Integrative Single-Plaque Analysis Reveals Signature Aß and Lipid Profiles in the Alzheimer's Brain.

Cerebral accumulation of amyloid-ß (Aß) initiates molecular and cellular cascades that lead to Alzheimer's disease (AD). However, amyloid deposition does not invariably lead to dementia. Amyloid-positive but cognitively unaffected (AP-CU) individuals present widespread amyloid pathology, suggesting that molecular signatures more complex than the total amyloid burden are required to better differentiate AD from AP-CU cases. Motivated by the essential role of Aß and the key lipid involvement in AD pathogenesis, we applied multimodal mass spectrometry imaging (MSI) and machine learning (ML) to investigate amyloid plaque heterogeneity, regarding Aß and lipid composition, in AP-CU versus AD brain samples at the single-plaque level. Instead of focusing on a population mean, our analytical approach allowed the investigation of large populations of plaques at the single-plaque level. We found that different (sub)populations of amyloid plaques, differing in Aß and lipid composition, coexist in the brain samples studied. The integration of MSI data with ML-based feature extraction further revealed that plaque-associated gangliosides GM2 and GM1, as well as Aß1-38, but not Aß1-42, are relevant differentiators between the investigated pathologies. The pinpointed differences may guide further fundamental research investigating the role of amyloid plaque heterogeneity in AD pathogenesis/progression and may provide molecular clues for further development of emerging immunotherapies to effectively target toxic amyloid assemblies in AD therapy. Our study exemplifies how an integrative analytical strategy facilitates the unraveling of complex biochemical phenomena, advancing our understanding of AD from an analytical perspective and offering potential avenues for the refinement of diagnostic tools.

pyM2aia: Python interface for mass spectrometry imaging with focus on deep learning.

SUMMARY: Python is the most commonly used language for deep learning (DL). Existing Python packages for mass spectrometry imaging (MSI) data are not optimized for DL tasks. We, therefore, introduce pyM2aia, a Python package for MSI data analysis with a focus on memory-efficient handling, processing and convenient data-access for DL applications. pyM2aia provides interfaces to its parent application M2aia, which offers interactive capabilities for exploring and annotating MSI data in imzML format. pyM2aia utilizes the image input and output routines, data formats, and processing functions of M2aia, ensures data interchangeability, and enables the writing of readable and easy-to-maintain DL pipelines by providing batch generators for typical MSI data access strategies. We showcase the package in several examples, including imzML metadata parsing, signal processing, ion-image generation, and, in particular, DL model training and inference for spectrum-wise approaches, ion-image-based approaches, and approaches that use spectral and spatial information simultaneously. AVAILABILITY AND IMPLEMENTATION: Python package, code and examples are available at (https://m2aia.github.io/m2aia).

PerSurge (NOA-30) phase II trial of perampanel treatment around surgery in patients with progressive glioblastoma.

BACKGROUND: Glioblastoma is the most frequent and a particularly malignant primary brain tumor with no efficacy-proven standard therapy for recurrence. It has recently been discovered that excitatory synapses of the AMPA-receptor subtype form between non-malignant brain neurons and tumor cells. This neuron-tumor network connectivity contributed to glioma progression and could be efficiently targeted with the EMA/FDA approved antiepileptic AMPA receptor inhibitor perampanel in preclinical studies. The PerSurge trial was designed to test the clinical potential of perampanel to reduce tumor cell network connectivity and tumor growth with an extended window-of-opportunity concept. METHODS: PerSurge is a phase IIa clinical and translational treatment study around surgical resection of progressive or recurrent glioblastoma. In this multicenter, 2-arm parallel-group, double-blind superiority trial, patients are 1:1 randomized to either receive placebo or perampanel (n = 66 in total). It consists of a treatment and observation period of 60 days per patient, starting 30 days before a planned surgical resection, which itself is not part of the study interventions. Only patients with an expected safe waiting interval are included, and a safety MRI is performed. Tumor cell network connectivity from resected tumor tissue on single cell transcriptome level as well as AI-based assessment of tumor growth dynamics in T2/FLAIR MRI scans before resection will be analyzed as the co-primary endpoints. Secondary endpoints will include further imaging parameters such as pre- and postsurgical contrast enhanced MRI scans, postsurgical T2/FLAIR MRI scans, quality of life, cognitive testing, overall and progression-free survival as well as frequency of epileptic seizures. Further translational research will focus on additional biological aspects of neuron-tumor connectivity. DISCUSSION: This trial is set up to assess first indications of clinical efficacy and tolerability of perampanel in recurrent glioblastoma, a repurposed drug which inhibits neuron-glioma synapses and thereby glioblastoma growth in preclinical models. If perampanel proved to be successful in the clinical setting, it would provide the first evidence that interference with neuron-cancer interactions may indeed lead to a benefit for patients, which would lay the foundation for a larger confirmatory trial in the future. TRIAL REGISTRATION: EU-CT number: 2023-503938-52-00 30.11.2023.

High-Throughput Miniaturized Synthesis of PROTAC-Like Molecules.

The development of miniaturized high-throughput in situ screening platforms capable of handling the entire process of drug synthesis to final screening is essential for advancing drug discovery in the future. In this study, an approach based on combinatorial solid-phase synthesis, enabling the efficient synthesis of libraries of proteolysis targeting chimeras (PROTACs) in an array format is presented. This on-chip platform allows direct biological screening without the need for transfer steps.  UV-induced release of target molecules into individual droplets facilitates further on-chip experimentation. Utilizing a mitogen-activated protein kinase kinases (MEK1/2) degrader as a template, a series of 132 novel PROTAC-like molecules is synthesized using solid-phase Ugi reaction. These compounds are further characterized using various methods, including matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) imaging, while consuming only a few milligrams of starting materials in total. Furthermore, the feasibility of culturing cancer cells on the modified spots and quantifying the effect of MEK suppression is demonstrated. The miniaturized synthesis platform lays a foundation for high-throughput in situ biological screening of potent PROTACs for potential anticancer activity and offers the potential for accelerating the drug discovery process by integrating miniaturized synthesis and biological steps on the same array.

APP substrate ectodomain defines amyloid-ß peptide length by restraining γ-secretase processivity and facilitating product release.

Sequential proteolysis of the amyloid precursor protein (APP) by γ-secretases generates amyloid-ß (Aß) peptides and defines the proportion of short-to-long Aß peptides, which is tightly connected to Alzheimer's disease (AD) pathogenesis. Here, we study the mechanism that controls substrate processing by γ-secretases and Aß peptide length. We found that polar interactions established by the APPC99 ectodomain (ECD), involving but not limited to its juxtamembrane region, restrain both the extent and degree of γ-secretases processive cleavage by destabilizing enzyme-substrate interactions. We show that increasing hydrophobicity, via mutation or ligand binding, at APPC99 -ECD attenuates substrate-driven product release and rescues the effects of Alzheimer's disease-associated pathogenic γ-secretase and APP variants on Aß length. In addition, our study reveals that APPC99 -ECD facilitates the paradoxical production of longer Aßs caused by some γ-secretase inhibitors, which act as high-affinity competitors of the substrate. These findings assign a pivotal role to the substrate ECD in the sequential proteolysis by γ-secretases and suggest it as a sweet spot for the potential design of APP-targeting compounds selectively promoting its processing by these enzymes.

Site-Specific Structural Changes in Long-Term-Stressed Monoclonal Antibody Revealed with DEPC Covalent-Labeling and Quantitative Mass Spectrometry.

Studies of structural changes in mAbs under forced stress and storage conditions are essential for the recognition of degradation hotspots, which can be further remodeled to improve the stability of the respective protein. Herein, we used diethyl pyrocarbonate (DEPC)-based covalent labeling mass spectrometry (CL-MS) to assess structural changes in a model mAb (SILuMAb). Structural changes in the heat-stressed mAb samples were confirmed at specific amino acid positions from the DEPC label mass seen in the fragment ion mass spectrum. The degree of structural change was also quantified by increased or decreased DEPC labeling at specific sites; an increase or decrease indicated an unfolded or aggregated state of the mAb, respectively. Strikingly, for heat-stressed SILuMAb samples, an aggregation-prone area was identified in the CDR region. In the case of longterm stress, the structural consequences for SILuMAb samples stored for up to two years at 2-8 °C were studied with SEC-UV and DEPC-based CL-MS. While SEC-UV analysis only indicated fragmentation of SILuMAb, DEPC-based CL-MS analysis further pinpointed the finding to structural disturbances of disulfide bonds at specific cysteines. This emphasized the utility of DEPC CL-MS for studying disulfide rearrangement. Taken together, our data suggests that DEPC CL-MS can complement more technically challenging methods in the evaluation of the structural stability of mAbs.

Alzheimer's disease linked Aß42 exerts product feedback inhibition on γ-secretase impairing downstream cell signaling.

Amyloid ß (Aß) peptides accumulating in the brain are proposed to trigger Alzheimer's disease (AD). However, molecular cascades underlying their toxicity are poorly defined. Here, we explored a novel hypothesis for Aß42 toxicity that arises from its proven affinity for γ-secretases. We hypothesized that the reported increases in Aß42, particularly in the endolysosomal compartment, promote the establishment of a product feedback inhibitory mechanism on γ-secretases, and thereby impair downstream signaling events. We show that human Aß42 peptides, but neither murine Aß42 nor human Aß17-42 (p3), inhibit γ-secretases and trigger accumulation of unprocessed substrates in neurons, including C-terminal fragments (CTFs) of APP, p75 and pan-cadherin. Moreover, Aß42 treatment dysregulated cellular homeostasis, as shown by the induction of p75-dependent neuronal death in two distinct cellular systems. Our findings raise the possibility that pathological elevations in Aß42 contribute to cellular toxicity via the γ-secretase inhibition, and provide a novel conceptual framework to address Aß toxicity in the context of γ-secretase-dependent homeostatic signaling.

Spatial Omics Imaging of Fresh-Frozen Tissue and Routine FFPE Histopathology of a Single Cancer Needle Core Biopsy: A Freezing Device and Multimodal Workflow.

The complex molecular alterations that underlie cancer pathophysiology are studied in depth with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and the immunohistochemistry (IHC) of a few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI is an emerging diagnostic technology for the identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable, and precise methods for the preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and the routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for the multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology of the same biopsy core. As a proof-of-concept, we analyzed surgical human liver cancer specimens using IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis of the same biopsy core. This workflow allowed for a spatial comparison between different spectral profiles and alterations in tissue histology, as well as a direct comparison for histological diagnosis without the need for an extra biopsy.

Spatial probabilistic mapping of metabolite ensembles in mass spectrometry imaging.

Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR ( https://github.com/CeMOS-Mannheim/moleculaR ) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.

In vivo characterization of the bacterial intramembrane-cleaving protease RseP using the heme binding tag-based assay iCliPSpy.

Regulated intramembrane proteolysis (RIP) describes the protease-dependent cleavage of transmembrane proteins within the hydrophobic core of cellular membranes. Intramembrane-cleaving proteases (I-CliPs) that catalyze these reactions are found in all kingdoms of life and are involved in a wide range of cellular processes, including signaling and protein homeostasis. I-CLiPs are multispanning membrane proteins and represent challenging targets in structural and enzyme biology. Here we introduce iCLiPSpy, a simple assay to study I-CLiPs in vivo. To allow easy detection of enzyme activity, we developed a heme-binding reporter based on TNFα that changes color after I-CLiP-mediated proteolysis. Co-expression of the protease and reporter in Escherichia coli (E. coli) results in white or green colonies, depending on the activity of the protease. As a proof of concept, we use this assay to study the bacterial intramembrane-cleaving zinc metalloprotease RseP in vivo. iCLiPSpy expands the methodological repertoire for identifying residues important for substrate binding or activity of I-CLiPs and can in principle be adapted to a screening assay for the identification of inhibitors or activators of I-CLiPs, which is of great interest for proteases being explored as biomedical targets.

A Caged In-Source Laser-Cleavable MALDI Matrix with High Vacuum Stability for Extended MALDI-MS Imaging.

Insufficient vacuum stability of matrix chemicals is a major limitation in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) of large tissue sample cohorts. Here, we designed and synthesized the photo-cleavable caged molecule 4,5-dimethoxy-2-nitrobenzyl-2,5-dihydroxyacetophenone (DMNB-2,5-DHAP) and employed it for lipid MALDI-MSI of mouse brain tissue sections. DMNB-2,5-DHAP is vacuum-stable in a high vacuum MALDI ion source for at least 72 h. Investigation of the uncaging process suggested that the built-in laser (355 nm) in the MALDI ion source promoted the in situ generation of 2,5-DHAP. A caging group is used for the first time in designing a MALDI matrix that is vacuum-stable, uncaged upon laser irradiation during the measurement process, and that boosts lipid ion intensity with MALDI-2 laser-induced postionization.

Nanoliter Scale Parallel Liquid-Liquid Extraction for High-Throughput Purification on a Droplet Microarray.

In the current drug discovery process, the synthesis of compound libraries is separated from biological screenings both conceptually and technologically. One of the reasons is that parallel on-chip high-throughput purification of synthesized compounds is still a major challenge. Here, on-chip miniaturized high-throughput liquid-liquid extraction in volumes down to 150 nL with efficiency comparable to or better than large-scale extraction utilizing separation funnels is demonstrated. The method is based on automated and programmable merging of arrays of aqueous nanoliter droplets with organic droplets. Multi-step extraction performed simultaneously or with changing conditions as well as handling of femtomoles of compounds are demonstrated. In addition, the extraction efficiency is analyzed with a fast optical readout as well as matrix-assisted laser desorption ionization-mass spectrometry on-chip detection. The new massively parallel and miniaturized purification method adds another important tool to the chemBIOS concept combining chemical combinatorial synthesis with biological screenings on the same miniaturized droplet microarray platform, which will be essential to accelerate drug discovery.

Device-Controlled Microcondensation for Spatially Confined On-Tissue Digests in MALDI Imaging of N-Glycans.

On-tissue enzymatic digestion is a prerequisite for MALDI mass spectrometry imaging (MSI) and spatialomic analysis of tissue proteins and their N-glycan conjugates. Despite the more widely accepted importance of N-glycans as diagnostic and prognostic biomarkers of many diseases and their potential as pharmacodynamic markers, the crucial sample preparation step, namely on-tissue digestion with enzymes like PNGaseF, is currently mainly carried out by specialized laboratories using home-built incubation arrangements, e.g., petri dishes placed in an incubator. Standardized spatially confined enzyme digests, however, require precise control and possible regulation of humidity and temperature, as high humidity increases the risk of analyte dislocation and low humidity compromises enzyme function. Here, a digestion device that controls humidity by cyclic ventilation and heating of the slide holder and the chamber lid was designed to enable controlled micro-condensation on the slide and to stabilize and monitor the digestion process. The device presented here may help with standardization in MSI. Using sagittal mouse brain sections and xenografted human U87 glioblastoma cells in CD1 nu/nu mouse brain, a device-controlled workflow for MALDI MSI of N-glycans was developed.

Enzyme-substrate interface targeting by imidazole-based γ-secretase modulators activates γ-secretase and stabilizes its interaction with APP.

Alzheimer's disease (AD) pathogenesis has been linked to the accumulation of longer, aggregation-prone amyloid ß (Aß) peptides in the brain. Γ-secretases generate Aß peptides from the amyloid precursor protein (APP). Γ-secretase modulators (GSMs) promote the generation of shorter, less-amyloidogenic Aßs and have therapeutic potential. However, poorly defined drug-target interactions and mechanisms of action have hampered their therapeutic development. Here, we investigate the interactions between the imidazole-based GSM and its target γ-secretase-APP using experimental and in silico approaches. We map the GSM binding site to the enzyme-substrate interface, define a drug-binding mode that is consistent with functional and structural data, and provide molecular insights into the underlying mechanisms of action. In this respect, our analyses show that occupancy of a γ-secretase (sub)pocket, mediating binding of the modulator's imidazole moiety, is sufficient to trigger allosteric rearrangements in γ-secretase as well as stabilize enzyme-substrate interactions. Together, these findings may facilitate the rational design of new modulators of γ-secretase with improved pharmacological properties.

LPS-induced lipid alterations in microglia revealed by MALDI mass spectrometry-based cell fingerprinting in neuroinflammation studies.

Pathological microglia activation can promote neuroinflammation in many neurodegenerative diseases, and it has therefore emerged as a potential therapeutic target. Increasing evidence suggests alterations in lipid metabolism as modulators and indicators in microglia activation and its effector functions. Yet, how lipid dynamics in activated microglia is affected by inflammatory stimuli demands additional investigation to allow development of more effective therapies. Here, we report an extensive matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) whole cell fingerprinting workflow to investigate inflammation-associated lipid patterns in SIM-A9 microglial cells. By combining a platform of three synergistic MALDI MS technologies we could detect substantial differences in lipid profiles of lipopolysaccharide (LPS)- stimulated and unstimulated microglia-like cells leading to the identification of 21 potential inflammation-associated lipid markers. LPS-induced lipids in SIM-A9 microglial cells include phosphatidylcholines, lysophosphatidylcholines (LysoPC), sphingolipids, diacylglycerols and triacylglycerols. Moreover, MALDI MS-based cell lipid fingerprinting of LPS-stimulated SIM-A9 microglial cells pre-treated with the non-selective histone deacetylase inhibitor suberoylanilide hydroxamic acid revealed specific modulation of LPS-induced-glycerolipids and LysoPC(18:0) with a significant reduction of microglial inflammation response. Our study introduces MALDI MS as a complementary technology for fast and label-free investigation of stimulus-dependent changes in lipid patterns and their modulation by pharmaceutical agents.

A new update of MALDI-TOF mass spectrometry in lipid research.

Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) is an indispensable tool in modern lipid research since it is fast, sensitive, tolerates sample impurities and provides spectra without major analyte fragmentation. We will discuss some methodological aspects, the related ion-forming processes and the MALDI MS characteristics of the different lipid classes (with the focus on glycerophospholipids) and the progress, which was achieved during the last ten years. Particular attention will be given to quantitative aspects of MALDI MS since this is widely considered as the most serious drawback of the method. Although the detailed role of the matrix is not yet completely understood, it will be explicitly shown that the careful choice of the matrix is crucial (besides the careful evaluation of the positive and negative ion mass spectra) in order to be able to detect all lipid classes of interest. Two developments will be highlighted: spatially resolved Imaging MS is nowadays well established and the distribution of lipids in tissues merits increasing interest because lipids are readily detectable and represent ubiquitous compounds. It will also be shown that a combination of MALDI MS with thin-layer chromatography (TLC) enables a fast spatially resolved screening of an entire TLC plate which makes the method competitive with LC/MS.

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis.

Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.

Structural amyloid plaque polymorphism is associated with distinct lipid accumulations revealed by trapped ion mobility mass spectrometry imaging.

Understanding of Alzheimer's disease (AD) pathophysiology requires molecular assessment of how key pathological factors, specifically amyloid ß (Aß) plaques, influence the surrounding microenvironment. Here, neuronal lipids have been implicated in Aß plaque pathology, though the lipid microenvironment in direct proximity to Aß plaques is still not fully resolved. A further challenge is the microenvironmental molecular heterogeneity, across structurally polymorphic Aß features, such as diffuse, immature, and mature, fibrillary aggregates, whose resolution requires the integration of advanced, multimodal chemical imaging tools. Herein, we used matrix-assisted laser desorption/ionization trapped ion mobility spectrometry time-of-flight based mass spectrometry imaging (MALDI TIMS TOF MSI) in combination with hyperspectral confocal microscopy to probe the lipidomic microenvironment associated with structural polymorphism of Aß plaques in transgenic Alzheimer's disease mice (tgAPPSWE ). Using on tissue and ex situ validation, TIMS MS/MS facilitated unambiguous identification of isobaric lipid species that showed plaque pathology-associated localizations. Integrated multivariate imaging data analysis revealed multiple, Aß plaque-enriched lipid patterns for gangliosides (GM), phosphoinositols (PI), phosphoethanolamines (PE), and phosphatidic acids (PA). Conversely, sulfatides (ST), cardiolipins (CL), and polyunsaturated fatty acid (PUFA)-conjugated phosphoserines (PS), and PE were depleted at plaques. Hyperspectral amyloid imaging further delineated the unique distribution of PA and PE species to mature plaque core regions, while PI, LPI, GM2 and GM3 lipids localized to immature Aß aggregates present within the periphery of Aß plaques. Finally, we followed AD pathology-associated lipid changes over time, identifying plaque- growth and maturation to be characterized by peripheral accumulation of PI (18:0/22:6). Together, these data demonstrate the potential of multimodal imaging approaches to overcome limitations associated with conventional advanced MS imaging applications. This allowed for the differentiation of both distinct lipid components in a complex micro-environment as well as their correlation to disease-relevant amyloid plaque polymorphs. Cover Image for this issue: https://doi.org/10.1111/jnc.15390.

Label-free cell assays to determine compound uptake or drug action using MALDI-TOF mass spectrometry.

Cell-based assays for compound screening and profiling are fundamentally important in life sciences, chemical biology and pharmaceutical research. Most cell assays measure the amount of a single reporter molecule or cellular endpoint, and require the use of fluorescence or other labeled materials. Consequently, there is high demand for label-free technologies that enable multiple biomolecules or endpoints to be measured simultaneously. Here, we describe how to develop, optimize and validate MALDI-TOF mass spectrometry (MS) cell assays that can be used to measure cellular uptake of transporter substrates, to monitor cellular drug target engagement or to discover cellular drug-response markers. In uptake assays, intracellular accumulation of a transporter substrate and its inhibition by test compounds is measured. In drug response assays, changes to multiple cellular metabolites or to abundant posttranslational protein modifications are monitored as reporters of drug activity. We detail a ten-part optimization protocol with every part taking 1-2 d that leads to a final 2 d optimized procedure, which includes cell treatment, transfer, MALDI MS-specific sample preparation, quantification using stable-isotope-labeled standards, MALDI-TOF MS data acquisition, data processing and analysis. Key considerations for validation and automation of MALDI-TOF MS cell assays are outlined. Overall, label-free MS cell-based assays offer speed, sensitivity, accuracy and versatility in drug research.

Tryptophan metabolism is inversely regulated in the tumor and blood of patients with glioblastoma.

Tryptophan (Trp)-catabolic enzymes (TCEs) produce metabolites that activate the aryl hydrocarbon receptor (AHR) and promote tumor progression and immunosuppression in glioblastoma. As therapies targeting TCEs or AHR become available, a better understanding of Trp metabolism is required. Methods: The combination of LC-MS/MS with chemical isobaric labeling enabled the simultaneous quantitative comparison of Trp and its amino group-bearing metabolites in multiple samples. We applied this method to the sera of a cohort of 43 recurrent glioblastoma patients and 43 age- and sex-matched healthy controls. Tumor volumes were measured in MRI data using an artificial neural network-based approach. MALDI MSI visualized Trp and its direct metabolite N-formylkynurenine (FK) in glioblastoma tissue. Analysis of scRNA-seq data was used to detect the presence of Trp metabolism and AHR activity in different cell types in glioblastoma. Results: Compared to healthy controls, glioblastoma patients showed decreased serum Trp levels. Surprisingly, the levels of Trp metabolites were also reduced. The decrease became smaller with more enzymatic steps between Trp and its metabolites, suggesting that Trp availability controls the levels of its systemic metabolites. High tumor volume associated with low systemic metabolite levels and low systemic kynurenine levels associated with worse overall survival. MALDI MSI demonstrated heterogeneity of Trp catabolism across glioblastoma tissues. Analysis of scRNA-seq data revealed that genes involved in Trp metabolism were expressed in almost all the cell types in glioblastoma and that most cell types, in particular macrophages and T cells, exhibited AHR activation. Moreover, high AHR activity associated with reduced overall survival in the glioblastoma TCGA dataset. Conclusion: The novel techniques we developed could support the identification of patients that may benefit from therapies targeting TCEs or AHR activation.