ABSTRACT
The unfolded protein response (UPR) detects and mitigates the harmful effects of dysregulated endoplasmic reticulum (ER) function. The UPR has been best characterized as a protein quality control response, and the sole UPR sensor in yeast, Ire1, is known to detect misfolded ER proteins. However, recent work suggests the UPR can also sense diverse defects within the ER membrane, including increased fatty acid saturation and altered phospholipid abundance. These and other lipid-related stimuli have been referred to as lipid bilayer stress and may be sensed independently through Ire1's transmembrane domain. Here, we show that the loss of Isc1, a phospholipase that catabolizes complex ceramides, causes UPR induction, even in the absence of exogenous stress. A series of chemical and genetic approaches identified a requirement for very long-chain fatty acid (VLCFA)-containing phytoceramides for UPR induction. In parallel, comprehensive lipidomics analyses identified large increases in the abundance of specific VLCFA-containing phytoceramides in the isc1Δ mutant. We failed to identify evidence of an accompanying defect in protein quality control or ER-associated protein degradation. These results extend our understanding of lipid bilayer stress in the UPR and provide a foundation for mechanistic investigation of this fascinating intersection between ceramide metabolism, membrane homeostasis, and the UPR.
Subject(s)
Ceramides , Endoplasmic Reticulum Stress , Endoplasmic Reticulum , Saccharomyces cerevisiae Proteins , Saccharomyces cerevisiae , Unfolded Protein Response , Ceramides/metabolism , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae/genetics , Endoplasmic Reticulum/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae Proteins/genetics , Fatty Acids/metabolism , Phospholipases/metabolism , Type C PhospholipasesABSTRACT
Medulloblastoma is one of the most common malignant brain tumors of children, and 30% of medulloblastomas are driven by gain-of-function genetic lesions in the Sonic Hedgehog (SHH) signaling pathway. EYA1, a haloacid dehalogenase phosphatase and transcription factor, is critical for tumorigenesis and proliferation of SHH medulloblastoma (SHH-MB). Benzarone and benzbromarone have been identified as allosteric inhibitors of EYA proteins. Using benzarone as a point of departure, we developed a panel of 35 derivatives and tested them in SHH-MB. Among these compounds, DS-1-38 functioned as an EYA antagonist and opposed SHH signaling. DS-1-38 inhibited SHH-MB growth in vitro and in vivo, showed excellent brain penetrance, and increased the lifespan of genetically engineered mice predisposed to fatal SHH-MB. These data suggest that EYA inhibitors represent promising therapies for pediatric SHH-MB. SIGNIFICANCE: Development of a benzarone derivative that inhibits EYA1 and impedes the growth of SHH medulloblastoma provides an avenue for improving treatment of this malignant pediatric brain cancer.
Subject(s)
Benzbromarone/analogs & derivatives , Brain Neoplasms , Cerebellar Neoplasms , Medulloblastoma , Animals , Mice , Humans , Child , Hedgehog Proteins , Medulloblastoma/drug therapy , Medulloblastoma/genetics , Cerebellar Neoplasms/drug therapyABSTRACT
The metabolic demands of neuronal activity are both temporally and spatially dynamic, and neurons are particularly sensitive to disruptions in fuel and oxygen supply. Glucose is considered an obligate fuel for supporting brain metabolism. Although alternative fuels are often available, the extent of their contribution to central carbon metabolism remains debated. Differential fuel metabolism likely depends on cell type, location, and activity state, complicating its study. While biosensors provide excellent spatial and temporal information, they are limited to observations of only a few metabolites. On the other hand, mass spectrometry is rich in chemical information, but traditionally relies on cell culture or homogenized tissue samples. Here, we use mass spectrometry imaging (MALDI-MSI) to focus on the fuel metabolism of the dentate granule cell (DGC) layer in murine hippocampal slices. Using stable isotopes, we explore labeling dynamics at baseline, as well as in response to brief stimulation or fuel competition. We find that at rest, glucose is the predominant fuel metabolized through glycolysis, with little to no measurable contribution from glycerol or fructose. However, lactate/pyruvate, ß-hydroxybutyrate (ßHB), octanoate, and glutamine can contribute to TCA metabolism to varying degrees. In response to brief depolarization with 50 mM KCl, glucose metabolism was preferentially increased relative to the metabolism of alternative fuels. With an increased supply of alternative fuels, both lactate/pyruvate and ßHB can outcompete glucose for TCA cycle entry. While lactate/pyruvate modestly reduced glucose contribution to glycolysis, ßHB caused little change in glycolysis. This approach achieves broad metabolite coverage from a spatially defined region of physiological tissue, in which metabolic states are rapidly preserved following experimental manipulation. Using this powerful methodology, we investigated metabolism within the dentate gyrus not only at rest, but also in response to the energetic demand of activation, and in states of fuel competition.
ABSTRACT
The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), lose aspects of normal biology and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to fuel these processes is poorly understood. Here we perform infusions of 13 C-labeled glucose into patients and mice with brain cancer to define the metabolic fates of glucose-derived carbon in tumor and cortex. By combining these measurements with quantitative metabolic flux analysis, we find that human cortex funnels glucose-derived carbons towards physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. In contrast, brain cancers downregulate these physiologic processes, scavenge alternative carbon sources from the environment, and instead use glucose-derived carbons to produce molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary modulation selectively alters GBM metabolism and slows tumor growth. Significance: This study is the first to directly measure biosynthetic flux in both glioma and cortical tissue in human brain cancer patients. Brain tumors rewire glucose carbon utilization away from oxidation and neurotransmitter production towards biosynthesis to fuel growth. Blocking these metabolic adaptations with dietary interventions slows brain cancer growth with minimal effects on cortical metabolism.
ABSTRACT
For the characterization of the metabolic heterogeneity of cell populations, high-throughput single-cell analysis platforms are needed. In this study, we utilized mass spectrometry (MS) enhanced with ion mobility separation (IMS) and coupled with an automated sampling platform, fiber-based laser ablation electrospray ionization (f-LAESI), for in situ high-throughput single-cell metabolomics in soybean (Glycine max) root nodules. By fully automating the in situ sampling platform, an overall sampling rate of 804 cells/h was achieved for high numbers (>500) of tissue-embedded plant cells. This is an improvement by a factor of 13 compared to the previous f-LAESI-MS configuration. By introducing IMS, the molecular coverage improved, and structural isomers were separated on a millisecond time scale. The enhanced f-LAESI-IMS-MS platform produced 259 sample-related peaks/cell, almost twice as much as the 131 sample-related peaks/cell produced by f-LAESI-MS without IMS. Using the upgraded system, two types of metabolic heterogeneity characterization methods became possible. For unimodal metabolite abundance distributions, the metabolic noise reported on the metabolite level variations within the cell population. For bimodal distributions, the presence of metabolically distinct subpopulations was established. Discovering these latent cellular phenotypes could be linked to the presence of different cell states, e.g., proliferating bacteria in partially occupied plant cells and quiescent bacteroids in fully occupied cells in biological nitrogen fixation, or spatial heterogeneity due to altered local environments.
Subject(s)
Laser Therapy , Spectrometry, Mass, Electrospray Ionization , Spectrometry, Mass, Electrospray Ionization/methods , Nitrogen Fixation , Metabolomics/methods , Glycine maxABSTRACT
Neuronal activity creates an intense energy demand that must be met by rapid metabolic responses. To investigate metabolic adaptations in the neuron-enriched dentate granule cell (DGC) layer within its native tissue environment, we employed murine acute hippocampal brain slices, coupled with fast metabolite preservation and followed by mass spectrometry (MS) imaging, to generate spatially resolved metabolomics and isotope-tracing data. Here we show that membrane depolarization induces broad metabolic changes, including increased glycolytic activity in DGCs. Increased glucose metabolism in response to stimulation is accompanied by mobilization of endogenous inosine into pentose phosphates via the action of purine nucleotide phosphorylase (PNP). The PNP reaction is an integral part of the neuronal response to stimulation, because inhibition of PNP leaves DGCs energetically impaired during recovery from strong activation. Performing MS imaging on brain slices bridges the gap between live-cell physiology and the deep chemical analysis enabled by MS.
Subject(s)
Dentate Gyrus , Neurons , Mice , Animals , Dentate Gyrus/physiology , Cell Membrane , Isotopes , MetabolomicsABSTRACT
Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a powerful analytical technique that provides spatially preserved detection and quantification of analytes in tissue specimens. However, clinical translation still requires improved throughput, precision, and accuracy. To accomplish this, we created "Chemical QuantArray", a gelatin tissue microarray (TMA) mold filled with serial dilutions of isotopically labeled endogenous metabolite standards. The mold is then cryo-sectioned onto a tissue homogenate to produce calibration curves. To improve precision and accuracy, we automatically remove pixels outside of each TMA well and investigated several intensity normalizations, including the utilization of a second stable isotope internal standard (IS). Chemical QuantArray enables the quantification of several endogenous metabolites over a wide dynamic range and significantly improve over current approaches. The technique reduces the space needed on the MALDI slides for calibration standards by approximately 80%. Furthermore, removal of empty pixels and normalization to an internal standard or matrix peak provided precision (<20% RSD) and accuracy (<20% DEV). Finally, we demonstrate the applicability of Chemical QuantArray by quantifying multiple purine metabolites in 14 clinical tumor specimens using a single MALDI slide. Chemical QuantArray improves the analytical characteristics and practical feasibility of MALDI-MSI metabolite quantification in clinical and translational applications.
Subject(s)
Diagnostic Imaging , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Calibration , Reference StandardsABSTRACT
Background: Although the epidermal growth factor receptor (EGFR) is a frequent oncogenic driver in glioblastoma (GBM), efforts to therapeutically target this protein have been largely unsuccessful. The present preclinical study evaluated the novel EGFR inhibitor WSD-0922. Methods: We employed flank and orthotopic patient-derived xenograft models to characterize WSD-0922 and compare its efficacy to erlotinib, a potent EGFR inhibitor that failed to provide benefit for GBM patients. We performed long-term survival studies and collected short-term tumor, plasma, and whole-brain samples from mice treated with each drug. We utilized mass spectrometry to measure drug concentrations and spatial distribution and to assess the impact of each drug on receptor activity and cellular signaling networks. Results: WSD-0922 inhibited EGFR signaling as effectively as erlotinib in in vitro and in vivo models. While WSD-0922 was more CNS penetrant than erlotinib in terms of total concentration, comparable concentrations of both drugs were measured at the tumor site in orthotopic models, and the concentration of free WSD-0922 in the brain was significantly less than the concentration of free erlotinib. WSD-0922 treatment provided a clear survival advantage compared to erlotinib in the GBM39 model, with marked suppression of tumor growth and most mice surviving until the end of the study. WSD-0922 treatment preferentially inhibited phosphorylation of several proteins, including those associated with EGFR inhibitor resistance and cell metabolism. Conclusions: WSD-0922 is a highly potent inhibitor of EGFR in GBM, and warrants further evaluation in clinical studies.
ABSTRACT
Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectrometric imaging data of the corresponding tissue to determine the cancerous regions and their unique chemical signatures and variations of the predicted regions with original pathological annotations. We obtain features from high-resolution optical micrographs of whole slide H&E stained data through deep learning and spatially register them with mass spectrometry imaging (MSI) data to correlate the chemical signature with the tissue anatomy of the data. We then use the learned correlation to predict prostate cancer from observed H&E images using trained coregistered MSI data. This multimodal approach can predict cancerous regions with â¼80% accuracy, which indicates a correlation between optical H&E features and chemical information found in MSI. We show that such paired multimodal data can be used for training feature extraction networks on H&E data which bypasses the need to acquire expensive MSI data and eliminates the need for manual annotation saving valuable time. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This study shows promise in generating improved patient treatment trajectories by predicting prostate cancer directly from readily available H&E-stained biopsy images aided by coregistered MSI data.
Subject(s)
Deep Learning , Prostatic Neoplasms , Humans , Male , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methodsABSTRACT
Glioblastoma (GBM) is a primary brain cancer with an abysmal prognosis and few effective therapies. The ability to investigate the tumor microenvironment before and during treatment would greatly enhance both understanding of disease response and progression, as well as the delivery and impact of therapeutics. Stereotactic biopsies are a routine surgical procedure performed primarily for diagnostic histopathologic purposes. The role of investigative biopsies - tissue sampling for the purpose of understanding tumor microenvironmental responses to treatment using integrated multi-modal molecular analyses ('Multi-omics") has yet to be defined. Secondly, it is unknown whether comparatively small tissue samples from brain biopsies can yield sufficient information with such methods. Here we adapt stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analysis methods including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue that was obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft models in a separate patient cohort. Dataset integration across modalities showed good correspondence between spatial modalities, highlighted immune cell associated metabolic pathways and revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data, provide data rich insight into a patient's disease process and tumor immune microenvironment and can be of value in evaluating treatment responses. One sentence summary: Integrative multi-omics analysis of stereotactic needle core biopsies in glioblastoma.
ABSTRACT
BACKGROUND: Topotecan is cytotoxic to glioma cells but is clinically ineffective because of drug delivery limitations. Systemic delivery is limited by toxicity and insufficient brain penetrance, and, to date, convection-enhanced delivery (CED) has been restricted to a single treatment of restricted duration. To address this problem, we engineered a subcutaneously implanted catheter-pump system capable of repeated, chronic (prolonged, pulsatile) CED of topotecan into the brain and tested its safety and biological effects in patients with recurrent glioblastoma. METHODS: We did a single-centre, open-label, single-arm, phase 1b clinical trial at Columbia University Irving Medical Center (New York, NY, USA). Eligible patients were at least 18 years of age with solitary, histologically confirmed recurrent glioblastoma showing radiographic progression after surgery, radiotherapy, and chemotherapy, and a Karnofsky Performance Status of at least 70. Five patients had catheters stereotactically implanted into the glioma-infiltrated peritumoural brain and connected to subcutaneously implanted pumps that infused 146 µM topotecan 200 µL/h for 48 h, followed by a 5-7-day washout period before the next infusion, with four total infusions. After the fourth infusion, the pump was removed and the tumour was resected. The primary endpoint of the study was safety of the treatment regimen as defined by presence of serious adverse events. Analyses were done in all treated patients. The trial is closed, and is registered with ClinicalTrials.gov, NCT03154996. FINDINGS: Between Jan 22, 2018, and July 8, 2019, chronic CED of topotecan was successfully completed safely in all five patients, and was well tolerated without substantial complications. The only grade 3 adverse event related to treatment was intraoperative supplemental motor area syndrome (one [20%] of five patients in the treatment group), and there were no grade 4 adverse events. Other serious adverse events were related to surgical resection and not the study treatment. Median follow-up was 12 months (IQR 10-17) from pump explant. Post-treatment tissue analysis showed that topotecan significantly reduced proliferating tumour cells in all five patients. INTERPRETATION: In this small patient cohort, we showed that chronic CED of topotecan is a potentially safe and active therapy for recurrent glioblastoma. Our analysis provided a unique tissue-based assessment of treatment response without the need for large patient numbers. This novel delivery of topotecan overcomes limitations in delivery and treatment response assessment for patients with glioblastoma and could be applicable for other anti-glioma drugs or other CNS diseases. Further studies are warranted to determine the effect of this drug delivery approach on clinical outcomes. FUNDING: US National Institutes of Health, The William Rhodes and Louise Tilzer Rhodes Center for Glioblastoma, the Michael Weiner Glioblastoma Research Into Treatment Fund, the Gary and Yael Fegel Foundation, and The Khatib Foundation.
Subject(s)
Glioblastoma , Glioma , Humans , Topotecan/adverse effects , Glioblastoma/drug therapy , Convection , Neoplasm Recurrence, Local/drug therapy , Glioma/pathologyABSTRACT
Poly(ADP)ribosylation inhibitors (PARPis) are toxic to cancer cells with homologous recombination (HR) deficiency but not to HR-proficient cells in the tumor microenvironment (TME), including tumor-associated macrophages (TAMs). As TAMs can promote or inhibit tumor growth, we set out to examine the effects of PARP inhibition on TAMs in BRCA1-related breast cancer (BC). The PARPi olaparib causes reprogramming of TAMs toward higher cytotoxicity and phagocytosis. A PARPi-related surge in NAD+ increases glycolysis, blunts oxidative phosphorylation, and induces reverse mitochondrial electron transport (RET) with an increase in reactive oxygen species (ROS) and transcriptional reprogramming. This reprogramming occurs in the absence or presence of PARP1 or PARP2 and is partially recapitulated by addition of NAD derivative methyl-nicotinamide (MNA). In vivo and ex vivo, the effect of olaparib on TAMs contributes to the anti-tumor efficacy of the PARPi. In vivo blockade of the "don't-eat-me signal" with CD47 antibodies in combination with olaparib improves outcomes in a BRCA1-related BC model.
Subject(s)
CD47 Antigen , Poly(ADP-ribose) Polymerase Inhibitors , Adenosine Diphosphate , Cell Line, Tumor , Macrophages , NAD , Niacinamide , Phenotype , Phthalazines/pharmacology , Poly(ADP-ribose) Polymerase Inhibitors/pharmacology , Poly(ADP-ribose) Polymerase Inhibitors/therapeutic use , Reactive Oxygen SpeciesABSTRACT
Gain-of-function mutations in isocitrate dehydrogenase (IDH) in human cancers result in the production of d-2-hydroxyglutarate (d-2HG), an oncometabolite that promotes tumorigenesis through epigenetic alterations. The cancer cell-intrinsic effects of d-2HG are well understood, but its tumor cell-nonautonomous roles remain poorly explored. We compared the oncometabolite d-2HG with its enantiomer, l-2HG, and found that tumor-derived d-2HG was taken up by CD8+ T cells and altered their metabolism and antitumor functions in an acute and reversible fashion. We identified the glycolytic enzyme lactate dehydrogenase (LDH) as a molecular target of d-2HG. d-2HG and inhibition of LDH drive a metabolic program and immune CD8+ T cell signature marked by decreased cytotoxicity and impaired interferon-γ signaling that was recapitulated in clinical samples from human patients with IDH1 mutant gliomas.
Subject(s)
CD8-Positive T-Lymphocytes , Carcinogenesis , Glutarates , Isocitrate Dehydrogenase , Neoplasms , Animals , CD8-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/metabolism , Carcinogenesis/genetics , Carcinogenesis/metabolism , Gain of Function Mutation , Glutarates/metabolism , Humans , Interferon-gamma/metabolism , Isocitrate Dehydrogenase/genetics , Isocitrate Dehydrogenase/metabolism , L-Lactate Dehydrogenase/antagonists & inhibitors , L-Lactate Dehydrogenase/metabolism , Mice , Neoplasms/genetics , Neoplasms/immunology , Neoplasms/metabolismABSTRACT
Cells adapt their metabolism to physiological stimuli, and metabolic heterogeneity exists between cell types, within tissues, and subcellular compartments. The liver plays an essential role in maintaining whole-body metabolic homeostasis and is structurally defined by metabolic zones. These zones are well-understood on the transcriptomic level, but have not been comprehensively characterized on the metabolomic level. Mass spectrometry imaging (MSI) can be used to map hundreds of metabolites directly from a tissue section, offering an important advance to investigate metabolic heterogeneity in tissues compared to extraction-based metabolomics methods that analyze tissue metabolite profiles in bulk. We established a workflow for the preparation of tissue specimens for matrix-assisted laser desorption/ionization (MALDI) MSI that can be implemented to achieve broad coverage of central carbon, nucleotide, and lipid metabolism pathways. Herein, we used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic tissue compartmentalization in livers, which becomes disrupted under high fat diet. Fasting caused changes in the abundance of several metabolites, including increased levels of fatty acids and TCA intermediates while fatty livers had higher levels of purine and pentose phosphate-related metabolites, which generate reducing equivalents to counteract oxidative stress. This spatially conserved approach allowed the visualization of liver metabolic compartmentalization at 30 µm pixel resolution and can be applied more broadly to yield new insights into metabolic heterogeneity in vivo.
Subject(s)
Diet, High-Fat , Fasting , Liver , Metabolomics/methods , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methodsABSTRACT
Background: EGFR targeting antibody-drug conjugates (ADCs) are highly effective against EGFR-amplified tumors, but poor distribution across the blood-brain barrier (BBB) limits their efficacy in glioblastoma (GBM) when administered systemically. We studied whether convection-enhanced delivery (CED) can be used to safely infuse ADCs into orthotopic patient-derived xenograft (PDX) models of EGFRvIII mutant GBM. Methods: The efficacy of the EGFR-targeted ADCs depatuxizumab mafodotin (Depatux-M) and Serclutamab talirine (Ser-T) was evaluated in vitro and in vivo. CED was performed in nontumor and tumor-bearing mice. Immunostaining was used to evaluate ADC distribution, pharmacodynamic effects, and normal cell toxicity. Results: Dose-finding studies in orthotopic GBM6 identified single infusion of 2 µg Ser-T and 60 µg Depatux-M as safe and effective associated with extended survival prolongation (>300 days and 95 days, respectively). However, with serial infusions every 21 days, four Ser-T doses controlled tumor growth but was associated with lethal toxicity approximately 7 days after the final infusion. Limiting dosing to two infusions in GBM108 provided profound median survival extension of over 200 days. In contrast, four Depatux-M CED doses were well tolerated and significantly extended survival in both GBM6 (158 days) and GBM108 (310 days). In a toxicity analysis, Ser-T resulted in a profound loss in NeuN+ cells and markedly elevated GFAP staining, while Depatux-M was associated only with modest elevation in GFAP staining. Conclusion: CED of Depatux-M is well tolerated and results in extended survival in orthotopic GBM PDXs. In contrast, CED of Ser-T was associated with a much narrower therapeutic window.
ABSTRACT
Diffuse midline glioma (DMG) is a uniformly fatal pediatric cancer driven by oncohistones that do not readily lend themselves to drug development. To identify druggable targets for DMG, we conducted a genome-wide CRISPR screen that reveals a DMG selective dependency on the de novo pathway for pyrimidine biosynthesis. This metabolic vulnerability reflects an elevated rate of uridine/uracil degradation that depletes DMG cells of substrates for the alternate salvage pyrimidine biosynthesis pathway. A clinical stage inhibitor of DHODH (rate-limiting enzyme in the de novo pathway) diminishes uridine-5'-phosphate (UMP) pools, generates DNA damage, and induces apoptosis through suppression of replication forks-an "on-target" effect, as shown by uridine rescue. Matrix-assisted laser desorption/ionization (MALDI) mass spectroscopy imaging demonstrates that this DHODH inhibitor (BAY2402234) accumulates in the brain at therapeutically relevant concentrations, suppresses de novo pyrimidine biosynthesis in vivo, and prolongs survival of mice bearing intracranial DMG xenografts, highlighting BAY2402234 as a promising therapy against DMGs.
Subject(s)
Glioma , Pyrimidines , Animals , Glioma/drug therapy , Glioma/genetics , Humans , Mice , Uridine/metabolism , Uridine/pharmacologyABSTRACT
Mutations affecting isocitrate dehydrogenase (IDH) enzymes are prevalent in glioma, leukemia, and other cancers. Although mutant IDH inhibitors are effective against leukemia, they seem to be less active in aggressive glioma, underscoring the need for alternative treatment strategies. Through a chemical synthetic lethality screen, we discovered that IDH1-mutant glioma cells are hypersensitive to drugs targeting enzymes in the de novo pyrimidine nucleotide synthesis pathway, including dihydroorotate dehydrogenase (DHODH). We developed a genetically engineered mouse model of mutant IDH1-driven astrocytoma and used it and multiple patient-derived models to show that the brain-penetrant DHODH inhibitor BAY 2402234 displays monotherapy efficacy against IDH-mutant gliomas. Mechanistically, this reflects an obligate dependence of glioma cells on the de novo pyrimidine synthesis pathway and mutant IDH's ability to sensitize to DNA damage upon nucleotide pool imbalance. Our work outlines a tumor-selective, biomarker-guided therapeutic strategy that is poised for clinical translation.
Subject(s)
Brain Neoplasms , Glioma , Leukemia , Animals , Brain Neoplasms/drug therapy , Brain Neoplasms/genetics , Enzyme Inhibitors/therapeutic use , Glioma/drug therapy , Glioma/genetics , Isocitrate Dehydrogenase/genetics , Isocitrate Dehydrogenase/metabolism , Mice , Mutation , Pyrimidines/pharmacology , Pyrimidines/therapeutic use , Salicylanilides , TriazolesABSTRACT
How the glioma immune microenvironment fosters tumorigenesis remains incompletely defined. Here, we use single-cell RNA-sequencing and multiplexed tissue-imaging to characterize the composition, spatial organization, and clinical significance of extracellular purinergic signaling in glioma. We show that microglia are the predominant source of CD39, while tumor cells principally express CD73. In glioblastoma, CD73 is associated with EGFR amplification, astrocyte-like differentiation, and increased adenosine, and is linked to hypoxia. Glioblastomas enriched for CD73 exhibit inflammatory microenvironments, suggesting that purinergic signaling regulates immune adaptation. Spatially-resolved single-cell analyses demonstrate a strong spatial correlation between tumor-CD73 and microglial-CD39, with proximity associated with poor outcomes. Similar spatial organization is present in pediatric high-grade gliomas including H3K27M-mutant diffuse midline glioma. These data reveal that purinergic signaling in gliomas is shaped by genotype, lineage, and functional state, and that core enzymes expressed by tumor and myeloid cells are organized to promote adenosine-rich microenvironments potentially amenable to therapeutic targeting.
Subject(s)
Glioblastoma , Glioma , 5'-Nucleotidase/genetics , Adenosine , Child , Glioblastoma/genetics , Humans , Single-Cell Analysis , Spatial Analysis , Tumor MicroenvironmentABSTRACT
The status of metabolomics as a scientific branch has evolved from proof-of-concept to applications in science, particularly in medical research. To comprehensively evaluate disease metabolomics, multiplatform approaches of NMR combining with mass spectrometry (MS) have been investigated and reported. This mixed-methods approach allows for the exploitation of each individual technique's unique advantages to maximize results. In this article, we present our findings from combined NMR and MS imaging (MSI) analysis of human lung and prostate cancers. We further provide critical discussions of the current status of NMR and MS combined human prostate and lung cancer metabolomics studies to emphasize the enhanced metabolomics ability of the multiplatform approach.
ABSTRACT
BRAF-targeted kinase inhibitors (KIs) are used to treat malignancies including BRAF-mutant non-small cell lung cancer, colorectal cancer, anaplastic thyroid cancer, and, most prominently, melanoma. However, KI selection criteria in patients remain unclear, as are pharmacokinetic/pharmacodynamic (PK/PD) mechanisms that may limit context-dependent efficacy and differentiate related drugs. To address this issue, we imaged mouse models of BRAF-mutant cancers, fluorescent KI tracers, and unlabeled drug to calibrate in silico spatial PK/PD models. Results indicated that drug lipophilicity, plasma clearance, faster target dissociation, and, in particular, high albumin binding could limit dabrafenib action in visceral metastases compared to other KIs. This correlated with retrospective clinical observations. Computational modeling identified a timed strategy for combining dabrafenib and encorafenib to better sustain BRAF inhibition, which showed enhanced efficacy in mice. This study thus offers principles of spatial drug action that may help guide drug development, KI selection, and combination.