Biology subjects

Zhu, X.

Publications and source records attributed to Zhu, X..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Engineering light robustness: Adaptive evolution uncovers new genetic determinants of HL tolerance in Synechocystis

Excess light absorption causes severe photo-oxidative damage and limits photosynthetic efficiency. Enhancing high-light (HL) tolerance and energy utilization in photosynthetic cyanobacteria holds great potential for sustainable biomanufacturing. Here, using Synechocystis sp. PCC 6803 (Syn6803) as a model, we generated eight independently evolved strains tolerant to hyper-HL (2000 mol photons/m2/s) through approximately two years of natural adaptive laboratory evolution (ALE). Remarkably, these strains circumvented common evolutionary trade-offs; all demonstrated markedly enhanced quantum yields and photosynthetic performance, with four strains exhibiting a 121.71%-168.36% increase in biomass accumulation under HL. When equipped with the heterologous sucrose transporter CscB, sucrose productivity under HL increased by up to 208.33%. Whole-genome resequencing unveiled a total of 77 mutations across the eight lineages, uncovering a diverse polygenic landscape for HL adaptation. Reverse genetics combined with structural modeling highlighted pivotal roles for regulatory and structural loci, including slr0758 (KaiC1) and slr1513 (SbtB), in modulating circadian rhythmicity and inorganic carbon uptake to prevent photo-oxidative overload. Overall, our findings uncover diverse evolutionary routes toward high-light acclimation and provide superior cyanobacterial chassis for photosynthetic biotechnology.

microbiology↗

bioRxiv2025

Improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning

Multivariable Mendelian randomization (MVMR) has been largely limited to individuals of European ancestry, due to the larger sample sizes available in European genome-wide association studies (GWAS). We introduce MRBEE-TL, one of the first multi-ancestry MVMR methods, which combines transfer learning with bias-corrected estimating equations to improve power in underpowered ancestries and to assess cross-ancestry heterogeneity of disease risk factors. In simulations, MRBEE-TL consistently outperformed MR methods that relied solely on ancestry-specific GWAS data. In real data analyses, MRBEE-TL not only identified ancestry-consistent and ancestry-specific causal effects missed by conventional methods, but also improved power in African and East Asian ancestries. MRBEE-TL is available through the R package MRBEEX at https://github.com/harryyiheyang/MRBEEX.

bioinformatics↗

bioRxiv2025

Cell type-specific master metabolic regulators of Alzheimer's disease

Alzheimers disease (AD) exhibits metabolic heterogeneity; yet, the consequences on metabolic dynamics in a cell-type-specific manner and the underlying metabolite-sensor network basis remain unclear. Here, we show that neurons exhibit a striking decrease in energy and lipid-related metabolic activity, contrasted by an increase in microglial metabolism associated with neuroinflammation. To identify cell-type specific master metabolic regulators of AD underlying the metabolic alterations in AD, we introduce scFUMES (single cell FUnctional MEtabolite-Sensor), an algorithm integrating single-cell RNA sequencing, interactomics, genomics, transcriptomics, and metabolomics from human brain biobanks. Applied to two AD-vulnerable regions (middle temporal gyrus and dorsolateral prefrontal cortex), scFUMES uncovers hundreds of AD-associated regulators, with neurons and microglia showing the most interactions. Particularly, scFUMES pinpoints genetics-informed master metabolic regulators across AD severity, sex and APOE genotype (e.g., PPARD-glycerol in microglia). Experimental testing reveals that two interaction pairs predicted by scFUMES, neuronal palmitic acid bound fatty acid binding protein 3 and gut metabolite indole-3-propionic acid binding to kynurenine aminotransferase 1, both lower pathological tau species in AD. Collectively, scFUMES systematically maps AD master metabolic regulators, offering insights into cellular metabolic heterogeneity and therapeutic strategies for AD and other AD-related dementia if broadly applied.

systems biology↗

bioRxiv2025

Structure and function of a cross-neutralizing influenza neuraminidase antibody that accommodates recent N2 NA Asn245 glycosylation

Monoclonal antibodies (mAbs) that recognize and inhibit a diverse range of influenza viruses, although relatively rare, have been isolated following infection or vaccination. Study of their ontology and mechanisms of action informs universal vaccine and therapeutic development. We have previously described a potent and broad neuraminidase (NA)-neutralizing human mAb, 1122A11, that neutralizes a wide range of H3N2 viruses. Here, further characterization of 1122A11 reveals reactivity to cross-group influenza A virus NAs, including group-1 N1 and N8, and group-2 N2 and N3 NAs. Recent H3N2 viruses have acquired Asn245 glycosylation on the active site rim. Crystal structures of an N2 NA from A/Singapore/INFIMH-16-0019/2016 (H3N2) at 2.3 [A] (apo) and 2.2 [A] (Fab bound) resolution showed that 1122A11 binding causes local changes to the periphery of NA active site to accommodate the glycan. The CDRH3 of 1122A11 inserts into the active site and mimics the substrate sialic acid. We then determined that the ability of 1122A11 to protect from lethal challenge in mice is not dependent on Fc-effector function. These results highlight the therapeutic potential of 1122A11 as a broad protective anti-viral and reinforce pursuit of immunogen development of NA antibodies toward achieving more universal influenza protection.

immunology↗

bioRxiv2025

MetaNet: a scalable and integrated tool for reproducible omics network analysis

Network analysis is a powerful strategy for uncovering complex relationships in high-throughput omics datasets. However, current tools often lack scalability, flexibility, and native support for multi-omics integration, posing significant barriers for exploring complex biological networks. To address these limitations, we developed MetaNet, a high-performance R package designed to construct, visualize, and analyze biological networks from multi-omics datasets. MetaNet supports highly efficient correlation-based network construction, scalable to datasets with over 10,000 features, and includes extensive layout algorithms and visualization options compatible with both static and interactive platforms. It also provides a comprehensive suite of topological and stability metrics for in-depth network characterization. Benchmarking results show that MetaNet outperforms existing R packages by up to 100-fold in computation time and reduces memory usage by up to 50-fold. We demonstrate its utility through two case studies: (1) a longitudinal analysis of microbial co-occurrence networks showing the dynamics of the airborne microbiome, and (2) an integrative exposome-transcriptome network of more than 40,000 features, uncovering distinct regulatory impacts of biological and chemical exposures. MetaNet bridges the gap between network theory and omics application by offering a robust, reproducible, and biologically informed framework for large-scale, interpretable, and integrative network analyses across diverse omics platforms, advancing systems-level understanding in modern life sciences. MetaNet is available on the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/MetaNet).

bioinformatics↗

bioRxiv2025

Synaptic plasticity of prefrontal long-range inhibition regulates cognitive flexibility

While glutamatergic synaptic plasticity is believed to be a fundamental mechanism mediating learning, the behavioral significance of plasticity at cortical GABAergic synapses remains less well understood. Furthermore, despite recent discoveries of long-range projections from neocortical GABAergic neurons, details about how they function are also sparse. Here we combine behavioral optogenetics with patch-clamp electrophysiology to link plasticity at long-range GABAergic synapses with higher-order cognitive functions. Specifically, learning extradimensional rule shifts potentiates callosal GABAergic synapses from prefrontal parvalbumin-expressing (PV) neurons onto corticothalamic neurons. Disrupting this potentiation by inhibiting callosal PV terminals during rule shifts induces perseveration, whereas reinstating this potentiation with subsequent gamma-frequency callosal PV terminal stimulation restores flexible behavior. This shows how a novel plasticity locus can regulate brain circuits underlying normal cognition and pathological states.

neuroscience↗

bioRxiv2025

Dose-dependent, opioid-induced sleep disruption is partially mediated by motor activity but not by body temperature in C57BL/6J mice

States of sleep and wakefulness, motor activity, and body temperature are temporally linked, yet these variables are often studied independently. Here we report novel results from male C57BL/6J mice (n = 24) that quantify the causal and correlational relationships between these temporally linked measures. The initial experiments used 12 mice to identify the lowest antinociceptive doses of fentanyl (0.1 mg/kg) and morphine (1 mg/kg). Twelve additional mice were implanted with telemeters to simultaneously record EEG, electromyogram, motor activity, and subcutaneous body temperature. Doses of fentanyl (0.1, 0.3, 1, 3 mg/kg) and morphine (1, 3, 10, 30 mg/kg) caused significant (P<0.05) increases in wakefulness and decreases in NREM and REM sleep. Fentanyl (0.1 to 3 mg/kg) and morphine (3 to 30 mg/kg) significantly increased motor activity. Body temperature during wakefulness was significantly decreased by fentanyl (1, 3 mg/kg). Morphine increased (3 mg/kg) and decreased (30 mg/kg) body temperature. Mediation analyses showed that the increase in wakefulness caused by fentanyl and morphine was partially mediated by motor activity, but not by changes in body temperature. These results provide the first complete dose-response data for effects of fentanyl and morphine on simultaneously acquired measures of sleep/wake states, body temperature, and motor activity. Compared to human data, these results from mice reveal similarities (sleep disruption, hyperthermia and hypothermia) and differences (increased motor activity) caused by fentanyl and morphine. The results also demonstrate the power of mediation analyses for providing nuanced insights into opioid effects on clinically relevant neurobehavioral phenotypes. Significance StatementSleep disruption is an undesired, clinically significant effect of opioids prescribed to manage pain. Sleep disruption exacerbates pain and can lead to increased opioid requirement, as well as increased risk of addiction relapse. The significance of this study is the discovery that in mice, even the lowest doses of fentanyl and morphine that caused antinociception also caused sleep disruption. Thus, in mice, it is not possible to provide antinociception using fentanyl or morphine without causing sleep disruption.

pharmacology and toxicology↗

bioRxiv2025

Dietary nitrate and nitrite protect against doxorubicin-induced cardiac fibrosis and oxidative protein damage in tumor-bearing mice

Anthracycline-induced cardiotoxicity remains a major limitation in cancer therapy, affecting long-term cardiovascular health in survivors. Dietary nitrate supplementation has shown cardioprotective effects in preclinical models of doxorubicin (Dox)-induced and ischemia-reperfusion injury. In this study, we evaluated the protective effects of nitrate and nitrite (NOx) supplementation in a syngeneic, tumor-bearing mouse model undergoing Dox chemotherapy (N=5 per group). NOx supplementation significantly reduced cardiac fibrosis and levels of 4-hydroxynonenal-modified proteins, a marker of oxidative stress. Tumor sizes varied, but most regressed by the final Dox dose. Importantly, NOx did not compromise the anti-tumor efficacy of Dox nor did it promote pulmonary metastasis. These findings support the potential clinical use of dietary nitrate and nitrite as adjuncts to Dox treatment to mitigate cardiotoxicity without impairing anti-cancer outcomes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/660942v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1ec0e52org.highwire.dtl.DTLVardef@a03beaorg.highwire.dtl.DTLVardef@1bdb02eorg.highwire.dtl.DTLVardef@79d23e_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

An atlas of cell type specific regulatory effects in cattle

Understanding the genetic and molecular architecture of complex traits and artificial selection is crucial for advancing sustainable precision breeding in cattle and other livestock. Yet, how genetic variation affects cellular gene expression remains elusive in cattle. Here, by integrating 8,866 bulk RNA-seq samples and 999,192 single cells of 81 cell types in 22 bovine tissues, we presented a comprehensive atlas of regulatory variants at the cell type resolution in cattle. By colocalizing with bulk-tissue expression quantitative trait loci (beQTL), we detected 57,043 novel cell-type stratified eQTL and cell-type/state interaction eQTL in 18,153 genes, which also exhibited a stronger tissue/cell-type specificity than beQTL. By examining genome-wide associations (GWAS) of 44 complex traits, these cell-resolved eQTL were colocalized with 505 (24%) additional GWAS loci compared to beQTL. Through integrating this resource with selection signatures between dairy and beef cattle, we provided tissue/cell-specific regulatory insights into cattle breeding. Overall, the current atlas of cell-type-specific regulatory variants will serve as an invaluable resource for cattle genomics and selective breeding.

genetics↗

bioRxiv2025

Population-specific brain charts reveal Chinese-Western differences in neurodevelopmental trajectories

Human brain charts provide unprecedented opportunities for decoding neurodevelopmental milestones and establishing clinical benchmarks for precision brain medicine 1-7. However, current lifespan brain charts are primarily derived from European and North American cohorts, with Asian populations severely underrepresented. Here, we present the first population-specific brain charts for China, developed through the Chinese Lifespan Brain Mapping Consortium (Phase I) using neuroimaging data from 43,037 participants (aged 0-100 years) across 384 sites nationwide. We establish the lifespan normative trajectories for 296 structural brain phenotypes, encompassing global, subcortical, and cortical measures. Cross-population comparisons with Western brain charts (based on data from 56,339 participants aged 0-100 years) reveal distinct neurodevelopmental patterns in the Chinese population, including prolonged cortical and subcortical maturation, accelerated cerebellar growth, and earlier development of sensorimotor regions relative to paralimbic regions. Crucially, these Chinese-specific charts outperform Western-derived models in predicting healthy brain phenotypes and detecting pathological deviations in Chinese clinical cohorts. These findings highlight the urgent need for diverse, population-representative brain charts to advance equitable precision neuroscience and improve clinical validity across populations.

neuroscience↗

bioRxiv2025

Image-Based Meta- and Mega-Analysis (IBMMA): A Unified Framework for Large-Scale, Multi-Site, Neuroimaging Data Analysis

The increasing scale and complexity of neuroimaging datasets aggregated from multiple study sites present substantial analytic challenges, as existing statistical analysis tools struggle to handle missing voxel-data, suffer from limited computational speed and inefficient memory allocation, and are restricted in the types of statistical designs they are able to model. We introduce Image-Based Meta- & Mega-Analysis (IBMMA), a novel software package implemented in R and Python that provides a unified framework for analyzing diverse neuroimaging features, efficiently handles large-scale datasets through parallel processing, offers flexible statistical modeling options, and properly manages missing voxel-data commonly encountered in multi-site studies. IBMMA produced stronger effect sizes and revealed findings in brain regions that traditional software overlooked due to missing voxel-data resulting in gaps in brain coverage. IBMMA has the potential to accelerate discoveries in neuroscience and enhance the clinical utility of neuroimaging findings.

neuroscience↗

bioRxiv2025

KRT6A and KRT17 mark distinct stem cell populations in the adult palpebral conjunctiva and Meibomian gland

PurposeTo investigate whether KRT6A or KRT17 label self-renewing stem cells (SCs) in adult Meibomian gland (MG) and palpebral conjunctiva (PC) homeostasis and explore the mechanisms that regulate their expression in these tissues. MethodsKRT6A and KRT17 expression in adult mouse MG and PC was examined by single nucleus RNA sequencing and immunofluorescence (IF). Bromodeoxyuridine pulse-chase assays were conducted to assess the turnover rate of PC progenitor cells. Lineage tracing experiments were performed using Krt6a-CreERT2and Krt17-CreERT2 mice carrying Rosa26RnTnG or Rosa26RmTmG reporter. As Hedgehog (Hh) signaling, the histone deacetylase HDAC3, and the transcription factor KLF4, regulate KRT6A and KRT17 in other contexts, IF was conducted to assess the in vivo effects of overexpression of the Hh pathway activator GLI2{Delta}N, and inducible epithelial deletion of Hdac3 or Klf4, on KRT6A and KRT17 expression in the MG and PC. ResultsKRT6A and KRT17 are primarily expressed in the MG central duct and ductules. KRT6A also shows robust expression in PC. MG and PC epithelial progenitor cells turn over within 14 days. Lineage tracing indicated that Krt17 labels self-renewing SCs in the MG whereas Krt6a labels SCs in the PC. GLI2{Delta}N overexpression induced ectopic KRT17 expression in MG acini and PC but did not affect KRT6A expression in either MG or PC. Hdac3 deficiency caused expanded expression of KRT6A and KRT17 in MG acini and ectopic KRT17 expression in PC. Klf4 deletion resulted in ectopic KRT17 expression in PC but did not influence KRT6A expression in MG or PC. ConclusionsKrt6a- and Krt17-expressing cells contribute to adult PC and MG homeostasis, respectively. KRT17 expression is enhanced by GLI2{Delta}N, and suppressed by HDAC3 and KLF4, whereas KRT6A expression is controlled only by HDAC3.

cell biology↗

bioRxiv2025

A high-throughput immunopeptidome platform for MHC II alleles to characterize antigen-specific CD4 + T cells

CD4+ T cells play a pivotal role in adaptive immunity, recognizing peptide antigens presented by MHC II molecules during infections and tumor development. Identifying immunodominant MHC II epitopess is essential for understanding CD4+ T cell responses; however, current methods such as mass spectrometry, suffer from low sensitivity and throughput, while computational algorithms show variable accuracy. To overcome these challenges, we developed EliteMHCII, a high-throughput immunopeptidome profiling platform that identifies antigen-derived MHC II epitopes and measures peptide binding affinity across 24 globally common MHC II alleles. Using EliteMHCII, we assessed the immunodominant epitopes of the SARS-CoV-2 RBD protein. Validation in vaccinated individuals and humanized mouse models revealed a strong correlation between high-affinity peptides and robust CD4+ T cell responses, while low-affinity peptides failed to elicit responses. Therefore, our immunopeptidome profiling platform, EliteMHCII, serves as a rapid, high throughput, feasible platform for CD4+ T cell epitope discovery at a global populational level in the context of infectious diseases and cancer immunotherapy.

biochemistry↗

bioRxiv2025

H3K4me1 directs H3K36me2 and H3K36me3 deposition in land plants

Monomethylation of histone H3 lysine 4 (H3K4me1) marks enhancers in mammals. However, the function of H3K4me1 in plants remains largely unclear. Here, we analyzed the genome-wide distribution of H3K4me1 in diverse species across evolution, revealing a distinctive H3K4me1 distribution pattern in land plants. To explore the function of H3K4me1 in plants, we identified an H3K4me1-specific reader protein, Early heading date 3 (Ehd3), and solved the structure of Ehd3 in complex with the H3K4me1 peptide, revealing a unique binding module differing from the previously reported PHD finger proteins. We further identified an Ehd3-binding protein, SET domain group 724 (SDG724), and the deletion of either Ehd3 or SDG724 caused similar defects in plant phenotype and changes in transcriptome and epigenome profiles. Both Ehd3 and SDG724 are enriched at chromatin regions marked by H3K4me1 but not H3K4me2 or H3K4me3. Ehd3 activates the H3K36 methyltransferase SDG724, and H3K36me2/me3 are colocalized with H3K4me1 in the genomes of land plants. Collectively, our results reveal that H3K4me1 directs the establishment of H3K36me2 and H3K36me3 in land plants.

molecular biology↗

bioRxiv2025

Contrastive Learning-Enhanced Drug Metabolite Prediction Drives the Discovery of an Orally Bioavailable RSK4 Inhibitor for Esophageal Cancer

Drug metabolism liabilities are a major bottleneck in drug development, necessitating accurate metabolite prediction tools. While AI-driven methods have advanced, challenges remain in achieving high-precision, robustness, broad reaction coverage and seamless integration into the drug development workflow. To address this, we first constructed the most comprehensive human-specific drug metabolism database to date, encompassing 11,665 human metabolic reactions and 2,497 high-quality rules. Leveraging this resource, we developed ConMeter (Contrastive learning and feature interaction based Metabolic Reaction prediction), a novel model integrating chemical feature interaction and contrastive learning. ConMeter demonstrates significant improvements, achieving [~]80% accuracy in identifying at least one metabolite within the top 5 predictions and showing an average 25% relative enhancement in ranking true positives compared to state-of-the-art methods. The comprehensive database also expands the range of predictable metabolic reactions. To demonstrate the utility of ConMeter, we integrated it into a metabolite prediction-guided drug design strategy aimed at addressing the low oral bioavailability of a metabolically vulnerable RSK4 lead compound -- a pervasive issue among known RSK inhibitors. This strategy successfully yielded R636, a novel RSK4 inhibitor exhibiting remarkably improved bioavailability (a 63-fold increase, reaching 63% absolute bioavailability) while maintaining its potent activity. Notably, R636 showed favorable safety profile and significant anti-tumor efficacy against esophageal squamous cell carcinoma (ESCC) in vitro and in two distinct patient-derived xenograft (PDX) mouse models. This work introduces ConMeter as a powerful and practical tool for high-accuracy metabolite prediction, demonstrating its potential to accelerate lead optimization, exemplified by the discovery of R636 as a promising orally bioavailable candidate for ESCC.

cancer biology↗

bioRxiv2025

Leveraging Dynamic Stability to Infer Regulation in Protein-Protein Interaction Networks: A Study of Infectious Vulnerability in COPD.

The fourth leading cause of death in the US, Chronic Obstructive Pulmonary Disease (COPD) is punctuated by frequent viral and bacterial infections causing severe acute exacerbations (AECOPD) and increased mortality. In previous work we have shown that altered immune cell signaling may confer increased and persistent susceptibility to infection. Here we continue this investigation by conducting broad-spectrum proteomic profiling of circulating white blood cells to assemble an empirical protein-protein interaction network associated with frequency of infectious exacerbation. In a novel extension of conventional cross-sectional data analyses, we translate these undirected protein-protein interactions into candidate regulatory relationships with both direction and mode of action. The latter are inferred by formulating and solving a constraint satisfaction problem (SAT) whereby predicted dynamic behaviors of any valid regulatory network must support the expected persistent nature of low and high vulnerability phenotypes. Solving this SAT problem produced a set of competing candidate protein regulatory network architectures and signalling rules that unanimously highlighted several novel candidate pathway elements involved in oxidative stress response. Analysis of the overall dynamics supported by these networks, again supported the hypothesis that progression beyond an immune tipping point may confer persistent susceptibility to infection and that this may constitute a stable phenotype or regulatory trap in COPD characterized by a reactive oxygen cascade. HIGHLIGHTSO_LIInfectious vulnerability phenotypes in COPD may represent immune regulatory traps. C_LIO_LIA 15-protein oxidative stress response interactome offers a phenotypic signature. C_LIO_LIHomeostasis in cross-sectional data can support inference of co-regulatory actions. C_LIO_LI8 of 11 documented regulatory actions recovered in candidate model majority vote C_LIO_LI17 new candidate protein co-regulatory actions proposed unanimously by all models. C_LI

systems biology↗

bioRxiv2025

IL-17A-driven Macrophage Disorder Promotes Plaque Instability in Psoriatic Atherosclerosis

Psoriasis is a common chronic inflammatory skin disease that predisposes individuals to cardiovascular diseases such as atherosclerosis. However, the underlying mechanisms linking these conditions have not yet been fully elucidated. Recent studies have indicated that the inflammatory cytokine IL-17A plays a significant role in both diseases. The aim of this study was to investigate how psoriasis affects the stability of atherosclerotic plaques via the IL-17A/IL-17RA pathway. We performed single-cell sequencing on patients with both psoriasis and atherosclerosis to analyze changes in the immune microenvironment within their carotid plaques and psoriatic lesions. We found that IL-17A significantly upregulated the expression of pro-inflammatory factors (e.g., CXCL8) in macrophages of psoriatic atherosclerosis patients, leading to weakening of the fibrous cap structure of plaques. Additionally, IL-17A further exacerbated plaque instability by interfering with macrophage lipid metabolism, particularly sphingolipid metabolism. Finally, using in vitro experiments and animal models, we demonstrated that IL-17A enhances pro-inflammatory and metabolic abnormalities in macrophages by downregulating PPAR{gamma}. Therapeutic strategies targeting IL-17A may contribute to the simultaneous mitigation of psoriasis and atherosclerosis-associated cardiovascular risk, providing new directions for clinical intervention.

cell biology↗

bioRxiv2025

Efficacy of DNA Methyltransferase Inhibitor Immune Priming Therapy in Combination with PD-1 Inhibitors to Treat High-Risk Pediatric Brain Tumors

BackgroundDespite intensive therapies, outcomes for high-risk pediatric brain tumors (PBTs) remain dismal, prompting the search for novel treatments. DNA methyltransferase inhibitors (DNMTi) have been shown to prime tumors to improve response to checkpoint inhibition. The aim of this study was to investigate the potential of decitabine (DAC), in combination with a PD-1 inhibitor, to improve survival in pediatric high-risk brain tumor models. MethodsAnalysis of human PBT datasets was performed to determine gene expression levels of immune cell associated markers. Tumor response to DAC, with or without a PD-1 inhibitor, was tested in murine models representing H3-wildtype diffuse intrinsic pontine glioma (DIPG), H3K27-mutant diffuse midline glioma (DMG), atypical teratoid rhabdoid tumor (ATRT), and medulloblastoma (MB). CyTOF analysis of allograft tumors was performed to characterize changes within the tumor microenvironment. ResultsAnalysis of PBT subtypes revealed heterogeneous expression of immune cell markers, checkpoint receptors, and MHC molecules. DAC treatment decreased DNA methylation and increased neoantigen expression in human and mouse tumor cells. DAC alone or in combination with a PD-1 inhibitor resulted in prolonged survival in syngeneic mouse models of DIPG and ATRT but not DMG and MB models. CyTOF analysis of mouse tumors revealed changes in local immune cell infiltration upon combination treatment. ConclusionsDAC in combination with a PD-1 inhibitor can alter the immune microenvironment in mouse tumor models. Changes were observed in H3-wildtype DIPG and ATRT models, suggesting that certain tumor subtypes may respond to checkpoint blockade after immune augmentation with DNMTi. Key PointsO_LIPBTs show heterogenous expression of immune cell infiltrates C_LIO_LIDAC or DAC plus a PD-1 inhibitor shows extension of survival in H3-wildtype DIPG and ATRT mouse models C_LIO_LIMyeloid-derived suppressor cell abundance could be a major contributing factor to treatment response C_LI Importance of the StudyChildren with high-risk PBTs face dismal outcomes. Immune checkpoint inhibitor (ICI) successes have been demonstrated in a variety of adult malignancies; however, such beneficial outcomes have not been realized in PBTs. Here we investigate single and combination treatment of DNMTi and PD-1 checkpoint inhibition in syngeneic mouse models of high-risk PBTs. Our results suggest that some H3-wildtype DIPG and ATRT tumor types may be responsive to checkpoint therapy post immunomodulation and warrant further investigation.

immunology↗