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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2022

MultiGML: Multimodal Graph Machine Learning for Prediction of Adverse Drug Events

Adverse drug events constitute a major challenge for the success of clinical trials. Several computational strategies have been suggested to estimate the risk of adverse drug events in preclinical drug development. While these approaches have demonstrated high utility in practice, they are at the same time limited to specific information sources and thus neglect a wealth of information that is uncovered by fusion of different data sources, including biological protein function, gene expression, chemical compound structure, cell-based imaging, etc. In this work we propose an integrative and explainable Graph Machine Learning approach (MultiGML), which fuses knowledge graphs with multiple further data modalities to predict drug related adverse events. MultiGML demonstrates excellent prediction performance compared to alternative algorithms, including various knowledge graph embedding techniques. MultiGML distinguishes itself from alternative techniques by providing in-depth explanations of model predictions, which point towards biological mechanisms associated with predictions of an adverse drug event. MotivationAdverse drug events are a major risk for failure of late-stage clinical trials. Attempts to prevent adverse drug events in preclinical drug development include experimental procedures for measuring liver-toxicity, cardio-toxicity, etc. Yet these procedures are costly and cannot fully guarantee success in later clinical studies, specifically in situations without a reliable animal model. Computational approaches developed for adverse event prediction have shown to be valuable, but are mostly limited to single data sources. Our approach successfully integrates various data sources on protein functions, gene expression, chemical compound structures and more, into the prediction of adverse events. A main distinguishing characteristic is the explainability of our model predictions which allow further insight into biological mechanisms.

bioinformatics↗
bioRxiv2024

Multiplexed nanopore amplicon sequencing to distinguish recrudescence from new infection in antimalarial drug trials

BackgroundThe assessment of antimalarial drug efficacy against Plasmodium falciparum requires PCR correction to distinguish recrudescence from new infections by comparing parasite genotypes before treatment and in recurrent infections. Nanopore sequencing offers a low-cost, portable, scalable, and rapid alternative to traditional methods, supporting the expansion and decentralization of sequencing in endemic, resource-limited settings, potentially providing rapid PCR-corrected drug failure estimates. MethodsWe optimized a multiplexed AmpSeq panel targeting six microhaplotypes for high and uniform coverage. We assessed sensitivity and specificity for detecting minority clones in polyclonal infections and evaluated genetic diversity across the microhaplotype markers. We used mixtures of four P. falciparum laboratory strains at different ratios and 20 paired patient samples from a clinical trial. A custom bioinformatics workflow was used to infer haplotypes from polyclonal infections, including minority clones, with defined cut-off criteria for accurate haplotype calling. FindingsThe nanopore AmpSeq assay achieved uniform and high read coverage across all six microhaplotype markers (median coverage: 12,989x to 15,440x for laboratory strain mixtures and 7,011x to 11,600x for patients samples, respectively). We found high sensitivity in detecting minority clones (up to 50:1:1:1 in the 3D7:K1:HB3:FCB1 laboratory strain mixtures) and high specificity with less than 0.01% of all reads being false-positive haplotypes. Genetic diversity in the markers used was high (HE [≥] 0.98 and up to 31 unique haplotypes in 20 paired samples with cpmp), and concordant results in classifying new infections and recrudescence across all markers used were observed in 18 (90%) of 20 paired samples. InterpretationOur study demonstrates the feasibility of nanopore AmpSeq for distinguishing recrudescence from new infections in clinical trials. FundingSwiss Tropical and Public Health Institute.

molecular biology↗
bioRxiv2020

Identification of SARS-CoV-2 induced pathways reveal drug repurposing strategies

The global outbreak of SARS-CoV-2 necessitates the rapid development of new therapies against COVID-19 infection. Here, we present the identification of 200 approved drugs, appropriate for repurposing against COVID-19. We constructed a SARS-CoV-2-induced protein (SIP) network, based on disease signatures defined by COVID-19 multi-omic datasets(Bojkova et al., 2020; Gordon et al., 2020), and cross-examined these pathways against approved drugs. This analysis identified 200 drugs predicted to target SARS-CoV-2-induced pathways, 40 of which are already in COVID-19 clinical trials(Clinicaltrials.gov, 2020) testifying to the validity of the approach. Using artificial neural network analysis we classified these 200 drugs into 9 distinct pathways, within two overarching mechanisms of action (MoAs): viral replication (130) and immune response (70). A subset of drugs implicated in viral replication were tested in cellular assays and two (proguanil and sulfasalazine) were shown to inhibit replication. This unbiased and validated analysis opens new avenues for the rapid repurposing of approved drugs into clinical trials.

pharmacology and toxicology↗
bioRxiv2024

A Mimicry-Based Strategy Between Human and Commensal Antigens for the Development of a New Family of Immune Therapies for Cancer

Peptide vaccines have emerged as a promising strategy for cancer immunotherapy, yet often lack of strong, specific and sustained immune responses against tumor antigens. To achieve a robust immune response, the effective selection of tumour antigens is crucial. While neoantigens trigger potent immune responses, their use suffers from patient specificity and their rarity in low-mutational tumors. Alternatively, the immunogenic potential of tumor-associated antigens (TAAs) is limited by central immune tolerance. Molecular mimicry and T cell cross-reactivity is a proposed mechanism to trigger a robust T cell-mediated antitumor response. Although molecular mimicry between pathogens and tumor antigens has been described, the potential benefits of exploiting this molecular mimicry with commensal bacterial antigens in antitumor immunity have not been thoroughly investigated despite strong evidence that the composition of the human microbiota significantly influences immune competency. Our new approach called OncoMimics, which uses molecular mimicry between commensal bacterial and tumoral antigens to induce cross-reactive cytotoxic T cells against tumor cells. In preclinical studies, vaccination with OncoMimic peptides (OMPs) led to the expansion of CD8+ T cells reacting against homologous tumor-associated antigen peptides and elicits cytotoxic activity against tumor cells. OMPs are efficiently recognized by a prevalent T cell population within the peripheral blood mononuclear cells of healthy individuals. An ongoing clinical trial (NCT04116658) using OncoMimics in patients with glioblastoma demonstrates early, durable, and cross-reactive tumor antigen CD8+ T cell responses with pronounced memory persistence. By overcoming the current vaccine limitations, OncoMimics constitutes a promising strategy for enhancing cancer immunity and improving patient outcomes. Statement of SignificanceThis study introduces OncoMimics, a peptide-based immunotherapy leveraging molecular mimicry to induce robust, cross-reactive T cell responses against tumor antigens, showing promising early results in an ongoing glioblastoma clinical trial (NCT04116658)

immunology↗
bioRxiv2025

High-dose oral pyrophosphate inhibits connective tissue calcification in Abcc6 null mice but affects bone structure

Pseudoxanthoma elasticum is a rare inherited disorder marked by abnormal calcium phosphate deposition in soft connective tissues, particularly the skin, arteries, and eyes. It is caused by inactivating mutations in the ABCC6 gene, which encodes a hepatic efflux transporter. Loss of ABCC6 function leads to reduced plasma levels of pyrophosphate, a key inhibitor of calcification, thereby promoting ectopic mineralization. Oral pyrophosphate therapy has emerged as a potential treatment, but its effectiveness is uncertain. Most ingested pyrophosphate is hydrolyzed in the gut to inorganic phosphate, which may worsen calcification. Moreover, its impact on mineralized tissues remains largely unexplored. Abcc6-/- mice closely mimic human pseudoxanthoma elasticum and are widely used in preclinical studies. Although patients are most concerned about ocular complications, eye calcification is rarely assessed in translational studies using Abcc6-/- mice. Using microcomputed tomography we found that ectopic calcification at the ciliary margin is a reliable marker of ocular disease progression in these mice. Administering pyrophosphate in drinking water at concentrations up to 90 mM did not increase calcification in skin or eyes. However, only very high doses effectively prevented ectopic calcification - doses that would equate to an impractical 2.5 g/kg/day of disodium pyrophosphate in humans. These high doses also led to pyrophosphate accumulation in bone and negatively affected bone structure and strength. In summary, only supraphysiological doses of orally administered pyrophosphate inhibited ectopic calcification in Abcc6-/- mice, but these doses are not feasible for human use and may compromise bone function. These data are especially important considering the currently ongoing clinical trial evaluating the safety and efficacy of oral pyrophosphate administration as a treatment for pseudoxanthoma elasticum. LAY SUMMARYPseudoxanthoma elasticum (PXE) is a rare inherited mineralization disorder caused by the absence of functional ABCC6, a liver-expressed protein. This deficiency leads to reduced plasma levels of pyrophosphate, a key inhibitor of mineralization, resulting in abnormal calcium phosphate deposition in the skin, eyes, and blood vessels. Oral pyrophosphate has been proposed as a therapeutic strategy for PXE, and a clinical trial evaluating its efficacy recently began in France. In a PXE mouse model, we show that only very high oral doses of pyrophosphate are effective, but these doses impair bone quality and are not suitable for human use.

pathology↗
bioRxiv2023

Discovery of Novel Small Molecule CB2 Agonist for the Treatment of Glioblastoma Tumors

Malignant brain tumors cause over 15,000 deaths per year in the United States. Survival for over five years is only 36%. Nearly 49% of malignant brain tumors are glioblastomas (GBM), and 30% of them have the ability to diffuse and infiltrate. Treatment frequently includes surgery, radiotherapy and chemotherapy. In case of GBM patients, combining temozolomide (TMZ) chemotherapy with radiation improved survival over radiotherapy alone (survival by 2 years: 17% vs. 11%; 5 years: 10% vs. 2%). Most primary GBM tumors from pediatric and adult patients express high levels of cannabinoid type II (CB2) receptors, and that expression correlated with tumor grade. Cannabinoids like (-)-trans-{Delta}9-tetrahydrocannabinol ({Delta}9-THC) were shown to suppress GBM tumor growth, trigger apoptosis in GBM stem cells, and slow down angiogenesis, thus cutting GBM cells off of blood supply. These data led to local administration of {Delta}9-THC in clinical trials in patients with recurrent glioblastomas, although the well-known psychotropic effects of {Delta}9 -THC and related compounds mediated via the CB1 receptors have raised some concerns among clinicians. Thus, the medicinal usage of cannabinoids has been limited. One leading strategy to avoid the side effects is administration of CB2-selective non-psychotic drugs. To create an effective solution, we designed a preclinical study to develop a novel GBM therapy, using NeuroTherapias lead molecule, the CB2 agonist NTRX-07. We have already demonstrated that NTRX-07 ameliorates Amyloid {beta} production and deposition in the hippocampus, and thus restored Long-Term Potentiation - the cellular mechanism for learning and memory formation. Consequently, we showed that NTRX-07 has a highly competitive target compound profile, and that is safe in murine models, dogs and humans. NTRX-07 has entered clinical trials for the management of AD as the first orally available CB2 agonist designed to be centrally active. The phase I single ascending dose study in normal volunteers demonstrated targeted plasma levels of the drug after oral administration with no serious adverse events or clinically significant changes in safety examinations or laboratory tests. In this pilot mouse GBM survival study, we found breakthrough evidence that our compound can exert potent anti-cancer activity and significantly extend the survival of GBM animals; even without previously exposing them to radiotherapy or TMZ. Our goal is to bring NTRX-07 into the clinic as a new therapeutic for patients with GBM.

neuroscience↗
bioRxiv2021

Modeling osteoporosis to design and optimize pharmacologic therapies comprising multiple drug types

For the treatment of postmenopausal osteoporosis, several drug classes with different mechanisms of action are available. Since only a limited set of dosing regimens and drug combinations can be tested in clinical trials, it is currently unclear whether common medication strategies achieve optimal bone mineral density gains or are outperformed by alternative dosing schemes and combination therapies that have not been explored so far. Here we develop a mathematical framework of drug interventions for postmenopausal osteoporosis that unifies fundamental mechanisms of bone remodeling and the mechanisms of action of four drug classes: bisphosphonates, parathyroid hormone (PTH) analogs, sclerostin inhibitors and receptor activator of NF-{kappa}B ligand (RANKL) inhibitors. Using data from several clinical trials, we calibrate and validate the model, demonstrating its predictive capacity for complex medication scenarios including sequential and parallel drug combinations. Via simulations, we reveal that there is a large potential to improve gains in bone mineral density by exploiting synergistic interactions between different drug classes, without increasing the total amount of drug administered.

pharmacology and toxicology↗
bioRxiv2024

Design of a novel epitope-based tetravalent subunit vaccine against dengue virus: an immunoinformatics approach

Dengue imposes a profound global impact, with millions affected annually. Its transmission by Aedes mosquitoes poses significant challenges to combat, aggravated by urbanization and climate change. Despite efforts, no impeccable antiviral treatment exists to date, highlighting the urgency for a vaccine. Developing one encounters hurdles like the four distinctive serotypes of the virus and complex immune responses. In this study, we employed an immunoinformatics approach to design an epitope-based tetravalent subunit vaccine aimed at confronting all DENV serotypes. The study contemplates epitopes prediction, toxicity assessment, molecular docking, molecular dynamics (MD) simulations, immune simulations. On sequence retrieval, the epitopes were predicted and prioritized. The sequence of the finally designed vaccine was reached after a broad analysis of the antigenicity scores, serotype coverage, and population coverage. Human {beta}-defensin 3 has been added as an adjuvant to the core vaccine sequence that comprises 23 epitopes and linkers. Notably, the vaccine has the highest antigenicity (0.9319) and 97.35% population coverage worldwide. The molecular docking operations of the vaccine with toll-like receptor 2 (TLR2) and TLR4 showed promising interactions with lowest energies of -1240.5 kJ/mol (76 members) and -1393.3 kJ/mol (40 members), respectively. Molecular dynamics (MD) simulations were run up to 200 nanoseconds, and the complexes of the vaccine with TLR2 and TLR4 were found to be very stable and flexible. Moreover, in immune simulations, the vaccine evoked robust immune responses. These findings suggest that our vaccine outperforms any other Dengue vaccine developed to date. However, since this study was conducted through in silico methods, in vitro and in vivo validations are required to confirm the vaccine as a potential candidate for clinical trials. Author summaryWe developed a novel epitope-based tetravalent subunit vaccine against all dengue virus (DENV) serotypes using immunoinformatics. Our vaccine demonstrated high antigenicity (0.9319) and wide population coverage (97.35%). Molecular docking and dynamics simulations indicated strong interactions with immune receptors which is crucial for the vaccines activity inside human body. Moreover, immune simulations showed robust responses indicating proper immunity against DENV. Therefore, our vaccine offers a promising solution to dengue fever, pending further in vitro and in vivo validations for clinical trials. Notably, this is the first ever dengue vaccine with such high efficacy in terms of immunoinformatics and vaccinomic approaches.

bioinformatics↗
bioRxiv2019

The Endless Frontier? The Recent Upsurge of R&D Productivity in Pharmaceuticals

Analyses of pharmaceutical pipelines of drug development in the 1990-2010 documented progressively increasing attrition rates and duration of clinical trials, leading to a diffuse perception of a \"productivity crisis\". We produced a new set of analyses for the last decade, using an extensive data of more than 45,000 projects between 1990 and 2017, and report a recent upsurge of R&D productivity within the industry. First, we investigated how R&D projects are allocated across therapeutic areas and found a polarization towards high-risk/high-reward indications, with a strong focus on oncology. Importantly, attrition rates have been decreasing at all clinical stages in recent years. In parallel, we observed an increase of early failures in preclinical research, and a significant reduction of time required to identify projects to be discontinued. Notably, more recent projects are increasingly based on novel mechanisms of action and target indications with small patient populations. Finally, by analyses of the relative contribution of different institutional types and development companies, we show that the observed increased performance in clinical trials is mostly due to the contribution of biotech-nological companies, while pharmaceutical companies have significantly improved their performances in identifying false positives in preclinical research.

pharmacology and toxicology↗
bioRxiv2022

Integrative transcriptomic and proteomic meta-analysis of Zika viral infection reveals potential mechanisms for oncolytic therapy in neuroblastoma

BACKGROUNDPaediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) is neurotropic and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma. METHODSHere, we perform an extensive meta-analysis of ZIKV infection studies to identify molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We summarise the neuroblastoma cell lines and ZIKV strains utilised and re-evaluate the infection data to deduce the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating transcriptomics, interaction proteomics, dependency factor and compound datasets we show the involvement of multiple host systems during ZIKV infection. RESULTSWe identify that most paediatric neuroblastoma cell lines are highly susceptible to ZIKV infection and that the PRVABC59 ZIKV strain is the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV is dependent on SREBP-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV nonstructural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon. CONCLUSIONSOur work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials. KEYPOINTSO_LIThe Zika virus may provide the basis for an oncolytic virotherapy against Neuroblastoma C_LIO_LIMost paediatric neuroblastoma cell lines are susceptible to Zika viral infection C_LIO_LIWe identified molecular mechanisms that may induce the oncolytic response in Neuroblastoma C_LI Contribution to the fieldThe ability to both induce direct oncolysis and provoke an anti-tumoral immune response makes oncolytic virotherapy an attractive candidate to combat aggressive and heterogenous cancers, such as high-risk neuroblastoma. To progress oncolytic virotherapy to clinical trial it is essential to understand the host mechanisms the virus manipulates to kill cancer cells, alongside any pathology as a consequence of infection of normal cells. Here, we show that ZIKV efficiently infects and induces oncolysis of paediatric neuroblastoma cells and propose a potential TNF pathway-driven immune response. ZIKVs specificity for infection of nervous system cancer cells, while rarely causing nervous system-related pathology in young children, addresses many of its safety concerns. The inclusion of more effective and less toxic novel therapies, such as a potential ZIKV-based therapeutic, in multimodal treatment regimens will pave the way for improving patient long-term health and overall survival.

cancer biology↗
bioRxiv2022

Dual inhibition of SHP2 and autophagy suppresses NF1-associated Malignant Peripheral Nerve Sheath Tumors

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas and the primary cause of mortality in patients with neurofibromatosis type 1 (NF1). MPNSTs develop within pre-existing benign plexiform neurofibromas (PNs). PNs are driven solely by biallelic NF1 loss eliciting RAS pathway activation and respond favorably to MEK inhibitor therapy. Our analysis of genetically engineered and orthotopic patient-derived xenograft MPNST indicates that MEK inhibition has poor anti-tumor efficacy. By contrast, upstream inhibition of RAS through the protein-tyrosine phosphatase SHP2 reduced downstream signaling and suppressed NF1 MPNST growth, although resistance eventually emerged. To investigate possible mechanisms of acquired resistance, kinomic analyses of resistant tumors was performed, and data analysis identified enrichment of activated autophagy pathway protein kinases. Combining pharmacological blockade of autophagy and SHP2 inhibition resulted in durable responses in NF1 MPNSTs in both genetic and orthotopic xenograft mouse models. Our studies can be rapidly translated into a clinical trial to evaluate SHP2 inhibition in conjunction with autophagy inhibitors as a novel treatment approach for NF1 MPNSTs. Statement of significanceCurrently, no effective therapies exist for MPNST. We demonstrate intrinsic MPNST resistance to MEKi monotherapy and identify SHP2 inhibition as an actionable vulnerability upstream of RAS. Furthermore, anti-tumor effects are extended and enhanced by dual exposure to autophagy pathway inhibition. Validation of these results as the most effective therapy to date in multiple genetically engineered models and in orthotopic patient-derived xenografts justify a clinical trial to evaluate SHP2i in conjunction with autophagy inhibitors as a novel treatment approach for NF1 MPNSTs.

cancer biology↗
bioRxiv2019

Modeling Resistance and Recurrence Patterns of Combined Targeted- Chemoradiotherapy Predicts Benefit of Shorter Induction Period

The optimal integration of molecularly targeted therapies with concurrent chemotherapy and radiation (CRT) to improve cures in genotype-defined cancers is unknown. Here, we develop a bio-mathematical framework to simulate patterns of local versus distant recurrences in a heterogeneous lung cancer population receiving combined targeted therapy and CRT. Our validated model predicts that targeted induction before CRT, an approach currently being tested in clinical trials, may render adjuvant targeted therapy less effective due to proliferation of drug-resistant cancer cells when using very long induction periods. Furthermore, our simulations not only demonstrate the competing effects of drug-resistant cell expansion versus overall tumor regression as a function of induction length, but can also directly estimate the probability of observing an improvement in progression-free survival at a given cohort size. We thus demonstrate that such stochastic biological simulations have the potential to quantitatively inform the design of multimodality clinical trials in genotype-defined cancers.

biophysics↗
bioRxiv2020

Inferring the infant pain experience: a translational fMRI-based signature approach

BackgroundIn the absence of verbal communication it is challenging to infer an individuals sensory and emotional experience. In adults, fMRI has been used to develop multivariate brain activity signatures, which reliably capture elements of human pain experience. We translate whole-brain fMRI signatures that encode pain perception in adults to the newborn infant brain, to advance understanding of functional brain development and pain perception in early life. MethodsA cohort of adults (n=10; mean age=28.3 years) and 2 cohorts of healthy infants (Cohort A: n=15; Cohort B: n=22; mean postnatal age=3 days) were stimulated with low intensity nociceptive stimuli (64-512mN) during acquisition of functional MRI data. fMRI pain signatures were applied directly to the adult data and transformed such that they could be applied to the infant brain. In each cohort, we assessed the concordance of the signatures with the brain responses using cosine-similarity scores, and we assessed stimulus intensity encoding of the signature responses using Spearman rank correlation. Brain activity in pro-pain and anti-pain brain regions were also examined. FindingsThe Neurologic Pain Signature (NPS), which reflects aspects of nociceptive pain experience, was activated in both the adults and infants, and reliably encoded stimulus intensity. However, the Stimulus Intensity Independent Pain Signature (SIIPS1), which reflects higher-level cognitive modulation of nociceptive input, was only expressed in adults. Pro-pain brain regions showed similar activation patterns in adults and infants, whereas, anti-pain brain regions exhibited divergent responses. InterpretationBasic intensity encoding of nociceptive information is similar in adults and infants. However, translation of adult brain signatures into infants reveals significant differences in infant cerebral processing of nociceptive information, which may reflect their lack of expectation, motivation and contextualisation. This study expands the use of brain activity pain signatures to non-verbal patients and provides a potential approach to assess analgesic interventions in infancy. FundingThis work was funded by Wellcome (Senior Research Fellowship awarded to Prof. Rebeccah Slater) and SSNAP "Support for Sick and Newborn Infants and their Parents" Medical Research Fund (University of Oxford Excellence Fellowship awarded to Dr Eugene Duff). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for research articles published prior to March 2020 using terms including fMRI, infant or neonate, and pain or nociception in the title or abstract. Due to the relatively new emergence of this field, and the experimental and analytical challenges involved in studying cerebral processing of pain in the MRI environment in healthy newborn infants, only five fMRI studies have examined infant brain responses to nociceptive input. In a foundational pilot study, Williams et al., applied an experimental noxious stimulus to a single infant, evoking widespread brain activity that included several brain regions involved in pain processing in adults. Goksan et al., subsequently performed an observational cohort study and used regional analyses to compare active brain regions in infants (n=10) and adults (n=10), concluding that the evoked patterns of brain activity were broadly similar in infants and adults. Further follow-up analysis in the infant cohort revealed that the functional connectivity of brain regions involved in descending pain modulation influences the magnitude of pain-related brain activity. Two further studies focused on methodological advances, providing evidence-based recommendations for fMRI acquisition parameters and image processing in order to maximise the quality of infant data, and these methods have been implemented in this study. Added value of this studyThis study translates validated adult pain fMRI brain signatures to a nonverbal patient population in which the assessment and management of pain presents a significant clinical challenge. Application of fMRI brain signatures to newborn infants expands on previous fMRI studies that provided only qualitative evidence that noxious stimulation commonly activates brain regions in the adult and infant brain. Here we demonstrate that the basic encoding of the sensory discriminative aspects of pain, as represented by the Neurologic Pain Signature (NPS), occurs in both adults and infants, whereas higher-level cognitive modulation of pain, represented by the Stimulus Intensity Independent Pain Signature (SIIPS1) is only present in adults and not observed in infants. The differences in how the immature infant brain processes pain, relative to the mature adult brain, are likely to reflect differences in their expectation, motivation and contextualisation of external events rather than differences in their core nociceptive cerebral processing of pain. This work allows us to use quantitative fMRI observations to make stronger inferences related to pain experience in nonverbal infants. Implications of all the available evidenceBehavioural pain scores used in neonatal clinical care offer limited sensitivity and specificity to pain. Neonatal clinical trials that use these scores as outcome measures frequently report a lack of efficacy of common analgesic interventions, resulting in few evidence-based drugs for treating pain. The value of using brain-based neuroimaging markers of pain as a means of providing objective evidence of analgesic efficacy in early proof of concept studies is well recognised in adults, even in the absence of behavioural pain modulation. Similarly, in infants EEG-based measures of noxious-evoked brain activity have been used as outcome measures in clinical trials of analgesics to overcome some of the inherent limitations of using behavioural observations to quantify analgesic efficacy. Considering the successful translation of the Neurologic Pain Signature (NPS) and its sensitivity to analgesic modulation in adults, this novel methodology represents an objective brain-based fMRI approach that could be used to advance the discovery and assessment of analgesic interventions in infancy.

neuroscience↗
bioRxiv2023

Soft robotics-enabled large animal model of HFpEF hemodynamics for device testing

Heart failure with preserved ejection fraction (HFpEF) is a major challenge in cardiovascular medicine, accounting for approximately 50% of all cases of heart failure. Due to the lack of effective therapies for this condition, the mortality associated with HFpEF remains higher than that of most cancers. Despite the ongoing efforts, no medical device has yet received FDA approval. This is largely due to the lack of an in vivo model of the HFpEF hemodynamics, resulting in the inability to evaluate device effectiveness in vivo prior to clinical trials. Here, we describe the development of a highly tunable porcine model of HFpEF hemodynamics using implantable soft robotic sleeves, where controlled actuation of a left ventricular and an aortic sleeve can recapitulate changes in ventricular compliance and afterload associated with a broad spectrum of HFpEF hemodynamic phenotypes. We demonstrate the feasibility of the proposed model in preclinical testing by evaluating the hemodynamic response of the model post-implantation of an interatrial shunt device, which was found to be consistent with findings from in silico studies and clinical trials. This work addresses several of the limitations associated with previous models of HFpEF, such as their limited hemodynamic fidelity, elevated costs, lengthy development time, and low throughput. By showcasing exceptional versatility and tunability, the proposed platform has the potential to revolutionize the current approach for HFpEF device development and selection, with the goal of improving the quality of life for the 32 million people affected by HFpEF worldwide.

bioengineering↗
bioRxiv2022

Increased severity of chronic kidney disease in response to high potassium intake is dependent on mineralocorticoid receptor activation

Dietary treatment is seminal for management of chronic kidney disease (CKD). The aim of our project was to assess the effects of potassium intake on the progression of CKD. We used 2 mouse CKD models to analyze the effects of potassium intake on CKD : the unilateral ureteral obstruction (UUO) and the POD-ATTAC models. POD-ATTAC mice display a podocyte-specific apoptosis after the administration of a chemical inducer. We also studied the effect of mineralocorticoid receptor (MR) using UUO in kidney tubule-specific MR knockout mice. In both UUO and POD-ATTAC mice, high potassium diet increased interstitial fibrosis. High potassium diet also increased the abundance of the extracellular matrix protein fibronectin and decreased the abundance of the epithelial marker Na+-K+ ATPase. Consistently, POD-ATTAC mice fed with high potassium diet displayed lower glomerular filtration rate. Spironolactone, a MR antagonist, decreased fibrosis induced by high potassium diet in POD-ATTAC mice. However, kidney tubule-specific MR knockout did not improve the fibrotic lesions induced by UUO under normal or high potassium diets. Macrophages from high potassium-fed POD-ATTAC mice displayed higher mRNA levels of the pro-inflammatory chemokine MCP1. This effect was decreased by spironolactone, suggesting a role of MR signaling in myeloid cells in the pro-fibrotic effect of potassium-rich diet. High potassium intake generates more fibrosis leading to decreased kidney function in experimental CKD. MR signaling plays a pivotal role in this potassium-induced fibrosis. The effect of reducing potassium intake on CKD progression should be assessed in future clinical trials. Translational statementDietetic approach is a cheap and effective therapy to slow down the development of chronic kidney diseases and kidney fibrosis. Potassium-rich diets are protective against renal and cardiovascular events in the general population, albeit some conflicting data were obtained in patients with chronic kidney disease. We showed that potassium-rich diet accelerates fibrosis development, by enhancing kidney inflammation in two mouse models of chronic kidney disease. These data suggest that potassium-rich diets should not be advised in patients with chronic kidney disease, unless future clinical trials demonstrate any beneficial effect in these patients.

physiology↗
bioRxiv2020

Mitochondrial determinants of response and resistance to venetoclax plus cytarabine duplet therapy in acute myeloid leukemia

The development of resistance to conventional and targeted therapy represents a major clinical barrier in treatment of acute myeloid leukemia (AML). We show that the resistance to cytarabine (AraC) and its associated mitochondrial phenotype were reversed by genetic silencing or pharmacological inhibition of BCL2 in a caspase-dependent manner. BCL2-inhibitor venetoclax (VEN) enhancement of AraC efficacy was independent of differentiation phenotype, a characteristic of response to another combination of VEN with hypomethylating agents (HMA). Furthermore, transcriptional profiles of patients with low response to VEN+AraC mirrored those of low responders to VEN+HMA in clinical trials. OxPHOS was found to be a patient stratification marker predictive of effective response to VEN+AraC but not to VEN+AZA. Importantly, whereas three cell subpopulations specifically emerged in VEN+AraC residual disease and were characterized by distinct developmental and transcriptional programs largely driven by MITF, E2F4 and p53 regulons, they each encoded proteins involved in assembly of NADH dehydrogenase complex. Notably, treatment of VEN+AraC-persisting AML cells with an ETCI inhibitor significantly increased the time-to-relapse in vivo. These findings provide the scientific rationale for new clinical trials of VEN+AraC combinations, especially in patients relapsing or non-responsive to chemotherapy, or after failure of frontline VEN+HMA regimen.

cancer biology↗
bioRxiv2025

Social interactions shape antiviral resistance outcomes in poliovirus via eco-evolutionary feedback

Antiviral resistance evolution poses a major obstacle for controlling viral infections. A promising strategy is to target shared viral proteins that allow drug susceptible viruses to sensitize resistant ones during cellular coinfection, muting selection for resistance. Pocapavir, a poliovirus capsid inhibitor, employs this sociovirological strategy. While susceptible viruses significantly suppressed resistance in the presence of pocapavir in cell culture, a pocapavir clinical trial observed widespread resistance evolution and limited improvements to clearance times. To reconcile these findings, we present an intra-host eco-evolutionary model of poliovirus in the presence of pocapavir, which reproduces both the potent interference observed in vitro and the resistance emergence seen in patients. In the short term, our model predicts that a high density of susceptible viruses sensitizes resistant ones to pocapavir, mirroring cell culture results. However, over multiple replication cycles, pocapavirs high potency collapses viral density, which reduces coinfection and allows resistance to evolve as observed in the clinical trial. Since coinfection is essential to suppress resistance, enabling greater survival of susceptible viruses could offer therapeutic advantages. Counterintuitively, we demonstrate that this can be achieved by lessening antiviral potency, which can limit resistance evolution while also maintaining a low viral load. These findings suggest that antivirals that rely on viral intracellular interaction must balance immediate neutralization with the preservation of future coinfection, yielding more sustained inhibition. Explicitly considering the eco-evolutionary feedback encompassing viral density, shared phenotypes and absolute fitness not only provides new insights into designing effective therapies but also illuminates viral evolutionary dynamics more broadly.

evolutionary biology↗
bioRxiv2017

Pair Matcher (PaM): Fast Model-Based Optimisation Of Treatment/Case-Control Matches Using Demographic And Genetic Data

In clinical trials, individuals are matched for demographic criteria, paired, and then randomly assigned to treatment and control groups to determine a drugs efficacy. The successful completion of pilot trials is a prerequisite to larger and more expensive Phase III trials. One of the chief causes for the irreproducibility of results across pilot to Phase III trials is population stratification bias caused by the uneven distribution of ancestries in the treatment and control groups. Pair Matcher (PaM) addresses stratification bias by optimising pairing assignments a priori- and\\or posteriori to the trial using both genetic and demographic criteria. Using simulated and real datasets, we show that PaM identifies ideal and near-ideal pairs that are more genetically homogeneous than those identified based on racial criteria or Principal Component Analysis (PCA) alone. Homogenising the treatment (or case) and control groups can be expected to improve the accuracy and reproducibility of the study. PaMs ability to infer the ancestry of the participants further allows identifying subgroup of responders and developing a precision medicine approach to treatment. PaM is simple to execute, fast, and can be used for clinical trials and association studies. PaM is freely available via R scripts and a web interface.

bioinformatics↗