Artemisinins Target GABAA Receptor Signaling and Impair α Cell Identity.

Type 1 diabetes is characterized by the destruction of pancreatic ß cells, and generating new insulin-producing cells from other cell types is a major aim of regenerative medicine. One promising approach is transdifferentiation of developmentally related pancreatic cell types, including glucagon-producing α cells. In a genetic model, loss of the master regulatory transcription factor Arx is sufficient to induce the conversion of α cells to functional ß-like cells. Here, we identify artemisinins as small molecules that functionally repress Arx by causing its translocation to the cytoplasm. We show that the protein gephyrin is the mammalian target of these antimalarial drugs and that the mechanism of action of these molecules depends on the enhancement of GABAA receptor signaling. Our results in zebrafish, rodents, and primary human pancreatic islets identify gephyrin as a druggable target for the regeneration of pancreatic ß cell mass from α cells.

Heme drives hemolysis-induced susceptibility to infection via disruption of phagocyte functions.

Hemolysis drives susceptibility to bacterial infections and predicts poor outcome from sepsis. These detrimental effects are commonly considered to be a consequence of heme-iron serving as a nutrient for bacteria. We employed a Gram-negative sepsis model and found that elevated heme levels impaired the control of bacterial proliferation independently of heme-iron acquisition by pathogens. Heme strongly inhibited phagocytosis and the migration of human and mouse phagocytes by disrupting actin cytoskeletal dynamics via activation of the GTP-binding Rho family protein Cdc42 by the guanine nucleotide exchange factor DOCK8. A chemical screening approach revealed that quinine effectively prevented heme effects on the cytoskeleton, restored phagocytosis and improved survival in sepsis. These mechanistic insights provide potential therapeutic targets for patients with sepsis or hemolytic disorders.

Repair of UV-Induced DNA Damage Independent of Nucleotide Excision Repair Is Masked by MUTYH.

DNA lesions caused by UV damage are thought to be repaired solely by the nucleotide excision repair (NER) pathway in human cells. Patients carrying mutations within genes functioning in this pathway display a range of pathologies, including an increased susceptibility to cancer, premature aging, and neurological defects. There are currently no curative therapies available. Here we performed a high-throughput chemical screen for agents that could alleviate the cellular sensitivity of NER-deficient cells to UV-induced DNA damage. This led to the identification of the clinically approved anti-diabetic drug acetohexamide, which promoted clearance of UV-induced DNA damage without the accumulation of chromosomal aberrations, hence promoting cellular survival. Acetohexamide exerted this protective function by antagonizing expression of the DNA glycosylase, MUTYH. Together, our data reveal the existence of an NER-independent mechanism to remove UV-induced DNA damage and prevent cell death.

Leveraging Cell Painting Images to Expand the Applicability Domain and Actively Improve Deep Learning Quantitative Structure-Activity Relationship Models.

The search for chemical hit material is a lengthy and increasingly expensive drug discovery process. To improve it, ligand-based quantitative structure-activity relationship models have been broadly applied to optimize primary and secondary compound properties. Although these models can be deployed as early as the stage of molecule design, they have a limited applicability domain─if the structures of interest differ substantially from the chemical space on which the model was trained, a reliable prediction will not be possible. Image-informed ligand-based models partly solve this shortcoming by focusing on the phenotype of a cell caused by small molecules, rather than on their structure. While this enables chemical diversity expansion, it limits the application to compounds physically available and imaged. Here, we employ an active learning approach to capitalize on both of these methods' strengths and boost the model performance of a mitochondrial toxicity assay (Glu/Gal). Specifically, we used a phenotypic Cell Painting screen to build a chemistry-independent model and adopted the results as the main factor in selecting compounds for experimental testing. With the additional Glu/Gal annotation for selected compounds we were able to dramatically improve the chemistry-informed ligand-based model with respect to the increased recognition of compounds from a 10% broader chemical space.

A widespread role for SLC transmembrane transporters in resistance to cytotoxic drugs.

Solute carriers (SLCs) are the largest family of transmembrane transporters in humans and are major determinants of cellular metabolism. Several SLCs have been shown to be required for the uptake of chemical compounds into cellular systems, but systematic surveys of transporter-drug relationships in human cells are currently lacking. We performed a series of genetic screens in a haploid human cell line against 60 cytotoxic compounds representative of the chemical space populated by approved drugs. By using an SLC-focused CRISPR-Cas9 library, we identified transporters whose absence induced resistance to the drugs tested. This included dependencies involving the transporters SLC11A2/SLC16A1 for artemisinin derivatives and SLC35A2/SLC38A5 for cisplatin. The functional dependence on SLCs observed for a significant proportion of the screened compounds suggests a widespread role for SLCs in the uptake and cellular activity of cytotoxic drugs and provides an experimentally validated set of SLC-drug associations for a number of clinically relevant compounds.

Global survey of the immunomodulatory potential of common drugs.

Small-molecule drugs may complement antibody-based therapies in an immune-oncology setting, yet systematic methods for the identification and characterization of the immunomodulatory properties of these entities are lacking. We surveyed the immumomodulatory potential of 1,402 small chemical molecules, as defined by their ability to alter the cell-cell interactions among peripheral mononuclear leukocytes ex vivo, using automated microscopy and population-wide single-cell image analysis. Unexpectedly, ∼10% of the agents tested affected these cell-cell interactions differentially. The results accurately recapitulated known immunomodulatory drug classes and revealed several clinically approved drugs that unexpectedly harbor the ability to modulate the immune system, which could potentially contribute to their physiological mechanism of action. For instance, the kinase inhibitor crizotinib promoted T cell interactions with monocytes, as well as with cancer cells, through inhibition of the receptor tyrosine kinase MSTR1 and subsequent upregulation of the expression of major histocompatibility complex molecules. The approach offers an attractive platform for the personalized identification and characterization of immunomodulatory therapeutics.

A combinatorial screen of the CLOUD uncovers a synergy targeting the androgen receptor.

Approved drugs are invaluable tools to study biochemical pathways, and further characterization of these compounds may lead to repurposing of single drugs or combinations. Here we describe a collection of 308 small molecules representing the diversity of structures and molecular targets of all FDA-approved chemical entities. The CeMM Library of Unique Drugs (CLOUD) covers prodrugs and active forms at pharmacologically relevant concentrations and is ideally suited for combinatorial studies. We screened pairwise combinations of CLOUD drugs for impairment of cancer cell viability and discovered a synergistic interaction between flutamide and phenprocoumon (PPC). The combination of these drugs modulates the stability of the androgen receptor (AR) and resensitizes AR-mutant prostate cancer cells to flutamide. Mechanistically, we show that the AR is a substrate for γ-carboxylation, a post-translational modification inhibited by PPC. Collectively, our data suggest that PPC could be repurposed to tackle resistance to antiandrogens in prostate cancer patients.

Mapping the chemical chromatin reactivation landscape identifies BRD4-TAF1 cross-talk.

Bromodomain-containing proteins of the BET family recognize histone lysine acetylation and mediate transcriptional activation of target genes such as the MYC oncogene. Pharmacological inhibitors of BET domains promise therapeutic benefits in a variety of cancers. We performed a high-diversity chemical compound screen for agents capable of modulating BRD4-dependent heterochromatization of a generic reporter in human cells. In addition to known and new compounds targeting BRD4, we identified small molecules that mimic BRD4 inhibition without direct engagement. One such compound was a potent inhibitor of the second bromodomain of TAF1. Using this inhibitor, we discovered that TAF1 synergizes with BRD4 to control proliferation of cancer cells, making TAF1 an attractive epigenetic target in cancers driven by MYC.

Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity.

Identifying active compounds for a target is a time- and resource-intensive task in early drug discovery. Accurate bioactivity prediction using morphological profiles could streamline the process, enabling smaller, more focused compound screens. We investigate the potential of deep learning on unrefined single-concentration activity readouts and Cell Painting data, to predict compound activity across 140 diverse assays. We observe an average ROC-AUC of 0.744 ± 0.108 with 62% of assays achieving ≥0.7, 30% ≥0.8, and 7% ≥0.9. In many cases, the high prediction performance can be achieved using only brightfield images instead of multichannel fluorescence images. A comprehensive analysis shows that Cell Painting-based bioactivity prediction is robust across assay types, technologies, and target classes, with cell-based assays and kinase targets being particularly well-suited for prediction. Experimental validation confirms the enrichment of active compounds. Our findings indicate that models trained on Cell Painting data, combined with a small set of single-concentration data points, can reliably predict the activity of a compound library across diverse targets and assays while maintaining high hit rates and scaffold diversity. This approach has the potential to reduce the size of screening campaigns, saving time and resources, and enabling primary screening with more complex assays.

Optimizing the Cell Painting assay for image-based profiling.

In image-based profiling, software extracts thousands of morphological features of cells from multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used for basic research and drug discovery. Powerful applications have been proven, including clustering chemical and genetic perturbations on the basis of their similar morphological impact, identifying disease phenotypes by observing differences in profiles between healthy and diseased cells and predicting assay outcomes by using machine learning, among many others. Here, we provide an updated protocol for the most popular assay for image-based profiling, Cell Painting. Introduced in 2013, it uses six stains imaged in five channels and labels eight diverse components of the cell: DNA, cytoplasmic RNA, nucleoli, actin, Golgi apparatus, plasma membrane, endoplasmic reticulum and mitochondria. The original protocol was updated in 2016 on the basis of several years' experience running it at two sites, after optimizing it by visual stain quality. Here, we describe the work of the Joint Undertaking for Morphological Profiling Cell Painting Consortium, to improve upon the assay via quantitative optimization by measuring the assay's ability to detect morphological phenotypes and group similar perturbations together. The assay gives very robust outputs despite various changes to the protocol, and two vendors' dyes work equivalently well. We present Cell Painting version 3, in which some steps are simplified and several stain concentrations can be reduced, saving costs. Cell culture and image acquisition take 1-2 weeks for typically sized batches of ≤20 plates; feature extraction and data analysis take an additional 1-2 weeks.This protocol is an update to Nat. Protoc. 11, 1757-1774 (2016): https://doi.org/10.1038/nprot.2016.105.

Quantitative proteomic analysis of A549 cells infected with human respiratory syncytial virus.

Human respiratory syncytial virus (HRSV) is a major cause of pediatric lower respiratory tract disease to which there is no vaccine or efficacious chemotherapeutic strategy. Although RNA synthesis and virus assembly occur in the cytoplasm, HRSV is known to induce nuclear responses in the host cell as replication alters global gene expression. Quantitative proteomics was used to take an unbiased overview of the protein changes in transformed human alveolar basal epithelial cells infected with HRSV. Underpinning this was the use of stable isotope labeling with amino acids in cell culture coupled to LC-MS/MS, which allowed the direct and simultaneous identification and quantification of both cellular and viral proteins. To reduce sample complexity and increase data return on potential protein localization, cells were fractionated into nuclear and cytoplasmic extracts. This resulted in the identification of 1,140 cellular proteins and six viral proteins. The proteomics data were analyzed using Ingenuity Pathways Analysis to identify defined canonical pathways and functional groupings. Selected data were validated using Western blot, direct and indirect immunofluorescence confocal microscopy, and functional assays. The study served to validate and expand upon known HRSV-host cell interactions, including those associated with the antiviral response and alterations in subnuclear structures such as the nucleolus and ND10 (promyelocytic leukemia bodies). In addition, novel changes were observed in mitochondrial proteins and functions, cell cycle regulatory molecules, nuclear pore complex proteins and nucleocytoplasmic trafficking proteins. These data shed light into how the cell is potentially altered to create conditions more favorable for infection. Additionally, the study highlights the application and advantage of stable isotope labeling with amino acids in cell culture coupled to LC-MS/MS for the analysis of virus-host interactions.

Molecular and Pharmacological Bladder Cancer Therapy Screening: Discovery of Clofarabine as a Highly Active Compound.

BACKGROUND: The heterogeneity of bladder cancers (BCs) is a major challenge for the development of novel therapies. However, given the high rates of recurrence and/or treatment failure, the identification of effective therapeutic strategies is an urgent clinical need. OBJECTIVE: We aimed to establish a model system for drug identification/repurposing in order to identify novel therapies for the treatment of BC. DESIGN, SETTING, AND PARTICIPANTS: A collection of commercially available BC cell lines (n = 32) was comprehensively characterized. A panel of 23 cell lines, representing a broad spectrum of BC, was selected to perform a high-throughput drug screen. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Positive hits were defined as compounds giving >50% inhibition in at least one BC cell line. RESULTS AND LIMITATIONS: Amongst >1700 tested chemical compounds, a total of 471 substances exhibited antineoplastic effects. Clofarabine, an antimetabolite drug used as third-line treatment for childhood acute lymphoblastic leukaemia, was amongst the limited number of drugs with inhibitory effects on cell lines of all intrinsic subtypes. We, thus, reassessed the substance and confirmed its inhibitory effects on commercially available cell lines and patient-derived cell cultures representing various disease stages, intrinsic subtypes, and histologic variants. To verify these effects in vivo, a patient-derived cell xenograft model for urothelial carcinoma (UC) was used. Well-tolerated doses of clofarabine induced complete remission in all treated animals (n = 12) suffering from both early- and late-stage disease. We further took advantage of another patient-derived cell xenograft model originating from the rare disease entity sarcomatoid carcinoma (SaC). Similarly to UC xenograft mice, clofarabine induced subcomplete to complete tumour remissions in all treated animals (n = 8). CONCLUSIONS: The potent effects of clofarabine in vitro and in vivo suggest that our findings may be of high clinical relevance. Clinical trials are needed to assess the value of clofarabine in improving BC patient care. PATIENT SUMMARY: We used commercially available cell lines for the identification of novel drugs for the treatment of bladder cancer. We confirmed the effects of one of these drugs, clofarabine, in patient-derived cell lines and two different mouse models, thereby demonstrating a potential clinical relevance of this substance in bladder cancer treatment.

An inhibitor-mediated beta-cell dedifferentiation model reveals distinct roles for FoxO1 in glucagon repression and insulin maturation.

OBJECTIVE: The loss of forkhead box protein O1 (FoxO1) signaling in response to metabolic stress contributes to the etiology of type II diabetes, causing the dedifferentiation of pancreatic beta cells to a cell type reminiscent of endocrine progenitors. Lack of methods to easily model this process in vitro, however, have hindered progress into the identification of key downstream targets and potential inhibitors. We therefore aimed to establish such an in vitro cellular dedifferentiation model and apply it to identify novel agents involved in the maintenance of beta-cell identity. METHODS: The murine beta-cell line, Min6, was used for primary experiments and high-content screening. Screens encompassed a library of small-molecule drugs representing the chemical and target space of all FDA-approved small molecules with an automated immunofluorescence readout. Validation experiments were performed in a murine alpha-cell line as well as in primary murine and human diabetic islets. Developmental effects were studied in zebrafish and C. elegans models, while diabetic db/db mouse models were used to elucidate global glucose metabolism outcomes. RESULTS: We show that short-term pharmacological FoxO1 inhibition can model beta-cell dedifferentiation by downregulating beta-cell-specific transcription factors, resulting in the aberrant expression of progenitor genes and the alpha-cell marker glucagon. From a high-content screen, we identified loperamide as a small molecule that can prevent FoxO inhibitor-induced glucagon expression and further stimulate insulin protein processing and secretion by altering calcium levels, intracellular pH, and FoxO1 localization. CONCLUSIONS: Our study provides novel models, molecular targets, and drug candidates for studying and preventing beta-cell dedifferentiation.

Mapping the perturbome network of cellular perturbations.

Drug combinations provide effective treatments for diverse diseases, but also represent a major cause of adverse reactions. Currently there is no systematic understanding of how the complex cellular perturbations induced by different drugs influence each other. Here, we introduce a mathematical framework for classifying any interaction between perturbations with high-dimensional effects into 12 interaction types. We apply our framework to a large-scale imaging screen of cell morphology changes induced by diverse drugs and their combination, resulting in a perturbome network of 242 drugs and 1832 interactions. Our analysis of the chemical and biological features of the drugs reveals distinct molecular fingerprints for each interaction type. We find a direct link between drug similarities on the cell morphology level and the distance of their respective protein targets within the cellular interactome of molecular interactions. The interactome distance is also predictive for different types of drug interactions.

Mapping the Human Kinome in Response to DNA Damage.

We provide a catalog for the effects of the human kinome on cell survival in response to DNA-damaging agents, covering all major DNA repair pathways. By treating 313 kinase-deficient cell lines with ten diverse DNA-damaging agents, including seven commonly used chemotherapeutics, we identified examples of vulnerability and resistance that are kinase specific. To investigate synthetic lethal interactions, we tested the response to carmustine for 25 cell lines by establishing a phenotypic fluorescence-activated cell sorting (FACS) assay designed to validate gene-drug interactions. We show apoptosis, cell cycle changes, and DNA damage and proliferation after alkylation- or crosslink-induced damage. In addition, we reconstitute the cellular sensitivity of DYRK4, EPHB6, MARK3, and PNCK as a proof of principle for our study. Furthermore, using global phosphoproteomics on cells lacking MARK3, we provide evidence for its role in the DNA damage response. Our data suggest that cancers with inactivating mutations in kinases, including MARK3, are particularly vulnerable to alkylating chemotherapeutic agents.

Pharmacologic inhibition of STAT5 in acute myeloid leukemia.

The transcription factor STAT5 is an essential downstream mediator of many tyrosine kinases (TKs), particularly in hematopoietic cancers. STAT5 is activated by FLT3-ITD, which is a constitutively active TK driving the pathogenesis of acute myeloid leukemia (AML). Since STAT5 is a critical mediator of diverse malignant properties of AML cells, direct targeting of STAT5 is of significant clinical value. Here, we describe the development and preclinical evaluation of a novel, potent STAT5 SH2 domain inhibitor, AC-4-130, which can efficiently block pathological levels of STAT5 activity in AML. AC-4-130 directly binds to STAT5 and disrupts STAT5 activation, dimerization, nuclear translocation, and STAT5-dependent gene transcription. Notably, AC-4-130 substantially impaired the proliferation and clonogenic growth of human AML cell lines and primary FLT3-ITD+ AML patient cells in vitro and in vivo. Furthermore, AC-4-130 synergistically increased the cytotoxicity of the JAK1/2 inhibitor Ruxolitinib and the p300/pCAF inhibitor Garcinol. Overall, the synergistic effects of AC-4-130 with TK inhibitors (TKIs) as well as emerging treatment strategies provide new therapeutic opportunities for leukemia and potentially other cancers.

Acquired nintedanib resistance in FGFR1-driven small cell lung cancer: role of endothelin-A receptor-activated ABCB1 expression.

Genomically amplified fibroblast growth factor receptor 1 (FGFR1) is an oncogenic driver in defined lung cancer subgroups and predicts sensibility against FGFR1 inhibitors in this patient cohort. The FGFR inhibitor nintedanib has recently been approved for treatment of lung adenocarcinoma and is currently evaluated for small cell lung cancer (SCLC). However, tumor recurrence due to development of nintedanib resistance might occur. Hence, we aimed at characterizing the molecular mechanisms underlying acquired nintedanib resistance in FGFR1-driven lung cancer. Chronic nintedanib exposure of the FGFR1-driven SCLC cell line DMS114 (DMS114/NIN) but not of two NSCLC cell lines induced massive overexpression of the multidrug-resistance transporter ABCB1. Indeed, we proved nintedanib to be both substrate and modulator of ABCB1-mediated efflux. Importantly, the oncogenic FGFR1 signaling axis remained active in DMS114/NIN cells while bioinformatic analyses suggested hyperactivation of the endothelin-A receptor (ETAR) signaling axis. Indeed, ETAR inhibition resensitized DMS114/NIN cells against nintedanib by downregulation of ABCB1 expression. PKC and downstream NFκB were identified as major downstream players in ETAR-mediated ABCB1 hyperactivation. Summarizing, ABCB1 needs to be considered as a factor underlying nintedanib resistance. Combination approaches with ETAR antagonists or switching to non-ABCB1 substrate FGFR inhibitors represent innovative strategies to manage nintedanib resistance in lung cancer.