Biology subjects

Xu, H.

Publications and source records attributed to Xu, H..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

Oocyte growth and maturation depend on tightly coordinated programs within oocytes and their surrounding granulosa cells, yet defining the transcriptional continuum of growing oocytes has been challenging due to their large size and the limitations of current droplet-based and spatial transcriptomic platforms. Here, we optimized a high-density array-based platform called Stereo-cell for high-throughput dual-modality profiling of large mouse oocytes, allowing for both the preservation of morphology and transcript capture. By integrating unsupervised transcriptomic clustering with cell morphological features, we delineated successive temporal windows from growing oocytes to metaphase II and uncovered stage-linked shifts from early programs toward later programs. We also profiled the ovarian somatic fraction, reconstructed granulosa-cell subtype relationships, and placed ovarian cell states in tissue context using single-cell-resolution spatial data.

developmental biology↗

bioRxiv2026

Systemic neoantigen-specific T cells reveal central determinants of PD-(L)1 blockade efficacy

The contribution of neoantigen-specific T cells to PD-(L)1 efficacy has largely been inferred from tumor mutational burden. We functionally profiled circulating T cell responses against 7,038 predicted HLA-I-restricted and 21,453 HLA-II-restricted neopeptides in 27 patients with advanced non-small cell lung cancer treated with anti-PD-(L)1. CD4 responses were frequent and correlated with neoantigen availability but not clinical benefit. In contrast, the magnitude and breadth of neoantigen-specific CD8 T cell responses were associated with clinical benefit, progression-free and overall survival, independently of tumor mutational burden. Patients mounting coordinated CD4 and CD8 responses experienced improved progression-free survival. Tumors from CD8 responders displayed immune signatures indicative of both T cell priming and effector functions. Circulating neoantigen-specific CD8 T cells recognized endogenously processed antigens, trafficked to tumors, and selectively expanded under therapy while retaining CD28, CD226, and CXCR3 expression. These findings identify coordinated, functionally engaged neoantigen-specific T cell responses as central determinants of PD-(L)1 efficacy.

cancer biology↗

bioRxiv2026

PROTOTYPE-BASED CONTINUAL LEARNING FOR SINGLE-CELL ANNOTATION

Large-scale single-cell atlases provide an increasingly comprehensive view of cellular diversity, but their continued expansion across studies poses a fundamental challenge: preserving consistent cell identities while capturing biological variation in cellular states. Most existing annotation frameworks are built around static references, making it difficult to incorporate newly generated datasets into established cellular representations without retraining on historical data. When updated sequentially, these methods are further constrained by catastrophic forgetting and batch-specific biases, limiting scalability and the continuity of knowledge integration. Here we introduce scEvolver, a continual learning framework for single-cell annotation that incrementally accumulates knowledge through memory-guided refinement of cell-type prototypes without revisiting historical data. Across sequencing platforms, tissue contexts and molecular modalities, scEvolver supports robust annotation and external query mapping with substantially fewer labelled reference cells. By preserving consistent cell-type semantics across datasets while capturing biologically meaningful within-class heterogeneity, scEvolver enables the identification of epithelial cell-state transitions in inflammatory gut disease. External mapping to the healthy Human Lung Cell Atlas further reveals shared cell-state deviations across multiple diseases, including an FCGR3A+ inflammatory monocyte programme in sarcoidosis, chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis, highlighting scEvolvers potential to characterize context-specific cellular dynamics in complex disease settings.

bioinformatics↗

bioRxiv2026

AAV-Mediated Dual-Gene Therapy Restores Metabolic Function in Mice with Propionic Acidemi

Background and AimsPropionic acidemia (PA) is a rare autosomal recessive disorder caused by mutations in PCCA or PCCB, which encode the two subunits of propionyl-CoA carboxylase (PCC). PCC deficiency causes toxic metabolite accumulation and multi-organ damage. Current management, including dietary restriction, pharmacological support, and liver transplantation, does not restore enzymatic activity. We developed a dual-gene adeno-associated virus (AAV) therapy that delivers both PCC subunits to treat both PA subtypes. MethodsWe generated a clinically relevant PCCA-R73W knock-in mouse model and administered AAV8 vectors encoding native human PCCA and PCCB under the control of a liver-specific thyroxine-binding globulin promoter (AAV8-TBG-hPCCA-P2A-hPCCB). Metabolite levels and organ safety were longitudinally assessed. ResultsDual-gene therapy produced dose-dependent reductions in plasma C3/C2 ratio, 3-hydroxypropionic acid, 2-methylcitric acid, and propionylglycine, and significantly outperformed single-gene (PCCA-only) therapy. Neonatal facial-vein injection achieved metabolic correction comparable to or better than adult treatment. The longitudinal follow-up revealed sustained efficacy over a 16-week period, with no signs of hepatotoxicity or adverse effects. ConclusionsSingle-dose, dual-gene AAV therapy achieves sustained metabolic correction and demonstrates long-term safety in a clinically relevant PA model, supporting its translational potential for both type I and type II propionic acidemia.

genetics↗

bioRxiv2026

Explainable Physicochemical Determinants of Protein Ligand Binding via Non-Covalent Interactions

Protein-ligand binding governs enzymatic catalysis, metabolic homeostasis, and therapeutic modulation. Thus, the accurate prediction of these interactions underpins modern rational drug discovery. However, existing deep-learning frameworks largely operate as black-box predictors that fail to resolve the individual residues mediating binding or decode the fundamental non-covalent forces that drive molecular recognition. To address these limitations, we present ExplainBind, an interaction-aware framework that predicts binding likelihood, localizes specific binding residues at single-amino-acid resolution rather than coarse pocket-level regions, and decodes the underlying non-covalent interaction patterns, all zero-shot, without requiring prior three-dimensional structural inputs. To support residue- and interaction-level training and evaluation, we construct InteractBind, a protein-ligand benchmark with residue-atom interaction maps. Simultaneously, benchmarking experiments demonstrate that ExplainBind consistently outperforms state-of-the-art baselines across diverse protein and ligand spaces, maintaining high precision when generalized to entirely novel sequences and chemical scaffolds. When applied to two unseen therapeutic targets, ExplainBind successfully ranks potent angiotensin-converting enzyme (ACE) inhibitors and clarifies differences in their potency via affinity-stratified interaction landscapes. Furthermore, we demonstrate the prospective utility of ExplainBind by discovering novel inhibitors and activators of L-2-hydroxyglutarate dehydrogenase (L2HGDH) through wet-lab validation, with mechanistically distinct interaction profiles providing a clear molecular rationale for their divergent functional outcomes. Collectively, these results establish ExplainBind as a powerful, generalizable tool for mechanistically informed, interpretable drug discovery.

molecular biology↗

bioRxiv2026

Environmental perturbation increases gene expression variability and unmasks genetic regulation for transcriptional robustness

Environmental perturbation reshapes phenotypes not only by shifting trait means but also by modulating phenotypic variability. Whether environmentally induced changes in variability -environmental robustness- are genetically regulated remains unclear. To address this question, we collected nearly 2,000 matched genomes and transcriptomes from an outbred population of Drosophila melanogaster before and after exposure to a high-sugar diet, and quantified how dietary stress remodels expression variability and its genetic architecture. We find that environmental perturbation induces a transcriptome-wide increase in expression variability, with the notable exception of key developmental pathways. At the same time, stress unmasks pervasive genetic regulation for expression variability (veQTL). These loci are mostly environment-dependent, show distinct functional and evolutionary constraints from mean-regulating loci, and appeared detrimental when they confer to much robustness to dietary perturbation. Together, our findings establish gene expression variability as a central dimension of the organismal response to environmental changes, and uncover its genetic basis as a distinct, evolutionary constrained layer of phenotypic regulation beyond mean effects.

evolutionary biology↗

bioRxiv2026

Postnatal conversion of methylcytosine to hydroxymethylcytosine reconfigures the human neuronal epigenome

Healthy brain development requires a coordinated process of postnatal cellular maturation throughout the first two decades of life that transforms neuronal morphology, connectivity, physiology, and gene expression. The maturation and stable maintenance of neuron identity is driven, in part, by large-scale reconfiguration of the neuronal DNA methylome. Neurons have uniquely high levels of 5-hydroxy-methyl-cytosine (hmC) compared to other cell types, yet the relative contributions of 5hmC and 5-methyl-cytosine (mC) remain unknown because most experimental assays do not distinguish these marks. We measured mC and hmC using bisulfite- and oxidative-bisulfite sequencing in excitatory and inhibitory neurons, along with mRNA and histone modifications, from the prefrontal cortex of 103 human donors, ranging from 38 days to 77 years of age. Up to half of all CG dinucleotides convert from mC to hmC in a gradual process extending throughout the first decade of life, dramatically reshaping the neuronal methylome. Asymmetric enrichment of hmC on the sense strand of actively transcribed genes increases in a linear, clock-like fashion throughout the lifespan, indicating a mechanistic link between transcription and hmC. We found that sex differences in X-linked DNA methylation in the human brain are primarily driven by hmCG rather than mCG, suggesting an important role for hmC in X-chromosome inactivation (XCI) and escape gene expression. We found key changes in 5hmC at dynamic cis-regulatory elements marked by changing cell type-specific levels of active and repressive histone modifications. Collectively, our findings reveal the dynamic trajectory of hmC in human neurons across the lifespan and highlight the association of DNA hydroxymethylation with transcription, chromatin state, and sex-specific gene regulation.

neuroscience↗

bioRxiv2026

ProtFlow: Flow Matching-based Protein Sequence Design with Comprehensive Protein Semantic Distribution Learning and High-quality Generation

Designing protein sequences with desired properties is a fundamental task in protein engineering. Recent advances in deep generative models have greatly accelerated this design process. However, most existing models face the issue of distribution centralization and focus on local compositional statistics of natural sequences instead of the global semantic organization of protein space, which confines their generation to specific regions of the distribution. These problems are amplified for functional proteins, whose sequence patterns strongly correlate with semantic representations and exhibit a long-tailed functional distribution, causing existing models to miss semantic regions associated with rare but essential functions. Here, we propose ProtFlow, a generative model designed for comprehensive semantic distribution learning of protein sequences, enabling high-quality sequence generation. ProtFlow employs a rectified flow matching algorithm to efficiently capture the underlying semantic distribution of the protein design manifold, and introduces a reflow technique enabling one-step sequence generation. We construct a semantic integration network to reorganize the representation space of large protein language models, facilitating stable and compact incorporation of global protein semantics. We pretrain ProtFlow on 2.6M peptide sequences and fine-tune it on antimicrobial peptides (AMPs), a representative class of therapeutic proteins exhibiting unevenly distributed activities across pathogen targets. Experiments show that ProtFlow outperforms state-of-the-art methods in generating high-quality peptides, and AMPs with desirable activity profiles across a range of pathogens, particularly against underrepresented bacterial species. These results demonstrate ProtFlows effectiveness in capturing the full training distribution and its potential as a general framework for computational protein design.

bioinformatics↗

bioRxiv2026

Proximity-Informed Graph Learning Defines Spatial Protein Communities for Tumor-Associated Proximity Antigen Discovery

The spatial organization of membrane proteins is an underexplored dimension of cell-surface biology. Spatial proximity shapes cellular function and therapeutic targetability, yet efforts to identify tumor-associated antigens (TAAs) have largely focused on expression alone. Here, we developed an industrialized surface-protein proximity mapping workflow to interrogate TAAs within their membrane microenvironments. In the process, we generated 248 proximity maps across 12 receptor tyrosine kinases (RTKs) and 28 tumor cell systems. This proximity atlas enabled two advances: first, MetaMap, a correlation-based analytical framework that defines spatial protein communities and infers non-targeted proximal proteins from reproducible proximity signatures; and second, tumor-associated proximity antigens (TAPAs), a conceptual class of co-targets defined by disease-specific spatial proximity to TAAs rather than expression alone. Applying these proximity-derived relationships within a multimodal prioritization framework, we identified and validated an EGFRxCDCP1 TAA-TAPA pair that enhanced tumor cell killing across therapeutic modalities. By integrating spatial organization with multimodal data, this work expands the design space for precision-guided therapeutic strategies.

cancer biology↗

bioRxiv2026

Characterization of the Gut Microbiota and Serum Metabolomics in Patients with Type 2 Diabetes Mellitus and Newly Diagnosed Acute Coronary Syndrome

Biomarkers for the early identification of acute coronary syndrome (ACS) risk remain inadequately investigated, particularly in patients with type 2 diabetes mellitus (T2DM), for whom timely clinical intervention may substantially enhance prognostic outcomes. The gut microbiota and serum metabolites may serve as pivotal mediators in the occurrence and progression of ACS among patients with T2DM, and whether these factors can be used for the precise discrimination of patients with T2DM complicated by ACS remains to be explored. Overall, 76 participants were enrolled (38 patients diagnosed with T2DM complicated by ACS and another 38 with T2DM without ACS). 16S rRNA sequencing combined with untargeted LC-MS metabolomics revealed a dysregulated gut-serum axis in patients with T2DM complicated by ACS: enrichment of proinflammatory microorganisms (Enterococcus spp.), reduction of butyrate producers (Butyricimonas spp.) and concomitant dysregulation of circulating lipid metabolites-upregulation of PC(16:0/9:0 (CHO)) and arachidonic acid alongside downregulation of cholesterol sulfate. By integrating multiomics data and applying various feature selection methods, we subsequently identified six key biomarkers. The final constructed combined model robustly distinguished patients with T2DM complicated by ACS from those with T2DM alone (AUC = 0.983), outperforming the other single omics models. Our study revealed that the gut microbiota and related serum metabolites serve as key mediators in the onset and progression of ACS among patients with T2DM, and demonstrated their potential value as noninvasive biomarkers for the early diagnosis of T2DM complicated by ACS. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSWe combined 16S rRNA sequencing with untargeted LC-MS metabolomics to dissect the gut-serum axis in patients with T2DM complicated by newly diagnosed ACS. We identified distinct gut microbial and serum metabolic signatures that distinguish ACS progression within the T2DM population. A multiomics classifier integrating clinical, microbial, and metabolic variables achieved robust diagnostic performance (AUC = 0.983) and outperformed single omics models. What Are the Clinical Implications?Integrated multiomics biomarkers facilitate the early identification of ACS progression in patients with T2DM, offering novel avenues for precision prevention, dynamic clinical surveillance, and individualized therapeutic strategies. Dysregulations of the gut microbiota and serum metabolome may play an important role in the development and progression of ACS in patients with T2DM.

microbiology↗

bioRxiv2026

Structural basis of canonical TIR-NLR activation in plant innate immunity

In plants, intracellular NLRs (nucleotide-binding leucine-rich repeat receptors) detect pathogen effector proteins, form oligomeric resistosomes, and activate ETI (effector-triggered immunity). NLRs contain N-terminal signaling, central NB-ARC (nucleotide-binding) and C-terminal LRR (leucine-rich repeat) domains. NLRs with N-terminal TIR (Toll/interleukin-1 receptor) domains (TNLs) hydrolyze NAD+ (nicotinamide adenine dinucleotide) to generate signaling molecules. We determined cryo-EM structures of flax M, a canonical non C-JID (C-terminal jellyroll/Ig-like domain) TNL, in both monomeric autoinhibited conformation, and tetrameric resistosome after activation by its rust fungal effector AvrM-A. AvrM-A homodimers dissociate into monomers to bind directly to the LRR and NB-ARC domains in the M resistosome. The resistosome structure includes a non-hydrolyzable NAD+ analogue, revealing the substrate NAD+ recognition mechanism by the TIR domains. M cleaves NAD+ and generates the same signaling compounds as the related flax TNL, L6. Our findings explain the mechanism of TNL signaling, and provide a basis for rational engineering of disease-resistant crops.

plant biology↗

bioRxiv2026

A Single-Cell and Spatial 3D Multi-omic Atlas of Developing Human Basal Ganglia and Inhibitory Neurons

The human basal ganglia (BG), subcortical nuclei fundamental to motor regulation and cognitive modulation, is constructed from neurons produced during gestation in the adjacent ganglionic eminences (GEs). GEs are transient structures in the ventral prenatal brain that also generate GABAergic inhibitory neurons which migrate to destinations in the BG, cortex and other destinations. This study aims to elucidate the epigenomic and 3D-genomic dynamics involved in the specification and maturation of GEs and GE-derived neurons, using single-nucleus methyl-3C sequencing (snm3C-seq), highly-multiplexed spatial transcriptomics, and chromatin+RNA single-molecule imaging. Our multi-modal data support a heterogeneous temporal progression across GE subregions, with the lateral GE (LGE) showing declining neurogenic activity in mid-gestation and caudal GE (CGE) exhibiting ongoing developmental progression through infancy. We identified regulatory programs that specify subtypes of BG principal cells, medium spiny neurons (MSN), via synchronized maturation of the 3D-epigenome. In infant brains, we found a transient short-range enriched (SE) chromatin conformation during the transition between oligodendrocyte progenitors (OPCs) and oligodendrocytes (ODCs), and a temporary shift toward Long-range Enriched (LE) chromatin conformation in projection neurons, extending previous works showing the differentiation of neurons and glial cells is associated with permanent SE and LE conformation, respectively. Lastly, we found that gene regulatory regions active in MSNs were enriched in loci associated with genetic risk for neuropsychiatric disease. Our study delineates the highly complex, lineage-specific 3D genomic dynamics in ventral progenitors and basal ganglia populations of the perinatal human brain. HighlightsO_LIJoint 3D genome and DNA methylome analysis of ventral brain progenitor zones C_LIO_LIHeterogeneous developmental progressions of the ganglionic eminences C_LIO_LIDistinct development dynamics and regulatory landscape of MSNs and interneurons C_LIO_LITransient remodeling of the 3D-genome in neurons and oligodendrocyte progenitors C_LI

genomics↗

bioRxiv2026

Novel Bacillus altitudinis endolysin (ArtE2) targeting both Gram-positive and Gram-negative bacteria

Antibiotic resistance is a major global health concern. The development of new antibiotics and therapeutics is crucial for the future. Bacteriophages produce endolysins that induce bacterial lysis, making them a promising treatment option. Deep sequencing was used to identify and isolate genes encoding endolysins from Bacillus spp.. We characterized the biological activities of these endolysins. Additionally, this study focused on the design of a new chimeric endolysin, ArtE2, which combines endolysin-2 with a polycationic peptide to address the bacterial activity in gram-negative pathogenic bacteria. Using bioinformatic tools, we conducted three-dimensional modeling of the endolysin ArtE2 and its interactions with peptidoglycan fragments. In this study, we tested the activity of chimeric endolysins against both Gram-positive and Gram-negative bacteria. All endolysins share the same catalytic domain and diverse cell-binding domains. Some endolysins are highly specific to certain bacterial species or strains, whereas others have broader specificities. Histidine interactions are an important part of the mechanism by which ArtE2 connects with bacterial peptidoglycan. Additionally, the engineered endolysin ArtE2 was highly effective at killing Staphylococcus aureus and Escherichia coli. In silico analysis showed that the fusion did not negatively affect endolysin folding or activity. These findings suggest that ArtE2 could be used to develop efficient antibacterial controls targeting pathogenic Gram-positive and Gram-negative bacteria.

microbiology↗

bioRxiv2026

Curcumin Promotes Myelin Repair after Spinal Cord Injury via Spatially Selective Regulation of CLASP2 Phosphorylation

Spinal cord injury (SCI) remains a devastating neurological disorder, where limited axonal regeneration and inefficient remyelination severely restrict recovery. Although curcumin has recognized neuroprotective properties, its mechanism in myelin repair is unclear. Here, we identify a phosphorylation-dependent cytoskeletal pathway as a key target of curcumin. In a mouse spinal cord transection model, curcumin treatment improved hindlimb motor function, reduced fibrotic scarring, and increased myelin basic protein (MBP) in the injured region. Phosphoproteomic profiling revealed cytoskeletal regulation as a major process affected by curcumin, with CLASP2 emerging as a critical target. Curcumin enhanced CLASP2 phosphorylation at Ser1025, a modification that strengthened Golgi association and increased EB1 distribution at the cell periphery, thereby promoting microtubule anchoring without altering global stability. This spatially selective regulation provides a novel mechanism by which curcumin fine-tunes cytoskeletal organization to support remyelination. Analysis of published single-cell sequencing data further showed CLASP2 enrichment in myelin-forming cells, underscoring its relevance. Unlike prior studies emphasizing anti-inflammatory or antioxidant effects, our findings reveal a defined molecular mechanism linking curcumin to cytoskeletal remodeling and myelin repair, highlighting its potential as a safe and accessible therapeutic candidate for SCI.

cell biology↗

bioRxiv2026

Biomimetic model for the identification of distinctive microenvironmental factors in glioblastoma radiosensitivity

Radiation therapy (RT) has long been included in the treatment of glioblastoma (GBM). However, radioresistance in cancer cells as well as toxicity in normal tissues are major obstacles to clinical efficacy. Improved understanding of the mechanisms of tumor microenvironment-induced radioresistance during and after radiation therapy can provide fundamental insights to improve clinical outcomes in GBM. Here, using three-dimensional engineered hydrogel models in vitro, we report the influence of extracellular matrix, hypoxia, and adjacent neuronal cells in radiotherapeutic sensitivity. We find that mechanical cues and oxygen availability regulate cellular response to radiation, with softer matrices allowing for more DNA damage. Hyaluronan fragments from the extracellular matrix also modulate rapid metabolic response to radiation, especially in hypoxic environments. We show that neuronal networks influence tumor metabolic activity and the inflammatory response. Overall, we demonstrate here that alternative radiation strategies, such as low dose rate radiation therapy and microenvironmental regulation, have the potential to be more effective in a specific subset of radiosensitive GBM tumors.

bioengineering↗

bioRxiv2026

A micropeptide component of the OGDH complex modulates ATP production in the TCA cycle

Since its elucidation, the tricarboxylic acid (TCA) cycle has been regarded as a fully defined enzymatic pathway. Here, we report the discovery of a previously unrecognized micropeptide component of this central metabolic system. Through analyzing ribosome profiling data from the mouse sORFs.org database, we discovered APPM (ATP production-promoting micropeptide), a 29-amino acid peptide encoded by a non-canonical small open reading frame within the mouse Ctsb gene. APPM localizes to the mitochondrial matrix and inner membrane, where it directly binds to the E1 subunit (OGDH) of the -ketoglutarate dehydrogenase complex (OGDHc). This interaction modulates OGDHc enzymatic activity, thereby regulating NADH and ATP production. We identified tyrosine-13 as the critical residue mediating the APPM-OGDH interaction and functional activation. Exogenous APPM administration increased ATP levels in vivo and, in a mouse model of heart failure, restored cardiac function, outperforming the reference drug trimetazidine. Collectively, our findings identify APPM as the first micropeptide regulator of the OGDH complex, expanding the known repertoire of the TCA cycle and presenting a potential therapeutic strategy for bioenergetic disorders.

molecular biology↗

bioRxiv2026

Benchmarking Peptide Spectral Library Search

Spectral library search (SLS) is a major approach for peptide identification from tandem mass spectrometry data, with performance depending substantially on the accuracy of the underlying Spectrum-Spectrum Matching (SSM) scoring functions. However, detailed comparative studies remain limited by the absence of comprehensive benchmark datasets. We propose new methods to build SSM scoring functions benchmarks and construct a benchmark dataset with (i) eight query spectrum sets with varying noise level for 476,063 precursors, and (ii) three spectral libraries with experimental, de-noised and predicted spectra for 3,065,819 precursors. We evaluate common spectrum preprocessing scenarios and SSM scoring functions, including SpectraST and EntropyScore. Results revealed this remains an important open problem, with the best recall for still assessed to be poor at just [~]70%, with SpectraST performing best for spectra with little-to-no noise, while JS-divergence showed superior noise resistance. Conversely, Cosine and Entropy score performed substantially worse, with Projected-Cosine performing especially poorly in most cases, with overall performance and relative ranking depending quite significantly on the minimum number of matching peaks. The benchmark dataset (MSV000095946/PXD056205) supports testing and development of new SSM scoring functions and the proposed benchmark construction approach provides an extensible foundation for additional types of SSM evaluation.

bioinformatics↗

bioRxiv2026

RIG-I RNA agonist activates immunostimulatory macrophages to enhance checkpoint immunotherapy for glioblastoma

Glioblastoma (GBM), the most frequent and aggressive primary brain tumor, remains refractory to all current therapies including surgical resection, chemotherapy, radiotherapy and immunotherapy. Immunosuppressive mechanisms in the GBM tumor microenvironment contribute to the lack of anti-tumor adaptive immunity. We found that a subset of tumor associated macrophages (TAMs) can be repolarized into an anti-tumor phenotype via agonist stimulation of the retinoic acid-inducible gene I (RIGI), a cytosolic double-stranded RNA pattern recognition receptor (PRR). In silico analysis of adult GBM datasets available in the public domain revealed that RIGI expression by a subset of activated TAMs positively correlated with patient survival. Studies in syngeneic mouse models of GBM showed that intratumoral delivery of stem-loop RNA 14 (SLR14), a RIG-I agonist, improved the efficacy of chemotherapy, radiotherapy and immunotherapy treatments, beyond the effects of other nuclei acid sensor agonists. We found that RIGI+ macrophages are the main drivers of SLR14 effect, combining activation of TAMs and priming of functional cytotoxic CD8+ T lymphocytes and NK cells. The anti-GBM effect of SLR14 is opening a significant new avenue for adult GBM treatment.

cancer biology↗