ILC2-driven innate immune checkpoint mechanism antagonizes NK cell antimetastatic function in the lung.

Metastasis constitutes the primary cause of cancer-related deaths, with the lung being a commonly affected organ. We found that activation of lung-resident group 2 innate lymphoid cells (ILC2s) orchestrated suppression of natural killer (NK) cell-mediated innate antitumor immunity, leading to increased lung metastases and mortality. Using multiple models of lung metastasis, we show that interleukin (IL)-33-dependent ILC2 activation in the lung is involved centrally in promoting tumor burden. ILC2-driven innate type 2 inflammation is accompanied by profound local suppression of interferon-γ production and cytotoxic function of lung NK cells. ILC2-dependent suppression of NK cells is elaborated via an innate regulatory mechanism, which is reliant on IL-5-induced lung eosinophilia, ultimately limiting the metabolic fitness of NK cells. Therapeutic targeting of IL-33 or IL-5 reversed NK cell suppression and alleviated cancer burden. Thus, we reveal an important function of IL-33 and ILC2s in promoting tumor metastasis via their capacity to suppress innate type 1 immunity.

Imaging tumor lactate is feasible for identifying intermediate-risk prostate cancer patients with postsurgical biochemical recurrence.

While radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making.

Dissecting the Kinetic Mechanism of Human Lysine Methyltransferase 2D and Its Interactions with the WRAD2 Complex.

Human lysine methyltransferase 2D (hKMT2D) is an epigenetic writer catalyzing the methylation of histone 3 lysine 4. hKMT2D by itself has little catalytic activity and reaches full activation as part of the WRAD2 complex, additionally comprising binding partners WDR5, RbBP5, Ash2L, and DPY30. Here, a detailed mechanistic study of the hKMT2D SET domain and its WRAD2 interactions is described. We characterized the WRAD2 subcomplexes containing full-length components and the hKMT2D SET domain. By performing steady-state analysis as a function of WRAD2 concentration, we identified the inner stoichiometry and determined the binding affinities for complex formation. Ash2L and RbBP5 were identified as the binding partners critical for the full catalytic activity of the SET domain. Contrary to a previous report, product and dead-end inhibitor studies identified hKMT2D as a rapid equilibrium random Bi-Bi mechanism with EAP and EBQ dead-end complexes. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS) analysis showed that hKMT2D uses a distributive mechanism and gives further insights into how the WRAD2 components affect mono-, di-, and trimethylation. We also conclude that the Win motif of hKMT2D is not essential in complex formation, unlike other hKMT2 proteins.

Method To Visualize the Intratumor Distribution and Impact of Gemcitabine in Pancreatic Ductal Adenocarcinoma by Multimodal Imaging.

Gemcitabine (dFdC) is a common treatment for pancreatic cancer; however, it is thought that treatment may fail because tumor stroma prevents drug distribution to tumor cells. Gemcitabine is a pro-drug with active metabolites generated intracellularly; therefore, visualizing the distribution of parent drug as well as its metabolites is important. A multimodal imaging approach was developed using spatially coregistered mass spectrometry imaging (MSI), imaging mass cytometry (IMC), multiplex immunofluorescence microscopy (mIF), and hematoxylin and eosin (H&E) staining to assess the local distribution and metabolism of gemcitabine in tumors from a genetically engineered mouse model of pancreatic cancer (KPC) allowing for comparisons between effects in the tumor tissue and its microenvironment. Mass spectrometry imaging (MSI) enabled the visualization of the distribution of gemcitabine (100 mg/kg), its phosphorylated metabolites dFdCMP, dFdCDP and dFdCTP, and the inactive metabolite dFdU. Distribution was compared to small-molecule ATR inhibitor AZD6738 (25 mg/kg), which was codosed. Gemcitabine metabolites showed heterogeneous distribution within the tumor, which was different from the parent compound. The highest abundance of dFdCMP, dFdCDP, and dFdCTP correlated with distribution of endogenous AMP, ADP, and ATP in viable tumor cell regions, showing that gemcitabine active metabolites are reaching the tumor cell compartment, while AZD6738 was located to nonviable tumor regions. The method revealed that the generation of active, phosphorylated dFdC metabolites as well as treatment-induced DNA damage primarily correlated with sites of high proliferation in KPC PDAC tumor tissue, rather than sites of high parent drug abundance.

Pharmacological inhibition of MERTK induces in vivo retinal degeneration: a multimodal imaging ocular safety assessment.

The receptor tyrosine kinase, MERTK, plays an essential role in homeostasis of the retina via efferocytosis of shed outer nuclear segments of photoreceptors. The Royal College of Surgeons rat model of retinal degeneration has been linked to loss-of-function of MERTK, and together with the MERTK knock-out mouse, phenocopy retinitis pigmentosa in humans with MERTK mutations. Given recent efforts and interest in MERTK as a potential immuno-oncology target, development of a strategy to assess ocular safety at an early pre-clinical stage is critical. We have applied a state-of-the-art, multi-modal imaging platform to assess the in vivo effects of pharmacological inhibition of MERTK in mice. This involved the application of mass spectrometry imaging (MSI) to characterize the ocular spatial distribution of our highly selective MERTK inhibitor; AZ14145845, together with histopathology and transmission electron microscopy to characterize pathological and ultra-structural change in response to MERTK inhibition. In addition, we assessed the utility of a human retinal in vitro cell model to identify perturbation of phagocytosis post MERTK inhibition. We identified high localized total compound concentrations in the retinal pigment epithelium (RPE) and retinal lesions following 28 days of treatment with AZ14145845. These lesions were present in 4 of 8 treated animals, and were characterized by a thinning of the outer nuclear layer, loss of photoreceptors (PR) and accumulation of photoreceptor outer segments at the interface of the RPE and PRs. Furthermore, the lesions were very similar to that shown in the RCS rat and MERTK knock-out mouse, suggesting a MERTK-induced mechanism of PR cell death. This was further supported by the observation of reduced phagocytosis in the human retinal cell model following treatment with AZ14145845. Our study provides a viable, translational strategy to investigate the pre-clinical toxicity of MERTK inhibitors but is equally transferrable to novel chemotypes.

Evaluation of UV-C Decontamination of Clinical Tissue Sections for Spatially Resolved Analysis by Mass Spectrometry Imaging (MSI).

Clinical tissue specimens are often unscreened, and preparation of tissue sections for analysis by mass spectrometry imaging (MSI) can cause aerosolization of particles potentially carrying an infectious load. We here present a decontamination approach based on ultraviolet-C (UV-C) light to inactivate clinically relevant pathogens such as herpesviridae, papovaviridae human immunodeficiency virus, or SARS-CoV-2, which may be present in human tissue samples while preserving the biodistributions of analytes within the tissue. High doses of UV-C required for high-level disinfection were found to cause oxidation and photodegradation of endogenous species. Lower UV-C doses maintaining inactivation of clinically relevant pathogens to a level of increased operator safety were found to be less destructive to the tissue metabolome and xenobiotics. These doses caused less alterations of the tissue metabolome and allowed elucidation of the biodistribution of the endogenous metabolites. Additionally, we were able to determine the spatially integrated abundances of the ATR inhibitor ceralasertib from decontaminated human biopsies using desorption electrospray ionization-MSI (DESI-MSI).

Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration.

An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occasionally overlapping information at different length scales and spatial resolutions. It is important to understand the information provided by one technique in the context of the other to achieve a more holistic overview of such complex samples. One way to achieve this is to use annotations from one modality to investigate additional modalities. For microscopy-based techniques, these annotations could be manually generated using digital pathology software or automatically generated by machine learning (including deep learning) methods. Here, we present a generic method for using annotations from one microscopy modality to extract information from complementary modalities. We also present a fast, general, multimodal registration workflow [evaluated on multiple mass spectrometry imaging (MSI) modalities, matrix-assisted laser desorption/ionization, desorption electrospray ionization, and rapid evaporative ionization mass spectrometry] for automatic alignment of complex data sets, demonstrating an order of magnitude speed-up compared to previously published work. To demonstrate the power of the annotation transfer and multimodal registration workflows, we combine MSI, histological staining (such as hematoxylin and eosin), and deep learning (automatic annotation of histology images) to investigate a pancreatic cancer mouse model. Neoplastic pancreatic tissue regions, which were histologically indistinguishable from one another, were observed to be metabolically different. We demonstrate the use of the proposed methods to better understand tumor heterogeneity and the tumor microenvironment by transferring machine learning results freely between the two modalities.

Comparison of 13 C MRI of hyperpolarized [1-13 C]pyruvate and lactate with the corresponding mass spectrometry images in a murine lymphoma model.

PURPOSE: To compare carbon-13 (13 C) MRSI of hyperpolarized [1-13 C]pyruvate metabolism in a murine tumor model with mass spectrometric (MS) imaging of the corresponding tumor sections in order to cross validate these metabolic imaging techniques and to investigate the effects of pyruvate delivery and tumor lactate concentration on lactate labeling. METHODS: [1-13 C]lactate images were obtained from tumor-bearing mice, following injection of hyperpolarized [1-13 C]pyruvate, using a single-shot 3D 13 C spectroscopic imaging sequence in vivo and using desorption electrospray ionization MS imaging of the corresponding rapidly frozen tumor sections ex vivo. The images were coregistered, and levels of association were determined by means of Spearman rank correlation and Cohen kappa coefficients as well as linear mixed models. The correlation between [1-13 C]pyruvate and [1-13 C]lactate in the MRS images and between [12 C] and [1-13 C]lactate in the MS images were determined by means of Pearson correlation coefficients. RESULTS: [1-13 C]lactate images generated by MS imaging were significantly correlated with the corresponding MRS images. The correlation coefficient between [1-13 C]lactate and [1-13 C]pyruvate in the MRS images was higher than between [1-13 C]lactate and [12 C]lactate in the MS images. CONCLUSION: The inhomogeneous distribution of labeled lactate observed in the MRS images was confirmed by MS imaging of the corresponding tumor sections. The images acquired using both techniques show that the rate of 13 C label exchange between the injected pyruvate and endogenous tumor lactate pool is more correlated with the rate of pyruvate delivery to the tumor cells and is less affected by the endogenous lactate concentration.

Characterization of the Kinetic Mechanism of Human Protein Arginine Methyltransferase 5.

Protein arginine methyltransferases (PRMTs) are of great interest for the development of therapeutics due to their involvement in a number of malignancies, such as lung and colon cancer. PRMT5 catalyzes the formation of symmetrical dimethylarginine of a wide variety of substrates and is responsible for the majority of this mark within cells. To gain insight into the mechanism of PRMT5 inhibition, we co-expressed the human PRMT5:MEP50 complex (hPRMT5:MEP50) in insect cells for a detailed mechanistic study. In this report, we carry out steady state, product, and dead-end inhibitor studies that show hPRMT5:MEP50 uses a rapid equilibrium random order mechanism with EAP and EBQ dead-end complexes. We also provide evidence of ternary complex formation in solution using hydrogen/deuterium exchange mass spectrometry. Isotope exchange and intact protein mass spectrometry further rule out ping-pong as a potential enzyme mechanism, and finally, we show that PRMT5 exhibits a pre-steady state burst that corresponds to an initial slow turnover with all four active sites of the hetero-octamer being catalytically active.

Characterization of an Aggregated Three-Dimensional Cell Culture Model by Multimodal Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is an established analytical tool capable of defining and understanding complex tissues by determining the spatial distribution of biological molecules. Three-dimensional (3D) cell culture models mimic the pathophysiological environment of in vivo tumors and are rapidly emerging as a valuable research tool. Here, multimodal MSI techniques were employed to characterize a novel aggregated 3D lung adenocarcinoma model, developed by the group to mimic the in vivo tissue. Regions of tumor heterogeneity and the hypoxic microenvironment were observed based on the spatial distribution of a variety of endogenous molecules. Desorption electrospray ionization (DESI)-MSI defined regions of a hypoxic core and a proliferative outer layer from metabolite distribution. Targeted metabolites (e.g., lactate, glutamine, and citrate) were mapped to pathways of glycolysis and the TCA cycle demonstrating tumor metabolic behavior. The first application of imaging mass cytometry (IMC) with 3D cell culture enabled single-cell phenotyping at 1 µm spatial resolution. Protein markers of proliferation (Ki-67) and hypoxia (glucose transporter 1) defined metabolic signaling in the aggregoid model, which complemented the metabolite data. Laser ablation inductively coupled plasma (LA-ICP)-MSI analysis localized endogenous elements including magnesium and copper, further differentiating the hypoxia gradient and validating the protein expression. Obtaining a large amount of molecular information on a complementary nature enabled an in-depth understanding of the biological processes within the novel tumor model. Combining powerful imaging techniques to characterize the aggregated 3D culture highlighted a future methodology with potential applications in cancer research and drug development.

Universal Sample Preparation Unlocking Multimodal Molecular Tissue Imaging.

A new tissue sample embedding and processing method is presented that provides downstream compatibility with numerous different histological, molecular biology, and analytical techniques. The methodology is based on the low temperature embedding of fresh frozen specimens into a hydrogel matrix composed of hydroxypropyl methylcellulose (HPMC) and polyvinylpyrrolidone (PVP) and sectioning using a cryomicrotome. The hydrogel was expected not to interfere with standard tissue characterization methods, histologically or analytically. We assessed the compatibility of this protocol with various mass spectrometric imaging methods including matrix-assisted laser desorption ionization (MALDI), desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS). We also demonstrated the suitability of the universal protocol for extraction based molecular biology techniques such as rt-PCR. The integration of multiple analytical modalities through this universal sample preparation protocol offers the ability to study tissues at a systems biology level and directly linking results to tissue morphology and cellular phenotype.

Untargeted Metabolite Mapping in 3D Cell Culture Models Using High Spectral Resolution FT-ICR Mass Spectrometry Imaging.

Multicellular tumor spheroids (MTS) are a well-established model system for drug development and are a valuable in vitro research tool for use prior to employing animal models. These 3D-cell cultures are thought to display chemical gradients of oxygen and nutrients throughout their structure, giving rise to distinct microenvironments in radial layers, thus, mimicking the pathophysiological environment of a tumor. Little is known about the localized distributions of metabolites within these microenvironments. To address this, here we utilize high spectral resolution Fourier-transform ion cyclotron resonance (FT-ICR), MALDI mass spectrometry imaging (MSI) to image the distribution of endogenous metabolites in breast cancer MCF-7 spheroids. We show that known specific metabolite markers (adenosine phosphates and glutathione) indicate that the central region of these cell culture models experiences increased hypoxic and oxidative stress. By using discriminatory analysis, we have identified which m/z values localize toward the outer proliferative or central hypoxic regions of an MTS. Elemental formulae were assigned with sub-ppm mass accuracy, allowing metabolite assignment. Using this information, we have mapped these metabolites back to distinct pathways to improve our understanding of the molecular environment and biochemistry of these tumor models.

Toxicologic Pathology Forum*: Opinion on Integrating Innovative Digital Pathology Tools in the Regulatory Framework.

Digital pathology is defined as the ability to examine digitized microscopic slides and to generate qualitative and quantitative data. The field of digital pathology is rapidly evolving and has the potential to revolutionize toxicologic pathology. Techniques such as automated 2-D image analysis, whole slide imaging, and telepathology are already considered "mature" technologies and have been used for decades in exploratory studies; however, many organizations are reluctant to use digital pathology in regulatory toxicology studies. Innovative technologies using digitized slides including high-content imaging modalities and artificial intelligence are still under development but are increasingly used in toxicologic pathology. While software validation requirements are already described, clear guidance for application of these rules to the digital pathology field are few and the acceptance of these technologies by regulatory authorities remains necessary for successful adoption of digital pathology into the mainstream of toxicologic pathology. This topic was discussed during a roundtable at the 2018 Annual Congress of the French Society of Toxicologic Pathology. This opinion article summarizes the discussion regarding the current questions and challenges on the integration of innovative digital pathology tools within a good laboratory practice framework and is meant to stimulate further discussion among the toxicologic pathology community. *This is an opinion article submitted to the Toxicologic Pathology Forum and does not constitute an official position of the Society of Toxicologic Pathology or the journal Toxicologic Pathology. The views expressed in this article are those of the authors and do not necessarily represent the policies, positions, or opinions of their respective agencies and organizations. The Toxicologic Forum is designed to stimulate broad discussion of topics relevant to regulatory issues in Toxicologic pathology. Readers of Toxicologic Pathology are encouraged to send their thoughts on these articles or ideas for new topics to toxicologicpathologyforum@toxpath.org .

A mass spectrometry imaging approach for investigating how drug-drug interactions influence drug blood-brain barrier permeability.

There is a high need to develop quantitative imaging methods capable of providing detailed brain localization information of several molecular species simultaneously. In addition, extensive information on the effect of the blood-brain barrier on the penetration, distribution and efficacy of neuroactive compounds is required. Thus, we have developed a mass spectrometry imaging method to visualize and quantify the brain distribution of drugs with varying blood-brain barrier permeability. With this approach, we were able to determine blood-brain barrier transport of different drugs and define the drug distribution in very small brain structures (e.g., choroid plexus) due to the high spatial resolution provided. Simultaneously, we investigated the effect of drug-drug interactions by inhibiting the membrane transporter multidrug resistance 1 protein. We propose that the described approach can serve as a valuable analytical tool during the development of neuroactive drugs, as it can provide physiologically relevant information often neglected by traditional imaging technologies.

MALDI Matrix Application Utilizing a Modified 3D Printer for Accessible High Resolution Mass Spectrometry Imaging.

Successful matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) relies on the selection of the most appropriate matrix and optimization of the matrix application parameters. In order to achieve reproducible high spatial-resolution imaging data, several commercially available automated matrix application platforms have become available. However, the high cost of these commercial matrix sprayers is restricting access into this emerging research field. Here, we report an automated platform for matrix deposition, employing a converted commercially available 3D printer ($300) and other parts commonly found in an analytical chemistry lab as a low-cost alternative to commercial sprayers. Using printed fluorescent rhodamine B microarrays and employing experimental design, the matrix deposition parameters were optimized to minimize surface analyte diffusion. Finally, the optimized matrix application method was applied to image three-dimensional MCF-7 cell culture spheroid sections (ca. 500 µm diameter tissue samples) and sections of mouse brain. Using this system, we demonstrate robust and reproducible observations of endogenous metabolite and steroid distributions with a high spatial resolution.

Quantitation of Endogenous Metabolites in Mouse Tumors Using Mass-Spectrometry Imaging.

Described is a quantitative-mass-spectrometry-imaging (qMSI) methodology for the analysis of lactate and glutamate distributions in order to delineate heterogeneity among mouse tumor models used to support drug-discovery efficacy testing. We evaluate and report on preanalysis-stabilization methods aimed at improving the reproducibility and efficiency of quantitative assessments of endogenous molecules in tissues. Stability experiments demonstrate that optimum stabilization protocols consist of frozen-tissue embedding, post-tissue-sectioning desiccation, and storage at -80 °C of tissue sections sealed in vacuum-tight containers. Optimized stabilization protocols are used in combination with qMSI methodology for the absolute quantitation of lactate and glutamate in tumors, incorporating the use of two different stable-isotope-labeled versions of each analyte and spectral-clustering performed on each tissue section using k-means clustering to allow region-specific, pixel-by-pixel quantitation. Region-specific qMSI was used to screen different tumor models and identify a phenotype that has low lactate heterogeneity, which will enable accurate measurements of lactate modulation in future drug-discovery studies. We conclude that using optimized qMSI protocols, it is possible to quantify endogenous metabolites within tumors, and region-specific quantitation can provide valuable insight into tissue heterogeneity and the tumor microenvironment.

Multimodal Mass Spectrometry Imaging of an Osteosarcoma Multicellular Tumour Spheroid Model to Investigate Drug-Induced Response.

A multimodal mass spectrometry imaging (MSI) approach was used to investigate the chemotherapy drug-induced response of a Multicellular Tumour Spheroid (MCTS) 3D cell culture model of osteosarcoma (OS). The work addresses the critical demand for enhanced translatable early drug discovery approaches by demonstrating a robust spatially resolved molecular distribution analysis in tumour models following chemotherapeutic intervention. Advanced high-resolution techniques were employed, including desorption electrospray ionisation (DESI) mass spectrometry imaging (MSI), to assess the interplay between metabolic and cellular pathways in response to chemotherapeutic intervention. Endogenous metabolite distributions of the human OS tumour models were complemented with subcellularly resolved protein localisation by the detection of metal-tagged antibodies using Imaging Mass Cytometry (IMC). The first application of matrix-assisted laser desorption ionization-immunohistochemistry (MALDI-IHC) of 3D cell culture models is reported here. Protein localisation and expression following an acute dosage of the chemotherapy drug doxorubicin demonstrated novel indications for mechanisms of region-specific tumour survival and cell-cycle-specific drug-induced responses. Previously unknown doxorubicin-induced metabolite upregulation was revealed by DESI-MSI of MCTSs, which may be used to inform mechanisms of chemotherapeutic resistance. The demonstration of specific tumour survival mechanisms that are characteristic of those reported for in vivo tumours has underscored the increasing value of this approach as a tool to investigate drug resistance.

Metabolic imaging across scales reveals distinct prostate cancer phenotypes.

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

Preclinical Characterization of AZD9574, a Blood-Brain Barrier Penetrant Inhibitor of PARP1.

PURPOSE: We evaluated the properties and activity of AZD9574, a blood-brain barrier (BBB) penetrant selective inhibitor of PARP1, and assessed its efficacy and safety alone and in combination with temozolomide (TMZ) in preclinical models. EXPERIMENTAL DESIGN: AZD9574 was interrogated in vitro for selectivity, PARylation inhibition, PARP-DNA trapping, the ability to cross the BBB, and the potential to inhibit cancer cell proliferation. In vivo efficacy was determined using subcutaneous as well as intracranial mouse xenograft models. Mouse, rat, and monkey were used to assess AZD9574 BBB penetration and rat models were used to evaluate potential hematotoxicity for AZD9574 monotherapy and the TMZ combination. RESULTS: AZD9574 demonstrated PARP1-selectivity in fluorescence anisotropy, PARylation, and PARP-DNA trapping assays and in vivo experiments demonstrated BBB penetration. AZD9574 showed potent single agent efficacy in preclinical models with homologous recombination repair deficiency in vitro and in vivo. In an O6-methylguanine-DNA methyltransferase (MGMT)-methylated orthotopic glioma model, AZD9574 in combination with TMZ was superior in extending the survival of tumor-bearing mice compared with TMZ alone. CONCLUSIONS: The combination of three key features-PARP1 selectivity, PARP1 trapping profile, and high central nervous system penetration in a single molecule-supports the development of AZD9574 as the best-in-class PARP inhibitor for the treatment of primary and secondary brain tumors. As documented by in vitro and in vivo studies, AZD9574 shows robust anticancer efficacy as a single agent as well as in combination with TMZ. AZD9574 is currently in a phase I trial (NCT05417594). See related commentary by Lynce and Lin, p. 1217.

Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies.

With increased use of mass spectrometry imaging (MSI) in support of pharmaceutical research and development, there are opportunities to develop analytical pipelines that incorporate exploratory high-performance analysis with higher capacity and faster targeted MSI. Therefore, to enable faster MSI data acquisition we present analyte-targeted desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) utilizing a triple-quadrupole (TQ) mass analyzer. The evaluated platform configuration provided superior sensitivity compared to a conventional time-of-flight (TOF) mass analyzer and thus holds the potential to generate data applicable to pharmaceutical research and development. The platform was successfully operated with sampling rates up to 10 scans/s, comparing positively to the 1 scan/s commonly used on comparable DESI-TOF setups. The higher scan rate enabled investigation of the desorption/ionization processes of endogenous lipid species such as phosphatidylcholines and a co-administered cassette of four orally dosed drugs-erlotininb, moxifloxacin, olanzapine, and terfenadine. This was used to enable understanding of the impact of the desorption/ionization processes in order to optimize the operational parameters, resulting in improved compound coverage for olanzapine and the main olanzapine metabolite, hydroxy-olanzapine, in brain tissue sections compared to DESI-TOF analysis or matrix-assisted laser desorption/ionization (MALDI) platforms. The approach allowed reducing the amount of recorded information, thus reducing the size of datasets from up to 150 GB per experiment down to several hundred MB. The improved performance was demonstrated in case studies investigating the suitability of this approach for mapping drug distribution, spatially resolved profiling of drug-induced nephrotoxicity, and molecular-histological tissue classification of ovarian tumors specimens.