Biology subjects

Dai, Y.

Publications and source records attributed to Dai, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

A sterol-binding pocket in iRhom1 underlies paralog-specific regulation of the sheddase ADAM17

ADAM17, the major sheddase in mammalian cells, releases membrane-tethered EGFR ligands and inflammatory cytokines, and is a central regulator of cell signalling. The rhomboid pseudoproteases, iRhom1 and iRhom2, function as essential cofactors of ADAM17, controlling its maturation and activation. In contrast to the well-characterized iRhom2, the mechanism and regulation of its ubiquitously expressed paralog iRhom1 remain undefined. Here, we present a 2.5 [A] cryo-EM structure of the full-length human iRhom1/ADAM17 complex, revealing a previously unrecognized sterol-binding pocket located between TMD2 and TMD5. Structure-guided mutagenesis and pharmacological perturbation of sterol binding demonstrate that sterol binding is required to stabilize the iRhom1/ADAM17 complex and sustain its shedding activity. Strikingly, this regulation is paralog-specific: iRhom2 precludes sterol binding and instead stabilizes ADAM17 through direct intramolecular interactions. Furthermore, two human iRhom1 variants associated with cardiac disease localize adjacent to the sterol-binding pocket and disrupt ADAM17 maturation and activity. Together, these findings uncover mechanistic divergence between iRhom paralogs and establish a sterol-binding pocket in iRhom1 as a critical determinant of ADAM17 stability, revealing a potential avenue for paralog-selective therapeutic targeting.

cell biology↗

bioRxiv2026

Integration of spatial single-cell proteomics and spatial metabolomics reveals tumor microenvironment predictive of immunotherapy response in mucosal melanoma

Mucosal melanoma (MuM) is a rare but aggressive malignancy with limited benefit from immune checkpoint inhibition and few predictive biomarkers. We integrated single-cell spatial proteomics (COMET) and spatial metabolomics (MALDI-IMS) to profile 97 tissue cores from 26 patients treated with PD-1/PD-L1 and/or CTLA-4 inhibitors. We profiled 695,444 cells and resolved 25 cell states across eight major cell types. Cellular neighborhood (CN) analysis revealed distinct tumor- and stromal-associated spatial architectures. Responders were enriched for tumor-associated CNs (invasive tumor and tumor boundary) with close spatial proximity among Ki67 tumor cells, CD163 macrophages, and CD11c dendritic cells (DCs), and increased proliferating/cytotoxic CD8+ T-cell subsets. Non-responders showed stromal CN dominance with reduced immune infiltration. Spatial metabolomics identified lower abundance of indole-derived metabolites and reduced indole/tryptophan pathway activity in responders within tumor and TME regions that tracked with DC/macrophage-enriched spatial contexts. This study advances MuM spatial biology and provides a framework for biomarker-driven immunotherapy strategies. Statement of significanceMucosal melanoma (MuM) responds poorly to immune checkpoint blockade, and predictive biomarkers are limited. Integrated spatial proteomics and metabolomics reveal response-associated tumor-immune neighborhood architecture, stromal contexts linked to immune exclusion, and altered indole/tryptophan metabolism in the microenvironment. These spatial features nominate biomarkers and therapeutic hypotheses to improve immunotherapy for MuM.

cancer biology↗

bioRxiv2026

Transcriptional regulators predicted to drive macrophage dysregulation during impaired wound healing in diabetic mice

Dysregulation of Mo/M{varphi} activity is known to contribute to impaired healing in diabetes; however, the mechanisms underlying this dysregulation are not well understood. In this study, we used a variety of bioinformatics approaches along with our time series scRNA-seq data on wound Mo/M{varphi} from non-diabetic and diabetic mice to identify transcriptional regulators (TRs) that drive Mo/M{varphi} state transitions during normal and impaired healing. First, we used the Lamian framework and our newly developed Pseudotime Graph Diffusion method to show that state transitions from early stage phenotypes to later stage reparative and antigen presenting phenotypes characteristic of normally healing wounds are impaired and that transitions to inflammatory, foam cell-like, and Lyve-1+ M{varphi} phenotypes are enhanced during impaired healing of diabetic mice. Using our BITFAM model, we identified a broad range of TRs predicted to be preferentially active in each cell state and using CellOracle, we performed in silico perturbation to identify groups of TRs predicted to drive cell state transitions along multiple trajectories (e.g. CEBPA, IRF8), whereas other TRs were predicted to drive cell state transition towards reparative phenotypes (e.g. NR1H3, NR3C1) or towards an antigen-presenting phenotype (e.g. IRF4, OGT). Selected findings were validated using existing experimental data, confirming the usefulness of this approach. In conclusion, we identified TRs that likely drive Mo/M{varphi} state transitions towards desirable and undesirable phenotypes for wound healing. These findings provide insight into novel targets for altering Mo/M{varphi} phenotypes to promote healing of diabetic wounds.

immunology↗

bioRxiv2026

Astrocytes mediate the pro-cognitive value of α7nAChRs and of α7nAChR-targeting therapeutics

The 7-nicotinic acetylcholine receptor (7nAChR) has driven extensive research over the past three decades for its pro-cognitive potential. It is the leading druggable target for the cognitive deficits associated with schizophrenia and has motivated major pharmaceutical and clinical efforts to ameliorate similar impairments in other neurological disorders, such as Alzheimers disease (AD). Yet, a systematic evaluation of the role played by 7nAChR in cognition, and its mechanistic underpinnings, is still lacking. Here we report that 7nAChRs on principal and inhibitory forebrain neurons are largely inconsequential to mouse behavior, including in domains that are most sensitive to schizophrenia-related cognitive impairments. By contrast, loss of 7nAChR from astrocytes produces profound behavioral alterations that are cognitive domain-specific, are time-of-day dependent, coincide with reduced levels of the N-methyl D-aspartate receptor (NMDAR) co-agonist D-serine, and are fully restored by D-serine supplementation. Further, an 7nAChR partial agonist previously evaluated in Phase III trials for cognitive enhancement in schizophrenia and AD fails to augment behavior in mice lacking astrocytic 7nAChRs. Together, these findings identify astrocytes and D-serine/NMDAR signaling as a central mechanism through which 7nAChR, a major drug target, promotes cognitive behavior.

neuroscience↗

bioRxiv2026

Cell state-specific metabolic networks govern ferroptosis versus apoptosis in small cell lung cancer

Cellular heterogeneity and plasticity are hallmarks of cancer that contribute to tumor growth and therapy resistance. Here we investigated metabolic heterogeneity in small cell lung cancer (SCLC), an aggressive neuroendocrine (NE) cancer type. Through integrated transcriptomic and metabolomic analyses, we identified a universal dependency on exogenous cysteine/cystine (Cys) across all NE/non-NE SCLC cell states. Notably, NE and non-NE cells with low levels of the ASCL1 transcription factor die from ferroptosis upon Cys depletion. In contrast, ASCL1-high cells die from apoptosis but are ferroptosis resistant. This resistance to ferroptosis is driven by the direct upregulation of the gene coding for the GCH1 enzyme by ASCL1, which results in higher levels of the BH4/BH2 antioxidants. Accordingly, combining cysteine depletion with BH4/BH2 synthesis inhibition effectively reduces tumor growth in patient-derived xenografts. This work elucidates distinct metabolic states in SCLC and suggests new approaches to induce cell death in this lethal form of cancer.

cancer biology↗

bioRxiv2026

UniST: A Unified Computational Framework for 3D Spatial Transcriptomics Reconstruction

Spatial transcriptomics (ST) enables the measurement of gene expression in its native spatial context, yet most ST datasets are acquired as two-dimensional (2D) sections. Consequently, the underlying three-dimensional (3D) organization of tissues is only partially observed, and 3D ST data generated from serial sections are typically sparse and heterogeneous, with substantial tissue loss and missing measurements. These limitations pose major analytical challenges for reconstructing coherent 3D tissue architecture, rather than issues of experimental scalability alone. Here, we present UniST, a unified generative artificial intelligence (AI) framework designed to computationally reconstruct dense and continuous 3D ST landscapes from sparse serial sections, without altering the underlying experimental ST technologies. UniST integrates three complementary modules: kernel point convolution with cross-attention layers for point cloud upsampling, optical flow-based interpolation for continuous slice reconstruction, and a graph autoencoder with implicit neural representations for gene expression imputation. Together, these components densify sparse slices, resolve discontinuities, and map spatial coordinates to high-dimensional transcriptomics. Across multiple ST platforms and tissue contexts, UniST accurately restored structural continuity and biologically meaningful expression patterns. In a mouse embryo dataset, UniST reconstructed a dense 3D heart architecture from sparsely sampled slices. In two 3D human cancer tissues, UniST recovered critical spatial features, including tumor-immune boundaries and tertiary lymphoid structures, that were fragmented in the original data. By providing a generalizable computational solution that complements existing ST acquisition protocols, UniST facilitates cost-efficient and scalable reconstruction of 3D ST landscapes, enabling more faithful investigation of tissue organization and disease biology.

bioinformatics↗

bioRxiv2026

Digital Twin Brain simulation and manipulation of a functional brain network underlying mental illness

Linking synaptic-level perturbations to distributed brain-network dynamics remains a central challenge for understanding and treating mental illness. Although recent whole-brain models can reproduce individual brain activity patterns, they largely function as descriptive simulators rather than mechanistic, intervention-capable systems. Here we present an intervention-capable digital twin of the human brain, integrating individual neuroanatomy and task-evoked dynamics within a neuronal-scale framework. Individualised digital twin brains recapitulate a participant-specific compact cortico-subcortical network phenotype that captures transdiagnostic psychopathology across population and clinical cohorts. In silico modulation of excitatory and inhibitory synaptic conductance produces bidirectional, heterogeneous network responses across individuals. Population-scale simulations stratify individuals and predict longitudinal symptom trajectories from DTB-derived response profiles. Independent pharmacological functional MRI data further validate the predicted baseline-dependent network responses in vivo. Together, these findings establish digital brain models as experimental platforms for mechanistic perturbation, behavioural prediction and stratification, providing a foundation for precision neuroscience and psychiatry.

neuroscience↗

bioRxiv2026

A Novel Monocyte-derived Antigen Presenting Cell-T regulatory Cell Axis Contributes to Skin Wound healing and is Impaired in Diabetic Mice

Despite a vast literature on the role of macrophages in wound healing, the role of dermal monocyte (Mo)-derived antigen presenting cells (APC) has received scant attention. Using scRNAseq and flow cytometry, we identify a population of APC that is prominent in wounds of non-diabetic mice but is reduced in wounds of diabetic mice. Using adoptive transfer experiments and Ccr2 knockout mice, we demonstrate that wound APC are derived primarily from Mo and that the diabetic wound environment inhibits differentiation of Mo into APC. We also show that Mo-specific Irf4 knockout mice exhibit reduced differentiation of Mo into APC, decreased levels of IL27 and numbers of activated Treg cells in wounds. and impaired wound healing. Importantly, adoptive transfer of bone marrow Mo that express Irf4 into wounds of Mo-specific Irf4 knockout mice rescued levels of wound APC and activated Treg, as well as wound healing. Local administration of recombinant IL27 into wounds of these mice also rescued levels of activated Treg in wounds, along with wound healing, Together, these findings identify a novel pathway in which IRF4 induces Mo differentiation into APC in wounds, which in turn produce IL27 that activates Treg to promote healing. This pathway is impaired in wounds of diabetic mice, which provides a novel target to improve diabetic wound healing.

immunology↗

bioRxiv2026

Estradiol modulates neuronal network hyperexcitability in select NDD risk genes

Sex hormone signaling during neurodevelopment may act as a modulator of risk for neurodevelopmental disorders (NDDs), including autism spectrum disorders (ASDs). By conducting a systematic and multi-modal evaluation of estradiol effects across loss-of-function deletions in 36 functionally diverse, large-effect ASD/NDD genes in human induced pluripotent stem cell-derived neurons and larval zebrafish, we uncover convergent and divergent gene-by-estradiol interactions at the transcriptomic, circuit, and behavioral levels. Whereas estradiol partially ameliorates dysregulated expression signatures across all ASD/NDD gene knockouts examined, it selectively and rapidly dampens network hyperexcitability phenotypes in only a subset of ASD/NDD gene knockouts. Two genes, ASH1L and SCN2A, are particularly responsive to estradiol treatment, with dramatic rescue of molecular and cellular effects in human knockout neurons, coupled with behavioral phenotypes in larval zebrafish mutants. The seven most estradiol responsive genes show enhanced protein-protein interaction network connectivity, strong co-expression in specific postnatal time periods, and enrichment in upper-layer mature excitatory neurons. Altogether, we describe distinct estradiol rescue in different modalities, elucidating shared transcriptomic effects as well as gene-specific cellular and behavioral rescue in the context of loss of function mutations of select ASD/NDD genes.

genomics↗

bioRxiv2026

Unwinding of RNA G-quadruplexes induces mouse and human totipotency

Totipotent stem cells (TotiSCs) have significant application prospects in regenerative medicine and assisted reproductive technologies. The mRNAs of totipotency-related genes are rich in G-quadruplex (G4) structures, while the G4 density of pluripotency-related genes mRNAs is relatively low, suggesting a potential functional link between RNA G4s and the totipotent state. Nevertheless, how G4s are involved in the establishment or maintenance of mouse and human totipotency remains poorly understood. Here, we demonstrate that FC3, a small-molecule RNA G4 unwinder, enables efficient induction and maintenance of mouse and human TotiSCs (mG4TotiSCs and hG4TotiSCs). These FC3-induced TotiSCs closely recapitulate the molecular features of 2-cell-stage blastomeres via transcriptomic and epigenomic profiling. Functionally, both mG4TotiSCs and hG4TotiSCs exhibit totipotent capacity: they differentiate into embryonic and extraembryonic lineages in vitro and in chimeric embryos; moreover, they autonomously self-organize into blastocyst-like structures without exogenous signalling. Mechanistically, we identify that Gata2 mRNA, a G4-containing transcript, is essential for FC3-mediated reprogramming. Genetic disruption of Gata2 would abolish totipotency induction. Collectively, RNA G4 unwinding is a new regulatory axis governing totipotency acquisition and maintenance, providing insight into the functional interplay between nucleic acid secondary structures and cell fate plasticity.

cell biology↗

bioRxiv2026

PathoResist AI: A One-Click Web Platform for Rapid Pathogen Resistance Analysis Based on the all_ratio Algorithm

This study introduces a one-stop analysis platform named "PathoResistAI" (https://www.resistpath.com/), which can be used to solve the technical bottlenecks of pathogenic microorganism detection and antimicrobial resistance analysis. The platform is based on nanopore sequencing and the innovative all-ratio algorithm, which integrates four-dimensional parameters (sequence similarity, abundance, matching number, and matching length), significantly improving the detection accuracy of low-abundance pathogens and drug-resistance genes. The platform adopts four layers of modular design (input layer, core engine, dual-channel output, and visualization layer). Users only need to upload data in FASTQ format, and they can obtain automated reports, including pathogen identification and drug-resistance gene prediction within 30 min. The verification results show that the platform can accurately identify bacteria (e.g., Staphylococcus aureus and Serratia marcescens), viruses (e.g., Ebola virus), and drug-resistance genes (e.g., SdeY), which are consistent with the published literature results. Limitations include only supporting long-read sequencing data, small sample size (fewer than 50 cases), and lack of real clinical sample verification. In general, this platform represents the application and exploration of nanopore sequencing in the field of rapid detection of pathogenic microorganisms, and provides a new tool for microbial pathogen or AMR detection research.

bioinformatics↗

bioRxiv2026

Elimination of intramuscular immunoglobulin accumulation alleviates Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a devastating neuromuscular disorder due to loss of dystrophin, a cytoskeletal protein critical for muscle integrity and functionality. Despite recent therapeutic advances, there remains a significant unmet need for more effective and accessible therapeutics. Here, we discovered an early accumulation of immunoglobulin G (IgG) in the sarcolemma, which exacerbates tissue inflammation and disease progression. The IgG accumulation primarily resulted from ectopic localization of Fc{gamma}R1, a high-affinity IgG Fc receptor, on dystrophin-deficient myofibers. In two independent murine models, eliminating IgG accumulation via B cell depletion provided sustained benefit to alleviate DMD progression. Our findings uncover a novel disease accelerator in DMD and demonstrate the potential to target this mechanism as therapeutics for broader population of patients with DMD.

immunology↗

bioRxiv2026

A high fermentable fiber Western diet reduces indole levels

Changes in gut microbiota composition due to diet impact health. Fiber-rich diets promote beneficial microbiota and reduce the risk of metabolic diseases, while low-fiber, calorie-dense diets are linked to dysbiosis and increased disease risk. This study examines the effects of a Western diet (WD) and explores dietary fiber supplements as potential modifiers of those effects. 10-week-old C57Bl/6J male mice were fed control (low-fat) or WD (high-fat, high-sucrose) containing 0% fermentable fiber (FF) or WD supplemented with 20% FF (fructooligosaccharides, FOS; guar gum, GG, or pectin, Pec). After 19 weeks, analysis of the cecal metagenome using whole-genome shotgun sequencing, metabolome by untargeted and targeted LC-MS/MS, and tissue RNA and protein expression by RT-PCR and immunoblotting was undertaken. WD-FF reduced metabolic derangements from WD while also improving GM diversity and altering cecal metabolites, particularly tryptophan metabolism. A profound increase in cecal indole levels (targeted metabolomics) was noted in WD vs WD-FF groups. As the primary indole-oxidizing enzyme, CYP2E1 generates indoxyl sulfate, which contributes to oxidative stress and a leaky gut. Mice on WD displayed higher expression of Cyp2e1 mRNA in the gut. In the liver, the levels of both CYP2E1 protein and mRNA were higher in the WD group compared to the WD-FOS group, with protein levels also higher than in the WD-Pec group and mRNA levels higher than in the WD-GG group. mRNA expression of markers of oxidative stress, inflammation, and leaky barrier was significantly higher in the liver and intestine of the WD vs the WD-FF groups. FFs reduced high plasma indoxyl sulfate levels (except in WD-GG), and boosted short-chain fatty acids and indole acetic acid. Our data suggest that WD disrupts GM tryptophan metabolism, possibly by altering the balance between indole-producing and utilizing gut bacteria. Dietary fiber supplementation exerts protective effects, in part, by mitigating this imbalance.

physiology↗

bioRxiv2026

Endothelial MRG15 Is a Mechanosensitive Suppressor of Atherosclerosis

Disturbed blood flow induces early endothelial inflammation in atherosclerosis, yet the precise mechanisms of endothelial sensing of disturbed flow remain incompletely understood. In this study, we integrated proteomic profiling of human endothelial cells (ECs) subjected to disturbed flow with coronary artery disease risk related genes from large-scale genome-wide association studies (GWAS). We identified mortality factor 4-like protein 1 (MORF4L1, also called MRG15) as a critical modulator in the pathogenesis of atherosclerosis induced by disturbed flow. We show that the expression of MRG15 is markedly reduced in ECs of human aortic atherosclerotic plaques, as well as in ECs exposed to disturbed flow in mouse carotid artery and in cultured human umbilical vein endothelial cells (HUVECs). Endothelial-specific deletion of Mrg15 significantly worsened, while its overexpression attenuated endothelial inflammation and atherosclerotic lesions in turbulent blood flow- or Western diet-induced mouse atherosclerosis model. Single-cell transcriptomics showed that Mrg15 deficiency increased endothelial inflammation and intercellular adhesion molecule 1 (Icam1) expression, and enhanced integrin-mediated adhesion pathways. Mechanistically, MRG15 facilitated the recruitment of enhancer of zeste homolog 2 (EZH2) to maintain repressive histone H3 lysine 27 trimethylation (H3K27me3) marks on the promoters of ICAM1 and integrin subunit alpha 5 (ITGA5). Disturbed blood flow rapidly led to an elevation of protein neddylation, which subsequently induced neddylation-dependent degradation of MRG15 within endothelial cells. This degradation of MRG15 alleviated the transcriptional repression of ICAM1 and ITGA5, thereby enhancing monocyte adhesion to ECs. These findings highlight endothelial MRG15 as a mechanosensitive suppressor of atherosclerosis induced by disturbed flow. Consequently, MRG15 emerges as a promising novel therapeutic target for atherosclerosis.

molecular biology↗

bioRxiv2026

RAGulate: Retrieval-Augmented Generation for Post-hoc Literature-Grounded Regulatory Assessment

MotivationPrioritization of transcription factor (TF)-target relationships predicted by computational models for experimental validation often requires biologists to manually inspect heterogeneous and context-dependent evidence scattered across the biomedical literature. Large Language Models (LLMs) offer a promising solution to streamline this task. However, their reliance on general-purpose knowledge may lead to hallucinations and inaccurate interpretations. ResultsWe present RAGulate, a retrieval-augmented generation (RAG) framework for literature-grounded assessment of transcriptional regulation. RAGulate leverages CollecTRI, an external regulatory knowledge base, and integrates alias-aware query expansion, sparse and dense retrieval, maximum-marginal-relevance re-ranking, and LLM-based classification of predictions within a modular pipeline. Using a balanced TF-target-context benchmark from the same resource, we evaluate retrieval, classification, and evidence faithfulness. While CollecTRI provides TF-target links with supporting PubMed Identifiers (PMIDs), RAGulate infers the context of each interaction from the retrieved literature. Results show that alias normalization markedly improves retrieval recall, while hybrid retrieval, which merges lexical and embedding-based candidates, achieves the highest evidence recovery across all cut-offs. Conditioning LLMs on retrieved documents consistently improves AUROC and AUPR for classifying whether a TF-target interaction is supported in the specified context compared with direct prompting. RAGulate reduces hallucinations and improves PMID-level citation correctness, producing explanations that faithfully reflect the supporting literature. RAGulate represents a knowledge-based AI tool that partners with biologists to accelerate the process of TF-target prioritization for experimental validation and foster hypothesis generation. Availability and implementationThe software and tutorials are available at github.com/YDaiLab/RAGulate.

bioinformatics↗

bioRxiv2026

Structure and mechanism of human sphingosine-1-phosphate transporter MFSD2B

Sphingosine-1-phosphate (S1P) is an essential signaling lipid that maintains vascular integrity and regulates immune cell trafficking. The major facilitator superfamily domain-containing protein 2B (MFSD2B) serves as the main S1P exporter in red blood cells and platelets; however, its structure and transport mechanism are unclear. Here, we report the 3.0 [A] cryo-EM structure of human MFSD2B bound to S1P. S1P is captured in a distinctive binding state, deeply buried within the C-domain, with its sphingoid tail accommodated by a hydrophobic pocket and its phosphate group coordinated by a cluster of polar residues within the transporters cavity. Mutagenesis and molecular dynamics simulations identify the TM2/TM11 lateral opening as the primary pathway for S1P translocation, with key charged residues acting as sequential anchors during transport. Furthermore, we demonstrate that MFSD2B functions as a uniporter, and that subtle rewiring of local charge networks can alter its coupling mechanism. Our work provides a molecular framework for understanding S1P transport mediated by MFSD2B in hematopoietic cells.

biochemistry↗

bioRxiv2026

GARD: Genomic Data based Drug Repurposing in Head and Neck Cancer with Large Language Model Validation

Background/ObjectivesHead and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surgery, radiation, and immunotherapy, have shown limited improvement in outcomes. Drug repurposing offers a cost-effective strategy to identify new therapeutic options by leveraging existing medications with known safety profiles. Within this study we developed the GARD pipeline (Genomic Alteration-based Repurposing for Drugs), designed to uncover repurposing candidates for HNC using genomic and network-based approaches. MethodsGARD integrates multi-omics data from The Cancer Genome Atlas (TCGA), including copy number variation (CNV) and somatic mutations (SOM). The cohort was stratified by human papillomavirus (HPV) status. Risk-associated genes were identified and then expanded via high-confidence protein-protein interaction (PPI) networks. Top candidate genes were filtered through comprehensive analysis of publicly available literature data in PubMed using LLM to validate the relationship between the identified genes and HNC. The validated top risk genes and their network-expanded neighbors were mapped against DrugBank, and through statistical significance testing, established significant drug-gene associations. ResultsSignificant genes associated with HNC, inferred by genomics alteration, were identified across HPV-positive and HPV-negative subgroups, such as PIK3CA, SOX2, TP53, EIF4G1, TLR7, CLDN1, PRKCI, and EPHA2. Further expansion through the PPI network identified other targetable genes such as EGFR, ERBB2, and the FGFRs. Literature based validation efforts ensured provided confidence in the gene-disease association. Drug-gene mapping revealed candidates spanning already in clinical trials for HNC (e.g. Afatinib, Cabozantinib, Dasatinib, Brigatinib, Lenvatinib, Capivasertib, Erdafitinib) and emerging or repurposing candidates (Amuvatinib, XL765 (Voxtalisib), Golotimod, Artenimol, Quercetin, and Acetylsalicylic Acid), offering opportunities for precision repurposing. ConclusionsThe GARD pipeline demonstrates a genomics-driven, network-informed framework for systematic drug repurposing in HNC. HPV stratification enhances precision, literature-based validation strengthens confidence, and integrated drug mapping enables refinement of existing therapies and discovery of novel candidates for personalized treatment strategies. Code AvailabilityThe full implementation of the GARD pipeline, including preprocessing scripts, statistical analysis modules, and visualization tools, is publicly available on GitHub at: https://github.com/pvtanike/Genomic-Landscape-Based-Drug-Repurposing.git Simple SummaryHead and neck cancer (HNC) is among the most prevalent and challenging cancers world-wide. Developing new drugs is expensive and time-consuming, so this study explored a faster, cost-effective approach utilizing existing medications with established safety profiles: drug repurposing. We developed the GARD pipeline (Genomic Alteration-based Repurposing for Drugs), which utilizes large-scale genomic data from The Cancer Genome Atlas (TCGA) to identify key genomics changes in HNC. These genes are expanded through protein-protein interaction networks to capture related pathways and then validated using evidence from thousands of PubMed articles extracted by large language model (LLM) tools. Finally, validated genes are matched with drugs using the DrugBank database. This approach uncovered both known cancer drugs and promising new candidates. These included targeted therapies such as Fostamatinib, Nintedanib, Brigatinib, Regorafenib, and Lenvatinib, as well as emerging compounds like Artenimol, Quercetin, and Acetylsalicylic Acid (Aspirin). Through a combination of genomic analysis, network expansion, and literature validation, the GARD pipeline offers a powerful way to accelerate personalized cancer treatments while reducing cost and development time.

bioinformatics↗

bioRxiv2025

Bivalent habenula modulation of human monoaminergic midbrain and cortical pathways

The habenula is implicated in signaling negative reward prediction errors (RPE), yet direct causal evidence demonstrating its influence on downstream human brain circuits is limited. Using ultra-high field (7T) fMRI and dynamic causal modelling across two negative RPE-inducing experimental tasks, we characterize habenula-directed connectivity with monoaminergic midbrain and cortical pathways in healthy adults. Negative feedback drove strong habenula inhibition of ventral tegmental area and dorsal raphe nucleus activity, while positive feedback had an excitatory effect. These core effects are replicated across reversal learning and perceptual decision uncertainty tasks, establishing a generalizable mechanism for behavioral adaptation. Task-specific modulatory effects emerged in pathways between the subcortical and cortical regions (ventral tegmental area[->]dorsal anterior cingulate cortex, dorsal raphe nucleus[->]medial prefrontal cortex, and dorsal anterior cingulate cortex[->]habenula), revealing context-dependent cortical elaboration of negative RPE-driven habenula signals. This provides the first evidence in humans for bivalent causal modulation of habenula function on monoaminergic midbrain and cortical pathways, demonstrating how the brain integrates negative and positive signals to guide adaptive behavior.

neuroscience↗