Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases

Loss of E-cadherin leads to Id2-dependent inhibition of cell cycle progression in metastatic lobular breast cancer

Invasive lobular breast carcinoma (ILC) is characterized by proliferative indolence and long-term latency relapses. This study aimed to identify how disseminating ILC cells control the balance between quiescence and cell cycle re-entry. In the absence of anchorage, ILC cells undergo a sustained cell cycle arrest in G0/G1 while maintaining viability. From the genes that are upregulated in anchorage independent ILC cells, we selected Inhibitor of DNA binding 2 (Id2), a mediator of cell cycle progression. Using loss-of-function experiments, we demonstrate that Id2 is essential for anchorage independent survival (anoikis resistance) in vitro and lung colonization in mice. Importantly, we find that under anchorage independent conditions, E-cadherin loss promotes expression of Id2 in multiple mouse and (organotypic) human models of ILC, an event that is caused by a direct p120-catenin/Kaiso-dependent transcriptional de-repression of the canonical Kaiso binding sequence TCCTGCNA. Conversely, stable inducible restoration of E-cadherin expression in the ILC cell line SUM44PE inhibits Id2 expression and anoikis resistance. We show evidence that Id2 accumulates in the cytosol, where it induces a sustained and CDK4/6-dependent G0/G1 cell cycle arrest through interaction with hypo-phosphorylated Rb. Finally, we find that Id2 is indeed enriched in ILC when compared to other breast cancers, and confirm cytosolic Id2 protein expression in primary ILC samples. In sum, we have linked mutational inactivation of E-cadherin to direct inhibition of cell cycle progression. Our work indicates that loss of E-cadherin and subsequent expression of Id2 drive indolence and dissemination of ILC. As such, E-cadherin and Id2 are promising candidates to stratify low and intermediate grade invasive breast cancers for the use of clinical cell cycle intervention drugs.

Characterization of Type 1 Angiotensin II Receptor Activation Induced Dual-Specificity MAPK Phosphatase Gene Expression Changes in Rat Vascular Smooth Muscle Cells

Activation of the type I angiotensin receptor (AT1-R) in vascular smooth muscle cells (VSMCs) plays a crucial role in the regulation of blood pressure; however, it is also responsible for the development of pathological conditions such as vascular remodeling, hypertension and atherosclerosis. Stimulation of the VSMC by angiotensin II (AngII) promotes a broad variety of biological effects, including gene expression changes. In this paper, we have taken an integrated approach in which an analysis of AngII-induced gene expression changes has been combined with the use of small-molecule inhibitors and lentiviral-based gene silencing, to characterize the mechanism of signal transduction in response to AngII stimulation in primary rat VSMCs. We carried out Affymetrix GeneChip experiments to analyze the effects of AngII stimulation on gene expression; several genes, including DUSP5, DUSP6, and DUSP10, were identified as upregulated genes in response to stimulation. Since various dual-specificity MAPK phosphatase (DUSP) enzymes are important in the regulation of mitogen-activated protein kinase (MAPK) signaling pathways, these genes have been selected for further analysis. We investigated the kinetics of gene-expression changes and the possible signal transduction processes that lead to altered expression changes after AngII stimulation. Our data shows that the upregulated genes can be stimulated through multiple and synergistic signal transduction pathways. We have also found in our gene-silencing experiments that epidermal growth factor receptor (EGFR) transactivation is not critical in the AngII-induced expression changes of the investigated genes. Our data can help us understand the details of AngII-induced long-term effects and the pathophysiology of AT1-R. Moreover, it can help to develop potential interventions for those symptoms that are induced by the over-functioning of this receptor, such as vascular remodeling, cardiac hypertrophy or atherosclerosis.

Polθ inhibitors elicit BRCA-gene synthetic lethality and target PARP inhibitor resistance

To identify approaches to target DNA repair vulnerabilities in cancer, we discovered nanomolar potent, selective, low molecular weight (MW), allosteric inhibitors of the polymerase function of DNA polymerase Polθ, including ART558. ART558 inhibits the major Polθ-mediated DNA repair process, Theta-Mediated End Joining, without targeting Non-Homologous End Joining. In addition, ART558 elicits DNA damage and synthetic lethality in BRCA1- or BRCA2-mutant tumour cells and enhances the effects of a PARP inhibitor. Genetic perturbation screening revealed that defects in the 53BP1/Shieldin complex, which cause PARP inhibitor resistance, result in in vitro and in vivo sensitivity to small molecule Polθ polymerase inhibitors. Mechanistically, ART558 increases biomarkers of single-stranded DNA and synthetic lethality in 53BP1-defective cells whilst the inhibition of DNA nucleases that promote end-resection reversed these effects, implicating these in the synthetic lethal mechanism-of-action. Taken together, these observations describe a drug class that elicits BRCA-gene synthetic lethality and PARP inhibitor synergy, as well as targeting a biomarker-defined mechanism of PARPi-resistance.

Application of high-content screening for the study of hepatotoxicity: Focus on food toxicology

Safety evaluation of thousands of chemicals that are directly added to or come in contact with food is needed. Due to the central role of the liver in intermediary and energy metabolism and in the biotransformation of foreign compounds, the hepatotoxicity assessment is essential. New approach methodologies have been proposed for the safety evaluation of compounds with the idea of rapidly gaining insight into effects on biochemical mechanisms and cellular processes and screening large number of compounds. In this sense, high-content screening (HCS) is the application of automated microscopy and image analysis for better understanding of complex biological functions and mechanisms of toxicity. HCS multiparametric measurements have been shown to be a useful tool in early toxicity testing during drug development, but also in assessing the impact from food chemicals and environmental toxicants. Reviewing the use of cellular imaging technology in the safety evaluation of food-relevant chemicals offers evidence about the impact of this technology in safety assessment.

Targeting TRIM37-driven centrosome dysfunction in 17q23-amplified breast cancer

Genomic instability is a hallmark of cancer, and has a central role in the initiation and development of breast cancer1,2. The success of poly-ADP ribose polymerase inhibitors in the treatment of breast cancers that are deficient in homologous recombination exemplifies the utility of synthetically lethal genetic interactions in the treatment of breast cancers that are driven by genomic instability3. Given that defects in homologous recombination are present in only a subset of breast cancers, there is a need to identify additional driver mechanisms for genomic instability and targeted strategies to exploit these defects in the treatment of cancer. Here we show that centrosome depletion induces synthetic lethality in cancer cells that contain the 17q23 amplicon, a recurrent copy number aberration that defines about 9% of all primary breast cancer tumours and is associated with high levels of genomic instability4-6. Specifically, inhibition of polo-like kinase 4 (PLK4) using small molecules leads to centrosome depletion, which triggers mitotic catastrophe in cells that exhibit amplicon-directed overexpression of TRIM37. To explain this effect, we identify TRIM37 as a negative regulator of centrosomal pericentriolar material. In 17q23-amplified cells that lack centrosomes, increased levels of TRIM37 block the formation of foci that comprise pericentriolar material-these foci are structures with a microtubule-nucleating capacity that are required for successful cell division in the absence of centrosomes. Finally, we find that the overexpression of TRIM37 causes genomic instability by delaying centrosome maturation and separation at mitotic entry, and thereby increases the frequency of mitotic errors. Collectively, these findings highlight TRIM37-dependent genomic instability as a putative driver event in 17q23-amplified breast cancer and provide a rationale for the use of centrosome-targeting therapeutic agents in treating these cancers.

3D Cell-Based Assays for Drug Screens: Challenges in Imaging, Image Analysis, and High-Content Analysis

The introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds progressing to preclinical stages in the drug development pipeline. In this review we discuss the current switch to more relevant 3D cell culture models and associated challenges for high-throughput screening and high-content analysis. We propose that overcoming these challenges will enable front-loading the drug discovery pipeline with better biology, extracting the most from that biology, and, in general, improving translation between in vitro and in vivo models. This is expected to reduce the proportion of compounds that fail in vivo testing due to a lack of efficacy or to toxicity.

Three-Dimensional Cell Cultures in Drug Discovery and Development

The past decades have witnessed significant efforts toward the development of three-dimensional (3D) cell cultures as systems that better mimic in vivo physiology. Today, 3D cell cultures are emerging, not only as a new tool in early drug discovery but also as potential therapeutics to treat disease. In this review, we assess leading 3D cell culture technologies and their impact on drug discovery, including spheroids, organoids, scaffolds, hydrogels, organs-on-chips, and 3D bioprinting. We also discuss the implementation of these technologies in compound identification, screening, and development, ranging from disease modeling to assessment of efficacy and safety profiles.

Machine learning and image-based profiling in drug discovery

The increase in imaging throughput, new analytical frameworks and high-performance computational resources open new avenues for data-rich phenotypic profiling of small molecules in drug discovery. Image-based profiling assays assessing single-cell phenotypes have been used to explore mechanisms of action, target efficacy and toxicity of small molecules. Technological advances to generate large data sets together with new machine learning approaches for the analysis of high-dimensional profiling data create opportunities to improve many steps in drug discovery. In this review, we will discuss how recent studies applied machine learning approaches in functional profiling workflows with a focus on chemical genetics. While their utility in image-based screening and profiling is predictably evident, examples of novel insights beyond the status quo based on the applications of machine learning approaches are just beginning to emerge. To enable discoveries, future studies also need to develop methodologies that lower the entry barriers to high-throughput profiling experiments by streamlining image-based profiling assays and providing applications for advanced learning technologies such as easy to deploy deep neural networks.

High-content imaging assays on a miniaturized 3D cell culture platform

The majority of high-content imaging (HCI) assays have been performed on two-dimensional (2D) cell monolayers for its convenience and throughput. However, 2D-cultured cell models often do not represent the in vivo characteristics accurately and therefore reduce the predictability of drug toxicity/efficacy in vivo. Recently, three-dimensional (3D) cell-based HCI assays have been demonstrated to improve predictability, but its use is limited due to difficulty in maneuverability and low throughput in cell imaging. To alleviate these issues, we have developed miniaturized 3D cell culture on a micropillar/microwell chip and demonstrated high-throughput HCI assays for mechanistic toxicity. Briefly, Hep3B human hepatoma cell line was encapsulated in a mixture of alginate and fibrin gel on the micropillar chip, cultured in 3D, and exposed to six model compounds in the microwell chip for rapidly assessing mechanistic hepatotoxicity. Several toxicity parameters, including DNA damage, mitochondrial impairment, intracellular glutathione level, and cell membrane integrity were measured on the chip, and the IC₅₀ values of the compounds at different readouts were determined to investigate the mechanism of toxicity. Overall, the Z' factors were between 0.6 and 0.8 for the HCI assays, and the coefficient of variation (CV) were below 20%. These results indicate high robustness and reproducibility of the HCI assays established on the miniaturized 3D cell culture chip. In addition, it was possible to determine the predominant mechanism of toxicity using the 3D HCI assays. Therefore, our miniaturized 3D cell culture coupled with HCI assays has great potential for high-throughput screening (HTS) of compounds and mechanistic toxicity profiling.

Novel 3D Liquid Cell Culture Method for Anchorage-independent Cell Growth, Cell Imaging and Automated Drug Screening

Cells grown in three-dimensional (3D) cultures are more likely to have native cell-cell and cell-matrix interactions than in 2D cultures that impose mechanical constraints to cells. However, most 3D cultures utilise gel matrix which, while serving as a scaffold, limits application due to its solid and opaque nature and inconsistency in cell exposure to exogenous signals. In 3D culture without gel matrix, cells tend to adhere to each other and form clumps with necrotic zone at the centre, making them unsuitable for analyses. Here we report that addition of low-molecular-weight agar named LA717 to culture media allows cells to grow as dispersed clonal spheroids in 3D. LA717 maintains cells dispersed and settled to the bottom of the medium while keeping the medium clear with little additional viscosity, making it suitable for microscopic observation. Importantly, cancer spheroids formed in LA717-containing medium show higher sensitivity to anti-cancer drugs such as Trametinib and MK-2206 that are not as effective in 2D. Because of the small and consistent size of spheroids, cell viability and drug toxicity are readily detectable in automated imaging analysis. These results demonstrate that LA717 offers a novel 3D culture system with great in vivo reflection and practicality.

High-Throughput Phenotypic Screening of Kinase Inhibitors to Identify Drug Targets for Polycystic Kidney Disease

Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1^–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD.