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bioRxiv2019

Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval.

1Despite strong vetting for disease activity, only 10% of candidate new molecular entities in early stage clinical trials are eventually approved. Analyzing historical pipeline data, Nelson et al. 2015 (Nat. Genet.) concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. Taking advantage of recent clinical development advances and rapid growth in GWAS datasets, we extend the original work using updated data, test whether genetic evidence predicts future successes and introduce statistical models adjusting for target and indication-level properties. Our work confirms drugs with genetically supported targets were more likely to be successful in Phases II and III. When causal genes are clear (Mendelian traits and GWAS associations linked to coding variants), we find the use of human genetic evidence increases approval from Phase I by greater than two-fold, and, for Mendelian associations, the positive association holds prospectively. Our findings suggest investments into genomics and genetics are likely to be beneficial to companies deploying this strategy.

genetics↗

bioRxiv2017

A New Big-Data Paradigm For Target Identification And Drug Discovery

Drug target identification is one of the most important aspects of pre-clinical development yet it is also among the most complex, labor-intensive, and costly. This represents a major issue, as lack of proper target identification can be detrimental in determining the clinical application of a bioactive small molecule. To improve target identification, we developed BANDIT, a novel paradigm that integrates multiple data types within a Bayesian machine-learning framework to predict the targets and mechanisms for small molecules with unprecedented accuracy and versatility. Using only public data BANDIT achieved an accuracy of approximately 90% over 2000 different small molecules - substantially better than any other published target identification platform. We applied BANDIT to a library of small molecules with no known targets and generated [~]4,000 novel molecule-target predictions. From this set we identified and experimentally validated a set of novel microtubule inhibitors, including three with activity on cancer cells resistant to clinically used anti-microtubule therapies. We next applied BANDIT to ONC201 - an active anti- cancer small molecule in clinical development - whose target has remained elusive since its discovery in 2009. BANDIT identified dopamine receptor 2 as the unexpected target of ONC201, a prediction that we experimentally validated. Not only does this open the door for clinical trials focused on target-based selection of patient populations, but it also represents a novel way to target GPCRs in cancer. Additionally, BANDIT identified previously undocumented connections between approved drugs with disparate indications, shedding light onto previously unexplained clinical observations and suggesting new uses of marketed drugs. Overall, BANDIT represents an efficient and highly accurate platform that can be used as a resource to accelerate drug discovery and direct the clinical application of small molecule therapeutics with improved precision.

pharmacology and toxicology↗

bioRxiv2021

Niclosamide Inhalation Powder Made by Thin-Film Freezing: Pharmacokinetic and Toxicology Studies in Rats and Hamsters

In this work, we have developed and tested in vivo a dry powder form of niclosamide made by thin-film freezing (TFF) and administered it by inhalation to rats and hamsters. The niclosamide dry powder, suitable for inhalation, is being developed as a therapeutic agent against COVID-19 infection. Niclosamide, a poorly water-soluble drug, is an interesting drug candidate because it was approved over 60 years ago for use as an anthelmintic medication, but recent studies demonstrated its potential as a broad-spectrum antiviral with a specific pharmacological effect against SARS-CoV-2 infection. In the past, clinical trials for other indications were terminated prior to completion due to low and highly variable oral bioavailability. In order to quickly address the current pandemic, targeting niclosamide directly to the lungs is rational to address the COVID-19 main clinical complications. Thin-film freezing technology was used to develop a niclosamide inhalation powder composition that exhibited acceptable aerosol performance with a fine particle fraction (FPF) of 86.0% and a mass median aerodynamic diameter (MMAD) and geometric standard deviation (GSD) of 1.11 m and 2.84, respectively. This formulation not only proved to be safe after an acute three-day, multi-dose pharmacokinetic study in rats as evidenced by histopathology analysis, but also was able to achieve lung concentrations above the required IC50 and IC90 levels for at least 24 h after a single administration in a Syrian hamster model. To conclude, we successfully developed a niclosamide dry powder inhalation formulation by thin-film freezing for further scale-up and clinical testing against the COVID-19 infection. This approach overcomes niclosamides limitation of poor oral bioavailability by targeting the drug directly to the primary site of infection, the lungs.

pharmacology and toxicology↗

bioRxiv2021

A human antibody with blocking activity to RBD proteins of multiple SARS-CoV-2 variants including B.1.351 showed potent prophylactic and therapeutic efficacy against SARS-CoV-2 in rhesus macaques

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease-2019 (COVID-19), interacts with the host cell receptor angiotensin-converting enzyme 2 (hACE2) via its spike 1 protein for infection. After the virus sequence was published, we identified two potent antibodies against SARS-CoV-2 RBD from antibody libraries using a phage-to-yeast (PtY) display platform in only 10 days. Our lead antibody JMB2002, now in a phase I clinical trial, showed broad-spectrum in vitro blocking activity against hACE2 binding to the RBD of multiple SARS-CoV-2 variants including B.1.351 that was reportedly much more resistant to neutralization by convalescent plasma, vaccine sera and some clinical stage neutralizing antibodies. Furthermore, JMB2002 has demonstrated complete prophylactic and potent therapeutic efficacy in a rhesus macaque disease model. Prophylactic and therapeutic countermeasure intervention of SARS-CoV-2 using JMB2002 would likely slow down the transmission of currently emerged SARS-CoV-2 variants and result in more efficient control of the COVID-19 pandemic.

microbiology↗

bioRxiv2021

Modulating D1 rather than D2 receptor-expressing spiny-projection neurons corresponds to optimal antipsychotic effect

Overactive dopamine transmission in psychosis is predicted to unbalance striatal output via D1- and D2-dopamine receptor-expressing spiny-projection neurons (SPNs). Antipsychotic drugs are thought to re-balance this output by blocking D2-receptor signaling. Here we imaged D1- and D2-SPN Ca2+ dynamics in mice to determine the neural signatures of antipsychotic effect. Initially we compared effective (clozapine and haloperidol) antipsychotics to a candidate drug that failed in clinical trials (MP-10). Clozapine and haloperidol normalized hyperdopaminergic D1-SPN dynamics, while MP-10 only normalized D2-SPN activity. Clozapine, haloperidol or chemogenetic manipulations of D1-SPNs also normalized sensorimotor gating. Given the surprising correlation between clinical efficacy and D1-SPN modulation, we evaluated compounds that selectively target D1-SPNs. D1R partial agonism, antagonism, or positive M4 cholinergic receptor modulation all normalized the levels of D1-SPN activity, locomotion, and sensorimotor gating. Our results suggest that D1-SPN activity is a more relevant therapeutic target than D2-SPN activity for the development of effective antipsychotics.

neuroscience↗

bioRxiv2021

A connectivity signature for glioblastoma

Tumor cell extensions called tumor microtubes (TMs) in glioma resemble neurites during neurodevelopment and connect glioma cells to a network that has considerable relevance for tumor progression and therapy resistance. The determination of interconnectivity in individual tumors has been challenging and the impact of tumor cell connectivity on patient survival remained unresolved so far. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells was established and clinically validated. Thirty-four of 40 connectivity genes were related to neurogenesis, neural tube development or glioma progression, including the TM-network-relevant GAP43 gene. Astrocytic-like and mesenchymal-like GB cells had the highest connectivity signature scores in scRNA-Seq data of patient-derived xenografts and patient samples. In 230 human GBs, high connectivity correlated with the mesenchymal expression subtype, TP53 wildtype, and with dismal patient survival. CHI3L1 was identified as a robust molecular marker of connectivity. Thus, the connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell connectivity is relevant for patients prognosis, and serves as a robust biomarker that can be used for future clinical trials. Statement of significanceIntegration of GB cells into functional networks drives tumor progression and resistance. Here, we established and validated a novel connectivity gene expression signature of single GB cells and whole tumors that can be easily applied to clinical and preclinical samples. It is shown that connectivity is determining prognosis combining molecular, functional and clinical insights into the disease.

cancer biology↗

bioRxiv2026

Neurobehavioral effects of focused ultrasound-mediated blood-brain barrier opening

Microbubble-enhanced focused ultrasound (MB-FUS) enables noninvasive blood-brain barrier (BBB) opening to improve the delivery of drugs and other therapeutics to the brain, supporting more effective treatment of brain disorders. The benefits of this rapidly advancing and highly versatile technology have been demonstrated in clinical trials, sparking a growing interest in expanding FUS applications that require higher intensity treatments, larger targeted brain volumes and larger therapeutics. However, in-depth safety profiling of such treatments has not been done and is limited in the clinic. Preclinical studies have been restricted in their readouts, focusing on acute imaging and simple behaviors. To address the need for more holistic safety profiling, we present a novel preclinical workflow for determining adverse effects of MB-FUS in rats, both acutely and long-term, by combining MRI, histology, and a custom motor task which provides fine-scaled readouts for complex learned behavior. Using this approach and taking advantage of our previous delineation of the relevant circuitry, we show dose- and target-dependent adverse effects in high dosing regimens. All prescribed acoustic doses opened the BBB; but while low doses had no overt adverse effects, high doses targeting the involved circuitry had severe effects on both behavior and brain tissue integrity. These effects persisted for weeks and recovered over differing time courses, with tissue disruptions and behavioral changes outlasting general performance deficits. Our results reinforce the need for multimodal, highly sensitive, and longitudinal readouts to holistically characterize adverse effects of MB-FUS, allowing for its safe use across a wide range of applications. SignificanceMicrobubble-enhanced focused ultrasound is emerging as a powerful noninvasive approach for delivering drugs, genes, and cell therapies through the blood-brain barrier, sparking broad interest in expanding clinical and preclinical applications. However, its effects on complex neurological function, especially for higher dosing regimens, remain poorly defined. To address this, we have established a novel multimodal preclinical strategy for defining functional safety limits and guiding clinical translation, integrating sensitive behavioral testing with MRI, histology and acoustic emissions analysis. We show dose- and target-dependent impairments in complex learned motor behavior and evidence of possible brain injury, with substantially different recovery time courses. Together, our findings demonstrate the importance of a multimodal, longitudinal approach for comprehensively characterizing treatment-related adverse effects and evaluating safety.

neuroscience↗

bioRxiv2017

A machine learning approach to predicting short-term mortality risk in patients starting chemotherapy

BackgroundCancer patients who die soon after starting chemotherapy incur costs of treatment without benefits. Accurately predicting mortality risk from chemotherapy is important, but few patient data-driven tools exist. We sought to create and validate a machine learning model predicting mortality for patients starting new chemotherapy.\n\nMethodsWe obtained electronic health records for patients treated at a large cancer center (26,946 patients; 51,774 new regimens) over 2004-14, linked to Social Security data for date of death. The model was derived using 2004-11 data, and performance measured on non-overlapping 2012-14 data.\n\nFindings30-day mortality from chemotherapy start was 2.1%. Common cancers included breast (21.1%), colorectal (19.3%), and lung (18.0%). Model predictions were accurate for all patients (AUC 0.94). Predictions for patients starting palliative chemotherapy (46.6% of regimens), for whom prognosis is particularly important, remained highly accurate (AUC 0.92). To illustrate model discrimination, we ranked patients initiating palliative chemotherapy by model-predicted mortality risk, and calculated observed mortality by risk decile. 30-day mortality in the highest-risk decile was 22.6%; in the lowest-risk decile, no patients died. Predictions remained accurate across all primary cancers, stages, and chemotherapies--even for clinical trial regimens that first appeared in years after the model was trained (AUC 0.94). The model also performed well for prediction of 180-day mortality (AUC 0.87; mortality 74.8% in the highest risk decile vs. 0.2% in the lowest). Predictions were more accurate than data from randomized trials of individual chemotherapies, or SEER estimates.\n\nInterpretationA machine learning algorithm accurately predicted short-term mortality in patients starting chemotherapy using EHR data. Further research is necessary to determine generalizability and the feasibility of applying this algorithm in clinical settings.

bioinformatics↗

bioRxiv2019

Boosting with ALVAC-HIV and AIDSVAX B/E enhances Env constant region 1 and 2 antibody-dependent cellular cytotoxicity

Induction of protective antibodies is a critical goal of HIV-1 vaccine development. One strategy is to induce non-neutralizing antibodies that kill virus-infected cells as these antibody specificities have been implicated in slowing HIV-1 disease progression and in protection. HIV-1 Env constant region 1 and 2 (C1C2) antibodies frequently contain potent antibody dependent cellular cytotoxicity (ADCC) making them a vaccine target. Here we explore the effect of delayed and repetitive boosting of RV144 vaccinee recipients with ALVAC/AIDSVAX B/E on the C1C2-specific antibody repertoire. It was found that boosting increased clonal lineage specific ADCC breadth and potency. A ligand crystal structure of a vaccine-induced broad and potent ADCC-mediating C1C2-specific antibody showed that it bound a highly conserved Env gp120 epitope. Thus, rationally designed boosting strategies to affinity mature these type of IgG C1C2-specific antibody responses may be one method by which to make an improved HIV vaccine with higher efficacy than seen in the RV144 trial.\n\nSignificanceOver one million people become infected with HIV-1 each year making the development of an efficacious HIV-1 vaccine an important unmet medical need. The RV144 human HIV-1 vaccine-regimen is the only HIV-1 clinical trial to date to demonstrate vaccine-efficacy. An area of focus has been on identifying ways by which to improve upon RV144 vaccine-efficacy. The RV305 HIV-1 vaccine-regimen was a follow-up boost of RV144 vaccine-recipients that occurred 6-8 years after the conclusion of RV144. Our studies focused on the effect of delayed boosting in humans on the vaccine-induced antibody repertoire. It was found that boosting with a HIV-1 Env vaccine increased antibody-mediated effector function potency and breadth.

immunology↗

bioRxiv2026

Preclinical evaluation of Brincidofovir in glioblastoma demonstrates improved long term-survival and cytomegalovirus-dependent and independent effects

Cytomegalovirus (CMV) has been implicated in glioblastoma (GBM) progression. Ongoing clinical trials are assessing therapeutic approaches targeting CMV in GBM but to date no new therapy has been approved outside the standard of care. Previous preclinical studies have highlighted the potential of the antiviral drug Cidofovir (CDV) in GBM; however, its clinical use is limited by dose-dependent nephrotoxicity and poor cellular uptake, necessitating high intravenous doses to achieve therapeutic activity. Brincidofovir (BCV), a lipid conjugate of CDV has been developed, which does not induce nephrotoxicity and has significantly greater cellular bioavailability. Here we examined the effects of BCV in a newly established CMV-driven GBM model (SB28) and in patient-derived tumor neurospheres. We show that BCV prolongs survival in vivo and exerts both CMV-dependent and independent antitumor effects. Mechanistically, BCV induces DNA damage and cell cycle dysregulation in GBM cells and inhibits proliferation of patient-derived neurospheres in a dose-dependent manner. These data identify BCV as a dual-action therapeutic that suppresses viral oncomodulation while directly targeting tumor cell viability.

cancer biology↗

bioRxiv2020

Evaluation of M2-like macrophage enrichment after diffuse traumatic brain injury through transient interleukin-4 expression from engineered mesenchymal stromal cells

Appropriately modulating inflammation after traumatic brain injury (TBI) may prevent disabilities for the millions of those inflicted annually. In TBI, cellular mediators of inflammation, including macrophages and microglia, possess a range of phenotypes relevant for an immunomodulatory therapeutic approach. It is thought that early phenotypic modulation of these cells will have a cascading healing effect. In fact, an anti-inflammatory, "M2-like" macrophage phenotype after TBI has been associated with neurogenesis, axonal regeneration, and improved white matter integrity. There already exists clinical trials seeking an M2-like bias through mesenchymal stem/stromal cells (MSCs). However, MSCs do not endogenously synthesize key signals that induce robust M2-like phenotypes such as Interleukin-4 (IL-4). To enrich M2-like macrophages in a clinically relevant manner, we augmented MSCs to transiently express IL-4 via synthetic IL-4 mRNA. We observed that these IL-4 expressing MSCs indeed induce a robust M2-like macrophage phenotype and promote anti-inflammatory gene expression in a modified TBI model of closed head injury. However, here we demonstrate that acute enrichment of M2-like macrophages did not translate to improved functional or histological outcomes. This suggests that an acute enrichment of M2-like macrophages cannot solely orchestrate the neurogenesis, axonal regeneration, and improved WMI after diffuse TBI. To further understand whether dysfunctional pathways underlie the lack of therapeutic effect, we report transcriptomic analysis of injured and treated brains. Through this, we discovered that inflammation persists in spite of acute enrichment of M2-like macrophages in the brain. Last, we comment on our modified TBI model, behavioral studies, and propose that IL-4 expressing MSCs may also have relevance in other cavitary diseases or in improving biomaterial integration into tissues.

neuroscience↗

bioRxiv2021

A Bayesian Precision Medicine Framework for Calibrating Individualized Therapeutic Indices in Cancer

The development and clinical implementation of evidence-based precision medicine strategies has become a realistic possibility, primarily due to the rapid accumulation of large-scale genomics and pharmacological data from diverse model systems: patients, cell-lines and drug perturbation studies. We introduce a novel Bayesian modeling framework called the individualized theRapeutic index (iRx) model to integrate high-throughput pharmacogenomic data across model systems. Our iRx model achieves three main goals: first, it exploits the conserved biology between patients and cell-lines to calibrate therapeutic response of drugs in patients; second, it finds optimal cell line avatars as proxies for patient(s); and finally, it identifies key genomic drivers explaining cell line-patient similarities. This is achieved through a semi-supervised learning approach, that conflates (unsupervised) sparse latent factor models with (supervised) penalized regression techniques. We propose a unified and tractable Bayesian model for estimation, and inference is conducted via efficient posterior sampling schemes. We illustrate and validate our approach using two existing clinical trial datasets in multiple myeloma and breast cancer studies. We show that our iRx model improves prediction accuracy compared to naive alternative approaches, and it consistently outperforms existing methods in literature in both in multiple simulation scenarios as well as real clinical examples.

genomics↗

bioRxiv2024

Gemcitabine and ATR inhibitors synergize to kill PDAC cells by blocking DNA damage response

The DNA-damaging agent gemcitabine (GEM) is a first-line treatment for pancreatic cancer but chemoresistance is frequently observed. Several clinical trials investigate the efficacy of GEM in combination with targeted drugs including kinase inhibitors but the experimental evidence for such rational is often unclear. Here, we phenotypically screened 13 human pancreatic adenocarcinoma (PDAC) cell lines against GEM in combination with 140 clinical kinase inhibitors and observed strong synergy for the ATR inhibitor Elimusertib in most cell lines. Dose-dependent phosphoproteome profiling of four ATR inhibitors following DNA damage induction by GEM revealed a strong block of the DNA damage response pathway including phosphorylated pS468 of CHEK1 as the underlying mechanism of drug synergy. The current work provides a strong rationale for why the combination of GEM and ATR inhibition may be useful for the treatment of PDAC patients and constitutes a rich phenotypic and molecular resource for further investigating effective drug combinations.

cancer biology↗

bioRxiv2019

Radiographic and clinical risk factors of total knee arthroplasty in asymptomatic knees; a 15-year follow-up study

BackgroundRadiographic signs of osteoarthritis (OA) are frequent in knees without symptoms. The long-term impact of these findings is not completely elucidated. We wanted to evaluate whether radiographic or clinical baseline findings are associated with the risk of total knee arthroplasty (TKA) in knees without symptomatic OA but with clinical OA of the other knee during a mean follow-up period of 15 years. MethodsA follow-up analysis was performed in 100 persons with unilateral, clinical knee OA according to the ACR (American College of Rheumatology) criteria, who participated in a clinical trial between 2000 and 2002. Baseline radiographs of the contralateral, non-symptomatic knee were available in 88 participants at follow-up. Data on TKA procedures were extracted from the Danish National Patient Register at follow-up. Radiographic and clinical findings were analyzed for associations with subsequent TKA. ResultsAt follow-up, 40% had received a TKA in their non-symptomatic knee. The risk of TKA was significantly associated with baseline joint space narrowing (risk ratio (RR) 1.6 (95% confidence interval (95% CI) 1.4 to 1.9)), osteophytes (RR 1.5 (95% CI 1.3 to 1.8)) and subchondral sclerosis (RR 2.4 (95% CI 1.6 to 3.7)). Among the clinical findings, only baseline body mass index (BMI) was significantly associated with the risk of TKA (RR 1.4 (95& CI 1.1 to 1.8)). ConclusionsRadiographic OA changes and BMI at baseline were significantly associated with the long-term risk of TKA in persons without symptomatic knee OA but with symptomatic OA in the contralateral knee, implying that radiographic OA findings are important prognostic factors regardless of symptoms.

pathology↗

bioRxiv2026

An electronically steerable epidural ultrasound interface for deep brain neuromodulation in freely moving rats

Low-intensity focused ultrasound (LI-FUS) clinical trials exploit either the neural activity modulating, or the blood-brain barrier opening, capacity of this stimulation modality. However, LI-FUS currently is applied only transcranially which means that it is conducive only for episodic and intermittent stimulation, although, clinical data shows that in numerous neurological and psychiatric applications, chronic and continuous stimulation is required for long-term, stable therapeutic effect. The paper presents experimental data on a novel and innovative approach describing an implantable, epidural focus ultrasound (eFUS) device, designed for continuous, chronic and multi-site steerable neuromodulation. The miniaturized eFUS device consists of a two-dimensional piezoelectric transducer array directly integrated onto a custom ASIC, specifically engineered for proof-of-principle neuromodulation studies in the rat brain. The system generates electronically steerable focused ultrasound with software-defined focal coordinates, sufficient to stimulate neuronal activity in deep brain structures. In vitro acoustic characterization confirmed accurate beam steering and focusing, while in vivo validation demonstrated reliable stimulation of a deep subcortical target with measurable physiological effects. eFUS-mediated targeting of the ventral tegmental area in awake and freely moving rats produced increase in dopamine release in the nucleus accumbens as confirmed using fiber photometry recordings. Post-mortem histological analysis of the target regions showed the absence of inflammatory markers, although the epidural placement of the eFUS device was associated with mild tissue damage. Overall, the study provides in vitro data demonstrating the energy efficiency, and steerability of the technology, and in vivo physiological evidence of neuromodulatory ability of a deep, subcortical brain structure.

neuroscience↗

bioRxiv2025

Assessment of ecological fidelity of human microbiome-associated mice in observational studies and an interventional trial

Composition and function of the gut microbiome is associated with diverse health conditions and treatment responses. Human microbiota-associated (HMA) mouse models are used to establish causal links for these associations but have important limitations. We assessed the fidelity of HMA mouse models to recapitulate ecological responses to a microbial consortium using stools collected from a human clinical trial. HMA mice were generated using different routes of consortium exposure and their ecological features were compared to human donors by metagenomic sequencing. HMA mice were more similar in gut composition to other mice than their respective human donors, with taxa including Akkermansia muciniphila and Bacteroides species enriched in mouse recipients. A limited repertoire of microbes was able to engraft into HMA mice regardless of route of consortium exposure. In publicly available HMA mouse datasets from four distinct health conditions, we confirmed our observation that a taxonomically restricted set of microbes reproducibly engrafts in HMA mice and observed that stool microbiome composition of HMA mice were more like other mice than their human donor. Our data suggest that HMA mice are limited models to assess the ecological impact of microbial consortia, with ecological effects in HMA mice being more strongly associated with host species than donor stool ecology or ecological responses to treatment in humans. Comparisons to published studies suggest this may be due to comparatively large host-species effects that overwhelm ecological effects of treatment in humans that HMA models aim to recapitulate. ImportanceHuman microbiota-associated (HMA) mice are models that better represent human gut ecology compared to conventional laboratory mice and are commonly used to test the effect of the gut microbiome on disease or treatment response. We evaluated the fidelity of using HMA mice as avatars of ecological response to a human microbial consortium, MET4. Our results show that HMA mice in our cohort and across other published studies are more similar to each other than the human donors or inoculum they are derived from and harbour a taxonomically restricted gut microbiome. These findings highlight the limitations of HMA mice in evaluating the ecological effects of complex human microbiome-targeting interventions, such as microbial consortia.

microbiology↗

bioRxiv2020

Single-Cell Transcriptomic Attributes and Unbiased Computational Modeling for the Prediction of Immunomodulatory Potency of Mesenchymal Stromal Cells

Mesenchymal stromal cells (MSCs) are currently being tested in numerous clinical trials as potential cell therapies for the treatment of various diseases and due to their potential immunomodulatory, pro-angiogenic, and regenerative properties. However, variabilities in tissue sources, donors, and manufacturing processes and the lack of defined critical quality attributes (CQAs) and clinically relevant mechanism of action (MoA) pose significant challenges to identify MSC cell therapy products with a predictable therapeutic outcome. This also hinders regulatory considerations and broad clinical translation of MSCs. MSC products are often administered to the patient immediately after thawing from cryopreserved vials (out-of-thaw). However, the qualifying quality-control assays are either performed before cryopreservation, or after culturing the post-thaw cells for 24-48 hours (culture-rescued), none of which represent the out-of-thaw product administered to patients. In this study, we performed a broad functional characterization of out-of-thaw and culture-rescue MSCs from bone marrow (BM-MSCs) and cord tissue (CT-MSCs) using macrophage activation and T cell proliferation-based in vitro potency assays and deep phenotypic characterization using single-cell RNA-sequencing. Using this data, we developed unbiased computational models, specifically symbolic regression (SR) and canonical correlation analysis (CCA) models to predict the immunomodulatory potency of MSCs. Overall, our results suggest that manufacturing conditions (OOT vs. CR) have a strong effect on MSC-function on MSC interactions with macrophages and T cells. Furthermore, single-cell RNA-seq analyses of out-of-thaw BM and CT-MSCs indicate a tissue of origin-dependent variability and heterogeneity in the transcriptome profile. Using symbolic regression modeling we identified specific single-cell transcriptomic attributes of MSCs that predict their immunomodulatory potency. In addition, CCA modeling predicted MSC donors with high or low immunomodulatory potency from their transcriptome profiles. Taken together, our results provide a broad framework for identifying predictive CQAs of MSCs that could ultimately help in better understanding of their MOAs and improved reproducibility and manufacturing control of MSCs.

immunology↗

bioRxiv2021

A comparative study of the effects of Aducanumab and scanning ultrasound on amyloid plaques and behavior in the APP23 mouse model of Alzheimer disease

BackgroundAducanumab is an anti-amyloid-{beta} (A{beta}) antibody that achieved reduced amyloid pathology in Alzheimers disease (AD) trials, but it is controversial whether it also improved cognition. It has been claimed that this would require a sufficiently high cumulative dose of the antibody in the brain. Therapeutic ultrasound, in contrast, has only begun to be investigated in human AD clinical trials. We have previously shown that scanning ultrasound in combination with intravenously injected microbubbles (SUS), that temporarily and safely opens the blood-brain barrier (BBB), removes amyloid and restores cognition in APP23 mice. It has not been directly tested how the effects of SUS compare to immunotherapy or whether a combination therapy is more effective. MethodsIn a study comprising four treatment arms, we tested the efficacy of an Aducanumab analogue, Adu, in comparison to SUS, as well as a combination therapy in APP23 mice, using sham as a control (aged 13-22 months). The active place avoidance (APA) test was used to test spatial memory, and histology and ELISA were used to measure amyloid. Brain antibody levels were also determined. ResultsWe found that both Adu and SUS reduced the total plaque area in the hippocampus to a similar degree, with no additive effect in the combination treatment (SUS+Adu). Whereas there was only a trend towards a reduction for both Adu and SUS in the cortex, the combination trial yielded a statistically significant reduction compared to sham. Only the SUS and SUS+Adu groups included animals that had their plaque load reduced to below 1% from above 10%. There was a robust improvement in spatial memory for SUS+Adu only. In this group, when measured three days post-treatment, Adu levels were still 5-fold increased in the combination therapy compared to delivery of Adu on its own. Together, these findings suggest that SUS should be seriously considered as a treatment option for AD. Alternatively, a combination trial using Aducanumab together with ultrasound to increase brain levels of Aducanumab may be warranted, as the two approaches may engage different (albeit shared) clearance mechanisms.

neuroscience↗