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.

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/.

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 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.

N-cadherin stabilises neural identity by dampening anti-neural signals.

A switch from E- to N-cadherin regulates the transition from pluripotency to neural identity, but the mechanism by which cadherins regulate differentiation was previously unknown. Here, we show that the acquisition of N-cadherin stabilises neural identity by dampening anti-neural signals. We use quantitative image analysis to show that N-cadherin promotes neural differentiation independently of its effects on cell cohesiveness. We reveal that cadherin switching diminishes the level of nuclear ß-catenin, and that N-cadherin also dampens FGF activity and consequently stabilises neural fate. Finally, we compare the timing of cadherin switching and differentiation in vivo and in vitro, and find that this process becomes dysregulated during in vitro differentiation. We propose that N-cadherin helps to propagate a stable neural identity throughout the emerging neuroepithelium, and that dysregulation of this process contributes to asynchronous differentiation in culture.

Trichoplein binds PCM1 and controls endothelial cell function by regulating autophagy.

Autophagy is an essential cellular quality control process that has emerged as a critical one for vascular homeostasis. Here, we show that trichoplein (TCHP) links autophagy with endothelial cell (EC) function. TCHP localizes to centriolar satellites, where it binds and stabilizes PCM1. Loss of TCHP leads to delocalization and proteasome-dependent degradation of PCM1, further resulting in degradation of PCM1's binding partner GABARAP. Autophagic flux under basal conditions is impaired in THCP-depleted ECs, and SQSTM1/p62 (p62) accumulates. We further show that TCHP promotes autophagosome maturation and efficient clearance of p62 within lysosomes, without affecting their degradative capacity. Reduced TCHP and high p62 levels are detected in primary ECs from patients with coronary artery disease. This phenotype correlates with impaired EC function and can be ameliorated by NF-κB inhibition. Moreover, Tchp knock-out mice accumulate of p62 in the heart and cardiac vessels correlating with reduced cardiac vascularization. Taken together, our data reveal that TCHP regulates endothelial cell function via an autophagy-mediated mechanism.

Combined targeting of MEK and the glucocorticoid receptor for the treatment of RAS-mutant multiple myeloma.

BACKGROUND: Multiple myeloma (MM) remains incurable despite recent therapeutic advances. RAS mutations are frequently associated with relapsed/refractory disease. Efforts to target the mitogen-activated protein kinase (MAPK) pathway with the MEK inhibitor, trametinib (Tra) have been limited by toxicities and the development of resistance. Dexamethasone (Dex) is a corticosteroid commonly used in clinical practice, to enhance efficacy of anti-myeloma therapy. Therefore, we hypothesised that the combination of Tra and Dex would yield synergistic activity in RAS-mutant MM. METHODS: The response of human MM cell lines to drug treatment was analysed using cell proliferation assays, Western blotting, Annexin V and propidium iodide staining by flow cytometry and reverse phase protein arrays. The efficacy of trametinib and dexamethasone treatment in the MM.1S xenograft model was assessed by measuring tumor volume over time. RESULTS: The Tra/Dex combination demonstrated synergistic cytotoxicity in KRASG12A mutant lines MM.1S and RPMI-8226. The induction of apoptosis was associated with decreased MCL-1 expression and increased BIM expression. Reverse phase proteomic arrays revealed suppression of FAK, PYK2, FLT3, NDRG1 and 4EBP1 phosphorylation with the Tra/Dex combination. Notably, NDRG1 expression was associated with the synergistic response to Tra/Dex. MM cells were sensitive to PDK1 inhibition and IGF1-induced signalling partially protected from Tra/Dex treatment, highlighting the importance of this pathway. In the MM.1S tumor xenograft model, only the combination of Tra/Dex resulted in a significant inhibition of tumor growth. CONCLUSIONS: Overall Tra/Dex demonstrates antiproliferative activity in RAS-mutant MM cell lines associated with suppression of pro-survival PDK1 signalling and engagement of apoptotic pathways. Our data support further investigation of this combination in RAS-mutant MM.

The retinal tyrosine kinome of diabetic Akimba mice highlights potential for specific Src family kinase inhibition in retinal vascular disease.

Although anti-VEGF therapies have radically changed clinical practice, there is still an urgent demand for novel, integrative approaches for sight-threatening retinal vascular diseases. As we hypothesize that protein tyrosine kinases are key signaling mediators in retinal vascular disease, we performed a comprehensive activity-based tyrosine kinome profiling on retinal tissue of 12-week-old Akimba mice, a translational model displaying hallmarks of early and advanced diabetic retinopathy. Western blotting was used to confirm retinal tyrosine kinase activity in Akimba mice. HUVEC tube formation and murine organotypic choroidal sprouting assays were applied to compare tyrosine kinase inhibitors with different specificity profiles. HUVEC toxicity and proliferation were evaluated using the CellTox™ Green Cytotoxicity and PrestoBlue™ Assays. Our results indicate a shift of the Akimba retinal tyrosine kinome towards a hyperactive state. Functional network analysis of significantly hyperphosphorylated peptides and upstream kinase prediction revealed a central role for Src-FAK family kinases. Western blotting confirmed hyperactivity of this signaling node in the retina of Akimba mice. We demonstrated that not only Src but also FAK family kinase inhibitors with different selectivity profiles were able to suppress angiogenesis in vitro and ex vivo. In the latter model, the novel selective Src family kinase inhibitor eCF506 was able to achieve potent reduction of angiogenesis, comparable to the less specific inhibitor Dasatinib. None of the tested compounds demonstrated acute endothelial cell toxicity. Overall, the collected findings provide the first comprehensive overview of retinal tyrosine kinome changes in the Akimba model of diabetic retinopathy and for the first time highlight Src family kinase inhibition using highly specific inhibitors as an attractive therapeutic intervention for retinal vascular pathology.

Reversal of proliferation deficits caused by chromosome 16p13.11 microduplication through targeting NFκB signaling: an integrated study of patient-derived neuronal precursor cells, cerebral organoids and in vivo brain imaging.

The molecular basis of how chromosome 16p13.11 microduplication leads to major psychiatric disorders is unknown. Here we have undertaken brain imaging of patients carrying microduplications in chromosome 16p13.11 and unaffected family controls, in parallel with iPS cell-derived cerebral organoid studies of the same patients. Patient MRI revealed reduced cortical volume, and corresponding iPSC studies showed neural precursor cell (NPC) proliferation abnormalities and reduced organoid size, with the NPCs therein displaying altered planes of cell division. Transcriptomic analyses of NPCs uncovered a deficit in the NFκB p65 pathway, confirmed by proteomics. Moreover, both pharmacological and genetic correction of this deficit rescued the proliferation abnormality. Thus, chromosome 16p13.11 microduplication disturbs the normal programme of NPC proliferation to reduce cortical thickness due to a correctable deficit in the NFκB signalling pathway. This is the first study demonstrating a biologically relevant, potentially ameliorable, signalling pathway underlying chromosome 16p13.11 microduplication syndrome in patient-derived neuronal precursor cells.

High content phenotypic screening identifies serotonin receptor modulators with selective activity upon breast cancer cell cycle and cytokine signaling pathways.

Heterogeneity in disease mechanisms between genetically distinct patients contributes to high attrition rates in late stage clinical drug development. New personalized medicine strategies aim to identify predictive biomarkers which stratify patients most likely to respond to a particular therapy. However, for complex multifactorial diseases not characterized by a single genetic driver, empirical approaches to identifying predictive biomarkers and the most promising therapies for personalized medicine are required. In vitro pharmacogenomics seeks to correlate in vitro drug sensitivity testing across panels of genetically distinct cell models with genomic, gene expression or proteomic data to identify predictive biomarkers of drug response. However, the vast majority of in vitro pharmacogenomic studies performed to date are limited to dose-response screening upon a single viability assay endpoint. In this article we describe the application of multiparametric high content phenotypic screening and the theta comparative cell scoring method to quantify and rank compound hits, screened at a single concentration, which induce a broad variety of divergent phenotypic responses between distinct breast cancer cell lines. High content screening followed by transcriptomic pathway analysis identified serotonin receptor modulators which display selective activity upon breast cancer cell cycle and cytokine signaling pathways correlating with inhibition of cell growth and survival. These methods describe a new evidence-led approach to rapidly identify compounds which display distinct response between different cell types. The results presented also warrant further investigation of the selective activity of serotonin receptor modulators upon breast cancer cell growth and survival as a potential drug repurposing opportunity.

Drug Screening Platforms and RPPA.

Since its inception as a scalable and cost-effective method for precise quantification of the abundance of multiple protein analytes and post-translational epitopes across large sample sets, reverse phase protein array (RPPA) has been utilized as a drug discovery tool. Key RPPA drug discovery applications include primary screening of abundance or activation state of nominated protein targets, secondary screening for toxicity and selectivity, mechanism-of-action profiling, biomarker discovery, and drug combination discovery. In recent decades, drug discovery strategies have evolved dramatically in response to continual advances in technology platforms supporting high-throughput screening, structure-based drug design, new therapeutic modalities, and increasingly more complex and disease-relevant cell-based and in vivo preclinical models of disease. Advances in biological laboratory capabilities in drug discovery are complemented by significant developments in bioinformatics and computational approaches for integrating large complex datasets. Bioinformatic and computational analysis of integrated molecular, pathway network and phenotypic datasets enhance multiple stages of the drug discovery process and support more informative drug target hypothesis generation and testing. In this chapter we discuss and present examples demonstrating how the latest advances in RPPA complement and integrate with other emerging drug screening platforms to support a new era of more informative and evidence-led drug discovery strategies.

Accelerating glioblastoma drug discovery: Convergence of patient-derived models, genome editing and phenotypic screening.

Patients diagnosed with glioblastoma (GBM) continue to face a bleak prognosis. It is critical that new effective therapeutic strategies are developed. GBM stem cells have molecular hallmarks of neural stem and progenitor cells and it is possible to propagate both non-transformed normal neural stem cells and GBM stem cells, in defined, feeder-free, adherent culture. These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities. For many solid tumours, including GBM, the genetic disruptions that drive tumour initiation and growth have now been catalogued. CRISPR/Cas-based genome editing technologies have recently emerged, transforming our ability to functionally annotate the human genome. Genome editing opens prospects for engineering precise genetic changes in normal and GBM-derived neural stem cells, which will provide more defined and reliable genetic models, with critical matched pairs of isogenic cell lines. Generation of more complex alleles such as knock in tags or fluorescent reporters is also now possible. These new cellular models can be deployed in cell-based phenotypic drug discovery (PDD). Here we discuss the convergence of these advanced technologies (iPS cells, neural stem cell culture, genome editing and high content phenotypic screening) and how they herald a new era in human cellular genetics that should have a major impact in accelerating glioblastoma drug discovery.

Potent organo-osmium compound shifts metabolism in epithelial ovarian cancer cells.

The organometallic "half-sandwich" compound [Os(η(6)-p-cymene)(4-(2-pyridylazo)-N,N-dimethylaniline)I]PF6 is 49× more potent than the clinical drug cisplatin in the 809 cancer cell lines that we screened and is a candidate drug for cancer therapy. We investigate the mechanism of action of compound 1 in A2780 epithelial ovarian cancer cells. Whole-transcriptome sequencing identified three missense mutations in the mitochondrial genome of this cell line, coding for ND5, a subunit of complex I (NADH dehydrogenase) in the electron transport chain. ND5 is a proton pump, helping to maintain the coupling gradient in mitochondria. The identified mutations correspond to known protein variants (p.I257V, p.N447S, and p.L517P), not reported previously in epithelial ovarian cancer. Time-series RNA sequencing suggested that osmium-exposed A2780 cells undergo a metabolic shunt from glycolysis to oxidative phosphorylation, where defective machinery, associated with mutations in complex I, could enhance activity. Downstream events, measured by time-series reverse-phase protein microarrays, high-content imaging, and flow cytometry, showed a dramatic increase in mitochondrially produced reactive oxygen species (ROS) and subsequent DNA damage with up-regulation of ATM, p53, and p21 proteins. In contrast to platinum drugs, exposure to this organo-osmium compound does not cause significant apoptosis within a 72-h period, highlighting a different mechanism of action. Superoxide production in ovarian, lung, colon, breast, and prostate cancer cells exposed to three other structurally related organo-Os(II) compounds correlated with their antiproliferative activity. DNA damage caused indirectly, through selective ROS generation, may provide a more targeted approach to cancer therapy and a concept for next-generation metal-based anticancer drugs that combat platinum resistance.

Reverse Phase Protein Arrays elucidate mechanisms-of-action and phenotypic response in 2D and 3D models.

The development of new 2D and 3D phenotypic screening assays combined with high-throughput genomic and proteomic technologies are well placed to advance a new era of molecular pathway informed Phenotypic Drug Discovery. We describe the application of Reverse Phase Protein Array (RPPA) technology to elucidate the mechanism-of-action of small molecules at the post-translational pathway level. We propose that profiling of phenotypic hits and lead molecules in increasingly more complex 3D in vitro and ex vivo models at the post-translational pathway network level represents an effective strategy to both triage and progress the preclinical development of phenotypic screening hits.

Naturally Inspired Peptide Leads: Alanine Scanning Reveals an Actin-Targeting Thiazole Analogue of Bisebromoamide.

Systematic alanine scanning of the linear peptide bisebromoamide (BBA), isolated from a marine cyanobacterium, was enabled by solid-phase peptide synthesis of thiazole analogues. The analogues have comparable cytotoxicity (nanomolar) to that of BBA, and cellular morphology assays indicated that they target the actin cytoskeleton. Pathway inhibition in human colon tumour (HCT116) cells was explored by reverse phase protein array (RPPA) analysis, which showed a dose-dependent response in IRS-1 expression. Alanine scanning reveals a structural dependence to the cytotoxicity, actin targeting and pathway inhibition, and allows a new readily synthesised lead to be proposed.

Dasatinib inhibits mammary tumour development in a genetically engineered mouse model.

Src family kinase activity is elevated in a number of human cancers including breast cancer. This increased activity has been associated with aggressive disease and poor prognosis. Src inhibitors are currently in clinical development with a number of trials currently assessing their activity in breast cancer. However, the results to date have been disappointing and a further evaluation of the preclinical effects of Src inhibitors is required to help establish whether these agents will be useful in the treatment of breast cancer. In this study we investigate the effects of dasatinib, which is a potent inhibitor of Src family kinases, on the initiation and development of breast cancer in a genetically engineered model of the disease. The mouse model utilized is driven by expression of activated ErbB-2 under the transcriptional control of its endogenous promoter coupled with conditional loss of Pten under the control of Cre recombinase expressed by the BLG promoter. We show that daily oral administration of dasatinib delays tumour onset and increases overall survival but does not inhibit the proliferation of established tumours. The striking difference between the dasatinib-treated group of tumours and the vehicle controls was the prominent squamous metaplasia that was seen in six out of 11 dasatinib-treated tumours. This was accompanied by a dramatic up-regulation of both E-cadherin and ß-catenin and down-regulation of ErbB-2 in the dasatinib-treated tumours. Dasatinib also inhibited both the migration and the invasion of tumour-derived cell lines in vitro. Together these data support the argument that benefits of Src inhibitors may predominate in early or even pre-invasive disease.

The role of focal-adhesion kinase in cancer - a new therapeutic opportunity.

Focal-adhesion kinase (FAK) is an important mediator of growth-factor signalling, cell proliferation, cell survival and cell migration. Given that the development of malignancy is often associated with perturbations in these processes, it is not surprising that FAK activity is altered in cancer cells. Mouse models have shown that FAK is involved in tumour formation and progression, and other studies showing that FAK expression is increased in human tumours make FAK a potentially important new therapeutic target.

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.

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.

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.