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Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.

Noncanonical inflammasome activation by cytosolic lipopolysaccharide (LPS) is a critical component of the host response to Gram-negative bacteria. Cytosolic LPS recognition in macrophages is preceded by a Toll-like receptor (TLR) priming signal required to induce transcription of inflammasome components and facilitate the metabolic reprograming that fuels the inflammatory response. Using a genome-scale arrayed siRNA screen to find inflammasome regulators in mouse macrophages, we identified the mitochondrial enzyme nucleoside diphosphate kinase D (NDPK-D) as a regulator of both noncanonical and canonical inflammasomes. NDPK-D was required for both mitochondrial DNA synthesis and cardiolipin exposure on the mitochondrial surface in response to inflammasome priming signals mediated by TLRs, and macrophages deficient in NDPK-D had multiple defects in LPS-induced inflammasome activation. In addition, NDPK-D was required for the recruitment of TNF receptor-associated factor 6 (TRAF6) to mitochondria, which was critical for reactive oxygen species (ROS) production and the metabolic reprogramming that supported the TLR-induced gene program. NDPK-D knockout mice were protected from LPS-induced shock, consistent with decreased ROS production and attenuated glycolytic commitment during priming. Our findings suggest that, in response to microbial challenge, NDPK-D-dependent TRAF6 mitochondrial recruitment triggers an energetic fitness checkpoint required to engage and maintain the transcriptional program necessary for inflammasome activation.

The Assay Guidance Manual (AGM) is an eBook of best practices for the design, development, and implementation of robust assays for early drug discovery. Initiated by pharmaceutical company scientists, the manual provides guidance for designing a "testing funnel" of assays to identify genuine hits using high-throughput screening (HTS) and advancing them through preclinical development. Combined with a workshop/tutorial component, the overall goal of the AGM is to provide a valuable resource for training translational scientists.

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.

Three-dimensional (3D) cell culture models are thought to mimic the physiological and pharmacological properties of tissues in vivo more accurately than two-dimensional cultures on plastic dishes. For the development of cancer therapies, 3D spheroid models are being created to reflect the complex histology and physiology of primary tumors with the hopes that drug responses will be more similar to and as predictive as those obtained in vivo. The effect of additional cell types in tumors, such as stromal cells, and the resulting heterotypic cell-cell crosstalk can be investigated in these heterotypic 3D cell cultures. Here, a high-throughput screening-compatible drug testing platform based on 3D multicellular spheroid models is described that enables the parallel assessment of toxicity on stromal cells and efficacy on cancer cells by drug candidates. These heterotypic microtissue tumor models incorporate NIH3T3 fibroblasts as stromal cells that are engineered with a reporter gene encoding secreted NanoLUC luciferase. By tracking the NanoLUC signal in the media over time, a time-related measurement of the cytotoxic effects of drugs on stromal cells over the cancer cells was possible, thus enabling the identification of a therapeutic window. An in vitro therapeutic index parameter is proposed to help distinguish and classify those compounds with broad cytotoxic effects versus those that are more selective at targeting cancer cells.

The tumor microenvironment (TME) is a key determinant of metastatic efficiency. We performed a quantitative high-throughput screen (qHTS) of diverse medicinal chemistry tractable scaffolds (44,420 compounds) and pharmacologically active small molecules (386 compounds) using a layered organotypic, robust assay representing the ovarian cancer metastatic TME. This 3D model contains primary human mesothelial cells, fibroblasts, and extracellular matrix, to which fluorescently labeled ovarian cancer cells are added. Initially, 100 compounds inhibiting ovarian cancer adhesion/invasion to the 3D model in a dose-dependent manner were identified. Of those, eight compounds were confirmed active in five high-grade serous ovarian cancer cell lines and were further validated in secondary in vitro and in vivo biological assays. Two tyrosine kinase inhibitors, PP-121 and milciclib, and a previously unreported compound, NCGC00117362, were selected because they had potency at 1 μmol/L in vitro. Specifically, NCGC00117362 and PP-121 inhibited ovarian cancer adhesion, invasion, and proliferation, whereas milciclib inhibited ovarian cancer invasion and proliferation. Using in situ kinase profiling and immunoblotting, we found that milciclib targeted Cdk2 and Cdk6, and PP-121 targeted mTOR. In vivo, all three compounds prevented ovarian cancer adhesion/invasion and metastasis, prolonged survival, and reduced omental tumor growth in an intervention study. To evaluate the clinical potential of NCGC00117362, structure–activity relationship studies were performed. Four close analogues of NCGC00117362 efficiently inhibited cancer aggressiveness in vitro and metastasis in vivo. Collectively, these data show that a complex 3D culture of the TME is effective in qHTS. The three compounds identified have promise as therapeutics for prevention and treatment of ovarian cancer metastasis.

Summary Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER+ breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.

Excess lipid storage is an epidemic problem in human populations. Thus, the identification of small molecules to treat or prevent lipid storage-related metabolic complications is of great interest. Here we screened > 320.000 compounds for their ability to prevent a cellular lipid accumulation phenotype. We used fly cells because the multifarious tools available for this organism should facilitate unraveling the mechanism-of-action of active small molecules. Of the several hundred lipid storage inhibitors identified in the primary screen we concentrated on three structurally diverse and potent compound classes active in cells of multiple species (including human) and negligible cytotoxicity. Together with Drosophila in vivo epistasis experiments, RNA-Seq expression profiles suggested that the target of one of the small molecules was diacylglycerol acyltransferase 1 (DGAT1), a key enzyme in the production of triacylglycerols and prominent human drug target. We confirmed this prediction by biochemical and enzymatic activity tests., Highlights • We identified > 600 potent small molecule inhibitors of cellular lipid storage deposition. • RNA-Seq expression profiling discriminated the activity of three lead scaffolds and guided subsequent functional studies. • We discovered a class of DGAT1 inhibitors, which is active in fly and mammalian cell lines as well as whole flies. Obesity and other lipid storage associated diseases are a growing health threat of human populations. In an undirected phenotypic screen, we identified pharmacologically active small molecules that reduce or enhance lipid storage. Our work focuses on three lead structures that prevent lipid storage in diverse cellular systems including cells from a diabetes patient. In order to elucidate the compound mechanisms-of-action and cellular targets, we used a combination of RNA-Seq transcriptional profiling and diverse functional assays. Our results strongly suggest that one of our lead structures represents a class of inhibitors targeting the key lipogenic enzyme diacylglycerol acyltransferase 1.

As we witness steady progress towards the development of robust, scalable, and reproducible 3D tissue models for preclinical drug testing, there is a need for systematic physiological and pharmacological validation and benchmarking. Ongoing and future studies should generate evidence as to whether 3D tissue models are more predictive, help reduce the risk of failure rate, and can be used for decision making in the drug discovery and development pipeline. Here, we discuss the importance of harmonizing the validation of these models based on throughput capacity and physiological complexity as a requirement to establish their true translational capacity. We also outline our strategy for a novel 3D-tailored holistic drug discovery concept rather than piecemeal integration of 3D models into the current process.

Lysine acetyltransferases (KATs) are critical regulators of signaling in many diseases, including cancer. A major challenge in establishing the targetable functions of KATs in disease is a lack of well-characterized, cell-active KAT inhibitors. To confront this challenge, here we report a microfluidic mobility shift platform for the discovery and characterization of small molecule KAT inhibitors. Novel fluorescent peptide substrates were developed for four well-known KAT enzymes (p300, Crebbp, Morf, and Gcn5). Enzyme-catalyzed acetylation alters the electrophoretic mobility of these peptides in a microfluidic chip, allowing facile and direct monitoring of KAT activity. A pilot screen was used to demonstrate the utility of microfluidic mobility shift profiling to identify known and novel modulators of KAT activity. Real-time kinetic monitoring of KAT activity revealed that garcinol, a natural product KAT inhibitor used in cellular studies, exhibits time-dependent and detergent-sensitive inhibition, consistent with an aggregation-based mechanism. In contrast, the cell-permeable bisubstrate inhibitor Tat-CoA exhibited potent and time-independent KAT inhibition, highlighting its potential utility as a cellular inhibitor of KAT activity. These studies define microfluidic mobility shift profiling as a powerful platform for the discovery and characterization of small molecule inhibitors of KAT activity, and provide mechanistic insights potentially important for the application of KAT inhibitors in cellular contexts.

Alveolar rhabdomyosarcoma is a life-threatening myogenic cancer of children and adolescent young adults, driven primarily by the chimeric transcription factor PAX3–FOXO1. The mechanisms by which PAX3–FOXO1 dysregulates chromatin are unknown. We find PAX3–FOXO1 reprograms the cis-regulatory landscape by inducing de novo super enhancers. PAX3–FOXO1 uses super enhancers to set up autoregulatory loops in collaboration with the master transcription factors MYOG, MYOD, and MYCN. This myogenic super enhancer circuitry is consistent across cell lines and primary tumors. Cells harboring the fusion gene are selectively sensitive to small-molecule inhibition of protein targets induced by, or bound to, PAX3–FOXO1-occupied super enhancers. Furthermore, PAX3–FOXO1 recruits and requires the BET bromodomain protein BRD4 to function at super enhancers, resulting in a complete dependence on BRD4 and a significant susceptibility to BRD inhibition. These results yield insights into the epigenetic functions of PAX3–FOXO1 and reveal a specific vulnerability that can be exploited for precision therapy. Significance: PAX3–FOXO1 drives pediatric fusion-positive rhabdomyosarcoma, and its chromatin-level functions are critical to understanding its oncogenic activity. We find that PAX3–FOXO1 establishes a myoblastic super enhancer landscape and creates a profound subtype-unique dependence on BET bromodomains, the inhibition of which ablates PAX3–FOXO1 function, providing a mechanistic rationale for exploring BET inhibitors for patients bearing PAX-fusion rhabdomyosarcoma. Cancer Discov; 7(8); 884–99. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 783

The tumor microenvironment plays an important role in the processes of tumor growth, metastasis and drug resistance. We have utilized a multilayered 3D primary cell culture model that reproduces the human ovarian cancer metastatic microenvironment to study the effect of the microenvironment on the pharmacological responses of cancer cells proliferation to different classes of drugs. A collection of oncology drugs was screened to identify compounds that inhibited the proliferation of ovarian cancer cells growing as monolayers or forming spheroids, on plastic and on a 3D microenvironment culture model of the omentum metastatic site, and also cells already in pre-formed spheroids. Target-based analysis of the pharmacological responses revealed that several classes of targets were more efficacious in cancer cells growing in the absence of the metastatic microenvironment, and other target classes were less efficacious in cancer cells in pre-formed spheres compared to forming spheroids cultures. These findings show that both the cellular context of the tumor microenvironment and cell adhesion mode have an essential role in cancer cell drug resistance. Therefore it is important to perform screens for new drugs using model systems that more faithfully recapitulate the tissue composition at the site of tumor growth and metastasis

Two-dimensional monolayer cell proliferation assays for cancer drug discovery have made the implementation of large-scale screens feasible but only seem to reflect a simplified view that oncogenes or tumor suppressor genes are the genetic drivers of cancer cell proliferation. However, there is now increased evidence that the cellular and physiological context in which these oncogenic events occur play a key role in how they drive tumor growth in vivo and, therefore, in how tumors respond to drug treatments. In vitro 3D spheroid tumor models are being developed to better mimic the physiology of tumors in vivo, in an attempt to improve the predictability and efficiency of drug discovery for the treatment of cancer. Here we describe the establishment of a real-time 3D spheroid growth, 384-well screening assay. The cells used in this study constitutively expressed green fluorescent protein (GFP), which enabled the real-time monitoring of spheroid formation and the effect of chemotherapeutic agents on spheroid size at different time points of sphere growth and drug treatment. This real-time 3D spheroid assay platform represents a first step toward the replication in vitro of drug dosing regimens being investigated in vivo. We hope that further development of this assay platform will allow the investigation of drug dosing regimens, efficacy, and resistance before preclinical and clinical studies.

The discovery of chemotherapeutic agents for the treatment of cancer commonly uses cell proliferation assays in which cells grow as two-dimensional (2D) monolayers. Compounds identified using 2D monolayer assays often fail to advance during clinical development, most likely because these assays do not reproduce the cellular complexity of tumors and their microenvironment in vivo. The use of three-dimensional (3D) cellular systems have been explored as enabling more predictive in vitro tumor models for drug discovery. To date, small-scale screens have demonstrated that pharmacological responses tend to differ between 2D and 3D cancer cell growth models. However, the limited scope of screens using 3D models has not provided a clear delineation of the cellular pathways and processes that differentially regulate cell survival and death in the different in vitro tumor models. Here we sought to further understand the differences in pharmacological responses between cancer tumor cells grown in different conditions by profiling a large collection of 1912 chemotherapeutic agents. We compared pharmacological responses obtained from cells cultured in traditional 2D monolayer conditions with those responses obtained from cells forming spheres versus cells already in 3D spheres. The target annotation of the compound library screened enabled the identification of those key cellular pathways and processes that when modulated by drugs induced cell death in all growth conditions or selectively in the different cell growth models. In addition, we also show that many of the compounds targeting these key cellular functions can be combined to produce synergistic cytotoxic effects, which in many cases differ in the magnitude of their synergism depending on the cellular model and cell type. The results from this work provide a high-throughput screening framework to profile the responses of drugs both as single agents and in pairwise combinations in 3D sphere models of cancer cells.