Clinically Observed Estrogen Receptor Alpha Mutations within the Ligand-Binding Domain Confer Distinguishable Phenotypes.

OBJECTIVE: Twenty to fifty percent of estrogen receptor-positive (ER+) metastatic breast cancers express mutations within the ER ligand-binding domain. While most studies focused on the constitutive ER signaling activity commonly engendered by these mutations selected during estrogen deprivation therapy, our study was aimed at investigating distinctive phenotypes conferred by different mutations within this class. METHODS: We examined the two most prevalent mutations, D538G and Y537S, employing corroborative genome-edited and lentiviral-transduced ER+ T47D cell models. We used a luciferase-based reporter and endogenous phospho-ER immunoblot analysis to characterize the estrogen response of ER mutants and determined their resistance to known ER antagonists. RESULTS: Consistent with their selection during estrogen deprivation therapy, these mutants conferred constitutive ER activity. While Y537S mutants showed no estrogen dependence, D538G mutants demonstrated an enhanced estrogen-dependent response. Both mutations conferred resistance to ER antagonists that was overcome at higher doses acting specifically through their ER target. CONCLUSIONS: These observations provide a tenable hypothesis for how D538G ESR1-expressing clones can contribute to shorter progression-free survival observed in the exemestane arm of the BOLERO-2 study. Thus, in those patients with dominant D538G-expressing clones, longitudinal analysis for this mutation in circulating free DNA may prove beneficial for informing more optimal therapeutic regimens.

A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens.

Heterogeneity is well recognized as a common property of cellular systems that impacts biomedical research and the development of therapeutics and diagnostics. Several studies have shown that analysis of heterogeneity: gives insight into mechanisms of action of perturbagens; can be used to predict optimal combination therapies; and can be applied to tumors where heterogeneity is believed to be associated with adaptation and resistance. Cytometry methods including high content screening (HCS), high throughput microscopy, flow cytometry, mass spec imaging and digital pathology capture cell level data for populations of cells. However it is often assumed that the population response is normally distributed and therefore that the average adequately describes the results. A deeper understanding of the results of the measurements and more effective comparison of perturbagen effects requires analysis that takes into account the distribution of the measurements, i.e. the heterogeneity. However, the reproducibility of heterogeneous data collected on different days, and in different plates/slides has not previously been evaluated. Here we show that conventional assay quality metrics alone are not adequate for quality control of the heterogeneity in the data. To address this need, we demonstrate the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in an SAR screen, describe a workflow for quality control in heterogeneity analysis. One major challenge in high throughput biology is the evaluation and interpretation of heterogeneity in thousands of samples, such as compounds in a cell-based screen. In this study we also demonstrate that three heterogeneity indices previously reported, capture the shapes of the distributions and provide a means to filter and browse big data sets of cellular distributions in order to compare and identify distributions of interest. These metrics and methods are presented as a workflow for analysis of heterogeneity in large scale biology projects.

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.

Identification of chemosensitivity nodes for vinblastine through small interfering RNA high-throughput screens.

Discovering chemosensitivity pathways or nodes is an attractive strategy for formulating new drug combinations for cancer. Microtubules are among the most successful anticancer drug targets. Therefore, we implemented a small interfering RNA (siRNA) synthetic lethal screen targeting 5520 unique druggable genes to identify novel chemosensitivity nodes for vinblastine, a microtubule-destabilizing agent used clinically. We transiently transfected human glioblastoma cells with siRNAs for 48 h and then treated cells with a sublethal concentration of vinblastine. Forty-eight hours later, we analyzed cell viability and, using a series of statistical methods, identified 65 gene products that, when suppressed, sensitized glioblastoma cells to vinblastine. After completion of the secondary assays, we focused on one siRNA, B-cell lymphoma extra large (BCL-xL), because of its role in the intrinsic apoptosis signaling pathway as well as the availability of pharmacological inhibitors. We found that nontoxic concentrations of 4-[4-[[2-(4-chlorophenyl)-5,5-dimethylcyclohexen-1-yl]methyl]piperazin-1-yl]-N-[4-[[(2R)-4-morpholin-4-yl-1-phenylsulfanylbutan-2-yl]amino]-3-(trifluoromethylsulfonyl)phenyl]sulfonylbenzamide (ABT-263), an inhibitor of the BCL-2 family members (BCL-2, BCL-xL, and BCL-w), sensitized glioblastoma and non-small-cell lung cancer cells to vinblastine and induced apoptosis through the intrinsic cell death pathway. These results illustrate the usefulness of unbiased siRNA screens as a method for identifying potential novel anticancer therapeutic combinations.

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.

Functional genomic analysis of glioblastoma multiforme through short interfering RNA screening: a paradigm for therapeutic development.

Glioblastoma multiforme (GBM) is a high-grade brain malignancy arising from astrocytes. Despite aggressive surgical approaches, optimized radiation therapy regimens, and the application of cytotoxic chemotherapies, the median survival of patients with GBM from time of diagnosis remains less than 15 months, having changed little in decades. Approaches that target genes and biological pathways responsible for tumorigenesis or potentiate the activity of current therapeutic modalities could improve treatment efficacy. In this regard, several genomic and proteomic strategies promise to impact significantly on the drug discovery process. High-throughput genome-wide screening with short interfering RNA (siRNA) is one strategy for systematically exploring possible therapeutically relevant targets in GBM. Statistical methods and protein-protein interaction network databases can also be applied to the screening data to explore the genes and pathways that underlie the pathological basis and development of GBM. In this study, we highlight several genome-wide siRNA screens and implement these experimental concepts in the T98G GBM cell line to uncover the genes and pathways that regulate GBM cell death and survival. These studies will ultimately influence the development of a new avenue of neurosurgical therapy by placing the drug discovery process in the context of the entire biological system.

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.

Identification of survival genes in human glioblastoma cells by small interfering RNA screening.

Target identification and validation remain difficult steps in the drug discovery process, and uncovering the core genes and pathways that are fundamental for cancer cell survival may facilitate this process. Glioblastoma represents a challenging form of cancer for chemotherapy. Therefore, we assayed 16,560 short interfering RNA (siRNA) aimed at identifying which of the 5520 unique therapeutically targetable gene products were important for the survival of human glioblastoma. We analyzed the viability of T98G glioma cells 96 h after siRNA transfection with two orthogonal statistical methods and identified 55 survival genes that encoded proteases, kinases, and transferases. It is noteworthy that 22% (12/55) of the survival genes were constituents of the 20S and 26S proteasome subunits. An expression survey of a panel of glioma cell lines demonstrated expression of the proteasome component PSMB4, and the validity of the proteasome complex as a target for survival inhibition was confirmed in a series of glioma and nonglioma cell lines by pharmacological inhibition and RNA interference. Biological networks were built with the other survival genes using a protein-protein interaction network, which identified clusters of cellular processes, including protein ubiquitination, purine and pyrimidine metabolism, nucleotide excision repair, and NF-kappaB signaling. The results of this study should broaden our understanding of the core genes and pathways that regulate cell survival; through either small molecule inhibition or RNA interference, we highlight the potential significance of proteasome inhibition.

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.

Development of a 384-well colorimetric assay to quantify hydrogen peroxide generated by the redox cycling of compounds in the presence of reducing agents.

We report here the development and optimization of a simple 384-well colorimetric assay to measure H(2)O(2) generated by the redox cycling of compounds incubated with reducing agents in high-throughput screening (HTS) assay buffers. The phenol red-horseradish peroxidase (HRP) assay readily detected H(2)O(2) either added exogenously or generated by the redox cycling of compounds in dithiothreitol (DTT). The generation of H(2)O(2) was dependent on the concentration of both the compound and DTT and was abolished by catalase. Although both DTT and tris(2-carboxyethyl) phosphine sustain the redox cycling generation of H(2)O(2) by a model quinolinedione, 6-chloro-7-(2-morpholin-4-yl-ethylamino)-quinoline-5,8-dione (NSC 663284; DA3003-1), other reducing agents such as beta-mercaptoethanol, glutathione, and cysteine do not. The assay is compatible with HTS. Once terminated, the assay signal was stable for at least 5 h, allowing for a reasonable throughput. The assay tolerated up to 20% dimethyl sulfoxide, allowing a wide range of compound concentrations to be tested. The assay signal window was robust and reproducible with average Z-factors of > or =0.8, and the redox cycling generation of H(2)O(2) by DA3003-1 in DTT exhibited an average 50% effective concentration of 0.830 +/- 0.068 microM. Five of the mitogen-activated protein kinase phosphatase (MKP) 1 inhibitors identified in an HTS were shown to generate H(2)O(2) in the presence of DTT, and their inhibition of MKP-1 activity was shown to be time dependent and was abolished or significantly reduced by either 100 U of catalase or by higher DTT levels. A cross-target query of the PubChem database with three structurally related pyrimidotriazinediones revealed active flags in 36-39% of the primary screening assays. Activity was confirmed against a number of targets containing active site cysteines, including protein tyrosine phosphatases, cathepsins, and caspases, as well as a number of cellular cytotoxicity assays. Rather than utilize resources to conduct a hit characterization effort involving several secondary assays, the phenol red-HRP assay provides a simple, rapid, sensitive, and inexpensive method to identify compounds that redox cycle in DTT or tris(2-carboxyethyl)phosphine to produce H(2)O(2) that may indirectly modulate target activity and represent promiscuous false-positives from a primary screen.

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.

High Content Imaging Assays for IL-6-Induced STAT3 Pathway Activation in Head and Neck Cancer Cell Lines.

In the canonical STAT3 signaling pathway, IL-6 receptor engagement leads to the recruitment of latent STAT3 to the activated IL-6 complex and the associated Janus kinase (JAK) phosphorylates STAT3 at Y705. pSTAT3-Y705 dimers traffic into the nucleus and bind to specific DNA response elements in the promoters of target genes to regulate their transcription. However, IL-6 receptor activation induces the phosphorylation of both the Y705 and S727 residues of STAT3, and S727 phosphorylation is required to achieve maximal STAT3 transcriptional activity. STAT3 continuously shuttles between the nucleus and cytoplasm and maintains a prominent nuclear presence that is independent of Y705 phosphorylation. The constitutive nuclear entry of un-phosphorylated STAT3 (U-STAT3) drives expression of a second round of genes by a mechanism distinct from that used by pSTAT3-Y705 dimers. The abnormally elevated levels of U-STAT3 produced by the constitutive activation of pSTAT3-Y705 observed in many tumors drive the expression of an additional set of pSTAT3-independent genes that contribute to tumorigenesis. In this chapter, we describe the HCS assay methods to measure IL-6-induced STAT3 signaling pathway activation in head and neck tumor cell lines as revealed by the expression and subcellular distribution of pSTAT3-Y705, pSTAT3-S727, and U-STAT3. Only the larger dynamic range provided by the pSTAT3-Y705 antibody would be robust and reproducible enough for screening.

Development and implementation of a miniaturized high-throughput time-resolved fluorescence energy transfer assay to identify small molecule inhibitors of polo-like kinase 1.

Polo-like kinase (Plk) 1 is a key enzyme involved in regulating the mammalian cell cycle that is also a validated anticancer drug target. Nonetheless, there are relatively few readily available potent and selective small molecule inhibitors of Plk1. To increase the availability of pharmacologically valuable Plk1 inhibitors, we describe herein the development, variability assessment, validation, and implementation of a 384-well automated, miniaturized high-throughput time-resolved fluorescence energy transfer screening assay designed to identify Plk1 kinase inhibitors. Using a small molecule library of pharmaceutically active compounds to gauge high-throughput assay robustness and reproducibility, we found nine general kinase inhibitors, including H-89, which was selected as the minimum control. We then interrogated a 97,101 compound library from the National Institutes of Health repository for small molecule inhibitors of Plk1 kinase activity. The initial primary hit rate in a single 10 microM concentration format was 0.21%. Hit compounds were subjected to concentration-response confirmation and interference assays. Identified in the screen were seven compounds with 50% inhibitory concentration (IC50) values below 1 microM, 20 compounds with IC50 values between 1 microM and 5 microM, and eight compounds with IC50 values between 5 and 10 microM, which could be assigned to seven distinct chemotype classes. Hit compounds were also examined for their ability to inhibit other kinases such as protein kinase D, focal adhesion kinase, rho-associated coiled coil protein kinase 2, c-jun NH2-terminal kinase 3, and protein kinase A via experimentation or data-mining. These compounds should be useful as probes for the biological activity of Plk1 and as leads for the development of new selective inhibitors of Plk1.

Development and implementation of a 384-well homogeneous fluorescence intensity high-throughput screening assay to identify mitogen-activated protein kinase phosphatase-1 dual-specificity protein phosphatase inhibitors.

We report here the miniaturization, development, and implementation of a homogeneous 384-well fluorescence intensity high-throughput screening (HTS) assay for identifying mitogen-activated protein kinase (MAPK) phosphatase-1 (MKP-1) dual-specificity phosphatase inhibitors. As part of the National Institutes of Health (NIH) Molecular Libraries Screening Center Network (MLSCN), the MKP-1 assay was utilized to screen an NIH diversity library of 65,239 compounds for inhibitors of MKP-1 activity at 10 microM and was also used to confirm the concentration dependence of active agents identified in the primary screen. We observed 100 (0.15%) compounds that inhibited MKP-1 in vitro by > or =50% at 10 microM in the primary assay, and 46 of the 100 compounds were confirmed as concentration-dependent inhibitors of MKP-1 with 50% inhibitory concentration (IC(50)) values of <50 microM; four exhibited IC(50) values <1.0 microM, six produced IC(50) values in the 1-10 microM range, and 36 produced IC(50) values in the 10-50 microM range. A clustering and classification analysis of the compound structures of the 46 confirmed MKP-1 inhibitors produced 29 singleton structures and seven clusters of related structures. Some MKP-1 inhibitors were members of structural classes or contained substructure pharmacophores that previously were reported to inhibit either MKP-1 or other protein tyrosine phosphatases, validating the HTS assay. Importantly, we have identified several attractive and novel MKP-1 inhibitor structures that warrant further investigation as potential probes to study the biology of MKP-1 and its role in controlling the amplitude and/or duration of MAPK signaling, cell survival, and tumor progression.

HTS identifies novel and specific uncompetitive inhibitors of the two-component NS2B-NS3 proteinase of West Nile virus.

West Nile virus (WNV), a member of the Flavividae family, is a mosquito-borne, emerging pathogen. In addition to WNV, the family includes dengue, yellow fever, and Japanese encephalitis viruses, which affect millions of individuals worldwide. Because countermeasures are currently unavailable, flaviviral therapy is urgently required. The flaviviral two-component nonstructural NS2B-NS3 proteinase (protease [pro]) is essential for viral life cycle and, consequently, is a promising drug target. We report here the results of the miniaturization of an NS2B-NS3pro activity assay, followed by high-throughput screening of the National Institutes of Health's 65,000 compound library and identification of novel, uncompetitive inhibitors of WNV NS2B-NS3pro that appear to interfere with the productive interactions of the NS2B cofactor with the NS3pro domain. We anticipate that following structure optimization, the identified probes could form the foundation for the design of novel and specific therapeutics for WNV infection. We also provide the structural basis for additional species-selective allosteric inhibitors of flaviviruses.

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

The Microphysiology Systems Database for Analyzing and Modeling Compound Interactions with Human and Animal Organ Models.

Microfluidic human organ models, microphysiology systems (MPS), are currently being developed as predictive models of drug safety and efficacy in humans. To design and validate MPS as predictive of human safety liabilities requires safety data for a reference set of compounds, combined with in vitro data from the human organ models. To address this need, we have developed an internet database, the MPS database (MPS-Db), as a powerful platform for experimental design, data management, and analysis, and to combine experimental data with reference data, to enable computational modeling. The present study demonstrates the capability of the MPS-Db in early safety testing using a human liver MPS to relate the effects of tolcapone and entacapone in the in vitro model to human in vivo effects. These two compounds were chosen to be evaluated as a representative pair of marketed drugs because they are structurally similar, have the same target, and were found safe or had an acceptable risk in preclinical and clinical trials, yet tolcapone induced unacceptable levels of hepatotoxicity while entacapone was found to be safe. Results demonstrate the utility of the MPS-Db as an essential resource for relating in vitro organ model data to the multiple biochemical, preclinical, and clinical data sources on in vivo drug effects.

A human liver microphysiology platform for investigating physiology, drug safety, and disease models.

This paper describes the development and characterization of a microphysiology platform for drug safety and efficacy in liver models of disease that includes a human, 3D, microfluidic, four-cell, sequentially layered, self-assembly liver model (SQL-SAL); fluorescent protein biosensors for mechanistic readouts; as well as a microphysiology system database (MPS-Db) to manage, analyze, and model data. The goal of our approach is to create the simplest design in terms of cells, matrix materials, and microfluidic device parameters that will support a physiologically relevant liver model that is robust and reproducible for at least 28 days for stand-alone liver studies and microfluidic integration with other organs-on-chips. The current SQL-SAL uses primary human hepatocytes along with human endothelial (EA.hy926), immune (U937) and stellate (LX-2) cells in physiological ratios and is viable for at least 28 days under continuous flow. Approximately, 20% of primary hepatocytes and/or stellate cells contain fluorescent protein biosensors (called sentinel cells) to measure apoptosis, reactive oxygen species (ROS) and/or cell location by high content analysis (HCA). In addition, drugs, drug metabolites, albumin, urea and lactate dehydrogenase (LDH) are monitored in the efflux media. Exposure to 180 µM troglitazone or 210 µM nimesulide produced acute toxicity within 2-4 days, whereas 28 µM troglitazone produced a gradual and much delayed toxic response over 21 days, concordant with known mechanisms of toxicity, while 600 µM caffeine had no effect. Immune-mediated toxicity was demonstrated with trovafloxacin with lipopolysaccharide (LPS), but not levofloxacin with LPS. The SQL-SAL exhibited early fibrotic activation in response to 30 nM methotrexate, indicated by increased stellate cell migration, expression of alpha-smooth muscle actin and collagen, type 1, alpha 2. Data collected from the in vitro model can be integrated into a database with access to related chemical, bioactivity, preclinical and clinical information uploaded from external databases for constructing predictive models.

HCS campaign to identify selective inhibitors of IL-6-induced STAT3 pathway activation in head and neck cancer cell lines.

Signal transducer and activator of transcription factor 3 (STAT3) is hyperactivated in head and neck squamous cell carcinomas (HNSCC). Cumulative evidence indicates that IL-6 production by HNSCC cells and/or stromal cells in the tumor microenvironment activates STAT3 and contributes to tumor progression and drug resistance. A library of 94,491 compounds from the Molecular Library Screening Center Network (MLSCN) was screened for the ability to inhibit interleukin-6 (IL-6)-induced pSTAT3 activation. For contractual reasons, the primary high-content screening (HCS) campaign was conducted over several months in 3 distinct phases; 1,068 (1.1%) primary HCS actives remained after cytotoxic or fluorescent outliers were eliminated. One thousand one hundred eighty-seven compounds were cherry-picked for confirmation; actives identified in the primary HCS and compounds selected by a structural similarity search of the remaining MLSCN library using hits identified in phases I and II of the screen. Actives were confirmed in pSTAT3 IC50 assays, and an IFNγ-induced pSTAT1 activation assay was used to prioritize selective inhibitors of STAT3 activation that would not inhibit STAT1 tumor suppressor functions. Two hundred three concentration-dependent inhibitors of IL-6-induced pSTAT3 activation were identified and 89 of these also produced IC50s against IFN-γ-induced pSTAT1 activation. Forty-nine compounds met our hit criteria: they reproducibly inhibited IL-6-induced pSTAT3 activation by ≥70% at 20 µM; their pSTAT3 activation IC50s were ≤25 µM; they were ≥2-fold selective for pSTAT3 inhibition over pSTAT1 inhibition; a cross target query of PubChem indicated that they were not biologically promiscuous; and they were ≥90% pure. Twenty-six chemically tractable hits that passed filters for nuisance compounds and had acceptable drug-like and ADME-Tox properties by computational evaluation were purchased for characterization. The hit structures were distributed among 5 clusters and 8 singletons. Twenty-four compounds inhibited IL-6-induced pSTAT3 activation with IC50s ≤20 µM and 13 were ≥3-fold selective versus inhibition of pSTAT1 activation. Eighteen hits inhibited the growth of HNSCC cell lines with average IC50s ≤ 20 µM. Four chemical series were progressed into lead optimization: the guanidinoquinazolines, the triazolothiadiazines, the amino alcohols, and an oxazole-piperazine singleton.