastoma multiforme (GBM) cells is a compelling goal for new approaches to manage this highly invasive and rapidly lethal human brain cancer. Work here characterized an array of pharmacological inhibitors of membrane ion and water channels, alone and in combination, as tools for restraining glioblastoma spread in human GBM cell lines U87-MG and U251-MG. Aquaporins, AMPA glutamate receptors, and ion channel classes (shown to be upregulated in human GBM at the transcript level and linked to mechanisms of motility in other cell types) were selected as pharmacological targets for analyses. Effective compounds reduced the transwell invasiveness of U87-MG and U251-MG glioblastoma cells by 20-80% as compared with controls, without cytotoxicity. The compounds and doses used were: AqB013 (14 μM); nifedipine (25 µM); amiloride (10 µM); apamin (10 µM); 4-aminopyridine (250 µM); and CNQX (6-cyano-7-nitroquinoxaline-2,3-dione; 30 µM). Invasiveness was quantified in vitro across transwell filter chambers layered with extracellular matrix. Co-application of each of the ion channel agents with the water channel inhibitor AqB013 augmented the inhibition of invasion (20 to 50% greater than either agent alone). The motility impairment achieved by co-application of pharmacological agents differed between the GBM proneural-like subtype U87-MG and classical-like subtype U251-MG, showing patterns consistent with relative levels of target channel expression (Human Protein Atlas database). In addition, two compounds, xanthurenic acid and caelestine C (from the Davis Open Access Natural Product-based Library, Griffith University QLD), were discovered to block invasion at micromolar doses in both GBM lines (IC₅₀ values from 0.03 to 1 µM), without cytotoxicity, as measured by full mitochondrial activity under conditions matching those in transwell assays and by normal growth in spheroid assays. Mechanisms of action of these agents based on published work are likely to involve modulation of glutamatergic receptor signaling. Treating glioblastoma by the concurrent inhibition of multiple channel targets could be a powerful approach for slowing invasive cell spread without cytotoxic side effects, potentially enhancing the effectiveness of clinical interventions focused on eradicating primary tumors.

Mass spectrometry imaging in gynecological cancers: the best is yet to come

Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.

Nanostructured Silicon Enabled HR-MS for the Label-Free Detection of Biomarkers in Colorectal Cancer Plasma Small Extracellular Vesicles

Despite improvements in treatment options for advanced colorectal cancer (CRC), survival outcomes are still best for patients with non-metastasised disease. Diagnostic tools to identify blood-based biomarkers and assist in CRC subtype classification could afford a means to track CRC progression and treatment response. Cancer cell-derived small extracellular vesicles (EVs) circulating in blood carry an elevated cargo of lipids and proteins that could be used as a signature of tumour suppressor/promoting events or stages leading up to and including metastasis. Here, we used pre-characterised biobanked plasma samples from surgical units, typically with a low volume (~100 µL), to generate and discover signatures of CRC-derived EVs. We employed nanostructured porous silicon (pSi) surface assisted-laser desorption/ionisation (SALDI) coupled with high-resolution mass spectrometry (HR-MS), to allow sensitive detection of low abundant analytes in plasma EVs. When applied to CRC samples, SALDI-HR-MS enabled the detection of the peptide mass fingerprint of cancer suppressor proteins, including serine/threonine phosphatases and activating-transcription factor 3. SALDI-HR-MS also allowed the detection of a spectrum of glycerophospholipids and sphingolipid signatures in metastatic CRC. We observed that lithium chloride enhanced detection sensitivity to elucidate the structure of low abundant lipids in plasma EVs. pSi SALDI can be used as an effective system for label-free and high throughput analysis of low-volume patient samples, allowing rapid and sensitive analysis for CRC classification.

Tissue sample preparations for preclinical research determined by molecular imaging mass spectrometry using MALDI

Matrix-assisted laser desorption/ionization - imaging mass spectrometry is an alternative tool, which can be implemented in order to obtain and visualize the "omic" signature of tissue samples. Its application to clinical study enables simultaneous imaging-based morphological observations and mass spectrometry analysis. Application of fully informative material like tissue, allows to obtain the complex and unique profile of analyzed samples. This knowledge leads to diagnose disease, study the mechanism of cancer development, select the potential biomarkers as well as correlating obtained image with prognosis. Nevertheless, it is worth to notice that this method is found to be objective but the result of analysis is mainly influenced by the sample preparation protocol, included collection of biological material, its preservation and processing. However, application of this approach requires a special sample preparation procedure. The main goal of the study is to present the current knowledge on the clinical application of matrix-assisted laser desorption/ionization - imaging mass spectrometry in cancer research, with particular emphasis on the sample preparation step. For this purpose, several protocols based on cryosections and formalin-fixed paraffin embedded tissue were compiled and compared, taking into account the measured metabolites of potential diagnostic importance for a given type of cancer. This article is protected by copyright. All rights reserved.

Advances in MALDI Mass Spectrometry Imaging Single Cell and Tissues

Compared with conventional optical microscopy techniques, mass spectrometry imaging (MSI) or imaging mass spectrometry (IMS) is a powerful, label-free analytical technique, which can sensitively and simultaneously detect, quantify, and map hundreds of biomolecules, such as peptides, proteins, lipid, and other organic compounds in cells and tissues. So far, although several soft ionization techniques, such as desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS) have been used for imaging biomolecules, matrix-assisted laser desorption/ionization (MALDI) is still the most widespread MSI scanning method. Here, we aim to provide a comprehensive review of MALDI-MSI with an emphasis on its advances of the instrumentation, methods, application, and future directions in single cell and biological tissues.

Pancreatic Ductal Adenocarcinoma: Preclinical in vitro and ex vivo Models

Pancreatic ductal adenocarcinoma (PDAC) is one of the most overlooked cancers despite its dismal median survival time of 6 months. The biggest challenges in improving patient survival are late diagnosis due to lack of diagnostic markers, and limited treatment options due to almost complete therapy resistance. The past decades of research identified the dense stroma and the complex interplay/crosstalk between the cancer- and the different stromal cells as the main culprits for the slow progress in improving patient outcome. For better ex vivo simulation of this complex tumor microenvironment the models used in PDAC research likewise need to become more diverse. Depending on the focus of the investigation, several in vitro and in vivo models for PDAC have been established in the past years. Particularly, 3D cell culture such as spheroids and organoids have become more frequently used. This review aims to examine current PDAC in vitro models, their inherent limitations, and their successful implementations in research.

MS imaging of multicellular tumor spheroids and organoids as an emerging tool for personalized medicine and drug discovery

MS imaging (MSI) is a powerful tool in drug discovery because of its ability to interrogate a wide range of endogenous and exogenous molecules in a broad variety of samples. The impressive versatility of the approach, where almost any ionizable biomolecule can be analyzed, including peptides, proteins, lipids, carbohydrates, and nucleic acids, has been applied to numerous types of complex biological samples. While originally demonstrated with harvested organs from animal models and biopsies from humans, these models are time consuming and expensive, which makes it necessary to extend the approach to 3D cell culture systems. These systems, which include spheroid models, prepared from immortalized cell lines, and organoid cultures, grown from patient biopsies, can provide insight on the intersection of molecular information on a spatial scale. In particular, the investigation of drug compounds, their metabolism, and the subsequent distribution of their metabolites in 3D cell culture systems by MSI has been a promising area of study. This review summarizes the different ionization methods, sample preparation steps, and data analysis methods of MSI and focuses on several of the latest applications of MALDI-MSI for drug studies in spheroids and organoids. Finally, the application of this approach in patient-derived organoids to evaluate personalized medicine options is discussed.

The emergence of imaging mass spectrometry in drug discovery and development: Making a difference by driving decision making

The pharmaceutical industry is a dynamic, science-driven business constantly under pressure to innovate and morph into a higher performing organization. Innovations can include the implementation of new technologies, adopting new scientific methods, changing the decision-making process, compressing timelines, or making changes to the organizational structure. The drivers for the constant focus on performance improvement are the high cost of R&D as well as the lengthy timelines required to deliver new medicines for unmet needs. Successful innovations are measured against both the quality and quantity of potential new medicines in the pipeline and the delivery to patients. In this special feature article, we share our collective experience implementing matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology as an innovative approach to better understand the tissue biodistribution of drugs in the early phases of drug discovery to establish pharmacokinetic-pharmacodynamic (PK-PD) relationships, as well as in the development phase to understand pharmacology, toxicology, and disease pathogenesis. In our experience, successful implementation of MALDI IMS in support of therapeutic programs can be measured by the impact IMS studies have on driving decision making in pipeline progression. This provides a direct quantifiable measurement of the return to the organization for the investment in IMS. We have included discussion not only on the technical merits of IMS study conduct but also the key elements of setting study objectives, building collaborations, data integration into the medicine progression milestones, and potential pitfalls when trying to establish IMS in the pharmaceutical arena. We categorized IMS study types into five groups that parallel pipeline progression from the earliest phases of discovery to late stages of preclinical development. We conclude the article with some perspectives on how we see MALDI IMS maintaining relevance and becoming further embedded as an essential tool in the constantly changing environment of the pharmaceutical industry.

Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry Imaging in Biology

Elemental imaging gives insight into the fundamental chemical makeup of living organisms. Every cell on Earth is comprised of a complex and dynamic mixture of the chemical elements that define structure and function. Many disease states feature a disturbance in elemental homeostasis, and understanding how, and most importantly where, has driven the development of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) as the principal elemental imaging technique for biologists. This review provides an outline of ICP-MS technology, laser ablation cell designs, imaging workflows, and methods of quantification. Detailed examples of imaging applications including analyses of cancers, elemental uptake and accumulation, plant bioimaging, nanomaterials in the environment, and exposure science and neuroscience are presented and discussed. Recent incorporation of immunohistochemical workflows for imaging biomolecules, complementary and multimodal imaging techniques, and image processing methods is also reviewed.

MSIWarp: A General Approach to Mass Alignment in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a technique that provides comprehensive molecular information with high spatial resolution from tissue. Today, there is a strong push toward sharing data sets through public repositories in many research fields where MSI is commonly applied; yet, there is no standardized protocol for analyzing these data sets in a reproducible manner. Shifts in the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free m/z alignment approach that is compatible with multiple instrument types and makes no assumptions on the sample's molecular composition. Our approach, MSIWarp (https://github.com/horvatovichlab/MSIWarp), finds an m/z recalibration function by maximizing a similarity score that considers both the intensity and m/z position of peaks matched between two spectra. MSIWarp requires only centroid spectra to find the recalibration function and is thereby readily applicable to almost any MSI data set. To deal with particularly misaligned or peak-sparse spectra, we provide an option to detect and exclude spurious peak matches with a tailored random sample consensus (RANSAC) procedure. We evaluate our approach with four publicly available data sets from both time-of-flight (TOF) and Orbitrap instruments and demonstrate up to 88% improvement in m/z alignment.

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.