Diffuse midline gliomas (DMGs) are universally lethal malignancies occurring chiefly during childhood and involving midline structures of the central nervous system, including thalamus, pons, and spinal cord. These molecularly related cancers are characterized by high prevalence of the histone H3K27M mutation. In search of effective therapeutic options, we examined multiple DMG cultures in sequential quantitative high-throughput screens (HTS) of 2706 approved and investigational drugs. This effort generated 19,936 single-agent dose responses that inspired a series of HTS-enabled drug combination assessments encompassing 9195 drug-drug examinations. Top combinations were validated across patient-derived cell cultures representing the major DMG genotypes. In vivo testing in patient-derived xenograft models validated the combination of the multi-histone deacetylase (HDAC) inhibitor panobinostat and the proteasome inhibitor marizomib as a promising therapeutic approach. Transcriptional and metabolomic surveys revealed substantial alterations to key metabolic processes and the cellular unfolded protein response after treatment with panobinostat and marizomib. Mitigation of drug-induced cytotoxicity and basal mitochondrial respiration with exogenous application of nicotinamide mononucleotide (NMN) or exacerbation of these phenotypes when blocking nicotinamide adenine dinucleotide (NAD+) production via nicotinamide phosphoribosyltransferase (NAMPT) inhibition demonstrated that metabolic catastrophe drives the combination-induced cytotoxicity. This study provides a comprehensive single-agent and combinatorial drug screen for DMG and identifies concomitant HDAC and proteasome inhibition as a promising therapeutic strategy that underscores underrecognized metabolic vulnerabilities in DMG.

IMPACT STATEMENT: This article describes a method for the biofabrication of skin tissue equivalents in a multiwell plate format. The technique and results overcome shortcomings of previously published engineering methods, and show good architecture and barrier function from well to well; thus it may be used for compound functional testing and for the development of disease tissue models for screening.

Nearly one-third of the encoded proteome is comprised of secretory proteins that enable communication between cells and organ systems, playing a ubiquitous role in human health and disease. High-throughput detection of secreted proteins would enhance efforts to identify therapies for secretion-related diseases. Using the Z mutant of alpha-1 antitrypsin as a human secretory model, we have developed 1536-well high-throughput screening assays that utilize acoustic droplet ejection to transfer nanoliter volumes of sample for protein quantification. Among them, the acoustic reverse phase protein array (acoustic RPPA) is a multiplexable, low-cost immunodetection technology for native, endogenously secreted proteins from physiologically relevant model systems like stem cells that is compatible with plate-based instrumentation. Parallel assay profiling with the LOPAC1280 chemical library validated performance and orthogonality between a secreted bioluminescent reporter and acoustic RPPA method by consistently identifying secretory modulators with comparable concentration response relationships. Here, we introduce a robust, multiplexed drug discovery platform coupling extracellular protein quantification by acoustic RPPA with intracellular and cytotoxicity analyses from single wells, demonstrating proof-of-principle applications for human induced pluripotent stem cell-derived hepatocytes.

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (-)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening.

Heterogeneous response to chemotherapy is a major issue for the treatment of cancer. For most gynecologic cancers including ovarian, cervical, and placental, the list of available small molecule therapies is relatively small compared to options for other cancers. While overall cancer mortality rates have decreased in the United States as early diagnoses and cancer therapies have become more effective, ovarian cancer still has low survival rates due to the lack of effective treatment options, drug resistance, and late diagnosis. To understand chemotherapeutic diversity in gynecologic cancers, we have screened 7914 approved drugs and bioactive compounds in 11 gynecologic cancer cell lines to profile their chemotherapeutic sensitivity. We identified two HDAC inhibitors, mocetinostat and entinostat, as pan-gynecologic cancer suppressors with IC50 values within an order of magnitude of their human plasma concentrations. In addition, many active compounds identified, including the non-anticancer drugs and other compounds, diversely inhibited the growth of three gynecologic cancer cell groups and individual cancer cell lines. These newly identified compounds are valuable for further studies of new therapeutics development, synergistic drug combinations, and new target identification for gynecologic cancers. The results also provide a rationale for the personalized chemotherapeutic testing of anticancer drugs in treatment of gynecologic cancer.

Glioblastoma (GBM) is a lethal brain cancer with a median survival time of approximately 15 months following treatment. Common in vitro GBM models for drug screening are adherent and do not recapitulate the features of human GBM in vivo. Here we report the genomic characterization of nine patient-derived, spheroid GBM cell lines that recapitulate human GBM characteristics in orthotopic xenograft models. Genomic sequencing revealed that the spheroid lines contain alterations in GBM driver genes such as PTEN, CDKN2A, and NF1. Two spheroid cell lines, JHH-136 and JHH-520, were utilized in a high-throughput drug screen for cell viability using a 1912-member compound library. Drug mechanisms that were cytotoxic in both cell lines were Hsp90 and proteasome inhibitors. JHH-136 was uniquely sensitive to topoisomerase 1 inhibitors, while JHH-520 was uniquely sensitive to Mek inhibitors. Drug combination screening revealed that PI3 kinase inhibitors combined with Mek or proteasome inhibitors were synergistic. However, animal studies to test these drug combinations in vivo revealed that Mek inhibition alone was superior to the combination treatments. These data show that these GBM spheroid lines are amenable to high-throughput drug screening and that this dataset may deliver promising therapeutic leads for future GBM preclinical studies.

Imaging and subsequent segmentation analysis in three-dimensional (3D) culture models are complicated by the light scattering that occurs when collecting fluorescent signal through multiple cell and extracellular matrix layers. For 3D cell culture models to be usable for drug discovery, effective and efficient imaging and analysis protocols need to be developed that enable high-throughput data acquisition and quantitative analysis of fluorescent signal. Here we report the first high-throughput protocol for optical clearing of spheroids, fluorescent high-content confocal imaging, 3D nuclear segmentation, and post-segmentation analysis. We demonstrate nuclear segmentation in multiple cell types, with accurate identification of fluorescently-labeled subpopulations, and develop a metric to assess the ability of clearing to improve nuclear segmentation deep within the tissue. Ultimately this analysis pipeline allows for previously unattainable segmentation throughput of 3D culture models due to increased sample clarity and optimized batch-processing analysis.

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 pre-clinical development. Combined with a workshop/tutorial component, the overall goal of the AGM is to provide a valuable resource for training translational scientists. This article is protected by copyright. All rights reserved.

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.