Biology subjects

Nagy, J.

Publications and source records attributed to Nagy, J..

4 recordsLinked to original sources

bioRxiv2026

CD99Targeted Irinotecan Containing Nanoparticles Show Twenty-Fold Greater Anti-Tumor Effect Than Free Irinotecan For Treatment of EwingSarcoma

PurposeTo assess the antitumor efficacy, pharmacokinetics, and safety of NV103, a CD99-targeted liposomal irinotecan nanoparticle, in a preclinical Ewing sarcoma model. Experimental DesignNV103 is a CD99-antibody targeted irinotecan containing nanoparticle, engineered to selectively deliver irinotecan to CD99 expressing tumor cells. In vitro studies measured binding, internalization, and cytotoxic IC50 values in several Ewing sarcoma cell lines. In vivo, mice bearing xenografts derived from treatment-naive and chemoresistant Ewing lines were treated. NV103 was compared with free irinotecan, untargeted nanoparticles, and OnivydeTM at multiple dosages. Plasma pharmacokinetics of irinotecan and SN-38, biodistribution of the nanoparticles, and toxicity (body weight, organ function, and hematology) were assessed. ResultsNV103 bound selectively to tumor cells (>80x over control), was rapidly internalized, and showed enhanced potency in vitro (IC50 {approx} 3-4 nM at 0.5-1 h). In vivo, biweekly dosing at 5 mg/kg resulted in full tumor regression sustained for 140 days, even after stopping treatment at day 70. Effective suppression and survival benefit were observed at doses as low as 1 mg/kg; the ED50 was estimated to be between 1-2.5 mg/kg versus 50mg/kg for free irinotecan. In a chemoresistant Ewing tumor cell line, NV103 induced similar tumor-free remission. Pharmacokinetics revealed prolonged and elevated plasma levels of irinotecan with NV103 versus free drug. No systemic toxicity was detected at doses of 10 mg/kg. Biodistribution showed tumor-preferential accumulation. ConclusionsNV103 displays potent and durable antitumor activity in Ewing sarcoma at low doses with no toxicity and favorable pharmacokinetics. These findings support further development for clinical translation. Translational RelevanceAlthough Irinotecan has shown activity against Ewing sarcoma, its clinical utility is limited by systemic toxicity and poor tumor selectivity. NV103, a CD99-targeted nanoparticle formulation of irinotecan delivers irinotecan selectively to Ewing sarcoma cells. CD99 is a surface antigen that is highly expressed in Ewing sarcoma cells but largely absent from irinotecan-sensitive organs like liver, kidney, and bone marrow. In preclinical xenograft models, NV103 induced complete and durable tumor regression at doses >10 fold lower than those of free irinotecan or untargeted nanoparticles, with no detectable systemic toxicity. These findings suggest that NV103 is a promising translational therapeutic agent that enhances the therapeutic index of irinotecan and other cytotoxic agents. This platform offers a broadly adaptable approach to tumor-specific drug delivery, which could significantly improve treatment outcomes and reduce long-term toxicity in children and young adults with Ewing sarcoma and other solid tumors.

cancer biology↗

bioRxiv2020

How to characterize a strain? The neglected influence of clonal heterogeneity on the phenotypes of industrial Saccharomyces

Populations of microbes are constantly evolving heterogeneity that selection acts upon, yet heterogeneity is non-trivial to assess methodologically. The practice of isolating single cell colonies for establishing, transferring, and using a strain results in single-cell bottlenecks with a generally neglected effect on the characteristics of the strain. We used six industrial yeasts to assess the level of heterogeneity in clonal populations, especially in terms of stress tolerance. First, we uncovered the existence of genome structure variants in available sequenced genomes of clonal lineages of thes strains. Subsequent phenotyping of strains and their newly isolated subclones showed that single-cell bottlenecks during isolation can considerably influence the observable phenotype. Next, we decoupled fitness distributions on the level of individual cells from clonal interference by plating single cell colonies. We used the obtained data on colony area for statistical modeling of the heterogeneity in phenotypes. One strain was further used to show how individual subclonal lineages are remarkably different not just in phenotype, but also in the level of heterogeneity. Thereby we call attention to the fact that choosing an initial clonal lineage from an industrial yeast strain may vastly influence downstream performances and observations on geno- and phenotype, and also on heterogeneity.

microbiology↗

bioRxiv2019

Prostate-Specific Antigen Dynamics Predict Individual Responses to Intermittent Androgen Deprivation

BackgroundIntermittent androgen deprivation therapy (IADT) is an attractive treatment approach for biochemically recurrent prostate cancer (PCa), whereby cycling treatment on and off can reduce cumulative dose, limit toxicities, and delay development of treatment resistance. To optimize treatment within the context of ongoing intratumoral evolution, underlying mechanisms of resistance and actionable biomarkers need to be identified.\n\nMethodsWe have developed a quantitative framework to simulate enrichment of prostate cancer stem cell (PCaSC) dynamics during treatment as a plausible mechanism of resistance evolution.\n\nResultsSimulated dynamics of PCaSC and non-stem cancer cells demonstrate that stem cell proliferation patterns correlate with longitudinal serum prostate-specific antigen (PSA) measurements in 70 PCa patients undergoing multiple cycles of IADT. By learning the dynamics from each treatment cycle, individual model simulations predict evolution of resistance in the subsequent IADT cycle with a sensitivity and specificity of 57% and 94%, respectively and an overall accuracy of 90%. Additionally, we evaluated the potential benefit of docetaxel for IADT in biochemically recurrent PCa. Model simulations based on response dynamics from the first IADT cycle identify patients who would or would not benefit from concurrent docetaxel in subsequent cycles.\n\nConclusionOur results demonstrate the feasibility and potential value of adaptive clinical trials guided by patient-specific mathematical models of intratumoral evolutionary dynamics continuously updated with each treatment cycle.\n\nTranslational RelevanceCompared to continuous androgen deprivation therapy, intermittent androgen deprivation (IADT) has been shown to reduce toxicity and delay time to progression in prostate cancer. While numerous mathematical models have been developed to study the response to both continuous and intermittent androgen deprivation, very few have identified actionable biomarkers of resistance and exploited them to predict how patients will or will not respond to subsequent treatment. Here, we identify prostate-specific antigen (PSA) dynamics as the first such biomarker. Mechanistic mathematical modeling of prostate cancer stem cell dynamics that dictate prostate-specific antigen serum levels predicts individual responses to IADT with 90% overall accuracy and can be used to develop patient-specific adaptive treatment protocols, and potentially identify patients that may benefit from concurrent chemotherapy. Model results demonstrate the feasibility and potential value of adaptive clinical trials guided by patient-specific mathematical models of intratumoral evolutionary dynamics continuously updated with each treatment cycle.

cancer biology↗

bioRxiv2017

An open resource for nonhuman primate imaging

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience.\n\nUnfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMate Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 13 independent data collections aggregated across 11 sites (total = 98 macaque monkeys). We also outline the unique pitfalls and challenges that should be considered in the analysis of the non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

neuroscience↗