Morphological profiling in human neural progenitor cells classifies hits in a pilot drug screen for Alzheimer's disease.

Alzheimer's disease accounts for 60-70% of dementia cases. Current treatments are inadequate and there is a need to develop new approaches to drug discovery. Recently, in cancer, morphological profiling has been used in combination with high-throughput screening of small-molecule libraries in human cells in vitro. To test feasibility of this approach for Alzheimer's disease, we developed a cell morphology-based drug screen centred on the risk gene, SORL1 (which encodes the protein SORLA). Increased Alzheimer's disease risk has been repeatedly linked to variants in SORL1, particularly those conferring loss or decreased expression of SORLA, and lower SORL1 levels are observed in post-mortem brain samples from individuals with Alzheimer's disease. Consistent with its role in the endolysosomal pathway, SORL1 deletion is associated with enlarged endosomes in neural progenitor cells and neurons. We, therefore, hypothesized that multi-parametric, image-based cell phenotyping would identify features characteristic of SORL1 deletion. An automated morphological profiling method (Cell Painting) was adapted to neural progenitor cells and used to determine the phenotypic response of SORL1-/- neural progenitor cells to treatment with compounds from a small internationally approved drug library (TargetMol, 330 compounds). We detected distinct phenotypic signatures for SORL1-/- neural progenitor cells compared to isogenic wild-type controls. Furthermore, we identified 16 compounds (representing 14 drugs) that reversed the mutant morphological signatures in neural progenitor cells derived from three SORL1-/- induced pluripotent stem cell sub-clones. Network pharmacology analysis revealed the 16 compounds belonged to five mechanistic groups: 20S proteasome, aldehyde dehydrogenase, topoisomerase I and II, and DNA synthesis inhibitors. Enrichment analysis identified DNA synthesis/damage/repair, proteases/proteasome and metabolism as key pathways/biological processes. Prediction of novel targets revealed enrichment in pathways associated with neural cell function and Alzheimer's disease. Overall, this work suggests that (i) a quantitative phenotypic metric can distinguish induced pluripotent stem cell-derived SORL1-/- neural progenitor cells from isogenic wild-type controls and (ii) phenotypic screening combined with multi-parametric high-content image analysis is a viable option for drug repurposing and discovery in this human neural cell model of Alzheimer's disease.

High throughput screening identifies dasatinib as synergistic with trametinib in low grade serous ovarian carcinoma.

BACKGROUND: Low grade serous ovarian carcinoma (LGSOC) is a distinct histotype of ovarian cancer characterised high levels of intrinsic chemoresistance, highlighting the urgent need for new treatments. High throughput screening in clinically-informative cell-based models represents an attractive strategy for identifying candidate treatment options for prioritisation in clinical studies. METHODS: We performed a high throughput drug screen of 1610 agents across a panel of 6 LGSOC cell lines (3 RAS/RAF-mutant, 3 RAS/RAF-wildtype) to identify novel candidate therapeutic approaches. Validation comprised dose-response analysis across 9 LGSOC models and 5 high grade serous comparator lines. RESULTS: 16 hits of 1610 screened compounds were prioritised for validation based on >50% reduction in nuclei counts in over half of screened cell lines at 1000 nM concentration. 11 compounds passed validation, and the four agents of greatest interest (dasatinib, tyrosine kinase inhibitor; disulfiram, aldehyde dehydrogenase inhibitor; carfilzomib, proteasome inhibitor; romidepsin, histone deacetylase inhibitor) underwent synergy profiling with the recently approved MEK inhibitor trametinib. Disulfiram demonstrated excellent selectivity for LGSOC versus high grade serous ovarian carcinoma comparator lines (P = 0.003 for IC50 comparison), while the tyrosine kinase inhibitor dasatinib demonstrated favourable synergy with trametinib across multiple LGSOC models (maximum zero interaction potency synergy score 46.9). The novel, highly selective Src family kinase (SFK) inhibitor NXP900 demonstrated a similar trametinib synergy profile to dasatinib, suggesting that SFK inhibition is the likely driver of synergy. CONCLUSION: Dasatinib and other SFK inhibitors represent novel candidate treatments for LGSOC and demonstrate synergy with trametinib. Disulfiram represents an additional treatment strategy worthy of investigation.

A cautionary note on the use of N-acetylcysteine as a reactive oxygen species antagonist to assess copper mediated cell death.

A new form of cell death has recently been proposed involving copper-induced cell death, termed cuproptosis. This new form of cell death has been widely studied in relation to a novel class of copper ionophores, including elesclomol and disulfiram. However, the exact mechanism leading to cell death remains contentious. The oldest and most widely accepted biological mechanism is that the accumulated intracellular copper leads to excessive build-up of reactive oxygen species and that this is what ultimately leads to cell death. Most of this evidence is largely based on studies using N-acetylcysteine (NAC), an antioxidant, to relieve the oxidative stress and prevent cell death. However, here we have demonstrated using inductively coupled mass-spectrometry, that NAC pretreatment significantly reduces intracellular copper uptake triggered by the ionophores, elesclomol and disulfiram, suggesting that reduction in copper uptake, rather than the antioxidant activity of NAC, is responsible for the diminished cell death. We present further data showing that key mediators of reactive oxygen species are not upregulated in response to elesclomol treatment, and further that sensitivity of cancer cell lines to reactive oxygen species does not correlate with sensitivity to these copper ionophores. Our findings are in line with several recent studies proposing the mechanism of cuproptosis is instead via copper mediated aggregation of proteins, resulting in proteotoxic stress leading to cell death. Overall, it is vital to disseminate this key piece of information regarding NAC's activity on copper uptake since new research attributing the effect of NAC on copper ionophore activity to quenching of reactive oxygen species is being published regularly and our studies suggest their conclusions may be misleading.

Discovery of pyrazolopyrimidines that selectively inhibit CSF-1R kinase by iterative design, synthesis and screening against glioblastoma cells.

Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer in adults, with an average life expectancy under treatment of approx. 15 months. GBM is characterised by a complex set of genetic alterations that results in significant disruption of receptor tyrosine kinase (RTK) signaling. We report here an exploration of the pyrazolo[3,4-d]pyrimidine scaffold in search for antiproliferative compounds directed to GBM treatment. Small compound libraries were synthesised and screened against GBM cells to build up structure-antiproliferative activity-relationships (SAARs) and inform further rounds of design, synthesis and screening. 76 novel compounds were generated through this iterative process that found low micromolar potencies against selected GBM lines, including patient-derived stem cells. Phenomics analysis demonstrated preferential activity against glioma cells of the mesenchymal subtype, whereas kinome screening identified colony stimulating factor-1 receptor (CSF-1R) as the lead's target, a RTK implicated in the tumourigenesis and progression of different cancers and the immunoregulation of the GBM microenvironment.

Crosstalk with lung fibroblasts shapes the growth and therapeutic response of mesothelioma cells.

Mesothelioma is an aggressive cancer of the mesothelial layer associated with an extensive fibrotic response. The latter is in large part mediated by cancer-associated fibroblasts which mediate tumour progression and poor prognosis. However, understanding of the crosstalk between cancer cells and fibroblasts in this disease is mostly lacking. Here, using co-cultures of patient-derived mesothelioma cell lines and lung fibroblasts, we demonstrate that fibroblast activation is a self-propagated process producing a fibrotic extracellular matrix (ECM) and triggering drug resistance in mesothelioma cells. Following characterisation of mesothelioma cells/fibroblasts signalling crosstalk, we identify several FDA-approved targeted therapies as far more potent than standard-of-care Cisplatin/Pemetrexed in ECM-embedded co-culture spheroid models. In particular, the SRC family kinase inhibitor, Saracatinib, extends overall survival well beyond standard-of-care in a mesothelioma genetically-engineered mouse model. In short, we lay the foundation for the rational design of novel therapeutic strategies targeting mesothelioma/fibroblast communication for the treatment of mesothelioma patients.

Evolution and impact of high content imaging.

The field of high content imaging has steadily evolved and expanded substantially across many industry and academic research institutions since it was first described in the early 1990's. High content imaging refers to the automated acquisition and analysis of microscopic images from a variety of biological sample types. Integration of high content imaging microscopes with multiwell plate handling robotics enables high content imaging to be performed at scale and support medium- to high-throughput screening of pharmacological, genetic and diverse environmental perturbations upon complex biological systems ranging from 2D cell cultures to 3D tissue organoids to small model organisms. In this perspective article the authors provide a collective view on the following key discussion points relevant to the evolution of high content imaging: • Evolution and impact of high content imaging: An academic perspective • Evolution and impact of high content imaging: An industry perspective • Evolution of high content image analysis • Evolution of high content data analysis pipelines towards multiparametric and phenotypic profiling applications • The role of data integration and multiomics • The role and evolution of image data repositories and sharing standards • Future perspective of high content imaging hardware and software.

Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells.

Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjusted for library size, cellular activity, chemical diversity and availability, and target selectivity. The resulting compound collections cover a wide range of protein targets and biological pathways implicated in various cancers, making them widely applicable to precision oncology. We characterized the compound and target spaces of the virtual libraries, in comparison with a minimal screening library of 1,211 compounds for targeting 1,386 anticancer proteins. In a pilot screening study, we identified patient-specific vulnerabilities by imaging glioma stem cells from patients with glioblastoma (GBM), using a physical library of 789 compounds that cover 1,320 of the anticancer targets. The cell survival profiling revealed highly heterogeneous phenotypic responses across the patients and GBM subtypes.

Discovery of senolytics using machine learning.

Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics are known due to the lack of well-characterised molecular targets. Here, we report the discovery of three senolytics using cost-effective machine learning algorithms trained solely on published data. We computationally screened various chemical libraries and validated the senolytic action of ginkgetin, periplocin and oleandrin in human cell lines under various modalities of senescence. The compounds have potency comparable to known senolytics, and we show that oleandrin has improved potency over its target as compared to best-in-class alternatives. Our approach led to several hundred-fold reduction in drug screening costs and demonstrates that artificial intelligence can take maximum advantage of small and heterogeneous drug screening data, paving the way for new open science approaches to early-stage drug discovery.

Drug screening in zebrafish larvae reveals inflammation-related modulators of secondary damage after spinal cord injury in mice.

Prolonged inflammation after spinal cord injury is detrimental to recovery. To find pharmacological modulators of the inflammation response, we designed a rapid drug screening paradigm in larval zebrafish followed by testing of hit compounds in a mouse spinal cord injury model. Methods: We used reduced il-1ß linked green fluorescent protein (GFP) reporter gene expression as a read-out for reduced inflammation in a screen of 1081 compounds in larval zebrafish. Hit drugs were tested in a moderate contusion model in mice for cytokine regulation, and improved tissue preservation and locomotor recovery. Results: Three compounds robustly reduced il-1ß expression in zebrafish. Cimetidine, an over-the-counter H2 receptor antagonist, also reduced the number of pro-inflammatory neutrophils and rescued recovery after injury in a zebrafish mutant with prolonged inflammation. Cimetidine action on il-1ß expression levels was abolished by somatic mutation of H2 receptor hrh2b, suggesting specific action. In mice, systemic treatment with Cimetidine led to significantly improved recovery of locomotor behavior as compared to controls, accompanied by decreased neuronal tissue loss and a shift towards a pro-regenerative profile of cytokine gene expression. Conclusion: Our screen revealed H2 receptor signaling as a promising target for future therapeutic interventions in spinal cord injury. This work highlights the usefulness of the zebrafish model for rapid screening of drug libraries to identify therapeutics to treat mammalian spinal cord injury.

Phenonaut: multiomics data integration for phenotypic space exploration.

SUMMARY: Data integration workflows for multiomics data take many forms across academia and industry. Efforts with limited resources often encountered in academia can easily fall short of data integration best practices for processing and combining high-content imaging, proteomics, metabolomics, and other omics data. We present Phenonaut, a Python software package designed to address the data workflow needs of migration, control, integration, and auditability in the application of literature and proprietary techniques for data source and structure agnostic workflow creation. AVAILABILITY AND IMPLEMENTATION: Source code: https://github.com/CarragherLab/phenonaut, Documentation: https://carragherlab.github.io/phenonaut, PyPI package: https://pypi.org/project/phenonaut/.

Macrophages promote anti-androgen resistance in prostate cancer bone disease.

Metastatic castration-resistant prostate cancer (PC) is the final stage of PC that acquires resistance to androgen deprivation therapies (ADT). Despite progresses in understanding of disease mechanisms, the specific contribution of the metastatic microenvironment to ADT resistance remains largely unknown. The current study identified that the macrophage is the major microenvironmental component of bone-metastatic PC in patients. Using a novel in vivo model, we demonstrated that macrophages were critical for enzalutamide resistance through induction of a wound-healing-like response of ECM-receptor gene expression. Mechanistically, macrophages drove resistance through cytokine activin A that induced fibronectin (FN1)-integrin alpha 5 (ITGA5)-tyrosine kinase Src (SRC) signaling cascade in PC cells. This novel mechanism was strongly supported by bioinformatics analysis of patient transcriptomics datasets. Furthermore, macrophage depletion or SRC inhibition using a novel specific inhibitor significantly inhibited resistant growth. Together, our findings elucidated a novel mechanism of macrophage-induced anti-androgen resistance of metastatic PC and a promising therapeutic approach to treat this deadly disease.

YAP/TAZ activation predicts clinical outcomes in mesothelioma and is conserved in in vitro model of driver mutations.

The Hippo signalling pathway is dysregulated across a wide range of cancer types and, although driver mutations that directly affect the core Hippo components are rare, a handful is found within pleural mesothelioma (PM). PM is a deadly disease of the lining of the lung caused by asbestos exposure. By pooling the largest-scale clinical datasets publicly available, we here interrogate associations between the most prevalent driver mutations within PM and Hippo pathway disruption in patients, while assessing correlations with a variety of clinical markers. This analysis reveals a consistent worse outcome in patients exhibiting transcriptional markers of YAP/TAZ activation, pointing to the potential of leveraging Hippo pathway transcriptional activation status as a metric by which patients may be meaningfully stratified. Preclinical models recapitulating disease are transformative in order to develop new therapeutic strategies. We here establish an isogenic cell-line model of PM, which represents the most frequently mutated genes and which faithfully recapitulates the molecular features of clinical PM. This preclinical model is developed to probe the molecular basis by which the Hippo pathway and key driver mutations affect cancer initiation and progression. Implementing this approach, we reveal the role of NF2 as a mechanosensory component of the Hippo pathway in mesothelial cells. Cellular NF2 loss upon physiological stiffnesses analogous to the tumour niche drive YAP/TAZ-dependent anchorage-independent growth. Consequently, the development and characterisation of this cellular model provide a unique resource to obtain molecular insights into the disease and progress new drug discovery programs together with future stratification of PM patients.

Patient derived glioma stem cell spheroid reporter assays for live cell high content analysis.

Three dimensional models of cell culture enables researchers to recreate aspects of tumour biology not replicated by traditional two dimensional techniques. Here we describe a protocol to enable automated high throughput phenotypic profiling across panels of patient derived glioma stem cell spheroid models. We demonstrate the use of both live/dead cell end-points and monitor the dynamic changes in the cell cycle using cell lines expressing the FUCCI cell cycle reporter. Together, these assays provide additional insight into the mechanism of action of compound treatments over traditional cell viability assay endpoints.

A multicomponent reaction platform towards multimodal near-infrared BODIPY dyes for STED and fluorescence lifetime imaging.

We report a platform combining multicomponent reaction synthesis and automated cell-based screening to develop biocompatible NIR-BODIPY fluorophores. From a library of over 60 fluorophores, we optimised compound NIRBD-62c as a multimodal probe with suitable properties for STED super-resolution and fluorescence lifetime imaging. Furthermore, we employed NIRBD-62c for imaging trafficking inside cells and to examine how pharmacological inhibitors can alter the vesicular traffic between intracellular compartments and the plasma membrane.

Control of cell state transitions.

Understanding cell state transitions and purposefully controlling them is a longstanding challenge in biology. Here we present cell state transition assessment and regulation (cSTAR), an approach for mapping cell states, modelling transitions between them and predicting targeted interventions to convert cell fate decisions. cSTAR uses omics data as input, classifies cell states, and develops a workflow that transforms the input data into mechanistic models that identify a core signalling network, which controls cell fate transitions by influencing whole-cell networks. By integrating signalling and phenotypic data, cSTAR models how cells manoeuvre in Waddington's landscape1 and make decisions about which cell fate to adopt. Notably, cSTAR devises interventions to control the movement of cells in Waddington's landscape. Testing cSTAR in a cellular model of differentiation and proliferation shows a high correlation between quantitative predictions and experimental data. Applying cSTAR to different types of perturbation and omics datasets, including single-cell data, demonstrates its flexibility and scalability and provides new biological insights. The ability of cSTAR to identify targeted perturbations that interconvert cell fates will enable designer approaches for manipulating cellular development pathways and mechanistically underpinned therapeutic interventions.

Multiparametric High-Content Cell Painting Identifies Copper Ionophores as Selective Modulators of Esophageal Cancer Phenotypes.

Esophageal adenocarcinoma is of increasing global concern due to increasing incidence, a lack of effective treatments, and poor prognosis. Therapeutic target discovery and clinical trials have been hindered by the heterogeneity of the disease, the lack of "druggable" driver mutations, and the dominance of large-scale genomic rearrangements. We have previously undertaken a comprehensive small-molecule phenotypic screen using the high-content Cell Painting assay to quantify the morphological response to a total of 19,555 small molecules across a panel of genetically distinct human esophageal cell lines to identify new therapeutic targets and small molecules for the treatment of esophageal adenocarcinoma. In this current study, we report for the first time the dose-response validation studies for the 72 screening hits from the target-annotated LOPAC and Prestwick FDA-approved compound libraries and the full list of 51 validated esophageal adenocarcinoma-selective small molecules (71% validation rate). We then focus on the most potent and selective hit molecules, elesclomol, disulfiram, and ammonium pyrrolidinedithiocarbamate. Using a multipronged, multitechnology approach, we uncover a unified mechanism of action and a vulnerability in esophageal adenocarcinoma toward copper-dependent cell death that could be targeted in the future.

A fluorogenic probe for granzyme B enables in-biopsy evaluation and screening of response to anticancer immunotherapies.

Immunotherapy promotes the attack of cancer cells by the immune system; however, it is difficult to detect early responses before changes in tumor size occur. Here, we report the rational design of a fluorogenic peptide able to detect picomolar concentrations of active granzyme B as a biomarker of immune-mediated anticancer action. Through a series of chemical iterations and molecular dynamics simulations, we synthesize a library of FRET peptides and identify probe H5 with an optimal fit into granzyme B. We demonstrate that probe H5 enables the real-time detection of T cell-mediated anticancer activity in mouse tumors and in tumors from lung cancer patients. Furthermore, we show image-based phenotypic screens, which reveal that the AKT kinase inhibitor AZD5363 shows immune-mediated anticancer activity. The reactivity of probe H5 may enable the monitoring of early responses to anticancer treatments using tissue biopsies.

Chemical Interrogation of Nuclear Size Identifies Compounds with Cancer Cell Line-Specific Effects on Migration and Invasion.

Background: Lower survival rates for many cancer types correlate with changes in nuclear size/scaling in a tumor-type/tissue-specific manner. Hypothesizing that such changes might confer an advantage to tumor cells, we aimed at the identification of commercially available compounds to guide further mechanistic studies. We therefore screened for Food and Drug Administration (FDA)/European Medicines Agency (EMA)-approved compounds that reverse the direction of characteristic tumor nuclear size changes in PC3, HCT116, and H1299 cell lines reflecting, respectively, prostate adenocarcinoma, colonic adenocarcinoma, and small-cell squamous lung cancer. Results: We found distinct, largely nonoverlapping sets of compounds that rectify nuclear size changes for each tumor cell line. Several classes of compounds including, e.g., serotonin uptake inhibitors, cyclo-oxygenase inhibitors, ß-adrenergic receptor agonists, and Na+/K+ ATPase inhibitors, displayed coherent nuclear size phenotypes focused on a particular cell line or across cell lines and treatment conditions. Several compounds from classes far afield from current chemotherapy regimens were also identified. Seven nuclear size-rectifying compounds selected for further investigation all inhibited cell migration and/or invasion. Conclusions: Our study provides (a) proof of concept that nuclear size might be a valuable target to reduce cell migration/invasion in cancer treatment and (b) the most thorough collection of tool compounds to date reversing nuclear size changes specific to individual cancer-type cell lines. Although these compounds still need to be tested in primary cancer cells, the cell line-specific nuclear size and migration/invasion responses to particular drug classes suggest that cancer type-specific nuclear size rectifiers may help reduce metastatic spread.

A Novel High-Content Phenotypic Screen To Identify Inhibitors of Mitochondrial DNA Maintenance in Trypanosomes.

Kinetoplastid parasites cause diverse neglected diseases in humans and livestock, with an urgent need for new treatments. The survival of kinetoplastids depends on their uniquely structured mitochondrial genome (kDNA), the eponymous kinetoplast. Here, we report the development of a high-content screen for pharmacologically induced kDNA loss, based on specific staining of parasites and automated image analysis. As proof of concept, we screened a diverse set of ∼14,000 small molecules and exemplify a validated hit as a novel kDNA-targeting compound.