A metabolic-dysfunction associated steatotic liver acinus biomimetic induces pancreatic islet dysfunction in a coupled microphysiology system.

Preclinical and clinical studies suggest that lipid-induced hepatic insulin resistance is a primary defect that predisposes to dysfunction in pancreatic islets, implicating a perturbed liver-pancreas axis underlying the comorbidity of T2DM and MASLD. To investigate this hypothesis, we developed a human biomimetic microphysiological system (MPS) coupling our vascularized liver acinus MPS (vLAMPS) with primary islets on a chip (PANIS) enabling MASLD progression and islet dysfunction to be quantitatively assessed. The modular design of this system (vLAMPS-PANIS) allows intra-organ and inter-organ dysregulation to be deconvoluted. When compared to normal fasting (NF) conditions, under early metabolic syndrome (EMS) conditions, the standalone vLAMPS exhibited characteristics of early stage MASLD, while no significant differences were observed in the standalone PANIS. In contrast, with EMS, the coupled vLAMPS-PANIS exhibited a perturbed islet-specific secretome and a significantly dysregulated glucose stimulated insulin secretion (GSIS) response implicating direct signaling from the dysregulated liver acinus to the islets. Correlations between several pairs of a vLAMPS-derived and a PANIS-derived secreted factors were significantly altered under EMS, as compared to NF conditions, mechanistically connecting MASLD and T2DM associated hepatic factors with islet-derived GLP-1 synthesis and regulation. Since vLAMPS-PANIS is compatible with patient-specific iPSCs, this platform represents an important step towards addressing patient heterogeneity, identifying complex disease mechanisms, and advancing precision medicine.

Comparison of Wild-Type and High-risk PNPLA3 variants in a Human Biomimetic Liver Microphysiology System for Metabolic Dysfunction-associated Steatotic Liver Disease Precision Therapy.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a worldwide health epidemic with a global occurrence of approximately 30%. The pathogenesis of MASLD is a complex, multisystem disorder driven by multiple factors including genetics, lifestyle, and the environment. Patient heterogeneity presents challenges for developing MASLD therapeutics, creation of patient cohorts for clinical trials and optimization of therapeutic strategies for specific patient cohorts. Implementing pre-clinical experimental models for drug development creates a significant challenge as simple in vitro systems and animal models do not fully recapitulate critical steps in the pathogenesis and the complexity of MASLD progression. To address this, we implemented a precision medicine strategy that couples the use of our liver acinus microphysiology system (LAMPS) constructed with patient-derived primary cells. We investigated the MASLD-associated genetic variant PNPLA3 rs738409 (I148M variant) in primary hepatocytes, as it is associated with MASLD progression. We constructed LAMPS with genotyped wild type and variant PNPLA3 hepatocytes together with key non-parenchymal cells and quantified the reproducibility of the model. We altered media components to mimic blood chemistries, including insulin, glucose, free fatty acids, and immune activating molecules to reflect normal fasting (NF), early metabolic syndrome (EMS) and late metabolic syndrome (LMS) conditions. Finally, we investigated the response to treatment with resmetirom, an approved drug for metabolic syndrome-associated steatohepatitis (MASH), the progressive form of MASLD. This study using primary cells serves as a benchmark for studies using patient biomimetic twins constructed with patient iPSC-derived liver cells using a panel of reproducible metrics. We observed increased steatosis, immune activation, stellate cell activation and secretion of pro-fibrotic markers in the PNPLA3 GG variant compared to wild type CC LAMPS, consistent with the clinical characterization of this variant. We also observed greater resmetirom efficacy in PNPLA3 wild type CC LAMPS compared to the GG variant in multiple MASLD metrics including steatosis, stellate cell activation and the secretion of pro-fibrotic markers. In conclusion, our study demonstrates the capability of the LAMPS platform for the development of MASLD precision therapeutics, enrichment of patient cohorts for clinical trials, and optimization of therapeutic strategies for patient subgroups with different clinical traits and disease stages.

Modeling mechanisms underlying differential inflammatory responses to COVID-19 in type 2 diabetes using a patient-derived microphysiological organ-on-a-chip system.

Background: COVID-19 pandemic has caused more than 6 million deaths worldwide. Co-morbid conditions such as Type 2 Diabetes (T2D) have increased mortality in COVID-19. With limited translatability of in vitro and small animal models to human disease, human organ-on-a-chip models are an attractive platform to model in vivo disease conditions and test potential therapeutics. Methods: T2D or non-diabetic patient-derived macrophages and human liver sinusoidal endothelial cells were seeded, along with normal hepatocytes and stellate cells in the liver-on-a-chip (LAMPS - liver acinus micro physiological system), perfused with media mimicking non-diabetic fasting or T2D (high levels of glucose, fatty acids, insulin, glucagon) states. The macrophages and endothelial cells were transduced to overexpress the SARS-CoV2-S (spike) protein with appropriate controls before their incorporation into LAMPS. Cytokine concentrations in the efflux served as a read-out of the effects of S-protein expression in the different experimental conditions (non-diabetic-LAMPS, T2D-LAMPS), including incubation with tocilizumab, an FDA-approved drug for severe COVID-19. Findings: S-protein expression in the non-diabetic LAMPS led to increased cytokines, but in the T2D-LAMPS, this was significantly amplified both in the number and magnitude of key pro-inflammatory cytokines (IL6, CCL3, IL1ß, IL2, TNFα, etc.) involved in cytokine storm syndrome (CSS), mimicking severe COVID-19 infection in T2D patients. Compared to vehicle control, tocilizumab (IL6-receptor antagonist) decreased the pro-inflammatory cytokine secretion in T2D-COVID-19-LAMPS but not in non-diabetic-COVID-19-LAMPS. Interpretation: macrophages and endothelial cells play a synergistic role in the pathophysiology of the hyper-inflammatory response seen with COVID-19 and T2D. The effect of Tocilizumab was consistent with large clinical trials that demonstrated Tocilizumab's efficacy only in critically ill patients with severe disease, providing confirmatory evidence that the T2D-COVID-19-LAMPS is a robust platform to model human in vivo pathophysiology of COVID-19 in T2D and for screening potential therapeutics.

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury.

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies.

Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials.

Quantifying the progression of non-alcoholic fatty liver disease in human biomimetic liver microphysiology systems with fluorescent protein biosensors.

Metabolic syndrome is a complex disease that involves multiple organ systems including a critical role for the liver. Non-alcoholic fatty liver disease (NAFLD) is a key component of the metabolic syndrome and fatty liver is linked to a range of metabolic dysfunctions that occur in approximately 25% of the population. A panel of experts recently agreed that the acronym, NAFLD, did not properly characterize this heterogeneous disease given the associated metabolic abnormalities such as type 2 diabetes mellitus (T2D), obesity, and hypertension. Therefore, metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed as the new term to cover the heterogeneity identified in the NAFLD patient population. Although many rodent models of NAFLD/NASH have been developed, they do not recapitulate the full disease spectrum in patients. Therefore, a platform has evolved initially focused on human biomimetic liver microphysiology systems that integrates fluorescent protein biosensors along with other key metrics, the microphysiology systems database, and quantitative systems pharmacology. Quantitative systems pharmacology is being applied to investigate the mechanisms of NAFLD/MAFLD progression to select molecular targets for fluorescent protein biosensors, to integrate computational and experimental methods to predict drugs for repurposing, and to facilitate novel drug development. Fluorescent protein biosensors are critical components of the platform since they enable monitoring of the pathophysiology of disease progression by defining and quantifying the temporal and spatial dynamics of protein functions in the biosensor cells, and serve as minimally invasive biomarkers of the physiological state of the microphysiology system experimental disease models. Here, we summarize the progress in developing human microphysiology system disease models of NAFLD/MAFLD from several laboratories, developing fluorescent protein biosensors to monitor and to measure NAFLD/MAFLD disease progression and implementation of quantitative systems pharmacology with the goal of repurposing drugs and guiding the creation of novel therapeutics.

Drug-Drug Interaction Between Oxycodone and Diazepam by a Combined in Silico Pharmacokinetic and Pharmacodynamic Modeling Approach.

Opioids and benzodiazepines have complex drug-drug interactions (DDIs), which serve as an important source of adverse drug effects. In this work, we predicted the DDI between oxycodone (OXY) and diazepam (DZP) in the human body by applying in silico pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation. First, we studied the PK interaction between OXY and DZP with a physiologically based pharmacokinetic (PBPK) model. Second, we applied molecular modeling techniques including molecular docking, molecular dynamics (MD) simulation, and the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) free energy method to predict the PD-DDI between these two drugs. The PK interaction between OXY and DZP predicted by the PBPK model was not obvious. No significant interaction was observed between the two drugs at normal doses, though very high doses of DZP demonstrated a non-negligible inhibitory effect on OXY metabolism. On the contrary, the molecular modeling study shows that DZP has potential to compete with OXY at the same binding pocket of the active µ-opioid receptor (MOR) and κ-opioid receptor (KOR). MD simulation and MM-PBSA calculation results demonstrated that there is likely a synergetic effect between OXY and DZP binding to opioid receptors, as OXY is likely to target the active MOR while DZP selectively binds to the active KOR. Thus, pharmacokinetics contributes slightly to the DDI between OXY and DZP although an overdose of DZP has been brought to attention. Pharmacodynamics is likely to play a more important role than pharmacokinetics in revealing the mechanism of DDI between OXY and DZP.

Human biomimetic liver microphysiology systems in drug development and precision medicine.

Microphysiology systems (MPS), also called organs-on-chips and tissue chips, are miniaturized functional units of organs constructed with multiple cell types under a variety of physical and biochemical environmental cues that complement animal models as part of a new paradigm of drug discovery and development. Biomimetic human liver MPS have evolved from simpler 2D cell models, spheroids and organoids to address the increasing need to understand patient-specific mechanisms of complex and rare diseases, the response to therapeutic treatments, and the absorption, distribution, metabolism, excretion and toxicity of potential therapeutics. The parallel development and application of transdisciplinary technologies, including microfluidic devices, bioprinting, engineered matrix materials, defined physiological and pathophysiological media, patient-derived primary cells, and pluripotent stem cells as well as synthetic biology to engineer cell genes and functions, have created the potential to produce patient-specific, biomimetic MPS for detailed mechanistic studies. It is projected that success in the development and maturation of patient-derived MPS with known genotypes and fully matured adult phenotypes will lead to advanced applications in precision medicine. In this Review, we examine human biomimetic liver MPS that are designed to recapitulate the liver acinus structure and functions to enhance our knowledge of the mechanisms of disease progression and of the absorption, distribution, metabolism, excretion and toxicity of therapeutic candidates and drugs as well as to evaluate their mechanisms of action and their application in precision medicine and preclinical trials.

A 3D microfluidic liver model for high throughput compound toxicity screening in the OrganoPlate®.

We report the development, automation and validation of a 3D, microfluidic liver-on-a-chip for high throughput hepatotoxicity screening, the OrganoPlate LiverTox™. The model is comprised of aggregates of induced pluripotent stem cell (iPSC)-derived hepatocytes (iHep) seeded in an extracellular matrix in the organ channel and co-cultured with endothelial cells and THP-1 monoblasts differentiated to macrophages seeded in the vascular channel of the 96 well Mimetas OrganoPlate 2-lane. A key component of high throughput screening is automation and we report a protocol to seed, dose, collect and replenish media and add assay reagents in the OrganoPlate 2-lane using a standard laboratory liquid handling robot. A combination of secretome measurements and image-based analysis was used to demonstrate stable 15 day cell viability, albumin and urea secretion. Over the same time-period, CYP3A4 activity increased and alpha-fetoprotein secretion decreased suggesting further maturation of the iHeps. Troglitazone, a clinical hepatotoxin, was chosen as a control compound for validation studies. Albumin, urea, hepatocyte nuclear size and viability staining provided Robust Z'factors > 0.2 in plates treated 72 h with 180 µM troglitazone compared with a vehicle control. The viability assay provided the most robust statistic for a Robust Z' factor = 0.6. A small library of 159 compounds with known liver effects was added to the OrganoPlate LiverTox model for 72 h at 50 µM and the Toxicological Prioritization scores were calculated. A follow up dose-response evaluation of select hits revealed the albumin assay to be the most sensitive in calculating TC50 values. This platform provides a robust, novel model which can be used for high throughput hepatotoxicity screening.

Analysis of reproducibility and robustness of a human microfluidic four-cell liver acinus microphysiology system (LAMPS).

A human microfluidic four-cell liver acinus microphysiology system (LAMPS), was evaluated for reproducibility and robustness as a model for drug pharmacokinetics and toxicology. The model was constructed using primary human hepatocytes or human induced pluripotent stem cell (iPSC)-derived hepatocytes and 3 human cell lines for the endothelial, Kupffer and stellate cells. The model was tested in two laboratories and demonstrated to be reproducible in terms of basal function of hepatocytes, Terfenadine metabolism, and effects of Tolcapone (88 µM), Troglitazone (150 µM), and caffeine (600 µM) over 9 days in culture. Additional experiments compared basal outputs of albumin, urea, lactate dehydrogenase (LDH) and tumor necrosis factor (TNF)α, as well as drug metabolism and toxicity in the LAMPS model, and in 2D cultures seeded with either primary hepatocytes or iPSC-hepatocytes. Further experiments to study the effects of Terfenadine (10 µM), Tolcapone (88 µM), Trovafloxacin (150 µM with or without 1 µg/mL lipopolysaccharide), Troglitazone (28 µM), Rosiglitazone (0.8 µM), Pioglitazone (3 µM), and caffeine (600 µM) were carried out over 10 days. We found that both primary human hepatocytes and iPSC-derived hepatocytes in 3D culture maintained excellent basal liver function and Terfenadine metabolism over 10 days compared the same cells in 2D cultures. In 2D, non-overlay monolayer cultures, both cell types lost hepatocyte phenotypes after 48 h. With respect to drug effects, both cell types demonstrated comparable and more human-relevant effects in LAMPS, as compared to 2D cultures. Overall, these studies show that LAMPS is a robust and reproducible in vitro liver model, comparable in performance when seeded with either primary human hepatocytes or iPSC-derived hepatocytes, and more physiologically and clinically relevant than 2D monolayer cultures.

Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks.

An unmet clinical need in solid tumor cancers is the ability to harness the intrinsic spatial information in primary tumors that can be exploited to optimize prognostics, diagnostics and therapeutic strategies for precision medicine. Here, we develop a transformational spatial analytics computational and systems biology platform (SpAn) that predicts clinical outcomes and captures emergent spatial biology that can potentially inform therapeutic strategies. We apply SpAn to primary tumor tissue samples from a cohort of 432 chemo-naïve colorectal cancer (CRC) patients iteratively labeled with a highly multiplexed (hyperplexed) panel of 55 fluorescently tagged antibodies. We show that SpAn predicts the 5-year risk of CRC recurrence with a mean AUROC of 88.5% (SE of 0.1%), significantly better than current state-of-the-art methods. Additionally, SpAn infers the emergent network biology of tumor microenvironment spatial domains revealing a spatially-mediated role of CRC consensus molecular subtype features with the potential to inform precision medicine.

Development and Optimization of a High-Content Analysis Platform to Identify Suppressors of Lamin B1 Overexpression as a Therapeutic Strategy for Autosomal Dominant Leukodystrophy.

Autosomal dominant leukodystrophy (ADLD) is a fatal, progressive adult-onset disease characterized by widespread central nervous system (CNS) demyelination and significant morbidity. The late age of onset together with the relatively slow disease progression provides a large therapeutic window for the disorder. However, no treatment exists for ADLD, representing an urgent and unmet clinical need. We have previously shown that ADLD is caused by duplications of the lamin B1 gene causing increased expression of the lamin B1 protein, a major constituent of the nuclear lamina, and demonstrated that transgenic mice with oligodendrocyte-specific overexpression of lamin B1 exhibit temporal and histopathological features reminiscent of the human disease. As increased levels of lamin B1 are the causative event triggering ADLD, approaches aimed at reducing lamin B1 levels and associated functional consequences represent a promising strategy for discovery of small-molecule ADLD therapeutics. To this end, we have created an inducible cell culture model of lamin B1 overexpression and developed high-content analysis in connection with multivariate analysis to define, analyze, and quantify lamin B1 expression and its associated abnormal nuclear phenotype in mouse embryonic fibroblasts (MEFs). The assay has been optimized to meet high-throughput screening (HTS) criteria in multiday variability studies. To control for batch-to-batch variation in the primary MEFs, we have implemented a screening strategy that employs sentinel cells to avoid costly losses during HTS. We posit the assay will identify bona fide suppressors of lamin B1 pathophysiology as candidates for development into potential therapies for ADLD.

Applications of the microphysiology systems database for experimental ADME-Tox and disease models.

To accelerate the development and application of Microphysiological Systems (MPS) in biomedical research and drug discovery/development, a centralized resource is required to provide the detailed design, application, and performance data that enables industry and research scientists to select, optimize, and/or develop new MPS solutions, as well as to harness data from MPS models. We have previously implemented an open source Microphysiology Systems Database (MPS-Db), with a simple icon driven interface, as a resource for MPS researchers and drug discovery/development scientists (https://mps.csb.pitt.edu). The MPS-Db captures and aggregates data from MPS, ranging from static microplate models to integrated, multi-organ microfluidic models, and associates those data with reference data from chemical, biochemical, pre-clinical, clinical and post-marketing sources to support the design, development, validation, application and interpretation of the models. The MPS-Db enables users to manage their multifactor, multichip studies, then upload, analyze, review, computationally model and share data. Here we discuss how the sharing of MPS study data in the MS-Db is under user control and can be kept private to the individual user, shared with a select group of collaborators, or be made accessible to the general scientific community. We also present a test case using our liver acinus MPS model (LAMPS) as an example and discuss the use of the MPS-Db in managing, designing, and analyzing MPS study data, assessing the reproducibility of MPS models, and evaluating the concordance of MPS model results with clinical findings. We introduce the Disease Portal module with links to resources for the design of MPS disease models and studies and discuss the integration of computational models for the prediction of PK/PD and disease pathways using data generated from MPS models.

Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology.

Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.

Modeling the Effect of the Metastatic Microenvironment on Phenotypes Conferred by Estrogen Receptor Mutations Using a Human Liver Microphysiological System.

Reciprocal coevolution of tumors and their microenvironments underlies disease progression, yet intrinsic limitations of patient-derived xenografts and simpler cell-based models present challenges towards a deeper understanding of these intercellular communication networks. To help overcome these barriers and complement existing models, we have developed a human microphysiological system (MPS) model of the human liver acinus, a common metastatic site, and have applied this system to estrogen receptor (ER)+ breast cancer. In addition to their hallmark constitutive (but ER-dependent) growth phenotype, different ESR1 missense mutations, prominently observed during estrogen deprivation therapy, confer distinct estrogen-enhanced growth and drug resistant phenotypes not evident under cell autonomous conditions. Under low molecular oxygen within the physiological range (~5-20%) of the normal liver acinus, the estrogen-enhanced growth phenotypes are lost, a dependency not observed in monoculture. In contrast, the constitutive growth phenotypes are invariant within this range of molecular oxygen suggesting that ESR1 mutations confer a growth advantage not only during estrogen deprivation but also at lower oxygen levels. We discuss the prospects and limitations of implementing human MPS, especially in conjunction with in situ single cell hyperplexed computational pathology platforms, to identify biomarkers mechanistically linked to disease progression that inform optimal therapeutic strategies for patients.

A High-Throughput Assay for DNA Replication Inhibitors Based upon Multivariate Analysis of Yeast Growth Kinetics.

Mcm2-7 is the molecular motor of eukaryotic replicative helicase, and the regulation of this complex is a major focus of cellular S-phase regulation. Despite its cellular importance, few small-molecule inhibitors of this complex are known. Based upon our genetic analysis of synthetic growth defects between mcm alleles and a range of other alleles, we have developed a high-throughput screening (HTS) assay using a well-characterized mcm mutant (containing the mcm2DENQ allele) to identify small molecules that replicate such synthetic growth defects. During assay development, we found that aphidicolin (inhibitor of DNA polymerase alpha) and XL413 (inhibitor of the DNA replication-dependent kinase CDC7) preferentially inhibited growth of the mcm2DENQ strain relative to the wild-type parental strain. However, as both strains demonstrated some degree of growth inhibition with these compounds, small and variable assay windows can result. To increase assay sensitivity and reproducibility, we developed a strategy combining the analysis of cell growth kinetics with linear discriminant analysis (LDA). We found that LDA greatly improved assay performance and captured a greater range of synthetic growth inhibition phenotypes, yielding a versatile analysis platform conforming to HTS requirements.

A glass-based, continuously zonated and vascularized human liver acinus microphysiological system (vLAMPS) designed for experimental modeling of diseases and ADME/TOX.

The vLAMPS is a human, biomimetic liver MPS, in which the ECM and cell seeding of the intermediate layer prior to assembly, simplifies construction of the model and makes the platform user-friendly. This primarily glass microfluidic device is optimal for real-time imaging, while minimizing the binding of hydrophobic drugs/biologics to the materials that constitute the device. The assembly of the three layered device with primary human hepatocytes and liver sinusoidal endothelial cells (LSECs), and human cell lines for stellate and Kupffer cells, creates a vascular channel separated from the hepatic channel (chamber) by a porous membrane that allows communication between channels, recapitulating the 3D structure of the liver acinus. The vascular channel can be used to deliver drugs, immune cells, as well as various circulating cells and other factors to a stand-alone liver MPS and/or to couple the liver MPS to other organ MPS. We have successfully created continuous oxygen zonation by controlling the flow rates of media in the distinct vascular and hepatic channels and validated the computational modeling of zonation with oxygen sensitive and insensitive beads. This allows the direct investigation of the role of zonation in physiology, toxicology and disease progression. The vascular channel is lined with human LSECs, recapitulating partial immunologic functions within the liver sinusoid, including the activation of LSECs, promoting the binding of polymorphonuclear leukocytes (PMNs) followed by transmigration into the hepatic chamber. The vLAMPS is a valuable platform to investigate the functions of the healthy and diseased human liver using all primary human cell types and/or iPSC-derived cells.

Integrating Analysis of Cellular Heterogeneity in High-Content Dose-Response Studies.

Heterogeneity is a complex property of cellular systems and therefore presents challenges to the reliable identification and characterization. Large-scale biology projects may span many months, requiring a systematic approach to quality control to track reproducibility and correct for instrumental variation and assay drift that could mask biological heterogeneity and preclude comparisons of heterogeneity between runs or even between plates. However, presently there is no standard approach to the tracking and analysis of heterogeneity. Previously, we demonstrated the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in a screen and described the use of three heterogeneity indices as a means to characterize, filter, and browse cellular heterogeneity in big data sets (Gough et al., Methods 96:12-26, 2016). In this chapter, we present a detailed method for integrating the analysis of cellular heterogeneity in assay development, validation, screening, and post screen. Importantly, we provide a detailed method for quality control, to normalize cellular data, track heterogeneity over time, and analyze heterogeneity in big data sets, along with software tools to assist in that process. The example screen for this method is from an HCS project, but the approach applies equally to other experimental methods that measure populations of cells.

Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images.

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. Cancer Res; 77(21); e71-74. ©2017 AACR.

Exploiting Analysis of Heterogeneity to Increase the Information Content Extracted from Fluorescence Micrographs of Transgenic Zebrafish Embryos.

Zebrafish embryos are a near-ideal animal model for drug discovery because of their high genetic and physiological similarity to mammals, small size, high fecundity, and optical transparency. The latter properties make zebrafish at larval stages especially suited for high-content analysis and high throughput screening (HTS). However, inherent biological complexity and the inability to screen multiple specimens in a single well present a challenge for HTS because limiting replicates and high variability often prevent assays from reaching the stringent performance criteria demanded of large-scale screening assays. In this report, we present methodology that overcomes these obstacles. We used our previously developed Tg(lhx1a:EGFP)pt303 line, which expresses a fluorescent transgene that enables live real-time measurements of kidney progenitor cell expansion. Since transgenes are expressed in specific cell populations, whose localization is precisely controlled, both spatially and temporally, we considered the developing embryo to be a "host" for a cell population, analogous to a well of a cell culture microplate, rather than a single specimen. By adopting this view, parameters routinely used to analyze cultured cells became applicable to characterize and quantify zebrafish transgene appearance beyond the overall intensity or area measurements, which are analogous to calculating well average data. Using the pixel-level distribution of transgene intensity as a proxy to cell-level data, we applied population-based intensity and heterogeneity measurements to quantitatively describe and characterize transgene expression in each embryo. Subsequent linear discriminant analysis on eight such parameters captured and condensed this information into a single assay parameter that maximizes the difference between positive and negative responses. The improvements in assay performance resulted in the Tg(lhx1a:EGFP)pt303 assay achieving HTS compatible assay performance in multi-day variability studies, documenting readiness for HTS of compounds that expand kidney progenitor cell populations.