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bioRxiv2016

Real-time predictions of reservoir size and rebound time during antiretroviral therapy interruption trials for HIV

Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients - between 40 and 150 - will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two \"Boston patients\", recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the residual reservoir that eventually caused rebound. Together, these tools will aid HIV researchers in the evaluating new potentially-curative strategies that target the latent reservoir.

Microbiology↗

bioRxiv2021

Caveolin-1 temporal modulation enhances trastuzumab and trastuzumab-drug conjugate efficacy in heterogeneous gastric cancer

Resistance mechanisms and heterogeneity in HER2-positive gastric cancers (GC) limit trastuzumab benefit in 32% of patients, and other targeted therapies have failed in clinical trials. Using genomic data from patient tissue, patient-derived xenografts (PDXs), partially humanized biological models, and HER2-targeted imaging we identified caveolin-1 (CAV1) as a complementary biomarker in GC selection for trastuzumab therapy. In retrospective analyses of samples from patients enrolled on trastuzumab trials, the CAV1-high profile was associated with low membrane HER2 density and reduced patient survival. We found a negative correlation between CAV1 tumoral protein levels - a major protein of cholesterol-rich membrane domains - and trastuzumab-drug conjugate TDM1 tumor uptake. Finally, CAV1 depletion using knockdown or pharmacologic approaches was shown to increase HER2-directed immunoPET uptake and TDM1 efficacy in GC with incomplete HER2 membranous reactivity. In support of these findings, background statin use in patients is associated with enhanced antibody efficacy. Together, this work provides mechanistic justification and clinical evidence that require prospective investigation of HER2-targeted therapies combined with statins to delay drug resistance in GC. SIGNIFICANCEThis study identifies how CAV1 protein expression and statin use relate to GC response in HER2-targeted imaging and therapeutic approaches. In addition, to support the synergy of CAV1 depletion with TDM1 observed in mouse models, we demonstrate that statin users had better clinical responses to antibody-based therapies in HER2+ GC.

cancer biology↗

bioRxiv2024

Hedgehog signaling controls cytotoxic T cell migration in the tumour microenvironment.

Cytotoxic T lymphocytes effectively eliminate cancer cells. Their abundance in the tumour microenvironment is one of the strongest pan-cancer predictors of clinical response. Here, we show that Hedgehog (Hh) signaling regulates T cell migration into tumours. Using conditional knockout mouse models of central Hh signaling components Ihh, Smo and Gli1 in CD8 T cells, we show that Smo deletion greatly impairs the anti-tumour response in vivo due to diminished CD8 T cell migration into the tumour microenvironment. The migration defect is mediated exclusively by Smo, both in in vivo cancer models and in vitro migration assays. This effect is independent of the canonical Hh pathway and relies on the GPCR function of Smo to regulate the migration of murine and human CD8 T cells via RhoA. Hh signaling is critical during embryonic development and adult stem cell homeostasis, but is also amplified in multiple cancer types. Hh inhibitors targeting SMO have been clinically-approved and shown efficacy in the treatment of Hh-driven basal cell carcinoma and medulloblastoma but have failed in clinical trials in other solid cancers with upregulated Hh signaling. We demonstrate that SMO inhibitors specifically decrease CD8 T cell migration into the tumour microenvironment, both in murine cancer models and resected BCCs from patients treated with the SMO inhibitor vismodegib, providing the first mechanistic explanation as to why Hh inhibitors have failed in solid cancers. Our data establishes a novel link between Hh inhibition in vivo and the anti-tumour immune response and reveals a fundamental mechanism controlling T cell migration. The work provides the basis for improved Hh targeting approaches in the clinic and new entry points into enhancing migration in T cell therapies.

immunology↗

bioRxiv2025

On-target mutations confer resistance to WRN helicase inhibitors in Microsatellite Unstable Cancer Cells.

Werner helicase inhibitors (WRNi) are in clinical development for microsatellite-unstable (MSI) tumors with defective DNA mismatch repair. Here, we investigate how cancer cell evolution shapes response to WRN inhibition and informs potential resistance mechanisms. Genome-wide CRISPR screens combined with WRN knockout did not identify bypass mechanisms, underscoring WRNs essential, non-redundant function in MSI cells. Pharmacogenomic screens identified modulators of WRNi sensitivity, including SMARCAL1, which links it to WRN-MSI synthetic lethality. Semi-saturation mutagenesis of WRN and prolonged drug treatment identified on-target WRN mutations driving acquired resistance to multiple WRNi in vitro and in vivo, which was mitigated by combination with standard chemotherapies. Some resistance mutations conferred broad cross-resistance, whereas others preserved sensitivity to alternative clinical-grade WRNi with distinct mechanism of action. Our findings could inform clinical trial design by suggesting the feasibility of real-time tracking of emerging resistance and enabling early therapeutic adaptations. SignificanceWe present the first exploration of how MSI cancer cells evolve under the selective pressure of WRN helicase inhibition, providing a framework for understanding adaptive responses to this newly identified synthetic-lethal dependency. This study identifies on-target WRN mutations as key drivers of resistance in MSI cancers, supporting the use of combination strategies with other standard-of-care treatments to prevent resistance. It highlights how mutation tracking can guide therapeutic switching to clinically available WRN inhibitors with distinct mechanisms of action, thereby refining clinical development and potentially improving biomarker-informed patient outcomes.

cancer biology↗

bioRxiv2026

Antibody Profiles in Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections

Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) is characterized by prepubertal abrupt onset of obsessive-compulsive disorder (OCD). The sine qua non is group A streptococcus (GAS) infection, which is hypothesized to elicit an IgG-class anti-GAS antibody response that cross-reacts with antigens in the basal ganglia. However, the association between GAS antibody (GAS-IgG) levels and PANDAS has been inconsistent, and qualitative differences in GAS-IgG profiles have not been carefully evaluated in well-phenotyped cohorts. Moreover, independent studies have yet to converge on anti-neural autoantibodies that are specific to PANDAS. Here, we used phage display immunoprecipitation sequencing (PhIP-Seq) to perform ultra-deep anti-pathogen antibody repertoire profiling of serum from definitive pediatric PANDAS patients (N = 34) collected as part of a prior double-blind, placebo-controlled clinical trial of intravenous immunoglobulin (IVIg). PANDAS cases were compared to pediatric controls without a history of neuropsychiatric illness (N = 31). To assess for objective evidence of neuroglial injury, serum neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) levels were compared to healthy pediatric controls. Within PANDAS, NfL and GFAP levels were compared between pre- and post-treatment sera. To evaluate for central autoantibodies, a subset of baseline cerebrospinal fluid (CSF) samples (N = 25) was profiled by full-length human protein microarray. Though GAS reactivity by PhIP-Seq was well correlated with clinical anti-DNaseB and anti-streptolysin O titers, there were no quantitative or qualitative differences in GAS-IgG profiles between PANDAS and controls. Furthermore, NfL and GFAP levels did not differ between cases and controls. Within PANDAS, changes in NfL or GFAP levels at six weeks did not differ between placebo and IVIg groups. However, CSF autoantibody profiling by protein microarray revealed infrequent but notable candidate autoantibodies. In one patient, we identified autoantibodies against Argonaute family proteins (AGO-IgG), a marker of autoimmune sensory neuropathy. Longitudinal measurement of AGO-IgG in sera revealed that titers were unchanged after placebo, but decreased after IVIg, coinciding with symptomatic improvement, including a decrease in that patients CY-BOCS score. Overall, these results do not support an etiologic role for GAS-IgG in PANDAS. However, some individuals diagnosed with PANDAS may harbor anti-neural autoantibodies.

immunology↗

bioRxiv2025

Enhanced yield and subtype identity of hPSC-derived midbrain dopamine neuron by modulation of WNT and FGF18 signaling

While clinical trials are ongoing using human pluripotent stem cell-derived midbrain dopamine (mDA) neuron precursor grafts in Parkinsons disease (PD), current protocols to derive mDA neurons remain suboptimal. In particular, the yield of TH+ mDA neurons after in vivo grafting and the expression of some mDA neuron and subtype-specific markers can be further improved. For example, characterization of mDA grafts by single cell transcriptomics has yielded only a small proportion of mDA neurons and a considerable fraction of contaminating cell populations. Here we present an optimized mDA neuron differentiation strategy that builds on our clinical grade ("Boost") protocol but includes the addition of FGF18 and IWP2 treatment ("Boost+") at the mDA neurogenesis stage. We demonstrate that Boost+ mDA neurons show higher expression of EN1, PITX3 and ALDH1A1. Improvements in both mDA neurons yield and transcriptional similarity to primary mDA neurons is observed both in vitro and in grafts. Furthermore, grafts are enriched in authentic A9 mDA neurons by single nucSeq. Functional studies in vitro demonstrate increased dopamine production and release and improved electrophysiological properties. In vivo analyses show increased percentages of TH+ mDA neurons resulting in efficient rescue of amphetamine induced rotation behavior in the 6-OHDA rat model and rescue of some motor deficits in non-drug induced assays, including the ladder rung assay that is not improved by Boost mDA neurons. The Boost+ conditions present an optimized protocol with advantages for disease modeling and mDA neuron grafting paradigms.

cell biology↗

bioRxiv2020

Do Support Vector Machines play a role in stratifying patient population based on cancer biomarkers?

Biomarkers are known to be the key driver behind targeted cancer therapies by either stratifying the patients into risk categories or identifying patient subgroups most likely to benefit. However, the ability of a biomarker to stratify patients relies heavily on the type of clinical endpoint data being collected. Of particular interest is the scenario when the biomarker involved is a continuous one where the challenge is often to identify cut-offs or thresholds that would stratify the population according to the level of clinical outcome or treatment benefit. On the other hand, there are well-established Machine Learning (ML) methods such as the Support Vector Machines (SVM) that classify data, both linear as well as non-linear, into subgroups in an optimal way. SVMs have proven to be immensely useful in data-centric engineering and recently researchers have also sought its applications in healthcare. Despite their wide applicability, SVMs are not yet in the mainstream of toolkits to be utilised in observational clinical studies or in clinical trials. This research investigates the very role of SVMs in stratifying the patient population based on a continuous biomarker across a variety of datasets. Based on the mathematical framework underlying SVMs, we formulate and fit algorithms in the context of biomarker stratified cancer datasets to evaluate their merits. The analysis reveals their superior performance for certain data-types when compared to other ML methods suggesting that SVMs may have the potential to provide a robust yet simplistic solution to stratify real cancer patients based on continuous biomarkers, and hence accelerate the identification of subgroups for improved clinical outcomes or guide targeted cancer therapies.

bioinformatics↗

bioRxiv2025

Comparative Molecular, Innate, and Adaptive Impacts of Chemically Diverse STING Agonists

Pharmacologic activation of the innate immune response is being actively being pursued for numerous clinical purposes including enhancement of vaccine potency and potentiation of anti-cancer immunotherapy. Pattern recognition receptors (PRRs) represent especially useful targets for these efforts as their engagement by agonists can trigger signaling pathways that associate with phenotypes desirable for specific immune outcomes. Stimulator of interferon genes (STING) is an ER-resident PRR reactive to cyclic dinucleotides such as those synthesized endogenously in response to cytosolic dsDNA. STING activation leads to transient generation of type I interferon (IFN-I) and proinflammatory responses that augment immunologically relevant effects including antiviral responses, antigen presentation, immune cell trafficking, and immunogenic cell death. In recent years engineered cyclic dinucleotides and small molecules have been discovered that induce STING and safely confer clinically useful outcomes in animal models such as adjuvanticity of anti-microbial vaccines and tumor clearance. Unfortunately, clinical trials examining the efficacy of STING agonists have thus far failed to satisfactorily recapitulate these positive outcomes and this has prevented their translational advancement. A likely relevant yet perplexingly under investigated aspect of pharmacologic STING activation is the diversity of molecular and immune responses that associate with chemical properties of the agonist. Based on this, a comparative survey of these was undertaken using unrelated STING-activating molecules to characterize the molecular, innate, cellular, and immune outcomes they elicit. This was done to inform and direct future studies aimed at designing and selecting agonists appropriate for desired clinical goals. This revealed demonstrable differences between the agonists in potency, transcriptomes, cytokine secretion profiles, immune cell trafficking, and antigen-directed humoral and cell mediated immune responses. As such, this work illustrates that phenotypes deriving from activation of a protein target can be linked to chemical properties of the engaging agonist and thus heightened scrutiny is necessary when selecting molecules to generate specific in vivo effects.

immunology↗

bioRxiv2025

Repurposing Romidepsin for Osteosarcoma: Screening FDA-Approved Oncology Drugs with Three-Dimensional Osteosarcoma Spheroids

Osteosarcoma is the most common primary malignant bone tumor and predominantly affects children, adolescents, and young adults. It is the third most common cause of cancer-related deaths among 9-24-year-olds. Despite aggressive chemotherapeutic and surgical therapies, the survival rate is only 25% for patients with detectable lung metastases at diagnosis and only 70% in patients that present without detectable lung metastases. The poor prognosis is due to growth of metastases irrespective of whether they are initially large enough to detect clinically. It is therefore necessary to develop new methods to target the growth of lung micrometastases. An NCI panel of FDA-approved oncology drugs was therefore screened using three highly metastatic human osteosarcoma cell lines. To more closely approximate in vivo micro-metastases, the screen used a 3D multicellular in vitro osteosarcoma spheroid (sarcosphere) model. Among 13 hits from the initial screen, we identified the histone deacetylase inhibitor (HDI) romidepsin as the most promising inhibitor in secondary screens based on sarcosphere viability. Romidepsin potency was evident with and without standard-of-care chemotherapeutics (MAP: Methotrexate, Adriamycin, Cisplatin) at drug concentrations that are clinically achievable and did not affect non-transformed cells. By those criteria, romidepsin also substantially outperformed the other three FDA-approved HDIs and eight HDIs in clinical trials. Importantly, sarcospheres derived from 30-50% of human and canine patient samples were also sensitive to romidepsin with ED50s 10- to 700-fold less than the Cmax in human patients. Based on these 3-D screening approaches, romidepsin is a promising drug to repurpose for osteosarcoma. Significance StatementOur unbiased sarcosphere-based drug screen identified romidepsin as a promising candidate to repurpose for canine and human patients with metastatic osteosarcoma. This screening strategy allowed us to identify romidepsin-sensitive and -resistant patients. Sarcosphere-based screening may therefore be useful to stratify patients most likely to respond clinically to romidepsin or other drugs.

cancer biology↗

bioRxiv2019

Analytical treatment interruption after short-term anti-retroviral therapy in a postnatally SHIV infected infant rhesus macaque model

To achieve long-term viral remission in HIV-infected children, novel strategies beyond early anti-retroviral therapy (ART) will be necessary. Identifying clinical predictors of time to viral rebound upon ART interruption will streamline the development of novel therapeutic strategies and accelerate their evaluation in clinical trials. However, identification of these biomarkers is logistically challenging in infants, due to sampling limitations and potential risks of treatment interruption. To facilitate identification of biomarkers predicting viral rebound, we have developed an infant rhesus macaque (RM) model of oral SHIV.CH505.375H.dCT challenge and analytical treatment interruption (ATI) after short-term ART. We used this model to characterize SHIV replication kinetics and virus-specific immune responses during short-term ART or post-ATI and demonstrated plasma viral rebound in 5 out of 6 (83%) infants. We observed a decline in humoral immune responses and partial dampening of systemic immune activation upon initiation of ART in these infants. Furthermore, we documented that infant and adult macaques have similar SHIV replication and rebound kinetics and equally potent virus-specific humoral immune responses. Finally, we validated our models by confirming a well-established correlate of time to viral rebound, namely pre-ART plasma viral load, as well as identified additional potential humoral immune correlates. Thus, this model of infant ART and viral rebound can be used and further optimized to define biomarkers of viral rebound following long-term ART as well as to pre-clinically assess novel therapies to achieve a pediatric HIV functional cure.\n\nIMPORTANCENovel interventions that do not rely on daily adherence to ART are needed to achieve sustained viral remission for perinatally infected children who currently rely on lifelong ART. Considering the risks and expense associated with ART-interruption trials, identification of biomarkers of viral rebound will prioritize promising therapeutic intervention strategies, including anti-HIV Env protein therapeutics. However, comprehensive studies to identify those biomarkers are logistically challenging in human infants, demanding the need for relevant non-human primate models of HIV rebound. In this study, we developed an infant RM model of oral Simian/Human Immunodeficiency virus infection expressing clade C HIV Env, and short-term ART followed by ATI, longitudinally characterizing immune responses to viral infection during ART and post-ATI. Additionally, we compared this infant RM model to an analogous adult RM rebound model and identified virologic and immunologic correlates of time to viral rebound post-ATI.

immunology↗

bioRxiv2020

Discovery of clinically approved drugs capable of inhibiting SARS-CoV-2 in vitro infection using a phenotypic screening strategy and network-analysis to predict their potential to treat covid-19

The disease caused by SARS-CoV2, covid-19, rapidly spreads worldwide, causing the greatest threat to global public health in the last 100 years. This scenario has become catastrophic as there are no approved vaccines to prevent the disease, and the main measures to contain the virus transmission are confinement and social distancing. One priority strategy is based on drug repurposing by pursuing antiviral chemotherapy that can control transmission and prevent complications associated with covid-19. With this aim, we performed a high content screening assay for the discovery of anti-SARS-CoV-2 compounds. From the 65 screened compounds, we have found four drugs capable to selectively inhibit SARS-CoV-2 in vitro infection: brequinar, abiraterone acetate, neomycin, and the extract of Hedera helix. Brequinar and abiraterone acetate had higher inhibition potency against SARS-CoV-2 than neomycin and Hedera helix extract, respectively. Drugs with reported antiviral activity and in clinical trials for covid-19, chloroquine, ivermectin, and nitazoxanide, were also included in the screening, and the last two were found to be non-selective. We used a data mining approach to build drug-host molecules-biological function-disease networks to show in a holistic way how each compound is interconnected with host node molecules and virus infection, replication, inflammatory response, and cell apoptosis. In summary, the present manuscript identified four drugs with active inhibition effect on SARS-CoV-2 in vitro infection, and by network analysis, we provided new insights and starting points for the clinical evaluation and repurposing process to treat SARS-CoV-2 infection. Summary sentenceDiscovery of drug repurposing candidates, inhibitors of SARS-CoV-2 infection in vitro, using a phenotypic screening strategy and network analysis.

microbiology↗

bioRxiv2025

Glucose-Fueled Histone Modifications Drive HIV-1 Latency Reversal at Hypoxia

The major barrier to curing HIV-1 infection is the persistence of a latent reservoir in CD4 T cells within tissues which readily fuel viral rebound upon antiretroviral therapy (ART) interruption. Clinical trials aimed at purging these viral reservoirs with latency reversal agents (LRAs) have been unsuccessful owing to our incomplete understanding of the molecular and physiological determinants that underlie latency reversal in these virus-harboring tissues. Here, using a combination of complementary pharmacological and metabolomic approaches, we uncover glucose as a conditionally essential nutrient for HIV-1 latency reversal at hypoxic conditions. By modelling physiological variations in both glucose and oxygen availability as found in vivo within tissues that may harbor the HIV reservoir, we show that hyperglycemic conditions potentiate HIV-1 latency reversal. Importantly, we found major classes of clinically relevant LRAs, PKC agonists (PKCags) and histone deacetylase inhibitors (HDACis) have disparate efficacies under glucose-limiting conditions. Mechanistically, we show that this differential glycolytic dependency is due to distinct capacities of LRAs to induce glycolytic flux during adaptation to hypoxia, a condition that increases glycolytic dependence. Furthermore, we show that PKCag-induced glycolysis drives histone lactylation, a post-translational modification (PTM) we found to be associated with HIV-1 latency reversal and promotes increased chromatin accessibility at the HIV promoter. Importantly, we identify KAT2A as a lactyl-transferase critical for histone lactylation induced upon latency reversal. Taken together, our findings uncover glucose and oxygen availability as critical metabolic determinants of HIV-1 latency reversal and underscore the importance of modeling physiologically relevant experimental conditions in vitro aimed at identifying therapeutic agents that effectively target the latent reservoir in vivo.

immunology↗

bioRxiv2025

A live tumor fragment platform to assess immunotherapy response in core needle biopsies while addressing challenges of tumor heterogeneity

BackgroundImmune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, providing durable and even curative responses. However, most patients do not respond and current biomarkers (eg, programmed death ligand (PD-L1), mismatch repair deficiency (dMMR)/high microsatellite instability (MSI) and tumor mutational burden) lack predictive accuracy. Ex vivo profiling of patient-derived tumor fragments shows promise as a predictive biomarker but relies on substantial surgical tissue to mitigate intra-specimen heterogeneity. Innovations are needed that address these challenges, particularly where limited tissue is available in core needle biopsies (CNBs). MethodsLive tumor fragments (LTFs) were generated from 59 human tumor resections and 31 CNBs from patients enrolled in observational clinical trials (ClinicalTrials.gov identifiers: NCT05478538, NCT05520099, NCT06349642) to assess cytokine induction following ICI treatment. LTFs were encapsulated in hydrogel and cultured ex vivo for up to 72 hours. A sequential treatment strategy that applies control and treatment within the same well was used with response to ICI or CD3/CD28 assessed using a multiplex secretome assay. Viability was assessed using established metabolic assays and dynamic optical coherence microscopy. ResultsLTFs maintained viability and retained T cells responsive to stimulation throughout ex vivo culture. Multiplex immunofluorescence and immunohistochemistry showed key components of the tumor microenvironment, including relative proportions of CD4+ and CD8+ immune cell populations, were preserved. Specimens positive for PD-L1 or dMMR/MSI-high were enriched for cytokine upregulation, including T-cell response cytokines IFN{gamma} and CXCL10, after PD-1 treatment. To demonstrate clinical applicability of the sequential treatment strategy, CNBs from patients with lung, gastrointestinal or kidney cancer were profiled and differential cytokine induction in response to ICI treatment was observed. ConclusionsThe novel ex vivo platform presented is capable of detecting T-cell response to ICI treatment by using a sequential treatment strategy. This approach addresses challenges associated with cross-well heterogeneity in tissue composition and requires half as much tissue as a cross-well comparison, mitigating tissue limitations typically associated with non-surgical biopsies. Importantly, the platform is compatible with established functional assays as well as non-destructive spatial imaging, enabling researchers to characterize response to ICI longitudinally. Ongoing trials will enable clinicians to assess platform performance in predicting response to immunotherapy.

cancer biology↗

bioRxiv2020

Decline of humoral responses against SARS-CoV-2 Spike in convalescent individuals

In the absence of effective vaccines and with limited therapeutic options, convalescent plasma is being collected across the globe for potential transfusion to COVID-19 patients. The therapy has been deemed safe and several clinical trials assessing its efficacy are ongoing. While it remains to be formally proven, the presence of neutralizing antibodies is thought to play a positive role in the efficacy of this treatment. Indeed, neutralizing titers of [≥]1:160 have been recommended in some convalescent plasma trials for inclusion. Here we performed repeated analyses at one-month interval on 31 convalescent individuals to evaluate how the humoral responses against the SARS-CoV-2 Spike, including neutralization, evolve over time. We observed that receptor-binding domain (RBD)-specific IgG slightly decreased between six and ten weeks after symptoms onset but RBD-specific IgM decreased much more abruptly. Similarly, we observed a significant decrease in the capacity of convalescent plasma to neutralize pseudoparticles bearing SARS-CoV-2 S wild-type or its D614G variant. If neutralization activity proves to be an important factor in the clinical efficacy of convalescent plasma transfer, our results suggest that plasma from convalescent donors should be recovered rapidly after symptoms resolution.

microbiology↗

bioRxiv2025

GLUT5 armouring enhances adoptive T cell therapy anti-tumour activity under glucose-limiting conditions

Cancer immunotherapy with engineered T cells has become a standard treatment for certain hematologic cancers. However, clinical trial outcomes for solid tumours are significantly lagging. A primary challenge in solid tumours is the lack of essential metabolites in the tumour microenvironment, such as glucose, due to poor vascularization and competition with tumour cells. To address this, we modified T cells to use fructose as an alternative energy source by introducing ectopic GLUT5 expression. We show that "GLUT5-armored" T cells, engineered with either chimeric antigen receptors (CARs) or an ectopic T cell receptor (TCR), achieve enhanced anti-tumour activity in low-glucose environments in both in vitro and in vivo models. This straightforward modification is compatible with current clinical approaches and may improve the efficacy of T cell therapies for solid tumours. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/633365v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@15e10e0org.highwire.dtl.DTLVardef@a5f029org.highwire.dtl.DTLVardef@3a32daorg.highwire.dtl.DTLVardef@e09ff9_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

A precision medicine approach for HCN1 Developmental and Epileptic Encephalopathy

Pathogenic variants in HCN1 causing cation leak result in a severe developmental and epileptic encephalopathy (DEE). Current treatment options for patients with HCN1-DEE are limited and are insufficient to fully address both the seizures and clinical comorbidities of this disorder. Org 34167 is a brain penetrant broad-spectrum HCN channel inhibitor that has completed phase I clinical trials. We used a range of assays at molecular, cellular, network and behavioural levels to explore the potential of Org 34167 as a precision medicine for HCN1-DEE. Org 34167 restored the voltage sensitivity of the DEE HCN1M305L mutated channel, significantly reducing cation leak. It also restored Ih-mediated sag, hyperpolarised the resting membrane potential and reduced firing of layer V neurons from the Hcn1M294L mouse model of HCN1-DEE, which was engineered based on the HCN1M305L pathogenic variant. Additionally, Org 34167 reduced neuronal epileptiform activity and restored retinal light sensitivity in these mice, suggesting it may improve both seizures and other clinical comorbidities. However, Org 34167-mediated tremors were noted at therapeutic doses. Org 34167 was also effective at reducing cation leak caused by five additional HCN1 pathogenic variants, suggesting broader utility. Overall, these data demonstrate that a small molecule HCN inhibitor can restore channel and consequent physiological functions, positioning it as a promising precision therapeutic approach for HCN1-DEE.

neuroscience↗

bioRxiv2019

A multimodal approach to identify clinically relevant parameters to monitor disease progression in a preclinical model of neuropediatric disease

While research has accelerated the development of new treatments for pediatric neurodegenerative disorders, the ability to demonstrate the long-term efficacy of these therapies has been hindered by the lack of convincing, noninvasive methods for tracking disease progression both in animal models and in human clinical trials. Here, we unveil a new translational platform for tracking disease progression in an animal model of a pediatric neurodegenerative disorder, CLN6-Batten disease. Instead of looking at a handful of parameters or a single \"needle in a haystack\", we embrace the idea that disease progression, in mice and patients alike, is a diverse phenomenon best characterized by a combination of relevant biomarkers. Thus, we employed a multi-modal quantitative approach where 144 parameters were longitudinally monitored to allow for individual variability. We use a range of noninvasive neuroimaging modalities and kinematic gait analysis, all methods that parallel those commonly used in the clinic, followed by a powerful statistical platform to identify key progressive anatomical and metabolic changes that correlate strongly with the progression of pathological and behavioral deficits. This innovative, highly sensitive platform can be used as a powerful tool for preclinical studies on neurodegenerative diseases, and provides proof-of-principle for use as a potentially translatable tool for clinicians in the future.\n\nOne Sentence SummaryPrincipal component analysis identifies a set of clinically relevant parameters able to measure progression of Batten disease in a mouse model.

pathology↗

bioRxiv2020

TMEM180 contributes to colorectal cancer proliferation through intracellular metabolic pathways

TMEM180, a novel colon cancer-specific membrane protein with a 12-transmembrane topology, is upregulated at low oxygen. Previously, we established a humanized monoclonal antibody against TMEM180 aimed at clinical trials. Prior to such trials, it is necessary to clarify the function of this molecule in cancer. To compare SW480 human colon cancer cells and their TMEM180-knockdown derivatives, we analyzed proliferation and oxygen consumption, and also performed phosphorylation proteomics, metabolomics, and next-generation sequencing. The results revealed that TMEM180 promoted the growth of colon cancer but had almost no effect on oxygen consumption or expression of phosphorylated proteins. By contrast, glycolysis differed dramatically between SW480 and TMEM180-knockdown cells. TMEM180 promotes nitric oxide synthesis, suggesting that it promotes glucose metabolism and glutamine metabolism, thereby contributing to cancer growth. Overall, the results of this study support the clinical development of an anti-TMEM180 antibody.

cancer biology↗