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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 pre-clinical study evaluated the novel EGFR inhibitor WSD-0922. Methods We employed flank and orthotopic patient derived xenograft (PDX) 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.

Optimal resection of breast tumors requires removing cancer with a rim of normal tissue while preserving uninvolved regions of the breast. Surgical and pathological techniques that permit rapid molecular characterization of tissue could facilitate such resections. Mass spectrometry (MS) is increasingly used in the research setting to detect and classify tumors and has the potential to detect cancer at surgical margins. Here, we describe the ex vivo intraoperative clinical application of MS using a liquid micro-junction surface sample probe (LMJ-SSP) to assess breast cancer margins. In a midpoint analysis of a registered clinical trial, surgical specimens from 21 women with treatment naïve invasive breast cancer were prospectively collected and analyzed at the time of surgery with subsequent histopathological determination. Normal and tumor breast specimens from the lumpectomy resected by the surgeon were smeared onto glass slides for rapid analysis. Lipidomic profiles were acquired from these specimens using LMJ-SSP MS in negative ionization mode within the operating suite and post-surgery analysis of the data revealed five candidate ions separating tumor from healthy tissue in this limited dataset. More data is required before considering the ions as candidate markers. Here, we present an application of ambient MS within the operating room to analyze breast cancer tissue and surgical margins. Lessons learned from these initial promising studies are being used to further evaluate the five candidate biomarkers and to further refine and optimize intraoperative MS as a tool for surgical guidance in breast cancer.

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.

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.

In biological tissues, cell-to-cell variations stem from the stochastic and modulated expression of genes and the varying abundances of corresponding proteins. These variations are then propagated to downstream metabolite products and result in cellular heterogeneity. Mass spectrometry imaging (MSI) is a promising tool to simultaneously provide spatial distributions for hundreds of biomolecules without the need for labels or stains. Technological advances in MSI instrumentation for the direct analysis of tissue-embedded single cells are dominated by improvements in sensitivity, sample pretreatment, and increased spatial resolution but are limited by low throughput. Herein, we introduce a bimodal microscopy imaging system combined with fiber-based laser ablation electrospray ionization (f-LAESI) MSI with improved throughput ambient analysis of tissue-embedded single cells (n > 1000) to provide insight into cellular heterogeneity. Based on automated image analysis, accurate single-cell sampling is achieved by f-LAESI leading to the discovery of cellular phenotypes characterized by differing metabolite levels.

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.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.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.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.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.

Therapeutic development of histone deacetylase inhibitors (HDACi) has been hampered by a number of barriers to drug delivery, including poor solubility and inadequate tissue penetration. Nanoparticle encapsulation could be one approach to improve the delivery of HDACi to target tissues; however, effective and generalizable loading of HDACi within nanoparticle systems remains a long-term challenge. We hypothesized that the common terminally ionizable moiety on many HDACi molecules could be capitalized upon for loading in polymeric nanoparticles. Here, we describe the simple, efficient formulation of a novel library of β-cyclodextrin-poly (β-amino ester) networks (CDN) to achieve this goal. We observed that network architecture was a critical determinant of CDN encapsulation of candidate molecules, with a more hydrophobic core enabling effective self-assembly and a PEGylated surface enabling high loading (up to ∼30% w/w), effective self-assembly of the nanoparticle, and slow release of drug into aqueous media (up to 24 days) for the model HDACi panobinostat. We next constructed a library of CDNs to encapsulate various small, hydrophobic, terminally ionizable molecules (panobinostat, quisinostat, dacinostat, givinostat, bortezomib, camptothecin, nile red, and cytarabine), which yielded important insights into the structural requirements for effective drug loading and CDN self-assembly. Optimized CDN nanoparticles were taken up by GL261 cells in culture and a released panobinostat was confirmed to be bioactive. Panobinostat-loaded CDNs were next administered by convection-enhanced delivery (CED) to mice bearing intracranial GL261 tumors. These studies confirm that CDN encapsulation enables a higher deliverable dose of drug to effectively slow tumor growth. Matrix-assisted laser desorption/ionization (MALDI) analysis on tissue sections confirms higher exposure of tumor to drug, which likely accounts for the therapeutic effects. Taken in sum, these studies present a novel nanocarrier platform for encapsulation of HDACi via both ionic and hydrophobic interactions, which is an important step toward better treatment of disease via HDACi therapy.

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 H&E-stained biopsy data with MALDI mass-spectrometric imaging of the corresponding tissue to determine the cancerous regions and their unique chemical signatures, and variation of the predicted regions with original pathological annotations. We spatially register features obtained through deep learning from high-resolution optical micrographs of whole slide H&E stained data with MSI data to correlate the chemical signature with the tissue anatomy of the data, and then use the learned correlation to predict prostate cancer from observed H&E images using trained co-registered MSI data. We found that this system is more robust than predicting from a single imaging modality and can predict cancerous regions with ∼80% accuracy. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This will improve on generating patient treatment trajectories by more accurately predicting prostate cancer directly from H&E-stained biopsy images.

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.

The establishment of the nitrogen-fixing symbiosis between soybean and Bradyrhizobium japonicum is a complex process. To document the changes in plant metabolism as a result of symbiosis, we utilized laser ablation electrospray ionization-mass spectrometry (LAESI-MS) for in situ metabolic profiling of wild-type nodules, nodules infected with a B. japonicum nifH mutant unable to fix nitrogen, nodules doubly infected by both strains, and nodules formed on plants mutated in the stearoyl-acyl carrier protein desaturase (sacpd-c) gene, which were previously shown to have an altered nodule ultrastructure. The results showed that the relative abundance of fatty acids, purines, and lipids was significantly changed in response to the symbiosis. The nifH mutant nodules had elevated levels of jasmonic acid, correlating with signs of nitrogen deprivation. Nodules resulting from the mixed inoculant displayed similar, overlapping metabolic distributions within the sectors of effective (fix+ ) and ineffective (nifH mutant, fix- ) endosymbionts. These data are inconsistent with the notion that plant sanctioning is cell autonomous. Nodules lacking sacpd-c displayed an elevation of soyasaponins and organic acids in the central necrotic regions. The present study demonstrates the utility of LAESI-MS for high-throughput screening of plant phenotypes. Overall, nodules disrupted in the symbiosis were elevated in metabolites related to plant defense.

Characterization of the metabolic heterogeneity in cell populations requires the analysis of single cells. Most current methods in single-cell analysis rely on cell manipulation, potentially altering the abundance of metabolites in individual cells. A small sample volume and the chemical diversity of metabolites are additional challenges in single-cell metabolomics. Here, we describe the combination of fiber-based laser ablation electrospray ionization (f-LAESI) with 21 T Fourier transform ion cyclotron resonance mass spectrometry (21TFTICR-MS) for in situ single-cell metabolic profiling in plant tissue. Single plant cells infected by bacteria were selected and sampled directly from the tissue without cell manipulation through mid-infrared ablation with a fine optical fiber tip for ionization by f-LAESI. Ultrahigh performance 21T-FTICR-MS enabled the simultaneous capture of isotopic fine structures (IFSs) for 47 known and 11 unknown compounds, thus elucidating their elemental compositions from single cells and providing information on metabolic heterogeneity in the cell population.

Over the past decades, crop yields have risen in parallel with increasing use of fossil fuel–derived nitrogen (N) fertilizers but with concomitant negative impacts on climate and water resources. There is a need for more sustainable agricultural practices, and biological nitrogen fixation (BNF) could be part of the solution. A variety of nitrogen-fixing, epiphytic, and endophytic plant growth–promoting bacteria (PGPB) are known to stimulate plant growth. However, compared with the rhizobium-legume symbiosis, little mechanistic information is available as to how PGPB affect plant metabolism. Therefore, we investigated the metabolic changes in roots of the model grass species Setaria viridis upon endophytic colonization by Herbaspirillum seropedicae SmR1 (fix+) or a fix− mutant strain (SmR54) compared with uninoculated roots. Endophytic colonization of the root is highly localized and, hence, analysis of whole-root segments dilutes the metabolic signature of those few cells impacted by the bacteria. Therefore, we utilized in-situ laser ablation electrospray ionization mass spectrometry to sample only those root segments at or adjacent to the sites of bacterial colonization. Metabolites involved in purine, zeatin, and riboflavin pathways were significantly more abundant in inoculated plants, while metabolites indicative of nitrogen, starch, and sucrose metabolism were reduced in roots inoculated with the fix− strain or uninoculated, presumably due to N limitation. Interestingly, compounds, involved in indole-alkaloid biosynthesis were more abundant in the roots colonized by the fix− strain, perhaps reflecting a plant defense response.

Motivation Mass spectrometry imaging (MSI) provides rich biochemical information in a label-free manner and therefore holds promise to substantially impact current practice in disease diagnosis. However, the complex nature of MSI data poses computational challenges in its analysis. The complexity of the data arises from its large size, high-dimensionality and spectral nonlinearity. Preprocessing, including peak picking, has been used to reduce raw data complexity; however, peak picking is sensitive to parameter selection that, perhaps prematurely, shapes the downstream analysis for tissue classification and ensuing biological interpretation. Results We propose a deep learning model, massNet, that provides the desired qualities of scalability, nonlinearity and speed in MSI data analysis. This deep learning model was used, without prior preprocessing and peak picking, to classify MSI data from a mouse brain harboring a patient-derived tumor. The massNet architecture established automatically learning of predictive features, and automated methods were incorporated to identify peaks with potential for tumor delineation. The model’s performance was assessed using cross-validation, and the results demonstrate higher accuracy and a substantial gain in speed compared to the established classical machine learning method, support vector machine. Availability and implementation https://github.com/wabdelmoula/massNet. The data underlying this article are available in the NIH Common Fund’s National Metabolomics Data Repository (NMDR) Metabolomics Workbench under project id (PR001292) with http://dx.doi.org/10.21228/M8Q70T. Supplementary information Supplementary data are available at Bioinformatics online.

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. publishedVersion

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 and achieved broad coverage of central carbon, nucleotide, and lipid metabolism pathways. We used this approach to visualize the effect of nutrient stress and excess on liver metabolism. Our data revealed a highly organized metabolic compartmentalization in livers, which becomes disrupted under nutrient stress conditions. Fasting caused changes in glucose metabolism and increased the levels of fatty acids in the circulation. In contrast, a prolonged high-fat diet (HFD) caused lipid accumulation within liver tissues with clear zonal patterns. Fatty livers had higher levels of purine and pentose phosphate related metabolites, which generates reducing equivalents to counteract oxidative stress. This MALDI MSI approach allowed the visualization of liver metabolic compartmentalization at high resolution and can be applied more broadly to yield new insights into metabolic heterogeneityin vivo.

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.

Glioblastoma, the most common primary brain malignancy, is invariably fatal. Systemic chemotherapy is ineffective mostly because of drug delivery limitations. To overcome this, we devised an internalized pump-catheter system for direct chronic convection-enhanced delivery (CED) into peritumoral brain tissue. Topotecan (TPT) by chronic CED in 5 patients with refractory glioblastoma selectively eliminated tumor cells without toxicity to normal brain. Large, stable drug distribution volumes were non-invasively monitored with MRI of co-infused gadolinium. Analysis of multiple radiographically localized biopsies taken before and after treatment showed a decreased proliferative tumor signature resulting in a shift to a slow-cycling mesenchymal/astrocytic-like population. Tumor microenvironment analysis showed an inflammatory response and preservation of neurons. This novel drug delivery strategy and innovative clinical trial paradigm overcomes current limitations in delivery and treatment response assessment as shown here for glioblastoma and is potentially applicable for other anti-glioma agents as well as other CNS diseases.

SUMMARYMutations affecting isocitrate dehydrogenase (IDH) enzymes are prevalent in glioma, leukemia, and other cancers. Although mutant IDH inhibitors are effective against leukemia, they appear 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 vulnerability selectively applies to de novo pyrimidine, but not purine, synthesis because glioma cells engage disparate programs to produce these nucleotide species and because IDH oncogenes increase DNA damage upon nucleotide pool imbalance. Our work outlines a tumor-selective, biomarker-guided therapeutic strategy that is poised for clinical translation.

SUMMARYDiffuse 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 pathway for pyrimidine biosynthesis. A clinical stage inhibitor of DHODH (rate limiting enzyme in the de novo pathway) diminishes UMP pools, generates DNA damage, and induces apoptosis through suppression of replication forks--an “on target” effect, as shown by uridine rescue. MALDI mass spectroscopy imaging demonstrates that this DHODH inhibitor (BAY2402234) accumulates in 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.

Although reprogramming of cellular metabolism is a hallmark of cancer, little is known about how metabolic reprogramming contributes to early stages of transformation. Here, we show that the histone deacetylase SIRT6 regulates tumor initiation during intestinal cancer by controlling glucose metabolism. Loss of SIRT6 results in an increase in the number of intestinal stem cells (ISCs), which translates into enhanced tumor initiating potential in APCmin mice. By tracking down the connection between glucose metabolism and tumor initiation, we find a metabolic compartmentalization within the intestinal epithelium and adenomas, where a rare population of cells exhibit features of Warburg-like metabolism characterized by high pyruvate dehydrogenase kinase (PDK) activity. Our results show that these cells are quiescent cells expressing +4 ISCs and enteroendocrine markers. Active glycolysis in these cells suppresses ROS accumulation and enhances their stem cell and tumorigenic potential. Our studies reveal that aerobic glycolysis represents a heterogeneous feature of cancer, and indicate that this metabolic adaptation can occur in non-dividing cells, suggesting a role for the Warburg effect beyond biomass production in tumors.

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.

Diffuse midline glioma (DMG) is a lethal pediatric brain cancer in dire need for therapeutic breakthroughs. To identify intrinsic addictions and therapeutic targets for DMG, we conducted a genome-wide k¬¬¬¬nockout CRISPR screen that identified de novo pyrimidine biosynthesis pathway as a targetable dependency. Since pyrimidine nucleotides can be synthesized by salvage and de novo pathways, identification of the latter as a dependency indicated a prominent role of de novo pathway in establishing the pyrimidine nucleotide pool in DMG. We investigated the molecular mechanism underlying this dependency using metabolic tracing of 15N-glutamine and genetic approaches. We report that DMG cells derive the majority of UMP (70%) through de novo synthesis, along with significantly elevated flux through the pyrimidine degradation pathway. High flux of 15N- labeled UMP through pyrimidine degradation in DMGs suggests that substrates (uridine and uracil) required for pyrimidine nucleotide salvage are limited, thus enhancing the dependency on de novo biosynthesis. To further confirm the causal role of pyrimidine degradation in driving de novo pathway dependency in DMG, we knocked down DPYD, the enzyme catalyzing the first committed step in pyrimidine degradation, using inducible shRNAs. Knockdown of DPYD diminished sensitivity of DMGs to de novo pathway inhibition as it rescued UMP pools and resultant DNA damage. Conversely, overexpression of DPYD in adult glioblastomas enhanced their sensitivity to de novo pyrimidine synthesis inhibition which was accompanied by greater depletion of UMP and induction of DNA damage. Consistent with this mechanism, we observed downregulation of DPYD in DMGs that acquired resistance to antagonists of de novo pyrimidine synthesis. Taken together, we have uncovered DPYD as a predictive biomarker of sensitivity to de novo pyrimidine synthesis inhibitors.

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.

Background Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy. Methods Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial. Results PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient’s response to adavosertib. Conclusions The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.

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.

Unfortunately, at present, there is no single technique that possesses all the characteristics needed to be considered an ideal global metabolite profiling tool. Thus, the use of multiple analytical platforms, such as combining the strengths of Mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), for metabolic profiling can maximize coverage and generate more global metabolomic profiles. In this study, we demonstrate the utilities of the combined NMR and MSI multiplatform in our metabolomics results on human prostate and lung cancers. Statistical data on the natural history of prostate cancer (PCa) show that >70% of patients diagnosed by PSA screening will likely experience indolent disease with little impact on well-being. For about 17% of newly PSA-diagnosed patients, however, aggressive PCa proliferation ensues, truncating life expectancy. At present, no reliable clinical test can differentiate between these two groups. Using HRMAS 1HNMR followed by quantitative histology, we showed statistically significant correlations between concentrations of Spm and the amount of histologically-benign epithelial (Hb Epi) prostatic cells and glands in human cancerous prostates. However, as above discussed that using HRMAS NMR alone we cannot prove that Spm was indeed generated or resided in the Hb Epi cells. Nevertheless, using MALDI MSI, we were able to locate Spm (m/z: 203.223 ± 0.001Da) onto Hb Epi, where spermine on the PCa lesions appeared below detection limits. From these maps, for the first time, we could visualize and confirm the differential localizations of Spm in prostates. This proof of Sym relationship to prostate pathologies and its proposed PCa inhibitory effects may support further studies that are critical in differentiating aggressive from indolent PCa for disease evaluations and patient personalized treatment strategies. To search for such screening metabolomics biomarkers in lung cancer, we used HRMAS NMR to analyze 93 pairs of human LuCa tissue and serum samples, and 29 healthy human sera. A number of potential metabolite candidates capable to differentiate LuCa characteristics were identified, including glutamate, lipids, alanine, glycerylphosphorylcholine, glutamine, phosphorylcholine, etc. This list can be further expanded by analyzing metabolite composition in the serum of cancer patients and control healthy subjects using LC-MS, which offers a dramatic increase in sensitivity compared to HRMAS NMR and, therefore, is better suited for the biomarker discovery. In addition to acquiring high-resolution mass data, the high data acquisition rate allows the fragment ion mass spectra (MS/MS) to be generated for the most abundant ionic species in each chromatographic peak. This feature allows specific classes of tumor-attenuated metabolites to be identified based on the presence of unique structurally diagnostic fragment ions in MS/MS spectra. Citation Format: Leo L. Cheng, Anya B. Zhong, Isabella H. Muti, Stephen J. Eyles, Richard W. Vachet, Sylwia A. Stopka, Kristen N. Sikora, Cedric E. Bobst, Jeffrey N. Agar, Mari A. Mino-Kenudson, Chin-Lee Wu, David C. Christiani, Igor A. Kaltashov, Nathalie Y. Agar. Multiplatform metabolomics studies of human cancers with NMR and mass spectrometry imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2322.

MotivationMass spectrometry imaging (MSI) provides rich biochemical information in a label-free manner and therefore holds promise to substantially impact current practice in disease diagnosis. However, the complex nature of MSI data poses computational challenges in its analysis. The complexity of the data arises from its large size, high dimensionality, and spectral non-linearity. Preprocessing, including peak picking, has been used to reduce raw data complexity, however peak picking is sensitive to parameter selection that, perhaps prematurely, shapes the downstream analysis for tissue classification and ensuing biological interpretation.ResultsWe propose a deep learning model, massNet, that provides the desired qualities of scalability, non-linearity, and speed in MSI data analysis. This deep learning model was used, without prior preprocessing and peak picking, to classify MSI data from a mouse brain harboring a patient-derived tumor. The massNet architecture established automatically learning of predictive features, and automated methods were incorporated to identify peaks with potential for tumor delineation. The model’s performance was assessed using cross-validation, and the results demonstrate higher accuracy and a 174-fold gain in speed compared to the established classical machine learning method, support vector machine.Availability and ImplementationThe code is publicly available on GitHub.

Due to the relatively small number of neurons (few tens of thousands), the well-established multipurpose model organism Lymnaea stagnalis, great pond snail, has been extensively used to study the functioning of the nervous system. Unlike the more complex brains of higher organisms, L. stagnalis has a relatively simple central nervous system (CNS) with well-defined circuits (e.g., feeding, locomotion, learning, and memory) and identified individual neurons (e.g., cerebral giant cell, CGC), which generate behavioral patterns. Accumulating information from electrophysiological experiments maps the network of neuronal connections and the neuronal circuits responsible for basic life functions. Chemical signaling between synaptic-coupled neurons is underpinned by neurotransmitters and neuropeptides. This review looks at the rapidly expanding contributions of mass spectrometry (MS) to neuropeptide discovery and identification at different granularity of CNS organization. Abundances and distributions of neuropeptides in the whole CNS, eleven interconnected ganglia, neuronal clusters, single neurons, and subcellular compartments are captured by MS imaging and single cell analysis techniques. Combining neuropeptide expression and electrophysiological data, and aided by genomic and transcriptomic information, the molecular basis of CNS-controlled biological functions is increasingly revealed.

Background Antibody drug conjugates (ADCs) targeting the epidermal growth factor receptor (EGFR), such as depatuxizumab mafodotin (Depatux-M), is a promising therapeutic strategy for glioblastoma (GBM) but recent clinical trials did not demonstrate a survival benefit. Understanding the mechanisms of failure for this promising strategy is critically important. Methods PDX models were employed to study efficacy of systemic vs intracranial delivery of Depatux-M. Immunofluorescence and MALDI-MSI were performed to detect drug levels in the brain. EGFR levels and compensatory pathways were studied using quantitative flow cytometry, Western blots, RNAseq, FISH, and phosphoproteomics. Results Systemic delivery of Depatux-M was highly effective in nine of 10 EGFR-amplified heterotopic PDXs with survival extending beyond one year in eight PDXs. Acquired resistance in two PDXs (GBM12 and GBM46) was driven by suppression of EGFR expression or emergence of a novel short-variant of EGFR lacking the epitope for the Depatux-M antibody. In contrast to the profound benefit observed in heterotopic tumors, only two of seven intrinsically sensitive PDXs were responsive to Depatux-M as intracranial tumors. Poor efficacy in orthotopic PDXs was associated with limited and heterogeneous distribution of Depatux-M into tumor tissues, and artificial disruption of the BBB or bypass of the BBB by direct intracranial injection of Depatux-M into orthotopic tumors markedly enhanced the efficacy of drug treatment. Conclusions Despite profound intrinsic sensitivity to Depatux-M, limited drug delivery into brain tumor may have been a key contributor to lack of efficacy in recently failed clinical trials.

INTRODUCTION: Extracellular purinergic signaling plays critical roles in the regulation of tumor growth and anti-tumor immunity via autocrine/paracrine binding of metabolites to receptors on neoplastic and non-neoplastic populations. Extracellular purine concentrations are principally mediated by the ectonucleotidase enzymes CD39 and CD73, which catabolize ATP to adenosine. Within the tumor microenvironment, neoplastic, immune, and stromal cells expressing these enzymes may co-localize to generate an immunosuppressive adenosine-rich niche. However, the cellular composition, spatial architecture and phenotypic properties of these tumor ecosystems and their relationship to tumor genotype have been poorly characterized. METHODS: We quantified CD73 expression by immunohistochemistry (IHC) in a cohort of CNS tumors [meningiomas(N=222), gliomas(N=244), ependymomas(N=44), medulloblastomas(N=24), craniopharyngiomas(N=38)]. We used publicly-available single-cell RNA-seq data and 36 marker multiplexed tissue imaging (t-CyCIF) of 139 clinically and genomically annotated glioblastomas to characterize CD39 and CD73 expressing populations, define immune architecture and tumor cell states at single cell resolution, evaluate spatial correlations, and identify markers of clinical outcome. Mass spectrometry imaging (MALDI-MSI) was employed to generate spatially-resolved quantification of purine metabolite levels in glioblastoma resections (N=9). RESULTS: IHC revealed strong CD73 expression in meningiomas and gliomas. Tumor CD73 expression was associated with poor progression-free-survival in IDH-wildtype glioblastoma (p=0.04). scRNA-seq in glioblastoma revealed that CD73 is predominantly expressed by tumor cell populations, while CD39 is predominantly expressed by monocytic (macrophage, microglial) populations. t-CyCIF showed enrichment of EGFR, Ki-67, and TP53 expression in CD73-high tumor cells at a single cell level independent of genotype, as well as significant spatial correlation between CD73 expression in tumor cells and CD39 expression in macrophages. MALDI-MSI showed significantly greater adenosine concentrations in glioblastomas with high CD73 expression. CD73 expression significantly correlated with EGFR amplification or C-terminal deletion (EGFRvIII or variants), type-II interferon signaling, and PD-L1 expression in glioblastoma. CONCLUSIONS: Phenogenomic analysis of purinergic signaling in glioblastoma revealed correlations between CD73 expression and genotype, adenosine concentration, and clinical outcome. Spatial analysis revealed interaction between macrophages CD39 expression and tumor cell CD73 expression, suggesting that these populations may interact to suppress anti-tumor immunity. Anti-CD73 therapy may provide therapeutic benefits in glioblastoma by blunting immunosuppressive and oncogenic adenosine signaling. Citation Format: Shannon Coy, Jia-Ren Lin, Shu Wang, Sylwia Stopka, Rumana Rashid, Jaeho Hwang, Prasidda Khadka, Philipp Euskirchen, Pratiti Bandopadhayay, Patrick Y. Wen, Peter K. Sorger, Nathalie Agar, Keith L. Ligon, Mehdi Touat, Sandro Santagata. Phenogenomic characterization of immunomodulatory purinergic signaling in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1816.

Diffuse midline gliomas (DMG) are aggressive and lethal pediatric brain tumors that cannot be cured by conventional therapeutic modalities. Using a genome wide CRISPR screen we identified the de novo pyrimidine biosynthesis pathway as a metaboilic vulnerability in DMGs. BAY2402234 is a small molecule inhibitor of DHODH -a rate liminting enzyme in the de novo pyrimidine biosynthesis pathway. BAY2402234 induces cell death in DMG cells at low nanomolar concentrations while sparing adult glioblastoma cells and normal astrocytes. Further investigations revealed drammatic reduction in cellular UMP pools, the precursor for all pyrimidine nucleotides, after DHODH inhibition, specifically in DMG cells. Cytotoxicity of DHODH inhibition in DMG cells is rescued by exogenous uridine, supporting UMP depletion as the mechanism underlying DMG cell death and also showing that cell death is an “on target” response to BAY2402234. Cell death induced by BAY2402234 is a consequence of replication fork stalling as evident by accumulation of chromatin-bound RPA foci and g-H2AX. Stalled replication forks eventually collapse, resulting in replication catastrophy and apoptosis. Cytotoxic effects of DHODH inhibition are further exacerbated by inhibition of the intra-S checkpoint protein, ATR. Combined treatment of DMG cells with DHODH and ATR inhibitors resulted in enhanced accumulation of chromatin-bound RPA, g-H2AX, replication fork collapse and apoptosis. Importantly, in vivo studies verify that both BAY2402234 (DHODHi), and BAY1895344 (ATRi), cross the blood-brain barrier, accumulate in the brain at therapeutically relevant concentrations, and induce DNA damage in intracranial DMG xenografts in mice. Taken together, our studies have identified DHODH inhibition as a DMG-specific vulnerability resulting in cell death; the mechanism of DHODHi-induced cell death led us to identify combined inhibition of DHODH and ATR as a synergistic therapy against DMG tumors.

Adequate exposure (effective concentration over time) of a therapeutic agent at its site of action is essential for antitumor efficacy. Given constraints of repeat tissue sampling, non-human primate models predictive of pharmacokinetics in pediatric patients have been utilized to assess central nervous system (CNS) exposure. Assessment of cerebrospinal fluid (CSF) drug levels have been used to extrapolate CNS penetration but the relationship of CSF drug levels with tissue distribution is unclear. Utilizing microdialysis, we previously demonstrated geographic variability of drug permeability across the blood:brain barrier (BBB), but this technique is complex and has a high standard deviation. We, therefore, explored a novel technique, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI), to compare plasma, CSF, and tissue drug levels in a terminal non-human primate model. Panobinostat, an HDAC inhibitor in clinical trials for DIPG/DMG, was selected for study as it has previously demonstrated poor CNS tissue penetration but suggested modest clinical activity. Methods Panobinostat (p.o., dose 1.6 mg/kg) was administered to non-tumor bearing primates (n=2). One hour following administration (Tmax), blood and CSF were collected, the animal euthanized, brain and spinal cord extracted, and immediately frozen at -80. Panobinostat distribution was mapped on ex vivo sagittal tissue sections using MALDI MSI. To provide specificity and degree of permeability, anatomical structures were segmented for analysis to determine drug concentrations. Blood, CSF and tissue levels of panobinostat were measured via LC-MS/MS. Results Segmentation analysis revealed quantifiable panobinostat, particularly in the lateral ventricles and choroid plexus, and also in the subventricular zone and brainstem, although the overall panobinostat concentration was below the limit of quantitation in these areas. Conclusions Although not reflected in CSF PK, panobinostat is widely distributed in brain tissue. MALDI MSI allows regional assessment of panobinostat penetration and complements CSF pharmacokinetics.

INTRODUCTION Purinergic signaling plays critical roles in the regulation of tumor growth and anti-tumor immunity via autocrine/paracrine binding of metabolites to receptors on neoplastic and non-neoplastic populations. Extracellular purine concentrations are mediated by the ectonucleotidase enzymes CD39 and CD73, which catabolize ATP to adenosine. Within tumors such as glioblastoma, neoplastic, immune, and stromal cells expressing these enzymes may co-localize to generate immunosuppressive adenosine-rich environments. However, the composition, architecture, and phenotypic properties of these tumor ecosystems and their relationship to tumor genotype are poorly characterized. METHODS We quantified CD73 expression by immunohistochemistry in a cohort of CNS tumors [meningiomas(n=222), gliomas(n=244), ependymomas(n=44), medulloblastomas(n=24), and craniopharyngiomas(n=38)]. We used publicly-available single-cell RNA-seq data and 36-marker multiplexed tissue imaging (t-CyCIF) of 139 clinically and genomically annotated glioblastoma resections to characterize CD39 and CD73-expressing populations, define the immune architecture and tumor cell-states at single cell resolution, and identify markers of clinical outcome. We used mass spectrometry imaging (MALDI-MSI) to generate spatially-resolved quantification of purine metabolite levels in glioblastoma resections (n=10). RESULTS CD73 exhibited strong expression in a subset of gliomas and meningiomas but was typically not expressed in ependymomas or medulloblastomas. CD73 expression correlated with poor progression-free-survival in IDH-wildtype glioblastoma (p=0.04). scRNA-seq and t-CyCIF in glioblastoma showed CD73 expression in tumor cells, and CD39 expression in macrophages and endothelial cells. MALDI-MSI showed significantly greater adenosine concentrations (3.5-fold;p=0.04) in glioblastomas with high CD73 expression. scRNA-seq showed direct correlations between stem-like mRNA expression, proliferation, and CD73 expression in DIPG. CD73 expression significantly correlated with EGFR amplification, interferon signaling, and PD-L1 expression in glioblastoma. CONCLUSIONS Phenogenomic analysis of purinergic immunomodulatory signaling revealed significant interplay between CD73 activity and genotype, adenosine concentration, differentiation-state, clinical outcome, and possible interaction between CD39-positive macrophages and CD73-positive neoplastic cells. Anti-CD73 therapy may provide therapeutic benefits in glioblastoma by blunting immunosuppressive and oncogenic adenosine signaling.

Ambient ionization-based mass spectrometry (MS) methods coupled with ion mobility separation (IMS) have emerged as promising approaches for high-throughput in situ analysis for biomedical to environmental applications. These methods are capable of direct profiling and molecular imaging of metabolites, lipids, peptides, and xenobiotics from biological tissues with minimal sample preparation. Furthermore, employing IMS within the workflow improves the molecular coverage, resolves isobaric species, and improves biomolecule identifications through accurate collision cross section measurements. Laser ablation electrospray ionization (LAESI)-MS coupled with IMS has been successful in profiling and molecular imaging of small biomolecules directly from biological tissues and single cells. Herein, we describe a protocol for the direct analysis of adherent mammalian cells with limited perturbations by LAESI-IMS-MS. A benefit of IMS is that within the same LAESI acquisition, the spectral features related to the ESI background, washing buffer, and cell signal can be extracted and isolated separately.

Ambient ionization-based mass spectrometry (MS) methods coupled with ion mobility separation (IMS) have emerged as promising approaches for high-throughput in situ analysis for biomedical to environmental applications. These methods are capable of direct profiling and molecular imaging of metabolites, lipids, peptides, and xenobiotics from biological tissues with minimal sample preparation. Furthermore, employing IMS within the workflow improves the molecular coverage, resolves isobaric species, and improves biomolecule identifications through accurate collision cross section measurements. Laser ablation electrospray ionization (LAESI)-MS coupled with IMS has been successful in profiling and molecular imaging of small biomolecules directly from biological tissues and single cells. Herein, we describe a protocol for the direct analysis of adherent mammalian cells with limited perturbations by LAESI-IMS-MS. A benefit of IMS is that within the same LAESI acquisition, the spectral features related to the ESI background, washing buffer, and cell signal can be extracted and isolated separately.

In recent years, innovations in mass spectrometry imaging (MSI) have enabled simultaneous detection and mapping of biomolecules and xenobiotics directly from biological tissues and single cells. Matrix-assisted laser desorption ionization (MALDI) has been the most widely embraced MSI technique. However, this technique can exhibit ion suppression effects hindering metabolite coverage and possesses a narrow dynamic range. Nanophotonic platforms, e.g., silicon nanopost array (NAPA) structures, can be used as an alternative for matrix-free imaging of biological tissues. Here, we present a protocol for MSI of large and small adherent cell clusters by laser desorption ionization from NAPA with minimal sample preparation.

In recent years, innovations in mass spectrometry imaging (MSI) have enabled simultaneous detection and mapping of biomolecules and xenobiotics directly from biological tissues and single cells. Matrix-assisted laser desorption ionization (MALDI) has been the most widely embraced MSI technique. However, this technique can exhibit ion suppression effects hindering metabolite coverage and possesses a narrow dynamic range. Nanophotonic platforms, e.g., silicon nanopost array (NAPA) structures, can be used as an alternative for matrix-free imaging of biological tissues. Here, we present a protocol for MSI of large and small adherent cell clusters by laser desorption ionization from NAPA with minimal sample preparation.

Over the past decades, crop yields have risen in parallel with increasing use of fossil fuel-derived nitrogen (N) fertilizers but with concomitant negative impacts on climate and water resources. There is a need for more sustainable agricultural practices, and biological nitrogen fixation (BNF) could be part of the solution. A variety of nitrogen-fixing, epiphytic, and endophytic plant growth-promoting bacteria (PGPB) are known to stimulate plant growth. However, compared with the rhizobium-legume symbiosis, little mechanistic information is available as to how PGPB affect plant metabolism. Therefore, we investigated the metabolic changes in roots of the model grass species

Single cell analysis is a field of increasing interest as new tools are continually being developed to understand intercellular differences within large cell populations. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging technique for single cell metabolomics. Over the years, it has been validated that this ionization technique is advantageous for probing the molecular content of individual cells in situ. Here, we report the integration of a microscope into the optical train of the LAESI source to allow for visually informed ambient in situ single cell analysis. Additionally, we have coupled this ‘LAESI microscope’ to a drift-tube ion mobility mass spectrometer to enable separation of isobaric species and allow for the determination of ion collision cross sections in conjunction with accurate mass measurements. This combined information helps provide higher confidence for structural assignment of molecules ablated from single cells. Here, we show that this system enables the analysis of the metabolite content of Allium cepa epidermal cells with high confidence structural identification together with their spatial locations within a tissue.

Diffuse midline glioma (DMG) is a uniformly fatal pediatric cancer that is in need of urgent “outside the box” therapeutic approaches. Recent studies show that tumor cells adapt to stresses created by oncogenic mutations and these oncogene-induced adaptations create vulnerabilities that can be exploited to therapeutic ends. To uncover these oncogene-induced vulnerabilities in DMGs we conducted a genome-wide CRIPSR knockout screen in three DMG lines. The top common DMG dependency pathway that we discovered is de novo pyrimidine biosynthesis. Under normal conditions pyrimidine nucleotide needs are met through the salvage pathway. However, in DMG tumorigenesis, pyrimidine nucleotide synthesis is rewired such that the cells become dependent on the de novo biosynthesis pathway. De novo pyrimidine synthesis is catalyzed by CAD, DHODH and UMPS; all three genes are identified as dependencies in our screen and have been validated using shRNA mediated gene knockdown. Interestingly, DMG cells did not exhibit a dependency on the de novo purine biosynthesis pathway. Using a small molecule inhibitor of DHODH, BAY2402234 [currently studied in phase I trial for myeloid malignancies (NCT03404726)], we have demonstrated and validated, (i) efficacy and specificity of de novo pyrimidine synthesis inhibition in vitro in DMG cells; (ii) de novo pyrimidine addiction is not attributable to cell proliferation; (iii) DHODH inhibition induces apoptosis by hindering replication and inciting DNA damage; (iv) DHODH and ATR inhibition act synergistically to induce DMG cell death; and (v) critical in vivo efficacy. The in vivo experiment documents that BAY2402234 crosses the blood-brain barrier, is present in the brain at therapeutically relevant concentrations, suppresses de novo pyrimidine biosynthesis in intracranial DMG tumors in mice, and prolongs survival of orthotopic DMG tumor bearing mice. Taken together, our studies have identified a novel metabolic vulnerability that can be translated for the treatment of DMG patients.

Mass spectrometry imaging (MSI) is a comprehensive tool for the analysis of a wide range of biomolecules. The mainstream method for molecular MSI is matrix-assisted laser desorption ionization, however, the presence of a matrix results in spectral interferences and the suppression of some analyte ions. Herein we demonstrate a new matrix-free MSI technique using nanophotonic ionization based on laser desorption ionization (LDI) from a highly uniform silicon nanopost array (NAPA). In mouse brain and kidney tissue sections, the distributions of over 80 putatively annotated molecular species are determined with 40 μm spatial resolution. Furthermore, NAPA-LDI-MS is used to selectively analyze metabolites and lipids from sparsely distributed algal cells and the lamellipodia of human hepatocytes. Our results open the door for matrix-free MSI of tissue sections and small cell populations by nanophotonic ionization.