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bioRxiv2020

Antigenicity, stability, and reproducibility of Zika reporter virus particles for long-term applications

The development of vaccines against flaviviruses, including Zika virus (ZIKV) and dengue virus (DENV), continues to be a major challenge, hindered by the lack of efficient and reliable methods for screening neutralizing activity of sera or antibodies. To address this need, we previously developed a plasmid-based, replication-incompetent DENV reporter virus particle (RVP) production system as an efficient and safe alternative to the Plaque Reduction Neutralization Test (PRNT). As part of the response to the 2015-2016 ZIKV outbreak, we recently developed pseudo-infectious ZIKV RVPs by modifying our DENV RVP system. The use of ZIKV RVPs as critical reagents in human clinical trials requires their further validation using stability and reproducibility metrics for large-scale applications. In the current study, we validated ZIKV RVPs using infectivity, neutralization, and enhancement assays with monoclonal antibodies (MAbs) and human ZIKV-positive patient serum. ZIKV RVPs are antigenically identical to live virus based on binding ELISA and neutralization results and are nonreplicating based on the results of plaque formation assays. We demonstrate reproducible neutralization titer data (NT50 values) across different RVP production lots, volumes, time frames, and laboratories. We also show RVP stability across experimentally relevant time intervals and temperatures. Our results demonstrate that ZIKV RVPs provide a safe, rapid, and reproducible reagent for large-scale, long-term studies of neutralizing antibodies and sera, which can facilitate large-scale screening and epidemiological studies to help expedite ZIKV vaccine development. AUTHOR SUMMARYZIKV is a mosquito-borne virus that can cause severe birth defects and other disorders. Large outbreaks of ZIKV occurred in 2015 and 2016 and there are still no drugs or vaccines available to protect against ZIKV infection. Vaccine development has been hindered by the lack of safe and efficient methods to screen ZIKV neutralizing properties of patient sera or antibodies, especially in the context of large clinical trials. To address this unmet need, we developed and validated the use of ZIKV reporter virus particles (RVPs), a safe, high-throughput and quantitative alternative to using live virus for neutralization studies. We show that ZIKV RVPs are stable, show lot-to-lot consistency and provide reproducible neutralization data that is suitable for large-scale studies are needed for development of a ZIKV vaccine, epidemiologic surveillance, and high-throughput screening.

microbiology↗

bioRxiv2020

Antiviral treatment of SARS-CoV-2-infected hamsters reveals a weak effect of favipiravir and a complete lack of effect for hydroxychloroquine

SARS-CoV-2 rapidly spread around the globe after its emergence in Wuhan in December 2019. With no specific therapeutic and prophylactic options available, the virus was able to infect millions of people. To date, close to half a million patients succumbed to the viral disease, COVID-19. The high need for treatment options, together with the lack of small animal models of infection has led to clinical trials with repurposed drugs before any preclinical in vivo evidence attesting their efficacy was available. We used Syrian hamsters to establish a model to evaluate antiviral activity of small molecules in both an infection and a transmission setting. Upon intranasal infection, the animals developed high titers of SARS-CoV-2 in the lungs and pathology similar to that observed in mild COVID-19 patients. Treatment of SARS-CoV-2-infected hamsters with favipiravir or hydroxychloroquine (with and without azithromycin) resulted in respectively a mild or no reduction in viral RNA and infectious virus. Micro-CT scan analysis of the lungs showed no improvement compared to non-treated animals, which was confirmed by histopathology. In addition, both compounds did not prevent virus transmission through direct contact and thus failed as prophylactic treatments. By modelling the PK profile of hydroxychloroquine based on the trough plasma concentrations, we show that the total lung exposure to the drug was not the limiting factor. In conclusion, we here characterized a hamster infection and transmission model to be a robust model for studying in vivo efficacy of antiviral compounds. The information acquired using hydroxychloroquine and favipiravir in this model is of critical value to those designing (current and) future clinical trials. At this point, the data here presented on hydroxychloroquine either alone or combined with azithromycin (together with previously reported in vivo data in macaques and ferrets) provide no scientific basis for further use of the drug in humans.

microbiology↗

bioRxiv2025

In Silico Post-screening of Anti-polymerization Agents to Treat Sickle Cell Disease

Sickle cell disease (SCD) is a genetic disorder that affects approximately 100,000 individuals in the United States and millions globally. Although curative therapies, such as stem cell transplant and gene therapy, are available, their application is limited by high cost and donor availability. Conseuently, drug therapy remains the most feasible treatment option for the majority of patients with SCD. To date, only four drugs have been approved by the FDA, but none of these treatments comprehensively address all SCD-related symptoms or crises, suggesting the pressing need for developing new drugs. Several high-throughput screening campaigns have been performed for SCD drug discovery based on the in vitro sickling of red blood cells (RBCs) and they have identified several hits. However, it is challenging to replicate the organ-specific oxygen level and physiological deoxygenation time in these in vitro RBC sickling assays. Furthermore, these assays do not consider the pharmacokinetics (PK) and pharmacodynamics (PD) of the identified drugs, which are essential to determine whether the drugs can provide robust and sustained efficacy in treated patients with SCD. To address these technical gaps, we have developed a computational platform to perform post-screening analysis of potential anti-sickling agents. This platform sequentially combines PK/PD models with a kinetic model of RBC sickling, enabling efficient prediction of the dosage-dependent therapeutic efficacy of various anti-sickling agents based on patient-specific hematological factors and organ-specific oxygen levels. We first demonstrate the effectiveness of our integrated platform by showcasing the therapeutic efficacy of two FDA-approved drugs, Hydroxyurea (HU) and voxelotor. Next, we evaluate the therapeutic efficacy of two potential anti-sickling agents under clinical trial, namely Bitopertin and osivelotor. Our findings suggest that Bitopertin exhibits anti-sickling effects that are considerably less pronounced than those of HU and voxelotor. On the other hand, osivelotor can achieve similar anti-sickling effects as voxelotor with significantly lower doses due to its improved PK properties. Furthermore, we show the versatility of the proposed platform in predicting the anti-sickling effect of multi-agent therapies and evaluate the conse-quences of drug noncompliance. In particular, our analysis indicates that noncompliance with voxelotor may result in rapid increases in RBC sickling, whereas osivelotor is likely to mitigate noncompliance-induced adverse effects due to improved PK properties. We further quantify the relationship between drug dosage and the duration of noncompliance that leads to loss of thera-peutic efficacy for voxelotor and osivelotor, providing guidance for optimizing dosage strategies to reduce the risk associated with noncompliance. In summary, our in silico platform serves as a valuable tool for post-screening analysis of potential anti-sickling agents by considering their PK and anti-sickling efficacy under patient-specific hemoglobin level and organ-specific oxygen level, thereby gaining insights into their potential therapeutic efficacy alone or in combination before clinical trials.

bioengineering↗

bioRxiv2023

Antitumor activity of intraperitoneal paclitaxel in orthotopic patient-derived xenograft models of mucinous appendiceal adenocarcinoma

Appendiceal adenocarcinomas (AAs) are a rare and heterogeneous mix of tumors for which few preclinical models exist. The rarity of AA has made performing prospective clinical trials difficult, and in part because of this AA remains an orphan disease with no chemotherapeutic agents approved by the FDA for its treatment. AA has a unique biology in which it frequently forms diffuse peritoneal metastases, but almost never spreads via a hematogenous route and rarely spreads to lymphatics. Given its localization to the peritoneal space we hypothesized that intraperitoneal (IP) delivery of chemotherapy could be an effective treatment strategy. Here we tested the efficacy paclitaxel given by IP administration using three orthotopic PDX models of AA established in NSG mice. Weekly treatment of 25.0 mg/kg of IP paclitaxel dramatically reduced AA tumor growth in TM00351 (81.9% reduction vs. control), PMP-2 (98.3% reduction vs. control), and PMCA-3 (71.4% reduction vs. control) PDX models. Comparing the safety and efficacy of intravenous (IV) to IP administration in PMCA-3, neither 6.25 nor 12.5 mg/kg of IV paclitaxel significantly reduced tumor growth. These results suggest that IP administration of paclitaxel is favorable to IV administration. Given the established safety record of IP paclitaxel in gastric and ovarian cancers, and lack of effective chemotherapeutics for AA, these data showing the activity of IP paclitaxel in orthotopic PDX models of mucinous AA support the evaluation of IP paclitaxel in a prospective clinical trial.

cancer biology↗

bioRxiv2018

Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory

BACKGROUNDRecent clinical trials have shown that the adaptive drug therapy can be more efficient than a standard MTD-based policy in treatment of cancer patients. The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are administered based on the current state of tumor. But the adaptive treatment policies examined so far have been largely ad hoc. In this paper we propose a method for systematically optimizing the rules of adaptive policies based on an Evolutionary Game Theory model of cancer dynamics.\n\nMETHODSGiven a set of treatment objectives, we use the framework of dynamic programming to find the optimal treatment strategies. In particular, we optimize the total drug usage and time to recovery by solving a Hamilton-Jacobi-Bellman equation based on a mathematical model of tumor evolution.\n\nRESULTSWe compare adaptive/optimal treatment strategy with MTD-based treatment policy. We show that optimal treatment strategies can dramatically decrease the total amount of drugs prescribed as well as increase the fraction of initial tumour states from which the recovery is possible. We also examine the optimization tradeoffs between the total administered drugs and recovery time.\n\nCONCLUSIONSThe adaptive therapy combined with optimal control theory is a promising concept in the cancer treatment and should be integrated into clinical trial design.

cancer biology↗

bioRxiv2019

GuiltyTargets: Prioritization of Novel Therapeutic Targets with Deep Network Representation Learning

The majority of clinical trial failures are caused by low efficacy of investigated drugs, often due to a poor choice of target protein. Computational prioritization approaches aim to support target selection by ranking candidate targets in the context of a given disease. We propose a novel target prioritization approach, GuiltyTargets, which relies on deep network representation learning of a genome-wide protein-protein interaction network annotated with disease-specific differential gene expression and uses positive-unlabeled machine learning for candidate ranking. We evaluated our approach on six diseases of different types (cancer, metabolic, neurodegenerative) within a 10 times repeated 5-fold stratified cross-validation and achieved AUROC values between 0.92 - 0.94, significantly outperforming a previous approach, which relies on manually engineered topological features. Moreover, we showed that GuiltyTargets allows for target repositioning across related disease areas. Applying GuiltyTargets to Alzheimers disease resulted into a number of highly ranked candidates that are currently discussed as targets in the literature. Interestingly, one (COMT) is also the target of an approved drug (Tolcapone) for Parkinsons disease, highlighting the potential for target repositioning of our method.\n\nAvailabilityThe GuiltyTargets Python package is available on PyPI and all code used for analysis can be found under the MIT License at https://github.com/GuiltyTargets.\n\nAuthor summaryMany drug candidates fail in clinical trials due to low efficacy. One of the reasons is the choice of the wrong target protein, i.e. perturbation of the protein does not effectively modulate the disease phenotype on a molecular level. In consequence many patients do not demonstrate a clear response to the drug candidate. Traditionally, targets are selected based on evidence from the literature and follow-up experiments. However, this process is very labor intensive and often biased by subjective choices. Computational tools could help a more rational and unbiased choice of target proteins and thus increase the chance of drug discovery programs. In this work we propose a novel machine learning based method for target candidate ranking. The method (GuiltyTargets) captures properties of known targets to learn a ranking of candidates. GuiltyTargets compares favorably against existing machine learning based target prioritization methods and allowed us to propose novel targets for Alzheimers disease.

bioinformatics↗

bioRxiv2022

Cellular Heterogeneity of Pluripotent Stem Cell Derived Cardiomyocyte Grafts is Mechanistically Linked to Treatable Arrhythmias

BackgroundExciting pre-clinical data have confirmed that human pluripotent stem cell derived cardiomyocytes (PSC-CMs) can remuscularise the injured or diseased heart, with several clinical trials now in planning or recruitment stages worldwide. However, ventricular arrhythmias are a predictable complication following engraftment of intramyocardially injected PSC-CMs. Therefore, there is an urgent unmet need to gain mechanistic insights and treatment strategies to control or prevent these engraftment arrhythmias (EAs). MethodsWe used a porcine model of myocardial infarction and PSC-CM transplantation to investigate efficacy of pharmacologic and catheter based anti-arrhythmic strategies in mitigating EAs. Furthermore, cell doses were robustly phenotyped using single cell ribonucleic acid sequencing and high parameter flow cytometry to identify cellular characteristics predictive of arrhythmogenesis. ResultsCombination therapy with amiodarone and ivabradine significantly reduced EA rate and burden following PSC-CM transplantation. Catheter ablation was also a feasible and effective treatment strategy which could be considered in the case of pharmacologically refractory arrhythmias. In addition, we show that EAs are mechanistically linked to cellular heterogeneity in the input PSC-CM and resultant graft. Specifically, we identify atrial and pacemaker-like cardiomyocytes as culprit arrhythmogenic subpopulations. We further describe two unique surface marker signatures, SIRPA+/CD90-/CD200+ and SIRPA+/CD90-/CD200-, which identify arrhythmogenic and non-arrhythmogenic cardiomyocytes respectively. ConclusionOur data deepens mechanistic understanding of EAs and suggests that modifications to current PSC-CM production and/or selection protocols could ameliorate this problem. We further show that current clinical pharmacologic and interventional anti-arrhythmic strategies can control and potentially abolish these arrhythmias, an important safety consideration given several impending clinical trials.

cell biology↗

bioRxiv2025

Atypical Alpha Oscillatory EEG Dynamics in Children with Angelman Syndrome

ObjectivesBiomarkers of atypical brain development are crucial for advancing clinical trials and guiding therapeutic interventions in Angelman syndrome (AS). Electroencephalography (EEG) captures well-characterized developmental changes in peak alpha frequency (PAF) that reflect underlying neural circuit maturation and may provide a sensitive metric for mapping atypical neural trajectories in AS. MethodWe analyzed EEG recordings from 159 children with AS (ages 1-15 years) and 185 age-matched typically developing (TD) controls. PAF was quantified using a well-established curve-fitting method applied to 1/f-corrected power spectra. To validate robustness, we further evaluated PAF using an alternative prominence-based peak detection approach across varying detection thresholds. ResultsSignificant disruptions in PAF were evident in children with AS. While over 90% of EEGs from TD children exhibited a clear alpha peak, fewer than 50% of EEGs from children with AS showed a detectable PAF. Furthermore, when PAF was present, its frequency was significantly lower in AS children and did not show the typical age-related increases observed in TD children. Validation analyses confirmed consistently lower rates of PAF detection in AS across varying sensitivity thresholds, demonstrating the robustness of these results. ConclusionsPAF is a robust and developmentally sensitive marker of disrupted neural maturation in children with Angelman syndrome. As a quantifiable and sensitive measure of neural disruptions in AS, PAF has the potential to complement and enhance existing clinical trial outcome assessments by providing an objective index of underlying brain function. Future analyses will explore individual differences related to PAF in AS, to better understand mechanistic insights to guide targeted therapeutic strategies.

neuroscience↗

bioRxiv2021

BpOmpW Antigen Stimulates the Necessary Immune Correlates of Protection Against Melioidosis

SUMMMARYMelioidosis is a fatal disease caused by Burkholderia pseudomallei Gram-negative bacteria. It is the causative of 89,000 deaths per year in endemic areas of Southeast Asia and Northern Australia. Diabetes mellitus is the most risk factor, increasing 12-fold the susceptibility for severe disease. IFN-{gamma} responses from CD4 and CD8 T cells, but also from NK and NKT cells are necessary to eliminate the pathogen. Elucidating the immune correlates of protection of our previously described protective BpOmpW vaccine is an essential step of any vaccine before clinical trials. Thus, we immunized non-insulin resistant C57BL/6j mice and an insulin resistant C57BL/6j mouse model of Type 2 Diabetes (T2D) with BpOmpW using Sigma Adjuvant System (SAS) (treatment) or SAS only (control). Two weeks later bloods and spleens were collected and serological analysis & in vitro exposure of splenocytes to the antigen for 60 hours were performed in both controls and treatment groups to finally analyze the stained splenocytes by flow cytometry. BpOmpW induced strong antibody response, stimulated effector CD4+ and CD8+ T cells and CD4+ CD25+ Foxp3+regulatory T cells and produced higher IFN-{gamma} responses in CD4+, CD8+, NK and NKT cells relative to the control group in non-insulin resistant mice. T cell responses of insulin resistant mice to BpOmpW were comparable to those in non-insulin resistant mice. In addition, as a precursor to its evaluation in human studies, humanised HLA-DR and HLA-DQ transgenic mice elicited IFN-{gamma} recall responses in an ELISPoT-based study and PBMCs from donors that were in contact to BpOmpW for seven days experienced T cell proliferation. Finally, plasma from melioidosis survivors with diabetes recognized our BpOmpW vaccine antigen. Overall, these range of approaches used strongly indicate that BpOmpW elicits the required immune correlates of protection to combat melioidosis and bring the vaccine closer to clinical trials.

immunology↗

bioRxiv2021

The Delta variant of SARS-CoV-2 maintains high sensitivity to interferons in human lung cells

Interferons are a major part of the anti-viral innate defense system. Successful pathogens, including the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), need to overcome these defenses to establish an infection. Early induction of interferons (IFNs) protects against severe coronavirus disease 2019 (COVID-19). In line with this, SARS-CoV-2 is inhibited by IFNs in vitro, and IFN-based therapies against COVID-19 are investigated in clinical trials. However, SARS-CoV-2 continues to adapt to the human population resulting in the emergence of variants characterized by increased transmission fitness and/or decreased sensitivity to preventive or therapeutic measures. It has been suggested that the efficient spread of these so-called "Variants of Concern" (VOCs) may also involve reduced sensitivity to IFNs. Here, we examined whether the four current VOCs (Alpha, Beta, Gamma and Delta) differ in replication efficiency or IFN sensitivity from an early isolate of SARS-CoV-2. All viruses replicated in a human lung cell line and in iPSC-derived alveolar type II cells (iAT2). The Delta variant showed accelerated replication kinetics and higher infectious virus production compared to the early 2020 isolate. Replication of all SARS-CoV-2 VOCs was reduced in the presence of exogenous type I, II and III IFNs. On average, the Alpha variant was the least susceptible to IFNs and the Alpha, Beta and Gamma variants show increased resistance against type III IFN. Although the Delta variant has outcompeted all other variants in humans it remained as sensitive to IFNs as an early 2020 SARS-CoV-2 isolate. This suggests that increased replication fitness rather than IFN resistance may be a reason for its dominance. Our results may help to understand changes in innate immune susceptibility of VOCs, and inform clinical trials exploring IFN-based COVID-19 therapies.

microbiology↗

bioRxiv2020

Inhibition of CAMKK2 impairs autophagy and castration-resistant prostate cancer via suppression of AMPK-ULK1 signaling

Previous work has suggested androgen receptor (AR) signaling mediates cancer progression in part through the modulation of autophagy. Accordingly, we demonstrate that chloroquine, an inhibitor of autophagy, can inhibit tumor growth in preclinical mouse models of castration-resistant prostate cancer (CRPC). However, clinical trials testing chloroquine derivatives in men with CRPC have yet to yield promising results, potentially due to side effects. We hypothesized that identification of the upstream activators of autophagy in prostate cancer could highlight alternative, context-dependent targets for blocking this important cellular process during disease progression. Here, we used molecular (inducible overexpression and shRNA-mediated knockdown), genetic (CRISPR/Cas9), and pharmacological approaches to elucidate an AR-mediated autophagy cascade involving Ca2+/calmodulin-dependent protein kinase kinase 2 (CAMKK2; a kinase with a restricted expression profile), 5-AMP-activated protein kinase (AMPK) and Unc-51 like autophagy activating kinase 1 (ULK1). These findings are consistent with data indicating CAMKK2-AMPK-ULK1 signaling correlates with disease progression in genetic mouse models and patient tumor samples. Importantly, CAMKK2 disruption impaired tumor growth and prolonged survival in multiple CRPC preclinical mouse models. Finally, we demonstrate that, similar to CAMKK2 inhibition, a recently described inhibitor of AMPK-ULK1 signaling blocked autophagy, cell growth and colony formation in prostate cancer cells. Taken together, our findings converge to demonstrate that AR signaling can co-opt the CAMKK2-AMPK-ULK1 signaling cascade to promote prostate cancer by increasing autophagy. Further, we propose that an inhibitor of this signaling cascade could serve as an alternative, more specific therapeutic compared to existing inhibitors of autophagy that, to date, have demonstrated limited efficacy in clinical trials due to their toxicity and poor pharmacokinetics.

cancer biology↗

bioRxiv2025

Induced pluripotent stem cell-derived human macrophages as an infection model for Trypanosoma cruzi

Chagas disease, caused by the parasite Trypanosoma cruzi, affects millions of people globally. Unfortunately, the available treatment options, especially for the chronic stage of the disease, are suboptimal. Given the chronic nature of the disease and the elusive nature of the parasite, there is a high need for new and safer drugs that deliver sterile cure. Posaconazole was a promising lead in the drug discovery pipeline but ultimately failed in clinical trials due to patient relapses. This failure illustrates the need for a drug screening assay that can predict sterile cure by assessing recrudescence after treatment. Here, we used human induced pluripotent stem cell (iPSC)-derived macrophages (iMACs) as host cells for T. cruzi. The iMACs were highly susceptible to infection by the parasites. By combining red fluorescent protein (RFP)-expressing iMACs with mNeonGreen-expressing T. cruzi, we were able to monitor the dynamics of the infection through live cell imaging. The activity of the compounds benznidazole and posaconazole was consistent with the results of an established infection system using mouse primary macrophages. The post-mitotic nature of iMACs makes them suitable host cells for long-term assays needed to assess recrudescence of parasites. Moreover, their human origin, stable genetic background, and capacity for genetic modification make the iMACs excellent host cells for studying host-pathogen interaction. Author summaryThe parasite Trypanosoma cruzi, the causative agent of Chagas disease, is a global health concern affecting millions each year. Infection with T. cruzi can cause chronic disease, often remaining asymptomatic for decades before resulting in severe cardiac or gastro-intestinal pathologies. To date, only benznidazole and nifurtimox are used for treatment of the infection, but both drugs are suboptimal for curing the chronic stage. Posaconazole showed great promise in preclinical studies but failed to achieve sterile cure in clinical trials, causing patient relapses. These disappointing results underline the need for drug screening assays able to predict sterile cure by evaluating recrudescence post-treatment. We used human induced pluripotent stem cell derived macrophages as host cells for T. cruzi and testing of trypanocidal compounds. This model can be used for long-term in vitro screening assays to find new drug candidates against Chagas disease. The human origin of these cells combined with the possibility of upscaling their production make them great host cells for drug screening campaigns.

microbiology↗

bioRxiv2025

Guiding treatment response by spatiotemporal control of α-particle deposition in solid tumors: the case for 'affinity cocktails' of antibody-radioconjugates

Antibody-radioconjugates are leading the investigational targeted alpha-particle (-particle) therapies for the treatment of solid tumors that do not respond to approved therapies. Yet, there is still treatment failure in the clinic largely attributed to the heterogenous patterns of tumor irradiation by -particles. Although -particles are essentially impervious to resistance, attributed to the complex double-strand DNA breaks they cause while traversing cells, cells not being directly hit by -particles will likely not be killed. The diffusion-limited poor tumor penetration of high-affinity (strongly-binding) antibody-radioconjugates combined with -particles short-range in tissue (only 40-80m), let tumor regions far from vasculature inadequately irradiated, therefore, possibly escaping treatment. METHODSTo improve penetration of delivered activity within tumors, we engineered separate actinium-225 antibody-radioconjugates of variable affinities ( affinity cocktails) targeting the same marker on cancer cells, that were chosen based on their preferential irradiation of complementary regions of the same tumors. The cocktails comprise: (a) high-affinity antibody-radioconjugates (as the ones on clinical trials), which mostly deliver their cargo in tumor cells close to the vasculature, where the low(er)-affinity antibody-radioconjugates fail to deliver effective doses, due to their fast clearance; and (b) low(er)-affinity antibody-radioconjugates, that penetrate the deeper parts of tumors farther from the vasculature, where the high-affinity antibodies fail to reach. The efficacy of affinity cocktails was assessed in spheroids, that were employed as surrogates of tumor avascular regions, and on mice with subcutaneous xenografts of different cancer origin, expression levels and/or type of the targeted receptor: HER2 highly-expressing BT-474 breast cancer cells, HER2 moderately-expressing HEPG2 hepatoma cells, and/or HER1 low-expressing BxPC-3 pancreatic cancer cells. RESULTSAlthough the high-affinity antibody-radioconjugates were most lethal against cancer cells in monolayers, affinity cocktails were most effective in inhibiting spheroid growth, due to better collective spreading of the antibody-conjugates within the spheroids volume. On all mouse models, and for the same total injected activity, affinity cocktails resulted in the best tumor growth inhibition, even at lower tumor absorbed doses, compared to the high-affinity antibody-radioconjugates alone. CONCLUSIONSThis proof-of-concept study in -particle antibody-delivery to solid tumors demonstrates that separating the two key processes of diffusion and reaction/binding improves treatment efficacy. This generalizable approach may augment antibody-radioconjugates already in clinical trials.

bioengineering↗

bioRxiv2020

Multiplex-inhibitor bead mass spectrometry reveals differential kinome signatures in newly diagnosed and recurrent glioblastoma

Glioblastoma (GBM) is the most common and aggressive adult brain tumor. Despite years of research, clinical trials have not improved the outcome for GBM. Standard of care for newly diagnosed GBM includes surgical resection, followed by radiation and chemotherapy. Tumor recurrence is inevitable and since most patients are not candidates for a second surgical resection, there is an urgent need to identify resistance mechanisms that arise in recurrent GBM. We postulated that examining the differences of activated kinases between newly diagnosed and recurrent GBM may provide insight to resistance mechanisms. To map the kinome landscape of newly diagnosed (nGBM) and recurrent GBM (rGBM) patient derived xenograft tumors, we used Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). We performed pathway analysis of kinases that differed in MIB-binding between nGBM and rGBM to identify kinase-driven signaling pathways. We also analyzed transcriptional profiles to determine the overlap in signaling pathways seen using proteomics or transcriptomics. Using MIB-MS kinome profiling, we found key differences in kinase-driven signaling pathways that may account for the increase in aggressive behavior seen in recurrent GBM. This included a shift in pathways driving cell invasion and proliferation, as well as upregulation of signaling pathways that drive GBM stem-cell like cell differentiation. Analysis of RNA-sequencing showed no statistically significant differences between enriched gene ontologies in nGBM and rGBM, demonstrating the importance of MIB-MS kinome profiling. Collectively, these studies suggest that kinome profiling may inform future clinical trials for kinase inhibitors in GBM.

cancer biology↗

bioRxiv2025

Repeated tDCS at clinically-relevant field intensity can boost concurrent motor learning in rats.

Electric fields used in clinical trials with transcranial direct current stimulation (tDCS) are small, with magnitudes that have yet to demonstrate measurable effects in preclinical animal models. We hypothesized that weak stimulation will nevertheless produce sizable effects, provided that it is applied concurrently with behavioral training, and repeated over multiple sessions. We tested this here in a rodent model of dexterous motor-skill learning. We developed a preparation that allows concurrent stimulation during the performance of a pellet-reaching task in freely behaving rats. The task was automated to minimize experimenter bias. We measured field magnitudes intracranially to calibrate the stimulation current. In this study, only male rats were used. Animals were trained for 20 min with concurrent epicranial tDCS over 10 daily sessions. Behavior was recorded with high-speed video to quantify reaching dynamics. We also measured motor-evoked potentials (MEPs) bilaterally with epidural microstimulation. The new electrode montage enabled stable stimulation over 10 sessions with a field intensity of 2V/m at the motor cortex. The number of successful reaches improved across days of training, and the rate of learning was higher in the anodal group as compared to sham-control animals (F(1)=7.12, p=0.008, N=24). MEPs were not systematically affected by tDCS. Posthoc analysis suggests that tDCS modulated motor learning only for right-pawed animals, improving success of reaching, but limiting stereotypy in these animals. Repeated and concurrent anodal tDCS can boost motor-skill learning at clinically-relevant field intensities. In this animal model the effect interacted with paw preference and was not associated with corticospinal excitability. Significance StatementThe effects of tDCS have been explored in numerous human clinical trials, but the mechanisms of action of weak electric fields remain unclear. In vitro studies show that constant electric fields at 2.5 V/m can enhance the efficacy of synapses undergoing plasticity. This study demonstrates in a rodent model that tDCS of only 2 Vm when applied concurrently to behavioral training can improve motor skill learning, and reduce stereotypy of reaching behavior. These effects accumulated over 10 days of training. Motor evoked potentials (MEP), which are often used to demonstrate plastic effects in humans on a time scale of hours, were not measurably affected by tDCS on this longer time scale.

animal behavior and cognition↗

bioRxiv2022

G2019S selective LRRK2 kinase inhibitor abrogates mitochondrial DNA damage

Pathogenic mutations in LRRK2 cause Parkinsons disease (PD). The G2019S variant is the most common, which results in abnormally high kinase activity. Compounds that target LRRK2 kinase activity are currently being developed and tested in clinical trials. We recently found that G2019S LRRK2 causes mitochondrial DNA (mtDNA) damage and treatment with multiple classes of LRRK2 kinase inhibitors at concentrations associated with dephosphorylation of LRRK2 reversed mtDNA damage to healthy control levels. Because maintaining the normal function of LRRK2 in heterozygous G2019S LRRK2 carriers while specifically targeting the G2019S LRRK2 activity could have an advantageous safety profile, we explored the efficacy of a G2019S mutant selective LRRK2 inhibitor to reverse mtDNA damage in G2019S LRRK2 models and patient cells relative to non-selective LRRK2 inhibitors. Potency of LRRK2 kinase inhibition by EB-42168, a G2019S mutant LRRK2 kinase inhibitor, and MLi-2, a nonselective inhibitor, was determined by measuring phosphorylation of LRRK2 at Ser935 and/or Ser1292 using quantitative western immunoblot analysis. The Mito DNADX assay, a novel system that allows for the accurate real-time quantification of mtDNA damage in a 96-well platform, was performed in parallel. We confirmed that EB-42168 selectively inhibits LRRK2 phosphorylation on G2019S LRRK2 relative to wild-type LRRK2. On the other hand, MLi-2 was equipotent for wild-type and G2019S LRRK2. Acute treatment with EB-42168 inhibited LRRK2 phosphorylation and also restored mtDNA damage to healthy control levels. Precision medicine is a common approach in modern day cancer research that is not yet routinely applied to neurodegenerative diseases. Abrogation of mtDNA damage with mutant selective tool inhibitor EB-42168 demonstrates the promise of a precision medicine approach for LRRK2 G2019S PD. Levels of mtDNA damage may serve as a potential pharmacodynamic biomarker of altered kinase activity that could be useful for small molecule development and clinical trials.

neuroscience↗

bioRxiv2017

Distinct Solubility and Cytotoxicity Regimes of Paclitaxel-Loaded Cationic Liposomes at Low and High Drug Content Revealed by Kinetic Phase Behavior and Cancer Cell Viability Studies

Lipid-based particles are used worldwide in clinical trials as carriers of hydrophobic paclitaxel (PTXL) for cancer chemotherapy, albeit with little improvement over the standard-of-care. Improving efficacy requires an understanding of intramembrane interactions between PTXL and lipids to enhance PTXL solubilization and suppress PTXL phase separation into crystals. We studied the solubility of PTXL in cationic liposomes (CLs) composed of positively charged 2,3-dioleyloxypropyltrimethylammonium chloride (DOTAP) and neutral 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC) as a function of PTXL membrane content and its relation to efficacy. Time-dependent kinetic phase diagrams were generated from observations of PTXL crystal formation by differential-interference-contrast microscopy. Furthermore, a new Synchrotron small-angle x-ray scattering in situ methodology applied to DOTAP/DOPC/PTXL membranes condensed with DNA enabled us to detect the time-dependent depletion of PTXL from membranes by measurements of variations in the membrane interlayer and DNA interaxial spacings. Our results revealed three regimes with distinct time scales for PTXL membrane solubility: hours for > 3 mol% PTXL (low), days for {approx} 3 mol% PTXL (moderate), and [≥] 20 days for < 3 mol% PTXL (long-term). Cell viability experiments on human cancer cell lines using CLPTXL nanoparticles (NPs) in the distinct CLPTXL solubility regimes reveal an unexpected nonmonotonic dependence of efficacy on PTXL content in NPs delivered at short time scales (hours) after liposome hydration, where we see two distinct high-efficacy regimes at low (< 2 mol%) and high (9 mol%) drug loading. These newly identified high-efficacy regimes flank the membrane solubility limit ({approx} 3 mol%, where efficacy declines), which has been the focus of most previous physicochemical studies (and clinical trials) of PTXL-loaded CLs. At longer times scales (days), CLPTXL NPs with [≥] 3 mol% PTXL lose efficacy while formulations with 1-2 mol% PTXL maintain high efficacy. Our findings underscore the importance of understanding the relationship of the kinetic phase behavior and physicochemical properties of CLPTXL NPs to efficacy.

biophysics↗

bioRxiv2019

Relapse prevention through health technology program reduces hospitalization in schizophrenia

ImportancePsychiatric hospitalization is a major driver of cost in the treatment of schizophrenia. Symptom relapses are a frequent cause of hospitalization and both are primary source of burden to patients and their supporters.\n\nObjectiveTo determine whether a novel, multicomponent, and technology-enhanced approach to relapse prevention in outpatients following a psychiatric hospitalization could reduce days spent in a hospital after discharge.\n\nDesignThe Improving Care and Reducing Cost (ICRC) study was a quasi-experimental clinical trial in outpatients with schizophrenia conducted between February 2013 and April 2015 at 10 different sites in the US. Data were obtained from 89 participants who received usual relapse prevention services, followed by a second cohort of 349 participants who received the technology-enhanced relapse prevention program. Both groups were followed for 6 months.\n\nSettingOutpatient setting.\n\nParticipantsPatients were between 18 and 60 years old; had a diagnosis of schizophrenia, schizoaffective disorder, or psychotic disorder not otherwise specified; and were currently hospitalized or had been hospitalized within the past 30 days.\n\nInterventionPatients received usual care or a technology-enhanced relapse prevention program during a 6-month period after discharge.\n\nMain Outcome(s) and Measure(s)Days spent in a psychiatric hospital during 6 months after discharge.\n\nResultsThe study included 438 patients. Control participants (N = 89; 37 females) were enrolled first and received usual care for relapse prevention, and followed by 349 participants (128 females) who received technology-enhanced relapse prevention. Days of hospitalization were reduced by 4 days (Mean days: b = -4.25, 95% CI: -8.29; -0.21, P = 0.039) during follow-up in the intervention condition compared to control.\n\nConclusions and RelevanceThe reduction in days spent in the hospital for participants in the technology-informed relapse prevention program compared to those who received usual care, and the previously reported high satisfaction and usability suggest that technology-enhanced relapse prevention is an effective and feasible way to reduce rehospitalization days among patients with schizophrenia.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSCan rehospitalizations in schizophrenia be prevented at reduced cost by innovative mobile technology-delivered interventions?\n\nFindingsIn this clinical trial with 438 patients, a technology-enhanced relapse prevention program compared to usual services reduced an average of four days of hospitalization per patient during the first 6 months following an index hospitalization.\n\nMeaningRelapse prevention through a health technology may improve care while reducing costs associated with hospitalization.

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