ABSTRACT
The ultrafast dynamics of neutral copper oxide clusters (CunOx, n < 5) are reported using femtosecond pump probe spectroscopy in the gas phase. The transient spectra recorded for each cluster demonstrate they relax on a 100s of fs timescale followed by a long-lived (>50 ps) response. Density functional theory calculations are performed to determine the lowest energy structures and spin states. Topological descripters for the excited states are calculated (time-dependent density functional theory) to relate the measured excited state dynamics to changes in the cluster's electronic structure with increasing oxidation. Strong field ionization is demonstrated here to be a soft form of ionization and able to record transient signals for clusters previously determined to be unstable to nanosecond multiphoton ionization. The relative cluster stability is further demonstrated by signal enhancement/depreciation that is recorded through the synergy from the two laser pulses. Once the oxygen atoms exceed the number of copper atoms, a weakly bound superoxide O2 unit forms, exhibiting a higher spin state. All clusters that are not in the lowest spin configuration demonstrate fragmentation.
ABSTRACT
The excited state lifetimes of neutral (Al)n clusters up to â¼1 nm in diameter in size, where n ≤ 43, are systematically measured with femtosecond time-resolved mass spectrometry. The onset of metallic behavior is identified as a distinct change in the relaxation behavior initiated with single ultraviolet (400 nm) photon excitation. The experimentally measured excited state lifetimes gradually decrease with size for small molecular scale clusters (n < 10) before becoming indistinguishable for larger clusters (n > 9), where the measurements are comparable to electron-lattice relaxation time of bulk Al (â¼300 fs). Particularly intense, or magic, Aln clusters do not exhibit any significant excited state lifetime behavior. Time-dependent density functional theory quantify the excited state properties and are presented to show that dynamics are strongly tied to the excited state charge carrier distributions and overlap, rather than detailed changes related to changes in the cluster's electronic and geometric structure. The consistency in excited state lifetimes for clusters larger than n = 9 is attributed to the hybridization of the s- and p-orbitals as well as increasing delocalization. Al3 exhibits unique temporal delay in its transient behavior that is attributed to a transition from triangular ground state to linear structure upon excitation.
ABSTRACT
Synovial Sarcoma (SS) is driven by the SS18::SSX fusion oncoprotein and is ultimately refractory to therapeutic approaches. SS18::SSX alters ATP-dependent chromatin remodeling BAF (mammalian SWI/SNF) complexes, leading to the degradation of canonical (cBAF) complex and amplified presence of an SS18::SSX-containing non-canonical BAF (ncBAF or GBAF) that drives an SS-specific transcription program and tumorigenesis. We demonstrate that SS18::SSX activates the SUMOylation program and SSs are sensitive to the small molecule SAE1/2 inhibitor, TAK-981. Mechanistically, TAK-981 de-SUMOylates the cBAF subunit SMARCE1, stabilizing and restoring cBAF on chromatin, shifting away from SS18::SSX-ncBAF-driven transcription, associated with DNA damage and cell death and resulting in tumor inhibition across both human and mouse SS tumor models. TAK-981 synergized with cytotoxic chemotherapy through increased DNA damage, leading to tumor regression. Targeting the SUMOylation pathway in SS restores cBAF complexes and blocks the SS18::SSX-ncBAF transcriptome, identifying a therapeutic vulnerability in SS, positioning the in-clinic TAK-981 to treat SS.
ABSTRACT
Synovial Sarcoma (SS) is driven by the SS18::SSX fusion oncoprotein. and is ultimately refractory to therapeutic approaches. SS18::SSX alters ATP-dependent chromatin remodeling BAF (mammalian SWI/SNF) complexes, leading to the degradation of canonical (cBAF) complex and amplified presence of an SS18::SSX-containing non-canonical BAF (ncBAF or GBAF) that drives an SS-specific transcription program and tumorigenesis. We demonstrate that SS18::SSX activates the SUMOylation program and SSs are sensitive to the small molecule SAE1/2 inhibitor, TAK-981. Mechanistically, TAK-981 de-SUMOylates the cBAF subunit SMARCE1, stabilizing and restoring cBAF on chromatin, shifting away from SS18::SSX-ncBAF-driven transcription, associated with DNA damage and cell death and resulting in tumor inhibition across both human and mouse SS tumor models. TAK-981 synergized with cytotoxic chemotherapy through increased DNA damage, leading to tumor regression. Targeting the SUMOylation pathway in SS restores cBAF complexes and blocks the SS18::SSX-ncBAF transcriptome, identifying a therapeutic vulnerability in SS, positioning the in-clinic TAK-981 to treat SS.
ABSTRACT
Triboelectric nanogenerators (TENG) are useful devices for converting mechanical motion into electric current using readily available materials. Though the applications for these devices span across many fields, TENG can be leveraged for mass spectrometry (MS) as inexpensive and effective power supplies for pulsed nanoelectrospray ionization (nESI). The inherently discontinuous spray provided by TENG is particularly useful in scenarios where high sample economy is imperative, as in the case of ultraprecious samples. Previous work has shown the utility of TENG MS as a highly sensitive technique capable of yielding quality spectra from only a few microliters of sample at low micromolar concentrations. As the field of miniaturized, fieldable mass spectrometers grows, it remains critical to develop advanced ion sources with similarly small power requirements and footprints. Here, we present a redesigned TENG ion source with a sub-1000 USD material cost, lower power consumption, reduced footprint, and improved capabilities. We validate the performance of this new device for a diverse set of applications, including lipid double bond localization and native protein analysis.
ABSTRACT
Monitoring the presence of commensal and pathogenic respiratory microorganisms is of critical global importance. However, community-based surveillance is difficult because nasopharyngeal swabs are uncomfortable and painful for a wide age range of participants. We designed a methodology for minimally invasive self-sampling at home and assessed its use for longitudinal monitoring of the oral, nasal and hand microbiota of adults and children within families. Healthy families with two adults and up to three children, living in and near Liverpool, United Kingdom, self-collected saliva, nasal lining fluid using synthetic absorptive matrices and hand swabs at home every two weeks for six months. Questionnaires were used to collect demographic and epidemiological data and assess feasibility and acceptability. Participants were invited to take part in an exit interview. Thirty-three families completed the study. Sampling using our approach was acceptable to 25/33 (76%) families, as sampling was fast (76%), easy (76%) and painless (60%). Saliva and hand sampling was acceptable to all participants of any age, whereas nasal sampling was accepted mostly by adults and children older than 5 years. Multi-niche self-sampling at home can be used by adults and children for longitudinal surveillance of respiratory microorganisms, providing key data for design of future studies.
Subject(s)
Microbiota , Nose , Adult , Child , Humans , Child, Preschool , Surveys and Questionnaires , Specimen Handling/methods , SalivaABSTRACT
The ultrafast proton transfer dynamics of homogeneous formic acid clusters (FA)n, n < 10, are investigated with femtosecond time-resolved mass spectrometry. We monitor the proton transfer pathway following Rydberg state electronic relaxation and find that successful ion pair formation increases logarithmically with cluster size. Ab initio calculations demonstrate similar excitation/relaxation behavior for each cluster, revealing a contact ion pair forms between two molecules composing the cluster before finally a formate anion (HCOO-) is dissociated by the probe pulse. The sub-ps time scale for rearrangement and proton transfer increases almost linearly with cluster size, requiring â¼67 fs per additional formic acid molecule and ranging from 213 ± 51 fs for the trimer to 667 ± 116 fs for FA9. The near-linear trends measured for both rearrangement lifetime and ion pair formation suggest that proton transfer is unlikely in the formic acid dimer but becomes prominent in small clusters.
ABSTRACT
Femtosecond time-resolved mass spectrometry, correlation mapping, and density functional theory calculations are employed to reveal the mechanism of CâC and C≡C formation (and related H2 production) following excitation to the p-Rydberg states of n-butyl bromide. Ultrafast pump-probe mass spectrometry shows that nonadiabatic relaxation operates as a multistep process reaching an intermediate state within â¼500 fs followed by relaxation to a final state within 10 ps of photoexcitation. Absorption of three ultraviolet photons accesses the dense p-Rydberg state manifold, which is further excited by the probe beam for CâC bond dissociation and dehydrogenation reactions. Rapid internal conversion deactivates the dehydrogenation pathways, while activating carbon backbone dissociation pathways. Thus, unsaturated carbon fragments decay with the lifetime of p-Rydberg (â¼500 fs), matching the growth recorded in saturated hydrocarbon fragments. The saturated hydrocarbon signals subsequently decay on the picosecond time scale as the molecule relaxes below the Rydberg states and into halogen release channels.
ABSTRACT
Incorporation of melanoma prevention behaviors into daily lifestyles is difficult. Data suggest that high school educational programs on skin cancer prevention can be successful and should incorporate evidence-based teaching and learning strategies to achieve greatest impact. The goal of this systematic review is to describe evidence-based educational practices for a high-school melanoma curriculum through a comprehensive review of the literature. Ovid MEDLINE, Embase, CINAHL, and PyscINFO were searched in June 2020 for all original articles published between June 18, 1946 and June 17, 2020. All studies that used an educational curriculum to promote sun safety, skin exams, and early detection to high school students were included. A total of 25 studies with 22,683 adolescent participants were analyzed. Sixteen studies showed a significant increase in knowledge, twenty-one studies showed changes in behavior, and fifteen studies showed significant changes in attitudes. Limitations of this review include the heterogeneity of implementation and outcome reporting of educational curricula. These findings support incorporating active learning strategies as key aspects of creating an effective curriculum aimed at the prevention and early detection of melanoma.
Subject(s)
Curriculum , Melanoma , Adolescent , Humans , Melanoma/diagnosis , Melanoma/prevention & control , Schools , Students , School Health ServicesABSTRACT
Ion mobility (IM) spectrometry provides semiorthogonal data to mass spectrometry (MS), showing promise for identifying unknown metabolites in complex non-targeted metabolomics data sets. While current literature has showcased IM-MS for identifying unknowns under near ideal circumstances, less work has been conducted to evaluate the performance of this approach in metabolomics studies involving highly complex samples with difficult matrices. Here, we present a workflow incorporating de novo molecular formula annotation and MS/MS structure elucidation using SIRIUS 4 with experimental IM collision cross-section (CCS) measurements and machine learning CCS predictions to identify differential unknown metabolites in mutant strains of Caenorhabditis elegans. For many of those ion features, this workflow enabled the successful filtering of candidate structures generated by in silico MS/MS predictions, though in some cases, annotations were challenged by significant hurdles in instrumentation performance and data analysis. While for 37% of differential features we were able to successfully collect both MS/MS and CCS data, fewer than half of these features benefited from a reduction in the number of possible candidate structures using CCS filtering due to poor matching of the machine learning training sets, limited accuracy of experimental and predicted CCS values, and lack of candidate structures resulting from the MS/MS data. When using a CCS error cutoff of ±3%, on average, 28% of candidate structures could be successfully filtered. Herein, we identify and describe the bottlenecks and limitations associated with the identification of unknowns in non-targeted metabolomics using IM-MS to focus and provide insights into areas requiring further improvement.
Subject(s)
Metabolomics , Tandem Mass Spectrometry , Metabolomics/methods , Machine Learning , Ion Mobility Spectrometry/methodsABSTRACT
Metabolite annotation continues to be the widely accepted bottleneck in nontargeted metabolomics workflows. Annotation of metabolites typically relies on a combination of high-resolution mass spectrometry (MS) with parent and tandem measurements, isotope cluster evaluations, and Kendrick mass defect (KMD) analysis. Chromatographic retention time matching with standards is often used at the later stages of the process, which can also be followed by metabolite isolation and structure confirmation utilizing nuclear magnetic resonance (NMR) spectroscopy. The measurement of gas-phase collision cross-section (CCS) values by ion mobility (IM) spectrometry also adds an important dimension to this workflow by generating an additional molecular parameter that can be used for filtering unlikely structures. The millisecond timescale of IM spectrometry allows the rapid measurement of CCS values and allows easy pairing with existing MS workflows. Here, we report on a highly accurate machine learning algorithm (CCSP 2.0) in an open-source Jupyter Notebook format to predict CCS values based on linear support vector regression models. This tool allows customization of the training set to the needs of the user, enabling the production of models for new adducts or previously unexplored molecular classes. CCSP produces predictions with accuracy equal to or greater than existing machine learning approaches such as CCSbase, DeepCCS, and AllCCS, while being better aligned with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. Another unique aspect of CCSP 2.0 is its inclusion of a large library of 1613 molecular descriptors via the Mordred Python package, further encoding the fine aspects of isomeric molecular structures. CCS prediction accuracy was tested using CCS values in the McLean CCS Compendium with median relative errors of 1.25, 1.73, and 1.87% for the 170 [M - H]-, 155 [M + H]+, and 138 [M + Na]+ adducts tested. For superclass-matched data sets, CCS predictions via CCSP allowed filtering of 36.1% of incorrect structures while retaining a total of 100% of the correct annotations using a ΔCCS threshold of 2.8% and a mass error of 10 ppm.
Subject(s)
Algorithms , Metabolomics , Metabolomics/methods , Mass Spectrometry/methods , Chromatography, High Pressure Liquid , Machine LearningABSTRACT
Untargeted metabolomics studies are unbiased but identifying the same feature across studies is complicated by environmental variation, batch effects, and instrument variability. Ideally, several studies that assay the same set of metabolic features would be used to select recurring features to pursue for identification. Here, we developed an anchored experimental design. This generalizable approach enabled us to integrate three genetic studies consisting of 14 test strains of Caenorhabditis elegans prior to the compound identification process. An anchor strain, PD1074, was included in every sample collection, resulting in a large set of biological replicates of a genetically identical strain that anchored each study. This enables us to estimate treatment effects within each batch and apply straightforward meta-analytic approaches to combine treatment effects across batches without the need for estimation of batch effects and complex normalization strategies. We collected 104 test samples for three genetic studies across six batches to produce five analytical datasets from two complementary technologies commonly used in untargeted metabolomics. Here, we use the model system C. elegans to demonstrate that an augmented design combined with experimental blocks and other metabolomic QC approaches can be used to anchor studies and enable comparisons of stable spectral features across time without the need for compound identification. This approach is generalizable to systems where the same genotype can be assayed in multiple environments and provides biologically relevant features for downstream compound identification efforts. All methods are included in the newest release of the publicly available SECIMTools based on the open-source Galaxy platform.
ABSTRACT
INTRODUCTION: At present, vaccines form the only mode of prophylaxis against COVID-19. The time needed to achieve mass global vaccination and the emergence of new variants warrants continued research into other COVID-19 prevention strategies. The severity of COVID-19 infection is thought to be associated with the initial viral load, and for infection to occur, viruses including SARS-CoV-2 must first penetrate the respiratory mucus and attach to the host cell surface receptors. Carrageenan, a sulphated polysaccharide extracted from red edible seaweed, has shown efficacy against a wide range of viruses in clinical trials through the prevention of viral entry into respiratory host cells. Carrageenan has also demonstrated in vitro activity against SARS-CoV-2. METHODS AND ANALYSIS: A single-centre, randomised, double-blinded, placebo-controlled phase III trial was designed. Participants randomised in a 1:1 allocation to either the treatment arm, verum Coldamaris plus (1.2 mg iota-carrageenan (Carragelose®), 0.4 mg kappa-carrageenan, 0.5% sodium chloride and purified water), or placebo arm, Coldamaris sine (0.5% sodium chloride) spray applied daily to their nose and throat for 8 weeks, while completing a daily symptom tracker questionnaire for a total of 10 weeks. PRIMARY OUTCOME: Acquisition of COVID-19 infection as confirmed by a positive PCR swab taken at symptom onset or seroconversion during the study. Secondary outcomes include symptom type, severity and duration, subsequent familial/household COVID-19 infection and infection with non-COVID-19 upper respiratory tract infections. A within-trial economic evaluation will be undertaken, with effects expressed as quality-adjusted life years. DISCUSSION: This is a single-centre, phase III, double-blind, randomised placebo-controlled clinical trial to assess whether carrageenan nasal and throat spray reduces the risk of development and severity of COVID-19. If proven effective, the self-administered prophylactic spray would have wider utility for key workers and the general population. TRIAL REGISTRATION: NCT04590365; ClinicalTrials.gov NCT04590365. Registered on 19 October 2020.
Subject(s)
COVID-19 , Carrageenan , COVID-19/prevention & control , Carrageenan/administration & dosage , Clinical Trials, Phase III as Topic , Double-Blind Method , Humans , Nasal Sprays , Pharynx , Randomized Controlled Trials as Topic , SARS-CoV-2 , Sodium Chloride , Treatment OutcomeABSTRACT
The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low or atmospheric pressure drift chamber. The sensitivity and reliability of computational prediction of CCS values depend on accurately modeling the molecular state over accessible conformations. In this work, we developed an efficient CCS computational workflow using a machine learning model in conjunction with standard DFT methods and CCS calculations. Furthermore, we have performed Traveling Wave IM-MS (TWIMS) experiments to validate the extant experimental values and assess uncertainties in experimentally measured CCS values. The developed workflow yielded accurate structural predictions and provides unique insights into the likely preferred conformation analyzed using IM-MS experiments. The complete workflow makes the computation of CCS values tractable for a large number of conformationally flexible metabolites with complex molecular structures.
Subject(s)
Ion Mobility Spectrometry , Machine Learning , Ion Mobility Spectrometry/methods , Molecular Conformation , Molecular Structure , Reproducibility of ResultsABSTRACT
Metabolic rate is a basic individual metric that extends beyond the individual to link the ecology of populations, communities, and ecosystems via its role as a central component of energy budgets. Metabolic rates are often measured indirectly by quantifying respiration under simplified, standard laboratory conditions. This approach limits the application of these measurements to a small range of conditions that commonly do not reflect natural field conditions. We measured metabolic rates of the squareback marsh crab Armases cinereum under field conditions. Previous work highlights that movement of individual A. cinereum, especially females, provides a potential spatial subsidy of energy, as individuals consume foods in salt marshes and then transfer the resulting energy to upland forest ecosystems. We show that metabolic rate increases with size for both males and females and that metabolic rates are influenced by temperature and by whether females are vitellogenic. The metabolic rates that we measured more closely approximate field metabolic rates than standard metabolic rates and demonstrate that individual crabs experience high energy expenditures, reducing the amount of energy that may be transferred as a subsidy between marsh and forest as a result of the daily movements of individual crabs. Our measurements are therefore also a key component for the construction of an energy budget for this species.
ABSTRACT
Synovial sarcoma (SS) is frequently diagnosed in teenagers and young adults and continues to be treated with polychemotherapy with variable success. The SS18-SSX gene fusion is pathognomonic for the disease, and high expression of the anti-apoptotic BCL-2 pathologically supports the diagnosis. As the oncogenic SS18-SSX fusion gene itself is not druggable, BCL-2 inhibitor-based therapies are an appealing therapeutic opportunity. Venetoclax, an FDA-approved BCL-2 inhibitor that is revolutionizing care in some BCL-2-expressing hematological cancers, affords an intriguing therapeutic possibility to treat SS. In addition, there are now dozens of venetoclax-based combination therapies in clinical trials in hematological cancers, attributing to the limited toxicity of venetoclax. However, preclinical studies of venetoclax in SS have demonstrated an unexpected ineffectiveness. In this study, we analyzed the response of SS to venetoclax and the underlying BCL-2 family biology in an effort to understand venetoclax treatment failure and find a therapeutic strategy to sensitize SS to venetoclax. We found remarkably depressed levels of the endogenous MCL-1 inhibitor, NOXA, in SS compared to other sarcomas. Expressing NOXA led to sensitization to venetoclax, as did the addition of the MCL-1 BH3 mimetic, S63845. Importantly, the venetoclax/S63845 combination induced tumor regressions in SS patient-derived xenograft (PDX) models. As a very close analog of S63845 (S64315) is now in clinical trials with venetoclax in AML (NCT03672695), the combination of MCL-1 BH3 mimetics and venetoclax should be considered for SS patients as a new therapy.
ABSTRACT
BACKGROUND: Suicide is a serious and growing public health concern, both for the United States (U.S.) and for the Department of Defense (DoD). METHODS: Using the social-ecological framework, we provide examples of how three newly developed, DoD-funded pilots/programs have incorporated a public health approach to help prevent military suicide. KEY RESULTS: The first two programs demonstrate how non-clinical, community-based approaches can be tailored to specific military subgroups at the individual, relational, and community levels. These programs include a universal suicide prevention program developed for Special Operations service members, spouses, and mental health providers, and a selective suicide prevention program pilot developed for military chaplains to support them in their role as a "gateway" to care for distressed service members, improve mental health and chaplaincy collaboration, and prevent burnout. The third program illustrates how the creation of and policy of a methodology/infrastructure to conduct standardized, theory-driven suicide death reviews across the DoD may inform the DoD public health approach to surveillance, review, and synthesis of suicide data, informed by the social-ecological model. Potential program limitations and evaluation efforts are discussed. CONCLUSION: Future prevention approaches should enhance coordination and communication between DoD, VA, and community organizations to enhance multi-level suicide prevention programming for military personnel, veterans, and civilians.
Subject(s)
Military Personnel , Suicide Prevention , Veterans , Humans , Public Health , United States , United States Department of Veterans AffairsABSTRACT
Human epidermal growth factor receptor 2 gene (HER2) is focally amplified in approximately 20% of breast cancers. HER2 inhibitors alone are not effective, and sensitizing agents will be necessary to move away from a reliance on heavily toxic chemotherapeutics. We recently demonstrated that the efficacy of HER2 inhibitors is mitigated by uniformly low levels of the myeloid cell leukemia 1 (MCL-1) endogenous inhibitor, NOXA. Emerging clinical data have demonstrated that clinically advanced cyclin-dependent kinase (CDK) inhibitors are effective MCL-1 inhibitors in patients, and, importantly, well tolerated. We, therefore, tested whether the CDK inhibitor, dinaciclib, could block MCL-1 in preclinical HER2-amplified breast cancer models and therefore sensitize these cancers to dual HER2/EGFR inhibitors neratinib and lapatinib, as well as to the novel selective HER2 inhibitor tucatinib. Indeed, we found dinaciclib suppresses MCL-1 RNA and is highly effective at sensitizing HER2 inhibitors both in vitro and in vivo. This combination was tolerable in vivo. Mechanistically, liberating the effector BCL-2 protein, BAK, from MCL-1 results in robust apoptosis. Thus, clinically advanced CDK inhibitors may effectively combine with HER2 inhibitors and present a chemotherapy-free therapeutic strategy in HER2-amplified breast cancer, which can be tested immediately in the clinic.
Subject(s)
Antineoplastic Combined Chemotherapy Protocols/pharmacology , Breast Neoplasms/drug therapy , Cyclic N-Oxides/pharmacology , Indolizines/pharmacology , Myeloid Cell Leukemia Sequence 1 Protein/antagonists & inhibitors , Protein Kinase Inhibitors/pharmacology , Pyridinium Compounds/pharmacology , Receptor, ErbB-2/antagonists & inhibitors , Animals , Breast Neoplasms/genetics , Breast Neoplasms/metabolism , Cell Line, Tumor , Cyclic N-Oxides/administration & dosage , Drug Synergism , Female , Gene Amplification , Humans , Indoles/administration & dosage , Indoles/pharmacology , Indolizines/administration & dosage , Mice , Myeloid Cell Leukemia Sequence 1 Protein/genetics , Myeloid Cell Leukemia Sequence 1 Protein/metabolism , Oxazoles/administration & dosage , Oxazoles/pharmacology , Pyridines/administration & dosage , Pyridines/pharmacology , Pyridinium Compounds/administration & dosage , Quinazolines/administration & dosage , Quinazolines/pharmacology , Quinolines/administration & dosage , Quinolines/pharmacology , Random Allocation , Receptor, ErbB-2/genetics , Receptor, ErbB-2/metabolism , Sulfonamides/administration & dosage , Sulfonamides/pharmacology , Xenograft Model Antitumor AssaysABSTRACT
MYCN is amplified in 20% to 25% of neuroblastoma, and MYCN-amplified neuroblastoma contributes to a large percent of pediatric cancer-related deaths. Therapy improvements for this subtype of cancer are a high priority. Here we uncover a MYCN-dependent therapeutic vulnerability in neuroblastoma. Namely, amplified MYCN rewires the cell through expression of key receptors, ultimately enhancing iron influx through increased expression of the iron import transferrin receptor 1. Accumulating iron causes reactive oxygen species (ROS) production, and MYCN-amplified neuroblastomas show enhanced reliance on the system Xc- cystine/glutamate antiporter for ROS detoxification through increased transcription of this receptor. This dependence creates a marked vulnerability to targeting the system Xc-/glutathione (GSH) pathway with ferroptosis inducers. This reliance can be exploited through therapy with FDA-approved rheumatoid arthritis drugs sulfasalazine (SAS) and auranofin: in MYCN-amplified, patient-derived xenograft models, both therapies blocked growth and induced ferroptosis. SAS and auranofin activity was largely mitigated by the ferroptosis inhibitor ferrostatin-1, antioxidants like N-acetyl-L-cysteine, or by the iron scavenger deferoxamine (DFO). DFO reduced auranofin-induced ROS, further linking increased iron capture in MYCN-amplified neuroblastoma to a therapeutic vulnerability to ROS-inducing drugs. These data uncover an oncogene vulnerability to ferroptosis caused by increased iron accumulation and subsequent reliance on the system Xc-/GSH pathway. SIGNIFICANCE: This study shows how MYCN increases intracellular iron levels and subsequent GSH pathway activity and demonstrates the antitumor activity of FDA-approved SAS and auranofin in patient-derived xenograft models of MYCN-amplified neuroblastoma.