Quantitative High-throughput Screening Research Articles

RosetteArray® Platform for Quantitative High-Throughput Screening of Human Neurodevelopmental Risk.

Neural organoids have revolutionized how human neurodevelopmental disorders (NDDs) are studied. Yet, their utility for screening complex NDD etiologies and in drug discovery is limited by a lack of scalable and quantifiable derivation formats. Here, we describe the RosetteArray® platform's ability to be used as an off-the-shelf, 96-well plate assay that standardizes incipient forebrain and spinal cord organoid morphogenesis as micropatterned, 3-D, singularly polarized neural rosette tissues (>9000 per plate). RosetteArrays are seeded from cryopreserved human pluripotent stem cells, cultured over 6-8 days, and immunostained images can be quantified using artificial intelligence-based software. We demonstrate the platform's suitability for screening developmental neurotoxicity and genetic and environmental factors known to cause neural tube defect risk. Given the presence of rosette morphogenesis perturbation in neural organoid models of NDDs and neurodegenerative disorders, the RosetteArray platform could enable quantitative high-throughput screening (qHTS) of human neurodevelopmental risk across regulatory and precision medicine applications.

Small-Molecule Disruptors of the Interaction between Calcium- and Integrin-Binding Protein 1 and Integrin αIIbβ3 as Novel Antiplatelet Agents.

Thrombosis, a key factor in most cardiovascular diseases, is a major contributor to human mortality. Existing antithrombotic agents carry a risk of bleeding. Consequently, there is a keen interest in discovering innovative antithrombotic agents that can prevent thrombosis without negatively impacting hemostasis. Platelets play crucial roles in both hemostasis and thrombosis. We have previously characterized calcium- and integrin-binding protein 1 (CIB1) as a key regulatory molecule that regulates platelet function. CIB1 interacts with several platelet proteins including integrin αIIbβ3, the major glycoprotein receptor for fibrinogen on platelets. Given that CIB1 regulates platelet function through its interaction with αIIbβ3, we developed a fluorescence polarization (FP) assay to screen for potential inhibitors. The assay was miniaturized to 1536-well and screened in quantitative high-throughput screening (qHTS) format against a diverse compound library of 14,782 compounds. After validation and selectivity testing using the FP assay, we identified 19 candidate inhibitors and validated them using an in-gel binding assay that monitors the interaction of CIB1 with αIIb cytoplasmic tail peptide, followed by testing of top hits by intrinsic tryptophan fluorescence (ITF) and microscale thermophoresis (MST) to ascertain their interaction with CIB1. Two of the validated hits shared similar chemical structures, suggesting a common mechanism of action. Docking studies further revealed promising interactions within the hydrophobic binding pocket of the target protein, particularly forming key hydrogen bonds with Ser180. The compounds exhibited a potent antiplatelet activity based on their inhibition of thrombin-induced human platelet aggregation, thus indicating that disruptors of the CIB1- αIIbβ3 interaction could carry a translational potential as antithrombotic agents.

Machine Learning Models Identify Inhibitors of New Delhi Metallo-β-lactamase.

The worldwide spread of the metallo-β-lactamases (MBL), especially New Delhi metallo-β-lactamase-1 (NDM-1), is threatening the efficacy of β-lactams, which are the most potent and prescribed class of antibiotics in the clinic. Currently, FDA-approved MBL inhibitors are lacking in the clinic even though many strategies have been used in inhibitor development, including quantitative high-throughput screening (qHTS), fragment-based drug discovery (FBDD), and molecular docking. Herein, a machine learning-based prediction tool is described, which was generated using results from HTS of a large chemical library and previously published inhibition data. The prediction tool was then used for virtual screening of the NIH Genesis library, which was subsequently screened using qHTS. A novel MBL inhibitor was identified and shown to lower minimum inhibitory concentrations (MICs) of Meropenem for a panel of E. coli and K. pneumoniae clinical isolates expressing NDM-1. The mechanism of inhibition of this novel scaffold was probed utilizing equilibrium dialyses with metal analyses, native state electrospray ionization mass spectrometry, UV-vis spectrophotometry, and molecular docking. The uncovered inhibitor, compound 72922413, was shown to be 9-hydroxy-3-[(5-hydroxy-1-oxa-9-azaspiro[5.5]undec-9-yl)carbonyl]-4H-pyrido[1,2-a]pyrimidin-4-one.

Abstract LB029: Degraders of TEAD transcription factors based on interface 3 binders

Abstract TEAD transcription factors have emerged as clinically validated targets for Hippo-altered cancers, e.g. mesothelioma driven by NF2 inactivation/deficiency. We have developed a series of novel small molecule targeted protein degraders of TEAD based on pan-TEAD interface 3 ligands. In cells, the compounds induce degradation of TEAD by formation of a ternary complex with Cereblon, leading to ubiquitination of TEAD and subsequent proteasomal degradation. In a cell-based luciferase reporter assay the degraders show low nanomolar activity. The downstream effects of TEAD degradation were further investigated by qPCR and WB analyses of bona fide YAP-TEAD target genes such as CTGF, Cyr61 and AMOTL2. The effectiveness of the TEAD degraders were compared to other classes of TEAD modulators such as palmitoylation inhibitors and YAP-TEAD protein-protein inhibitors by means of cellular viability assays using various mesothelioma cell lines. Finally, we performed an unbiased, quantitative high-throughput drug combination screening by combining a TEAD degrader with a library of approximately 2,800 oncology-focused drugs. This research was supported in part by the Intramural/Extramural research program of the NCATS, NIH. Citation Format: Rajiv Sawant, Matthis Geitmann, Thomas Gossas, Wei B. Emond, Ulf Bremberg, Konrad Koehler, Michele Ceribelli, Craig J. Thomas, Peter Brandt. Degraders of TEAD transcription factors based on interface 3 binders [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB029.

Abstract 4301: Increasing the therapeutic vulnerability of heterogenous cell phenotypes within prostate cancer

Abstract Phenotype heterogeneity is a hallmark of prostate adenocarcinoma and is a major source of recurrent disease. We tested pre-clinical therapies to eradicate phenotypically distinct cell populations derived from the parental DU145WT prostate cancer cell line. The derived cell lines are called DU145AA, DU145J7, and DU145G6. The DU145AA variant is a non-aggressive cell population while the DU145J7 and DU145G6 are aggressive phenotypes that invade through muscle and metastasize to bone. Flow cytometry analysis documented the phenotypic plasticity of the DU145 cell variants since DU145 aggressive lines expressed 1.3-fold increases in matrix metalloprotease 14 surface expression and a 2-fold increase in tri-methyl Histone H3 at lysine 27 as compared to the DU145WT parent line. The DU145AA non-aggressive line expressed an epithelial cell-cell lineage phenotype with up to 2-fold increases in E-cadherin, claudin 4, claudin 7, and a unique cytokeratin 6A expression and a 2-fold loss of Zinc finger E-box-binding homeobox 1, EVL, and Kindlin 2. A collaboration with the National Center for Advancing Translational Science (NCATS) resulted in the identification of pharmacological agents active in eradicating DU145J7 and DU145G6 cells as compared to the DU145WT population. The agents were selected from a quantitative high-throughput screen of 10,677 combined investigative and approved anti-cancer agents using the Cell Titer-Glo Luminescent Cell Viability assay. We independently validated 31 compounds from the assay that have 2-fold, or greater, differences in concentration to inhibit 50% cell growth (IC50) between the wild-type and aggressive variants of DU145 cells. The top 10 hits were tested for the efficacy of different combinations to eradicate defined admixtures of aggressive and non-aggressive phenotypes, including the DU145AA cells, to model tumor heterogeneity. Tested compounds with differential sensitivity between aggressive and non-aggressive cells were those inhibiting histone deacetylase (vorinostat, fimepinostat, and pracinostat), proteasomes (bortezomib, delanzomib, ixazomib), topoisomerases (gimatecan and daunorubicin), and other compounds identified independently by us targeting nicotinamide phosphoribosyl transferase (FK866) and DNA (bleomycin). Using admixtures of tumor cell phenotypes, we determined optimal combinations of compounds that would selectively eradicate the sub-populations. The results suggest that determination of phenotypes within tumor populations may eliminate the heterogenous tumor and prevent recurrent disease. Funding was provided by the University of Arizona Cancer Center (NCI-P30 CA23074 and NCI-R01 CA159406) and by the Partnership in Native American Cancer Prevention at the University of Arizona (U54CA143924) and Northern Arizona University (U54CA143925). Collaborators at NCATS were supported by the intramural research program. Citation Format: Allan I. Paxson, Loren H. Chang, Kendra D. Marr, Jaime M. Gard, Colin S. Nelson, Abhijeet Kapoor, William L. Harryman, Juan J. Marugan, Mark J. Henderson, Tino W. Sanchez, Anne E. Cress. Increasing the therapeutic vulnerability of heterogenous cell phenotypes within prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4301.

Use of in vitro methods combined with in silico analysis to identify potential skin sensitizers in the Tox21 10K compound library.

Introduction: Skin sensitization, which leads to allergic contact dermatitis, is a key toxicological endpoint with high occupational and consumer prevalence. This study optimized several in vitro assays listed in OECD skin sensitization test guidelines for use on a quantitative high-throughput screening (qHTS) platform and performed in silico model predictions to assess the skin sensitization potential of prioritized compounds from the Tox21 10K compound library. Methods: First, we screened the entire Tox21 10K compound library using a qHTS KeratinoSensTM (KS) assay and built a quantitative structure-activity relationship (QSAR) model based on the KS results. From the qHTS KS screening results, we prioritized 288 compounds to cover a wide range of structural chemotypes and tested them in the solid phase extraction-tandem mass spectrometry (SPE-MS/MS) direct peptide reactivity assay (DPRA), IL-8 homogeneous time-resolved fluorescence (HTRF) assay, CD86 and CD54 surface expression in THP1 cells, and predicted in silico sensitization potential using the OECD QSAR Toolbox (v4.5). Results: Interpreting tiered qHTS datasets using a defined approach showed the effectiveness and efficiency of in vitro methods. We selected structural chemotypes to present this diverse chemical collection and to explore previously unidentified structural contributions to sensitization potential. Discussion: Here, we provide a skin sensitization dataset of unprecedented size, along with associated tools, and analysis designed to support chemical assessments.

Highly scalable and standardized organ-on-chip platform with TEER for biological barrier modeling

ABSTRACT The development of new therapies is hampered by the lack of predictive, and patient-relevant in vitro models. Organ-on-chip (OOC) technologies can potentially recreate physiological features and hold great promise for tissue and disease modeling. However, the non-standardized design of these chips and perfusion control systems has been a barrier to quantitative high-throughput screening (HTS). Here we present a scalable OOC microfluidic platform for applied kinetic in vitro assays (AKITA) that is applicable for high, medium, and low throughput. Its standard 96-well plate and 384-well plate layouts ensure compatibility with existing laboratory workflows and high-throughput data collection and analysis tools. The AKITA plate is optimized for the modeling of vascularized biological barriers, primarily the blood-brain barrier, skin, and lung, with precise flow control on a custom rocker. The integration of trans-epithelial electrical resistance (TEER) sensors allows rapid and repeated monitoring of barrier integrity over long time periods. Together with automated liquid handling and compound permeability testing analyses, we demonstrate the flexibility of the AKITA platform for establishing human-relevant models for preclinical drug and precision medicine’s efficacy, toxicity, and permeability under near-physiological conditions.

A novel quantitative high-throughput screening assay identifies small-molecule therapeutic candidates for Gaucher and Parkinson disease

A novel quantitative high-throughput screening assay identifies small-molecule therapeutic candidates for Gaucher and Parkinson disease

CRISPR-Cas9-Mediated Bioluminescent Tagging of Endogenous Proteins by Fluorescent Protein-Assisted Cell Sorting.

Oncogenic fusion genes are attractive therapeutic targets because of their tumor-specific expression and central "driver" roles in various human cancers. However, oncogenic fusions involving transcription factors such as PAX3-FOXO1 in alveolar fusion gene-positive rhabdomyosarcoma (FP-RMS) have been difficult to inhibit due to the apparent lack of tractable drug-like binding sites comparable to that recognized by Gleevec (imatinib mesylate) on the BCR-ABL1 tyrosine kinase fusion protein. Toward the identification of novel small molecules that selectively target PAX3-FOXO1, we used CRISPR-Cas9-mediated knock-in to append the pro-luminescent HiBiT tag onto the carboxy terminus of the endogenous PAX3-FOXO1 fusion protein in two human FP-RMS cell lines (RH4 and SCMC). HiBiT is an 11-amino acid peptide derived from the NanoLuc luciferase that produces a luminescence signal which is ~100-fold brighter than firefly or Renilla luciferases through high-affinity binding to a complementary NanoLuc peptide fragment called LgBiT. To facilitate single-cell clonal isolation of knock-ins, the homology-directed repair template encoding HiBiT was followed by a P2A self-cleaving peptide for coexpression of an mCherry fluorescent protein as a fluorescence-activated cell sorter (FACS)-selectable marker. HiBiT tagging thus allows highly sensitive luminescence detection of endogenous PAX3-FOXO1 levels permitting quantitative high-throughput screening of large compound libraries for the discovery of PAX3-FOXO1 inhibitors and degraders.

Comparative Assessment and High-Throughput Drug-Combination Profiling of TEAD-Palmitoylation Inhibitors in Hippo Pathway Deficient Mesothelioma.

The hippo signaling pathway is a central tumor suppressor cascade frequently inactivated in selected human cancers, leading to the aberrant activation of TEAD transcription factors. Whereas several TEAD auto-palmitoylation inhibitors are currently in development, a comprehensive assessment of this novel drug-modality is missing. Here, we report a comparative analysis among six TEADi(s) using cell-based and biochemical assays in Hippo pathway deficient mesothelioma. Our analysis revealed varying potency and selectivity across TEADi, also highlighting their limited efficacy. To overcome this limitation, we performed an unbiased, quantitative high-throughput drug screening by combining the TEADi VT-103 with a library of approximately 3000 oncology-focused drugs. By exploiting this library's mechanistic redundancy, we identified several drug-classes robustly synergized with TEADi. These included glucocorticoid-receptor (GR) agonists, Mek1/2 inhibitors, mTOR inhibitors, and PI3K inhibitors, among others. Altogether, we report a coherent single-agent dataset informing on potency and selectivity of TEAD-palmitoylation inhibitors as single-agents. We also describe a rational pipeline enabling the systematic identification of TEAD druggable co-dependencies. This data should support the pre-clinical development of drug combination strategies for the treatment of Hippo-deficient mesothelioma, and more broadly, for other cancers dependent on the oncogenic activity of YAP/TEAD.

Opportunities and Prospects for Preclinical Drug Safety Assessment Using Alternative Methods: Experience from the Toxicology in the 21st Century (Tox21) Programme in the USA

SCIENTIFIC RELEVANCE. The Tox21 (Toxicology in the 21st Century) programme was developed by the US Tox21 Consortium with the aim to replace animal-based toxicity assessments of chemicals with a wide range of in vitro and in silico testing approaches and has since been successfully applied in practice.AIM. The study aimed to review information on alternative in vitro models developed as part of the Tox21 programme for testing the toxicity of chemical compounds.DISCUSSION. According to the information provided by the National Toxicology Program, Environmental Protection Agency, National Center for Advancing Translational Sciences, and other Tox21 Consortium members on their official websites and in the literature, the Tox21 Consortium has developed a quantitative high-throughput screening technology for testing the safety of chemicals and created the Tox21 10K library of chemical compounds using this screening technology. The library has been successfully used to create models that predict the toxicity of chemicals prior to preclinical studies. Researchers have proposed new approaches to studying the safety of chemical compounds in human cell lines to replace in vivo studies. Innovative organ-on-chip, multi-organ-on-chip, and organoid models are free from the drawbacks and limitations of cell-line models and offer more accurate representations of complex cell–matrix and organ–organ interactions. Developed under the Tox21 programme to search for new chemical toxicity biomarkers and gene signatures, novel transcriptomics (toxicogenomics) technologies can be used to classify toxicants according to their health risks and to identify potential side effects long before discovering any pathological changes in the body. The Interagency Coordinating Committee on the Validation of Alternative Methods conducts technical evaluation of alternative testing methods and promotes their implementation into regulatory practice.CONCLUSIONS. Thus, new tools and technologies provide an opportunity for switching from in vivo toxicity testing of candidate medicinal products to in silico and in vitro methods.

A novel mixture sampling strategy combining latin hypercube sampling with optimized one factor at a time method: A case study on mixtures of antibiotics and pesticides

Global sensitivity analysis in conjunction with quantitative high-throughput screening presents a novel technique for identifying the key components that induce the toxicities of mixtures. However, the mixtures currently designed with this method suffer from unequal frequency sampling, repeated mixtures, and only odd factor levels being considered. Accordingly, we use latin hypercube sampling to generate the starting points of the trajectories to achieve equal frequency sampling and non-repeated mixtures, as well as apply different one factor at a time methods for factors with odd and even levels to achieve suitability for factors with both odd and even levels. This method is called LHS-OAT. LHS-OAT was successfully applied to design 110 equal-frequency and non-repeated mixtures consisting of six antibiotics and four pesticides. It was found that four factors, roxithromycin (A5), tetracycline (A6), dichlorvos (P1), and demeton-S (P3), induce the toxicities of mixtures, and A5 and P1 in the Shaying River Basin have risk quotients ≥ 1. Additionally, we developed the toxicity deviation ratio to correct the risk quotients of interacting mixtures for effective risk assessments. This study provides a rational and effective method for mixture design that accurately identifies the important factors that induce the toxicities of mixtures.

High-throughput screening identifies cell cycle-associated signaling cascades that regulate a multienzyme glucosome assembly in human cells.

We have previously demonstrated that human liver-type phosphofructokinase 1 (PFK1) recruits other rate-determining enzymes in glucose metabolism to organize multienzyme metabolic assemblies, termed glucosomes, in human cells. However, it has remained largely elusive how glucosomes are reversibly assembled and disassembled to functionally regulate glucose metabolism and thus contribute to human cell biology. We developed a high-content quantitative high-throughput screening (qHTS) assay to identify regulatory mechanisms that control PFK1-mediated glucosome assemblies from stably transfected HeLa Tet-On cells. Initial qHTS with a library of pharmacologically active compounds directed following efforts to kinase-inhibitor enriched collections. Consequently, three compounds that were known to inhibit cyclin-dependent kinase 2, ribosomal protein S6 kinase and Aurora kinase A, respectively, were identified and further validated under high-resolution fluorescence single-cell microscopy. Subsequent knockdown studies using small-hairpin RNAs further confirmed an active role of Aurora kinase A on the formation of PFK1 assemblies in HeLa cells. Importantly, all the identified protein kinases here have been investigated as key signaling nodes of one specific cascade that controls cell cycle progression in human cells. Collectively, our qHTS approaches unravel a cell cycle-associated signaling network that regulates the formation of PFK1-mediated glucosome assembly in human cells.

Using a Quantitative High-Throughput Screening Platform to Identify Molecular Targets and Compounds as Repurposing Candidates for Endometriosis

Endometriosis, defined as the growth of hormonally responsive endometrial-like tissue outside of the uterine cavity, is an estrogen-dependent, chronic, pro-inflammatory disease that affects up to 11.4% of women of reproductive age and gender-diverse people with a uterus. At present, there is no long-term cure, and the identification of new therapies that provide a high level of efficacy and favourable long-term safety profiles with rapid clinical access are a priority. In this study, quantitative high-throughput compound screens of 3517 clinically approved compounds were performed on patient-derived immortalized human endometrial stromal cell lines. Following assay optimization and compound criteria selection, a high-throughput screening protocol was developed to enable the identification of compounds that interfered with estrogen-stimulated cell growth. From these screens, 23 novel compounds were identified, in addition to their molecular targets and in silico cell-signalling pathways, which included the neuroactive ligand–receptor interaction pathway, metabolic pathways, and cancer-associated pathways. This study demonstrates for the first time the feasibility of performing large compound screens for the identification of new translatable therapeutics and the improved characterization of endometriosis molecular pathophysiology. Further investigation of the molecular targets identified herein will help uncover new mechanisms involved in the establishment, symptomology, and progression of endometriosis.

Small-molecule High-throughput Screening Identifies an MEK Inhibitor PD198306 that Enhances Sorafenib Efficacy via MCL-1 and BIM in Hepatocellular Carcinoma Cells.

Sorafenib is the most widely used systematic therapy drug for treating unresectable Hepatocellular Carcinoma (HCC) but showed dissatisfactory efficacy in clinical applications. We conducted a combinational quantitative small-molecule high-throughput screening (qHTS) to identify potential candidates to enhance the treatment effectiveness of sorafenib. First, using a Hep3B human HCC cell line, 7051 approved drugs and bioactive compounds were screened, then the primary hits were tested with/without 0.5 μM sorafenib respectively, the compound has the half maximal Inhibitory Concentration (IC50) shift value greater than 1.5 was thought to have the synergistic effect with sorafenib. Furthermore, the MEK inhibitor PD198306 was selected for the further mechanistic study. 12 effective compounds were identified, including kinase inhibitors targeting MEK, AURKB, CAMK, ROCK2, BRAF, PI3K, AKT and EGFR, and a μ-opioid receptor agonist and a Ltype calcium channel blocker. The mechanistic research of the combination of sorafenib plus PD198306 showed that the two compounds synergistically inhibited MEK-ERK and mTORC1- 4EBP1 and induced apoptosis in HCC cells, which can be attributed to the transcriptional and posttranslational regulation of MCL-1 and BIM. Small-molecule qHTS identifies MEK inhibitor PD1938306 as a potent sorafenib enhancer, together with several novel combination strategies that are valuable for further studies.

A novel equal frequency sampling of factor levels (EFSFL) method is applied to identify the dominant factor inducing the combined toxicities of 13 factors

The research framework combining global sensitivity analysis (GSA) with quantitative high-throughput screening (qHTS), called GSA-qHTS, provides a potentially feasible way to screen for important factors that induce toxicities of complex mixtures. Despite its value, the mixture samples designed using the GSA-qHTS technique still have a shortage of unequal factor levels, which leads to an asymmetry in the importance of elementary effects (EEs). In this study, we developed a novel method for mixture design that enables equal frequency sampling of factor levels (called EFSFL) by optimizing both the trajectory number and the design and expansion of the starting points for the trajectory. The EFSFL has been successfully employed to design 168 mixtures of 13 factors (12 chemicals and time) that each have three levels. By means of high-throughput microplate toxicity analysis, the toxicity change rules of the mixtures are revealed. Based on EE analysis, the important factors affecting the toxicities of the mixtures are screened. It was found that erythromycin is the dominant factor and time is an important non-chemical factor in mixture toxicities. The mixtures can be classified into types A, B, and C mixtures according to their toxicities at 12 h, and all the types B and C mixtures contain erythromycin at the maximum concentration. The toxicities of the type B mixtures increase firstly over time (0.25 ∼ 9 h) and then decrease (12 h), while those of the type C mixtures consistently increase over time. Some type A mixtures produce stimulation that increases with time. With the present new approach to mixture design, the frequency of factor levels in mixture samples is equal. Consequently, the accuracy of screening important factors is improved based on the EE method, providing a new method for the study of mixture toxicity.

Abstract 5505: Combination nitazoxanide and auranofin treatment has synergistic anticancer activity in anaplastic thyroid cancer and act by enhanced activation of multiple cell death pathways

Abstract Purpose: Anaplastic thyroid cancer (ATC) is one of the most aggressive human cancers, with a median survival time of 6 months and with no current curative treatment. We have used quantitative high-throughput screening (qHTS) of clinically approved or investigational agents to identify candidate compounds for ATC therapy. As monotherapy for most cancers is not effective, we used combination drug matrix screening of highly active compounds from our single agent qHTS to identify compound combinations that may show synergistic effect. In this study, we evaluated the anticancer activity of nitazoxanide and auranofin combination treatment and its mechanism of action and biomarkers of treatment response in in vitro and in vivo models of ATC. Experimental Design: We used four (8505C, C643, SW1736, THJ16T) ATC cell lines in in vitro and in vivo ATC models to evaluate the safety and efficacy of this combination treatment compared to single agent and vehicle control. Results: Combination nitazoxanide and auranofin treatment synergistically inhibited cellular proliferation (p<0.001) and inhibited colony formation and migration (p<0.001) in ATC cell lines. We observed cellular oxidative stress with significant increase in ROS levels in the combination treatment group (p<0.001). Nitazoxanide treatment alone and in combination with auranofin caused G1/G0 arrest in cell cycle, induced autophagy (increased LC3BII expression) and later apoptosis. Auranofin treatment alone and in combination with nitazoxanide induced ferroptosis (decreased GPX4 expression and intracellular GSH/GSSG ratios). RNA-Seq analysis, to identify biomarkers of response, showed >7-fold increase in HMOX-1 (heme oxygenase 1) with combination treatment which was validated by western blot. Combination treatment significantly inhibited tumor growth as compared to single agents (p<0.01) and had no significant treatment-related toxicity in vivo. Analysis of tumor samples showed significantly increased LC3BII expression by immunohistochemistry and reduced GPX4 mRNA expression (p<0.0001) with combination treatment compared to control in vivo. Conclusions: Combination nitazoxanide and auranofin treatment has synergistic anticancer activity in both in vitro and in vivo ATC models. The synergistic activity of the combination is due to enhanced G1/G0 arrest, greater activation of autophagy, apoptosis and ferroptosis than single drug treatment. LC3BII, HMOX-1 and GPX4 levels could be useful biomarkers of treatment response to combination nitazoxanide and auranofin. Citation Format: Chandrayee Ghosh, Viswanath Gunda, Jiangnan Hu, Lisa Zhang, Ya-Qin Zhang, Min Shen, Electron Kebebew. Combination nitazoxanide and auranofin treatment has synergistic anticancer activity in anaplastic thyroid cancer and act by enhanced activation of multiple cell death pathways. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5505.

Abstract 2684: Synergistic efficacy of HSP90 and PI3K inhibitors in adrenocortical carcinoma

Abstract Adrenocortical cancer (ACC) is a rare and aggressive cancer (0.5-2 cases/million/year) with poor 5-year survival. Most patients inevitably succumb to widespread metastasis due to a lack of effective systemic treatment; therefore, it is critically important to identify new therapies for clinical trials. In this direction, we identified a potent synergistic combination of Heat Shock Protein 90 (HSP90) and PI3K inhibitors via quantitative high-throughput drug screening (qHTS) for ACC, using a pharmaceutical library of ~5000 drugs (FDA approved or investigational), and evaluating the drug synergy by computerized drug combination matrix analysis. Preclinical in vitro studies were performed to validate the efficacy of HSP90 inhibitors (STA9090, AUY922, HSP990), with PI3K inhibitors; PIK75 (investigational) or clinically available BGT226, and their pairwise combinations, in NCI-H295R and SW13 ACC cells. The drug combination of STA9090 and PIK75 significantly inhibited cell proliferation (monolayer and 3-dimensional culture and induced apoptosis more effectively than the individual drugs, with simultaneous upregulation of apoptotic protein markers (cleaved-Caspase3, cleaved-PARP), inhibition of the phosphorylated members of PI3K signaling pathway (AKT1, mTOR, S6K, 4EB1 and GSK3α/β), and the G2/M phase cell cycle arrest in ACC cells. Additionally, the synergetic effect of the drug combination was effective in reducing the metastatic potential as revealed by invasion/migration assay, which was confirmed by the downregulation of the epithelial-to-mesenchymal transition proteins (Vimentin, N-cadherin, SNAIL and Zeb1). An inhibition of cortisol production and altered oncogenic proteomic profiling was also observed. We validated the synergy of BGT226 with STA9090 and observed similar phenotypic changes by the drug combination in ACC cells. Interestingly, RNA sequencing and pathway analysis further revealed distinct gene expression profiles of STA9090 combined with PIK75 or BGT226, indicating different mechanism of cell death in both the PI3K drug combination treatment groups. Consistent with our in vitro findings, observations from the gene expression data from TCGA revealed significant mRNA overexpression of genes in HSP90 and PI3K signaling pathways (HSP90AA1, HSP90AB1 HSP90B1, TRAP1, PI3KCA, PI3KCB, AKT2, CDK1, CDK4, NR3C1) in 64% (n=59/92) ACC samples, with a positive correlation of mesenchymal markers TWIST1, ZEB1, VIM with HSP90AB1 and PI3KCA, suggesting our drug combination can be applicable in patients with ACC. A similar pattern of gene expressions was confirmed in independent GEO datasets. Conclusively, combination of HSP90 and PI3K inhibitors demonstrated a promising in vitro synergistic efficacy by inhibiting the key oncogenic targets of ACC. Further validation of in vivo efficacy is warranted. Citation Format: Prachi Mishra, Dipranjan Laha, Brieann Sobieski, Min Shen, Ya-Qin Zhang, Matthew Hall, Naris Nilubol. Synergistic efficacy of HSP90 and PI3K inhibitors in adrenocortical carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2684.

Identification of Potent and Selective Acetylcholinesterase/Butyrylcholinesterase Inhibitors by Virtual Screening.

Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) play important roles in human neurodegenerative disorders such as Alzheimer's disease. In this study, machine learning methods were applied to develop quantitative structure-activity relationship models for the prediction of novel AChE and BChE inhibitors based on data from quantitative high-throughput screening assays. The models were used to virtually screen an in-house collection of ∼360K compounds. The optimal models achieved good performance with area under the receiver operating characteristic curve values ranging from 0.83 ± 0.03 to 0.87 ± 0.01 for the prediction of AChE/BChE inhibition activity and selectivity. Experimental validation showed that the best-performing models increased the assay hit rate by several folds. We identified 88 novel AChE and 126 novel BChE inhibitors, 25% (AChE) and 53% (BChE) of which showed potent inhibitory effects (IC50 < 5 μM). In addition, structure-activity relationship analysis of the BChE inhibitors revealed scaffolds for chemistry design and optimization. In conclusion, machine learning models were shown to efficiently identify potent and selective inhibitors against AChE and BChE and novel structural series for further design and development of potential therapeutics against neurodegenerative disorders.

QHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data

High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents having pharmacologic properties often by evaluation of large chemical libraries. Standard HTS data can be simply plotted as an x–y graph usually represented as % activity of a compound tested at a single concentration vs compound ID, whereas quantitative HTS (qHTS) data incorporates a third axis represented by concentration. By virtue of the additional data points arising from the compound titration and the incorporation of logistic fit parameters that define the concentration–response curve, such as EC50 and Hill slope, qHTS data has been challenging to display on a single graph. Here we provide a flexible solution to the rapid plotting of complete qHTS data sets to produce a 3-axis plot we call qHTS Waterfall Plots. The software described here can be generally applied to any 3-axis dataset and is available as both an R package and an R shiny application.Graphical