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bioRxiv2020

Crystallization and structure of ebselen bound to cysteine 141 of human inositol monophosphatase (IMPase)

Inositol monophosphatase (IMPase) is inhibited by lithium, the most efficacious treatment for bipolar disorder. Several therapies have been approved, or are going through clinical trials, aimed at the replacement of lithium in the treatment of bipolar disorder. One candidate small molecule is ebselen, a selenium-containing antioxidant, which has been demonstrated to produce lithium-like effects, both in a murine model and in clinical trials. Here we present the crystallization and first structure of human IMPase covalently complexed with ebselen, a 1.47[A] crystal structure (PDB entry 6ZK0). In the human-IMPase-complex ebselen, in a ring opened conformation, is covalently attached to Cys141, a residue located away from the active site. IMPase is a dimeric enzyme and, in the crystal structure, two adjacent dimers share four ebselen molecules, creating a tetramer with [~]222 symmetry. In the crystal structure presented in this publication, the active site in the tetramer is still accessible, suggesting that ebselen may function as an allosteric inhibitor, or may block the binding of partner proteins. SynopsisHere we present a 1.47[A] crystal structure of human inositol monophosphatase (IMPase) bound to the inhibitor ebselen (PDB entry 6ZK0). In the structure, ebselen forms a seleno-sulfide bond with cysteine 141 and ebselen-mediated contacts between two dimers give a [~]222 tetramer.

pharmacology and toxicology↗

bioRxiv2025

In Vitro Evidence to Support Amphotericin B and Flucytosine Combination Therapy for Talaromycosis

BackgroundTalaromyces marneffei causes talaromycosis, a life-threatening fungal disease with limited treatment options. The standard treatment of amphotericin B (AmB) induction followed by itraconazole consolidation still results in 15% to 30% mortality. This study aimed to investigate the potential of AmB and flucytosine (5FC) combination therapy to enhance antifungal activity. MethodsThe in vitro antifungal activity of AmB and 5FC alone and in combination against 60 T. marneffei clinical isolates was evaluated using a validated colorimetric antifungal susceptibility assay and the checkerboard method. The minimum inhibitory concentration (MIC) was defined as the lowest drug concentration inhibiting [≥] 95% fungal growth (MIC95) for both AmB and 5FC. The combination effect between AmB and 5FC against T. marneffei was determined using fractional inhibitory concentration index. Combination effects were further tested using a time-kill assay. ResultsThe MIC95 was 0.25 - 2 g/mL (geometric mean [GM] 0.68 g/mL) for AmB, and 0.03 - 0.5 g/mL (GM 0.28 g/mL) for 5FC. Full synergy was observed in 4 isolates (7%), and indifference was observed in the remaining 56 isolates (93%). The time-kill experiments revealed a concentration-dependent fungicidal activity of AmB, and concentration-independent fungistatic effect of 5FC. Synergy between AmB and 5FC was confirmed, showing greater than 2-log10 reduction in colony forming units when used in combination. No antagonism was observed. ConclusionsOur study demonstrated in vitro evidence of synergistic activity between AmB and 5FC against T. marneffei, providing the evidence to support in vivo and clinical trial testing of AmB and 5FC combination therapy, and dosing reduction strategies of 5FC. Lay SummaryThis study demonstrated in vitro synergy between amphotericin B and flucytosine against Talaromyces marneffei, providing the proof of concept to test this antifungal combination in a clinical trial of talaromycosis.

pharmacology and toxicology↗

bioRxiv2019

Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative syndrome of the human motor neuron system, for which no effective treatment exists. Variability in the rate of disease progression limits the efficacy of ALS clinical trials, suggesting that developing of better biomarkers for prognosis will facilitate therapeutic progress. Here, we applied unbiased next-generation sequencing to investigate the potential of plasma cell-free microRNAs as biomarkers of ALS prognosis, in 252 patients with detailed clinical-phenotyping. First, we identified miRNAs, whose plasma levels remain stable over the course of disease in a longitudinal cohort of 22 patients. Next, we demonstrated that high levels of miR-181, a miRNA enriched in neurons of the brain and spinal cord, predicts a >2 fold risk of death in discovery cohort (126 patients) and an independent replication cohort (additional 122 patients). miR-181 performance is comparable with the established neurofilament light chain (NfL) biomarker and when combined together, miR-181+NfL establish a novel RNA-protein biomarker pair with superior prediction capacity of ALS prognosis. Therefore, plasma miR-181 predicts ALS disease course, and a novel miRNA-protein biomarker approach, based on miR-181+NfL, boosts precision of patient stratification and may greatly enhance the power of clinical trials. One Sentence Summaryplasma miR-181 levels indicate high mortality risk in ALS patients.

neuroscience↗

bioRxiv2024

Independent derivations of the axis of arrhythmia for predicting drug-induced torsades de pointes

Torsades de pointes is a potentially lethal ventricular arrhythmia that may be caused by many classes of drugs. The likelihood of arrhythmia depends upon the particular combination of cardiac ion-channels that the drug targets. The risk for a given drug can be measured against the axis of arrhythmia, which is a conceptual line in the parameter space of ventricular cardiomyocyte electrophysiology. The axis describes the most potent combination of ion-channel blocks that is theoretically possible. It thus serves as a convenient yardstick for quantifying the pro-arrhythmic risk of novel drugs from their channel-blocking profiles. To date, the axis of arrhythmia has only been derived from biophysical computer simulations. Here, we derive the axis directly from the response profiles of selected ion-channels to known drugs (n=109). The new method provides an independent line of evidence for estimating the axis of arrhythmia. Using step-wise reduction, the two methods were found to converge to identical estimates of the axis in two ion-currents (ICaL and IKr). The resulting axis predicted the pro-arrhythmic risk of the test drugs with 89.9% to 91.7% accuracy, depending on the dose at which the drug was assessed. The axis of arrhythmia offers a practical method for predicting the pro-arrhythmic risk of novel drugs without the need for drug-specific computer simulations. It is the only metric of pro-arrhythmic risk that has been derived from both a biophysical model and a purely statistical model. It thus combines the benefits of biophysical interpretation and computational efficiency in assessing the torsadogenic risk of new drugs prior to clinical trials. Significance StatementMany classes of drugs can cause lethal cardiac arrhythmias by blocking ion-channels that are needed by heart cells for normal rhythm. International safety guidelines thus require all new drugs be tested in animal hearts or cell cultures prior to undertaking clinical trials in humans. Computer models offer an ethical alternative for drug testing that is gaining acceptance in the safety pharmacology community. However, the current corpus of models are usually too complex to apply outside of specialist computing laboratories. We recently proposed a new approach that eliminates the need for drug-specific computer simulations by using a large one-off computer simulation to identify the most pro-arrhythmic drug that is theoretically possible. Thereafter, that hypothetical drug can be used to assess the pro-arrhythmic risk of real drugs using only pen-and-paper calculations. In that study, the hypothetical drug was described by the axis of arrhythmia in the cardiac cell model. In the present study, we propose an alternative method for deriving the axis of arrhythmia directly from drug datasets. The two derivations are independent, yet they arrive at the same result. Together, they provide converging lines of evidence in support of this new approach to drug testing in safety pharmacology.

pharmacology and toxicology↗

bioRxiv2025

The anti-virus T cell response dominates the anti-cancer response in oncolytic virus therapy

Oncolytic viruses have strong potential as immunotherapies. By causing cancer cells to die and relieve antigens, these viruses can stimulate robust, systemic immune responses that may eliminate disseminated disease and prevent recurrence. Unfortunately, clinical trials using oncolytic viruses have not induced clearance of metastasis or protection from recurrence. Likewise, the combination of the only FDA-approved oncolytic virus-- Talimogene laherparapvec--with immune checkpoint blockade did not improve progression-free or overall survival. Because of these disappointing clinical trials, we sought to measure the ability of oncolytic viruses to induce cancer antigen presentation and the elicitation of cancer antigen-specific immune responses. Our data revealed that despite improved antigen presentation by dendritic cells, priming of cancer antigen-specific T cells was limited. However, viral antigen-specific T cells did develop and were in a phenotypic state to induce an effective response against virally infected cells. These preclinical results were mirrored in human peripheral blood samples. Overall, these data show that oncolytic virus treatment induces a response against the virus itself, but not cancer antigen, explaining the lack of response in metastatic disease. These interesting findings identify a critical mechanism that needs to be overcome to increase the efficacy of oncolytic virus therapy.

immunology↗

bioRxiv2025

Distinct tumor immune microenvironmental (TIME) landscapes drive divergent immunotherapy responses in glioblastoma

BackgroundImmunotherapies have improved outcomes in many cancers but show limited efficacy in glioblastoma (GBM). This study aimed to determine whether immunotherapy could be tailored to GBM by functional subtyping of vascular-immune landscapes. MethodsWe employed single-cell RNA sequencing, multiplex immunohistochemistry to characterize three distinct TIME subtypes in human and murine GBMs. We evaluated responses to combination of anti-angiogenic immunomodulating therapies (CD40 Ag, anti-PDL1, PI3K{gamma}/{delta} inhibition) in orthotopic syngeneic GBM mouse models. ResultsWe identified three distinct functional TIME subtypes with unique vascular-immune landscapes in human and murine GBM: TIME-low (immune-low/deserted, leaky vasculature), TIME-med (intermediate immune-infiltration, angiogenic), and TIME-high (heavily infiltrated with immunosuppressive myeloid cells and dysfunctional T cells). Representative mouse models of TIME-GBMs responded in subtype specific ways to anti-angiogenic immunomodulating therapies. TIME-low GBMs enhanced T-cell activity but relapsed due to emerging myeloid immunosuppression, concomitant with mesenchymal transition. TIME-med displayed the most immune-activated, yet angiogenic phenotype, and showed overall good responses to various anti-angiogenic immunomodulating therapies. TIME-high GBMs were mostly non-responsive but improved when the myeloid-cell PI3K{gamma} was targeted. However, CD40 agonist treatment, expected to enhance APC function, unexpectedly worsened survival by promoting angiogenesis and heightening immunosuppression, leading to dysfunctional T cells and reduced NK cell recruitment, and subsequent enhanced tumor propagation. ConclusionsOur study reveals three GBM TIME subtypes with distinct vascular-immune landscapes that require tailored therapies. TIME-med tumors are predicted to respond best to immunotherapies, TIME-low tumors show transient effects with anti-angiogenic immunomodulating therapies, while TIME-high tumors, due to their profound immunosuppression, can even have worse outcomes. Key pointsO_LIThree TIME subtypes were identified in GBM with distinct vascular-immune landscapes C_LIO_LITIME subtypes show divergent immunotherapy responses C_LIO_LITIME classification supports personalized treatment strategy for GBM immunotherapy C_LI Importance of the StudyThis study advances glioblastoma immunotherapy by providing the first comprehensive single-cell characterization of TIME subtypes, moving beyond bulk RNA-sequencing to reveal detailed functional states of immune cells. We establish clinically relevant murine models that recapitulate human TIME subtypes, enabling preclinical testing of TIME-targeted therapies. Our findings identify TIME-low GBM as immune deserted and TIME-med tumors as the most immunotherapy-responsive subtype that should be prioritized for clinical selection. We found that high immune infiltration correlates with non-responsiveness and even unexpected detrimental effects with CD40 agonist treatment in TIME-high tumors--critical information given ongoing clinical trials. Identifying distinct immunosuppressive mechanisms across TIME subtypes and differential treatment responses provides a framework for personalized immunotherapy selection. The immediate translational impact of this work highlights the importance of TIME classification for treatment stratification and the urgent need to consider TIME status in clinical trial design, potentially explaining variable patient responses in previous GBM immunotherapy trials.

cancer biology↗

bioRxiv2025

Levosimendan Ameliorates Adverse Pulmonary Vascular Remodeling in Group-2 Pulmonary Hypertension.

AimsPulmonary hypertension (PH) due to left heart disease (Group-2PH) is the most common form of PH and comprises two distinct subtypes: isolated post-capillary-PH (IpcPH) and combined post-and pre-capillary-PH (CpcPH). Despite its high prevalence and poor prognosis, no targeted therapies are currently approved, largely due to the absence of reliable preclinical models that recapitulate these human hemodynamic phenotypes. Levosimendan, a calcium sensitizer with inotropic and vasodilatory properties, has shown promise in early clinical trials for Group-2PH, but its mechanisms of action remain unclear. This study aimed to develop and validate experimental models of IpcPH and CpcPH and to assess the therapeutic effects of levosimendan on pulmonary vascular remodeling, inflammation, and cardiac function to support ongoing clinical translation. Methods and ResultsIn a multicentre preclinical study, we established two rodent models that faithfully replicate the human IpcPH and CpcPH hemodynamic profiles. CpcPH animals exhibited severe pulmonary vascular remodeling, inflammatory cell infiltration, and a distinct pro-proliferative transcriptomic signature, whereas IpcPH animals showed minimal pulmonary vascular involvement. Levosimendan (3 mg/kg/day, 3 weeks) improved biventricular function and pulmonary hemodynamics in both models. In CpcPH, levosimendan additionally reduced pulmonary vascular remodeling, attenuated inflammation, and partially reversed disease-associated transcriptomic reprogramming. Transcription factor enrichment analysis identified NF-{kappa}B as a key upstream regulator inhibited by treatment. In a translational extension, nine circulating inflammation-related-proteins differentiated CpcPH from IpcPH patients; among them, TNF, IL-12B, 4E-BP1, NT-3, NGF, FGF21, and FGF23 predicted poor survival. IL-18 and 4E-BP1 were elevated in CpcPH lungs and decreased following levosimendan treatment. ConclusionsInflammation is a major contributor to adverse pulmonary vascular remodeling in CpcPH. Levosimendan improves cardiac performance and mitigates pulmonary vascular inflammation and remodeling, supporting its potential as a dual-action therapeutic agent in Group-2PH. These findings validate novel preclinical models and provide mechanistic evidence reinforcing ongoing clinical evaluation of levosimendan in this condition. Translational perspectiveGroup-2 PH lacks targeted therapies, partly due to the absence of validated preclinical models. We validated models recapitulating human IpcPH and CpcPH and identified inflammation as a key driver of pulmonary vascular remodeling in CpcPH. Levosimendan improved biventricular function and reduced vascular remodeling and inflammation through NF-{kappa}B inhibition. Circulating IL-18 and 4E-BP1 reflected disease severity and treatment response. These findings establish robust translational models, reveal inflammatory mechanisms underlying CpcPH, and provide mechanistic evidence supporting ongoing clinical trials of levosimendan as a dual-action therapeutic strategy in Group-2 PH.

molecular biology↗

bioRxiv2024

Uncovering the Interleukin-12 Pharmacokinetic Desensitization Mechanism and Its Consequences with Mathematical Modeling

The cytokine interleukin-12 (IL-12) is a potential immunotherapy because of its ability to induce a Th1 immune response. However, success in the clinic has been limited due to a phenomenon called IL-12 desensitization - the trend where repeated exposure to IL-12 leads to reduced IL-12 concentrations (pharmacokinetics) and biological effects (pharmacodynamics). Here, we investigated IL-12 pharmacokinetic desensitization via a modeling approach to (i) validate proposed mechanisms in literature and (ii) develop a mathematical model capable of predicting IL-12 pharmacokinetic desensitization. Two potential causes of IL-12 pharmacokinetic desensitization were identified: increased clearance or reduced bioavailability of IL-12 following repeated doses. Increased IL-12 clearance was previously proposed to occur due to the upregulation of IL-12 receptor on T-cells that causes increased receptor-mediated clearance in the serum. However, our model with this mechanism, the accelerated-clearance model, failed to capture trends in clinical trial data. Alternatively, our novel reduced-bioavailability model assumed that upregulation of IL-12 receptor on T-cells in the lymphatic system leads to IL-12 sequestration, inhibiting the transport to the blood. This model accurately fits IL-12 pharmacokinetic data from three clinical trials, supporting its biological relevance. Using this model, we analyzed the model parameter space to illustrate that IL-12 desensitization occurs over a robust range of parameter values and to identify the conditions required for desensitization. We next simulated local, continuous IL-12 delivery and identified several methods to mitigate systemic IL-12 exposure. Ultimately, our results provide quantitative validation of our proposed mechanism and allow for accurate prediction of IL-12 pharmacokinetics over repeated doses.

bioengineering↗

bioRxiv2026

Functional and sensitivity profiling of theKITMutation Landscape in Melanoma

Melanoma in Asia presents a unique epidemiological profile, with a higher prevalence of acral and mucosal subtypes compared to Western populations. While KIT mutations are found in up to 15% of Asian melanoma cases, clinical outcomes with KIT inhibitors have been modest due to heterogeneous mutation profiles and a lack of specific patient selection criteria. This study characterizes the landscape of KIT mutations in melanoma using the GENIE database, identifying 86 recurrent hotspots, many of which are variants of unknown significance (VUS). We validated drug sensitivities for key mutations using in vitro and in vivo models. Our results indicate that while the L576P mutation is highly sensitive to multiple inhibitors, the N822K mutation shows resistance to imatinib but responds to sunitinib, nilotinib, and nintedanib. These findings highlight the necessity of genotype-guided therapeutic strategies and provide a rationale for future clinical trials combining broad-spectrum KIT inhibitors with immune checkpoint inhibitors. Translational SignificanceMelanoma subtypes prevalent in Asia, specifically acral and mucosal melanoma, frequently harbor KIT mutations but show poor response rates (23-26%) to the standard-of-care inhibitor, imatinib. This study challenges the current clinical practice of treating all KIT-mutated melanomas uniformly. We demonstrate that specific recurrent mutations, such as N822K, are intrinsically resistant to imatinib but highly sensitive to broad-spectrum inhibitors like sunitinib and nintedanib. By establishing a comprehensive "lookup table" of drug sensitivities for both common and previously uncharacterized KIT variants, this work provides the evidence base required to transition from a "one-size-fits-all" approach to a genotype-guided precision medicine strategy. Furthermore, validating these targets informs the design of next-generation clinical trials, particularly those combining optimal KIT inhibitors with immune checkpoint blockade to improve survival in currently underserved patient populations.

cancer biology↗

bioRxiv2020

Targeted DNA Damage Repair CRISPR/Cas9 Knockout Screen Identifies Novel Classification of Poly-ADP Ribose Polymerase Inhibitors Based on Key Base Excision Repair Proteins

DNA repair deficiencies have become an increasingly promising target for novel therapeutics within the realm of clinical oncology. Recently, several inhibitors of Poly(ADP-ribose) Polymerases (PARPs) have received approval for the treatment of cancers primarily with deleterious mutations in the homologous recombination (HR) proteins, BRCA1 and BRCA2. Despite numerous clinical trials which have been completed or are currently ongoing, the mechanism of action by which PARP inhibitors selectively kill tumor cells is poorly understood. While many believe "trapping" of PARP proteins to DNA at sites of damage is the most important determinant driving cytotoxicity by these drugs, clinically effective inhibitors exist with a diverse range of PARP-trapping qualities. These findings suggest that characterization of inhibitors as strong versus weak trappers does not properly capture the intra-class characteristics of these drugs. Here, we use a novel, targeted DNA damage response (DDR) CRISPR/Cas9 screening library to reveal heterogenous genetic dependencies on the base excision repair (BER) pathway for PARP inhibitors, which is not correlated with PARP trapping ability or catalytic inhibition of PARP. These findings demonstrate that inhibition of PARylation and induction of PARP trapping are not the only factors contributing to distinct biological activity for different PARP inhibitors, and they provide insight into the optimal choice of PARP inhibitors for use in the setting of specific DDR defects. AUTHOR SUMMARYTargeted cancer therapies rely on our general understanding of which genetic mutations are involved in both sensitivity and resistance to such anticancer agents. In this study, we describe the use of functional genetic screening to evaluate the role of various DNA repair proteins in response to inhibitors of PARP, a quintessential example of targeted therapy. While PARP inhibitors are best known for their utility in cancers with homologous recombination defects, we show that some inhibitors within this class may have additional functionality in cancers with deficient base excision repair. These findings highlight not only the importance of PARP inhibitor selection in the appropriate context, but also the mechanistic differences that exist within this class of inhibitors. It is our hope that our findings will inspire future work evaluating the use of specific PARP inhibitor selection in designing clinical trials to further expand the use of PARP inhibitors beyond tumors with homologous recombination deficiencies.

cancer biology↗

bioRxiv2020

Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks

Multiple Sclerosis (MS) is a neurodegenerative disorder characterized by a complex set of clinical assessments. We use an unsupervised machine learning model called a Conditional Restricted Boltzmann Machine (CRBM) to learn the relationships between covariates commonly used to characterize subjects and their disease progression in MS clinical trials. A CRBM is capable of generating digital twins, which are simulated subjects having the same baseline data as actual subjects. Digital twins allow for subject-level statistical analyses of disease progression. The CRBM is trained using data from 2395 subjects enrolled in the placebo arms of clinical trials across the three primary subtypes of MS. We discuss how CRBMs are trained and show that digital twins generated by the model are statistically indistinguishable from their actual subject counterparts along a number of measures.

bioinformatics↗

bioRxiv2026

Ex vivo human tumor slices more accurately predict patient responses to an oncolytic virus than in vivo mouse models

Immunotherapies, including oncolytic viruses (OV), are promising therapies that can enhance anti-tumor immune responses. However, preclinical success of immunotherapies in mouse models has not always translated to clinical benefit in cancer patients. This study compared preclinical efficacy and mechanism of action for ASP9801, a vaccinia virus expressing IL-7 and IL-12, using mouse models of colorectal cancer (CRC) in vivo and in human organotypic tumor slice models ex vivo. The murine surrogate for ASP9801 significantly reduced tumor volumes in treated and abscopal tumors in two different CRC models in vivo (MC38 and RO100). Treatment efficacy was accentuated when combined with anti-PD1 treatment, and single-cell RNA sequencing analysis revealed depletion of tumor cells and increased T cell infiltration and activation in both treated and abscopal tumors. However, human tissue analysis ex vivo (E-slices) using PDX models and patient samples showed that ASP9801 is not effective in CRC, consistent with clinical trial results. On the other hand, ASP9801 was highly effective in GBM, indicating indication-specific efficacy of ASP9801, and how E-slice assays can be used to identify treatment-sensitive indications. This study demonstrates the superiority of E-slices over mouse models for predicting clinical response and its utility in planning clinical trials.

cancer biology↗

bioRxiv2018

Accurate Prediction of Antibody Resistance in Clinical HIV-1 Isolates

Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection with several undergoing clinical trials. Due to high sequence diversity and mutation rate of HIV-1, viral isolates are often resistant to particular bNAbs. Resistant strains are commonly identified by time-consuming and expensive in vitro neutralization experiments. Here, we developed machine learning-based classifiers that accurately predict resistance of HIV-1 strains to 33 neutralizing antibodies. Notably, our classifiers achieved an overall prediction accuracy of 96% for 212 clinical isolates from patients enrolled in four different clinical trials. Moreover, use of the tree-based machine learning method gradient boosting machine enabled us to identify critical epitope features that distinguish between antibody resistance and sensitivity. The availability of an in silico antibody resistance predictor will facilitate informed decisions of antibody usage in clinical settings.

bioinformatics↗

bioRxiv2026

A Conversational Multi-Agent AI System for Integrated Multi-Omics Analysis and Biomedical Discovery

Single-cell and spatial omics offer unprecedented opportunities to decipher the mechanisms of disease, however, this process requires teams of experts, iterative trial-and-error and reasoning across modalities. Here we present LungChat (https://chat.lungmap.net), a conversational system for integrated multi-omics analysis and biomedical discovery, deployed as a hierarchical multi-agent architecture in which a supervisor decomposes natural-language questions into parallel, tool-grounded tasks spanning single-cell and spatial analyses, literature and clinical-trial synthesis, and drug repurposing. To predict new therapeutics, LungChat implements Direction-Aware Repurposing and Targeting (DART) to distinguish perturbations that reverse disease transcriptional programs from those that reinforce them, at the cell-type level, for safety prediction. Controlled architecture ablations showed that hierarchical orchestration improved grounded abstention and token efficiency and preserved strong performance on complex multi-step tasks. In pulmonary disease case studies, LungChat independently prioritized saracatinib for IPF through drug-connectivity screening, followed by DART-based cell-type analysis; the same compound has been evaluated in the STOP-IPF clinical trial (NCT04598919). The system also recovered fluticasone propionate, an established COPD therapy, through a single orchestrated analysis. This tissue-agnostic system provides a blueprint for verifiable agentic AI systems that support reproducible scientific discovery.

bioinformatics↗

bioRxiv2025

Decades-long elevation of interferon-alpha drives a Sjogren disease endotype: an interdisciplinary study

BACKGROUNDMechanistic heterogeneity is a major obstacle to the development of effective treatment for Sjogren disease (SjD) and there is a pressing need to stratify SjD according to precision medicine principles. Aberrant activation of the type I interferon (IFN) pathway represents a leading candidate pathway, but a causal role of elevated IFN- in driving a Sjogren disease endotype remains to be established. METHODSWe used ultrasensitive single molecule ELISA, and an oligoprotein interferon signature score (derived from broad capture proteomics), to study the role of IFN- in Sjogren disease. We analysed samples from the UK Primary Sjogren Syndrome Registry (UKPSSR, n=177) and UK Biobank Plasma Proteomics Project (n=47606 without Sjogren, n=257 with Sjogren, including 137 individuals sampled prior to diagnosis) to determine the timecourse and immune endotype associated with elevated IFN-. To address causality we created a new transgenic mouse model of IFN- overexpression to establish whether chronically elevated IFN- drives this immune endotype. FINDINGSOligoprotein interferon signatures can be detected at least 14 years prior to diagnosis of Sjogren disease in the UK Biobank-PPP. IFN- concentrations are elevated in 60% of Sjogren disease patients in the UKPSSR. Individuals with elevated IFN- display a distinct immunological endotype characterised by cytopenias, hypergammaglobulinaemia, multiple autoantibodies and autoimmunity against the Sjogren autoantigen TRIM21/Ro52. To address the key question of causal direction, we created a new mouse model of systemic chronic IFN- elevation, in which Ifn4 is overexpressed by conventional dendritic cells. This model recapitulates key features of the endotype and can be partially reversed by IFNAR1 blockade. INTERPRETATIONElevation of IFN- drives an immune endotype of Sjogren disease, originating over a decade prior to diagnosis. SjD patients with elevated IFN- concentrations are broadly clinically similar to those with normal IFN- concentrations, yet are immunologically distinct. This highlights the mechanistic heterogeneity of SjD and the need for immunological stratification along precision medicine principles, using high resolution biomarkers. As well as demonstrating causal direction, biological modelling shows that chronic IFN- elevation over the lifecourse has the potential to establish persistent immune dysregulation which responds only partially to interferon receptor blockade. These findings provide insights into SjD and other "interferonopathic" rheumatological disorders. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched MEDLINE for "Sjogrens Syndrome/Disease" and "interferon", including the terms "subsets", "sub-groups", "phenotypes", and "endotypes", filtering by "clinical trial", "stratification", and "immune-mediated inflammatory". We also included major review articles from noted experts. We identified reports of associations between IFN- and SjD, usually using indirect or imprecise measures of IFN-. None of these studies included prediagnostic samples and causal inference was limited. Added value of this studyThis study shows that IFN-, when measured directly using ultrasensitive single molecule ELISA approaches (uniquely optimised to determine healthy control concentrations), is elevated in a subset of people with SjD with a specific immunological endotype. Analysis of prediagnostic proteomics shows this elevation can be detected up to 14 years before diagnosis. We show that IFN- drives this endotype (as opposed to vice versa) by recapitulating key endotype features in a novel and unambiguous experimental mouse model of chronic IFN- elevation. We also show that the pathogenic consequences of IFN- elevation over long periods of time can only be partially reversed using IFNAR blockade. Implications of all the available evidenceThese data have important implications for future research, clinical practice, trial design, and therapeutic development. First, our findings provide clinical evidence, supported by unambiguous preclinical evidence, that decades-long elevated IFN can cause and drive a SjD endotype - and accurately defines the level of heterogeneity. Secondly, we provide biomarkers which may be of use in stratifying clinical trial design and also for early identification of at-risk individuals. Thirdly we provide biological proof of principle that longstanding and potentially undiagnosed elevation of IFN- can establish persistent immune dysregulation which may respond only partially to IFNAR blockade. Together these findings inform precision medicine approaches and future trial design.

immunology↗

bioRxiv2022

LAT1 enables T cell activation under inflammatory conditions: a new therapeutic target for rheumatoid arthritis

ObjectiveTo assess the L-type amino acid transporter-1 (LAT1) as a possible therapeutic target for rheumatoid arthritis (RA). MethodsSynovial LAT1 expression was monitored by immunohistochemistry and transcriptomic datasets. The contribution of LAT1 to gene expression and immune synapse formation was assessed by RNA-sequencing and total internal reflection fluorescent (TIRF) microscopy, respectively. Mouse models of RA were used to assess the impact of therapeutic targeting of LAT1. ResultsLAT1 was strongly expressed by CD4+ T cells in the synovial membrane of patients with active RA and the level of expression correlated with levels of ESR and CRP as well as DAS-28 scores. Deletion of LAT1 in murine CD4+ T cells inhibited the development of experimental arthritis and prevented the differentiation of CD4+ T cells expressing IFN-{gamma} and TNF-, without affecting regulatory T cells. LAT1 deficient CD4+ T cells demonstrated reduced transcription of genes associated with TCR/CD28 signalling, including Akt1, Akt2, Nfatc2, Nfkb1 and Nfkb2. Functional studies using TIRF microscopy revealed a significant impairment of immune synapse formation with reduced recruitment of CD3{zeta} and phospho-tyrosine signalling molecules in LAT1 deficient CD4+ T cells from the inflamed joints but not the draining lymph nodes of arthritic mice. Finally, it was shown that a small molecule LAT1 inhibitor, currently undergoing clinical trials in man, was highly effective in treating experimental arthritis in mice. ConclusionsIt was concluded that LAT1 plays a critical role in activation of pathogenic T cell subsets under inflammatory conditions and represents a promising new therapeutic target for RA. Key MessagesO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LILAT1 is an amino acid transporter that has previously been shown to play a role in T cell activation. C_LI What does this study add?O_LILAT1 is expressed by synovial T cells in human rheumatoid arthritis and the level of expression correlates with disease severity. C_LIO_LILAT1 expression by T cells is necessary for development of severe arthritis in animal models. C_LIO_LILAT1 is required for immune synapse formation and activation of pathogenic CD4+ T cell subsets in the inflamed joint, but not the lymph nodes. C_LIO_LIA small molecular weight LAT1 inhibitor, currently in clinical trials for cancer, is highly effective in animal models of rheumatoid arthritis. C_LI How might this impact on clinical practice of future developments?O_LIThe context-specific nature of LAT1 involvement in T cell activation positions it as an ideal therapeutic target to distinguish between pathogenic and protective T cell responses and this study provides the scientific rationale for clinical evaluation of LAT1 inhibitors in the treatment of rheumatoid arthritis. C_LI

immunology↗

bioRxiv2025

Gut microbiota of dogs with cancer receiving anti-EGFR/HER2 immunization reveals potential biomarkers of patient survival

BackgroundCanine cancer remains a leading cause of death in dogs, yet advances in veterinary oncology lag behind human medicine, particularly in immunotherapy. While immune checkpoint inhibitors are just entering clinical trials in dogs, other immunotherapies, such as anti-EGFR/HER2 vaccines, have shown promise. In parallel, mounting evidence in human oncology links gut microbiota composition to immunotherapy response. However, this relationship remains unexplored in canine patients. In this pilot study, we analyzed the gut microbiome of dogs enrolled in a clinical trial of anti-EGFR/HER2 immunotherapy to identify microbial biomarkers associated with survival outcomes. MethodsRectal swab samples of 51 dogs were collected at the time of first vaccine administration (baseline microbiota) and underwent 16S rRNA gene sequencing according to standard protocols. ResultsMicrobiome composition showed no significant differences by cancer type, sex, or breed, suggesting no inherent microbiome bias in the cohort. However, Cox regression analysis revealed 11 bacterial taxa whose abundances were significantly associated with overall survival (FDR < 0.1), independently of cancer type. Seven taxa were linked to increased mortality risk, while four were associated with prolonged survival. These associations remained significant after adjusting for confounders such as hemangiosarcoma diagnosis and advanced age. ConclusionsTo our knowledge, this is the first study to identify gut microbial signatures associated with survival in dogs undergoing cancer immunotherapy. These findings suggest that specific bacterial taxa may serve as prognostic biomarkers for immunotherapy outcomes in canine cancer, laying the groundwork for microbiota-targeted strategies to improve therapeutic efficacy in veterinary oncology.

cancer biology↗

bioRxiv2020

Evaluation of 19 antiviral drugs against SARS-CoV-2 Infection

The global pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or 2019-nCoV) has prompted multiple clinical trials to jumpstart search for anti-SARS-CoV-2 therapies from existing drugs, including those with reported in vitro efficacies as well as those ones that are not known to inhibit SARS-CoV-2, such as ritonavir/lopinavir and favilavir. Here we report that after screening 19 antiviral drugs that are either in clinical trials or with proposed activity against SARS-CoV-2, remdesivir was the most effective. Chloroquine only effectively protected virus-induced cytopathic effect at around 30 {micro}M with a therapeutic index of 1.5. Our findings also suggest that velpatasvir, ledipasvir, ritonavir, litonavir, lopinavir, favilavir, sofosbuvir, danoprevir, and pocapavir do not have direct antiviral effect.

microbiology↗