Hypothesis-free detection of gene-interaction effects on biomarker concentration in UK Biobank using variance prioritisation

Blood biomarkers include disease intervention targets that may interact with genetic and environmental factors resulting in subgroups of individuals who respond differently to treatment. Such interactions may be observed in genetic effects on trait variance. Variance prioritisation is an approach to identify genetic loci with interaction effects by estimating their association with trait variance, even where the modifier is unknown or unmeasured. Here, we develop and evaluate a regression-based Brown-Forsythe test and variance effect estimate to detect such interactions. We provide scalable open-source software (varGWAS) for genome-wide association analysis of SNP-variance effects (https://github.com/MRCIEU/varGWAS) and apply our software to 30 blood biomarkers in UK Biobank. We find 468 variance quantitative trait loci across 24 biomarkers and follow up findings to detect 82 gene-environment and six gene-gene interactions independent of strong scale or phantom effects. Our results replicate existing findings and identify novel epistatic effects of TREH rs12225548 x FUT2 rs281379 and TREH rs12225548 x ABO rs635634 on alkaline phosphatase and ZNF827 rs4835265 x NEDD4L rs4503880 on gamma glutamyltransferase. These data could be used to discover possible subgroup effects for a given biomarker during preclinical drug development.

The Development of Sleep/Wake Disruption and Cataplexy as Hypocretin/Orexin Neurons Degenerate in Male vs. Female Orexin/tTA; TetO-DTA Mice

Narcolepsy Type 1 (NT1), a sleep disorder with similar prevalence in both sexes, is thought to be due to loss of the hypocretin/orexin (Hcrt) neurons. Several transgenic strains have been created to model this disorder and are increasingly being used for preclinical drug development and basic science studies, yet most studies have solely used male mice. We compared the development of narcoleptic symptomatology in male vs. female orexin-tTA; TetO-DTA mice, a model in which Hcrt neuron degeneration can be initiated by removal of doxycycline (DOX) from the diet. EEG, EMG, body temperature, gross motor activity and video recordings were conducted for 24-h at baseline and 1, 2, 4 and 6 weeks after DOX removal. Female DTA mice exhibited cataplexy, the pathognomonic symptom of NT1, by Week 1 in the DOX(-) condition but cataplexy was not consistently present in males until Week 2. By Week 2, both sexes showed an impaired ability to sustain long wake bouts during the active period, the murine equivalent of excessive daytime sleepiness in NT1. Body temperature appeared to be regulated at lower levels in both sexes as the Hcrt neurons degenerated. During degeneration, both sexes also exhibited the Delta State, characterized by sudden cessation of activity, high delta activity in the EEG, maintenance of muscle tone and posture, and the absence of phasic EMG activity. Since the phenotypes of the two sexes were indistinguishable by Week 6, we conclude that both sexes can be safely combined in future studies to reduce cost and animal use.

Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs

We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia–telangiectasia-mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately 8 days post-tumour injection. Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article, we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development.

Progress and Challenges in the Use of a Liver-on-a-Chip for Hepatotropic Infectious Diseases

The liver is a target organ of life-threatening pathogens and prominently contributes to the variation in drug responses and drug-induced liver injury among patients. Currently available drugs significantly decrease the morbidity and mortality of liver-dwelling pathogens worldwide; however, emerging clinical evidence reveals the importance of host factors in the design of safe and effective therapies for individuals, known as personalized medicine. Given the primary adherence of cells in conventional two-dimensional culture, the use of these one-size-fit-to-all models in preclinical drug development can lead to substantial failures in assessing therapeutic safety and efficacy. Advances in stem cell biology, bioengineering and material sciences allow us to develop a more physiologically relevant model that is capable of recapitulating the human liver. This report reviews the current use of liver-on-a-chip models of hepatotropic infectious diseases in the context of precision medicine including hepatitis virus and malaria parasites, assesses patient-specific responses to antiviral drugs, and designs personalized therapeutic treatments to address the need for a personalized liver-like model. Second, most organs-on-chips lack a monitoring system for cell functions in real time; thus, the review discusses recent advances and challenges in combining liver-on-a-chip technology with biosensors for assessing hepatocyte viability and functions. Prospectively, the biosensor-integrated liver-on-a-chip device would provide novel biological insights that could accelerate the development of novel therapeutic compounds.

Comparative analysis of molecular representations in prediction of cancer drug combination synergy and sensitivity

Application of machine and deep learning (ML/DL) methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel DL solutions in relation to established techniques. To this end we compare rule-based and data-driven molecular representations in prediction of drug combination sensitivity and drug synergy scores using standardized results of 14 high throughput screening studies, comprising 64,200 unique combinations of 4,153 molecules tested in 112 cancer cell lines. We evaluate the clustering performance of molecular fingerprints and quantify their similarity by adapting Centred Kernel Alignment metric. Our work demonstrates that in order to identify an optimal representation type it is necessary to supplement quantitative benchmark results with qualitative considerations, such as model interpretability and robustness, which may vary between and throughout preclinical drug development projects.

Microfluidic and Organ-on-a-Chip Approaches to Investigate Cellular and Microenvironmental Contributions to Cardiovascular Function and Pathology

Over the past decade, advances in microfabrication and biomaterials have facilitated the development of microfluidic tissue and organ models to address challenges with conventional animal and cell culture systems. These systems have largely been developed for human disease modeling and preclinical drug development and have been increasingly used to understand cellular and molecular mechanisms, particularly in the cardiovascular system where the characteristic mechanics and architecture are difficult to recapitulate in traditional systems. Here, we review recent microfluidic approaches to model the cardiovascular system and novel insights provided by these systems. Key features of microfluidic approaches include the ability to pattern cells and extracellular matrix (ECM) at cellular length scales and the ability to use patient-derived cells. We focus the review on approaches that have leveraged these features to explore the relationship between genetic mutations and the microenvironment in cardiovascular disease progression. Additionally, we discuss limitations and benefits of the various approaches, and conclude by considering the role further advances in microfabrication technology and biochemistry techniques play in establishing microfluidic cardiovascular disease models as central tools for understanding biological mechanisms and for developing interventional strategies.

Immunotherapies and Metastatic Cancers: Understanding Utility and Predictivity of Human Immune Cell Engrafted Mice in Preclinical Drug Development

Metastases cause high mortality in several cancers and immunotherapies are expected to be effective in the prevention and treatment of metastatic disease. However, only a minority of patients benefit from immunotherapies. This creates a need for novel therapies that are efficacious regardless of the cancer types and metastatic environments they are growing in. Preclinical immuno-oncology models for studying metastases have long been limited to syngeneic or carcinogenesis-inducible models that have murine cancer and immune cells. However, the translational power of these models has been questioned. Interactions between tumor and immune cells are often species-specific and regulated by different cytokines in mice and humans. For increased translational power, mice engrafted with functional parts of human immune system have been developed. These humanized mice are utilized to advance understanding the role of immune cells in the metastatic process, but increasingly also to study the efficacy and safety of novel immunotherapies. From these aspects, this review will discuss the role of immune cells in the metastatic process and the utility of humanized mouse models in immuno-oncology research for metastatic cancers, covering several models from the perspective of efficacy and safety of immunotherapies.