A 1536-well quantitative high-throughput screen to identify compounds targeting cancer stem cells

RAS isoform specific activities are disrupted by disease associated mutations during cell differentiation

The RAS-MAPK-pathway is aberrantly regulated in cancer and developmental diseases called RASopathies. While typically the impact of Ras on the proliferation of various cancer cell lines is assessed, it is poorly established how Ras affects cellular differentiation. Here we implement the C2C12 myoblast cell line to systematically study the effect of Ras mutants and Ras-pathway drugs on differentiation. We first provide evidence that a minor pool of Pax7+ progenitors replenishes a major pool of transit amplifying cells that are ready to differentiate. Our data indicate that Ras isoforms have distinct roles in the differentiating culture, where K-Ras depletion increases and H-Ras depletion decreases terminal differentiation. This assay could therefore provide significant new insights into Ras biology and Ras-driven diseases. In line with this, we found that all oncogenic Ras mutants block terminal differentiation of transit amplifying cells. By contrast, RASopathy associated K-Ras variants were less able to block differentiation. Profiling of eight targeted Ras-pathway drugs on seven oncogenic Ras mutants revealed their allele-specific activities and distinct abilities to restore normal differentiation as compared to triggering cell death. In particular, the MEK-inhibitor trametinib could broadly restore differentiation, while the mTOR-inhibitor rapamycin broadly suppressed differentiation. We expect that this quantitative assessment of the impact of Ras-pathway mutants and drugs on cellular differentiation has great potential to complement cancer cell proliferation data.

Schlafen 11 (SLFN11) Kills Cancer Cells Undergoing Unscheduled Re-replication

Schlafen 11 (SLFN11) is an increasingly prominent predictive biomarker and a molecular sensor for a wide range of clinical drugs: topoisomerases, PARP and replication inhibitors, and platinum derivatives. To expand the spectrum of drugs and pathways targeting SLFN11, we ran a high-throughput screen with 1,978 mechanistically annotated, oncology-focused compounds in two isogenic pairs of SLFN11-proficient and -deficient cells (CCRF-CEM and K562). We identified 29 hit compounds that selectively kill SLFN11-proficient cells, including not only previously known DNA-targeting agents, but also the neddylation inhibitor pevonedistat (MLN-4924) and the DNA polymerase α inhibitor AHPN/CD437, which both induced SLFN11 chromatin recruitment. By inactivating cullin-ring E3 ligases, pevonedistat acts as an anticancer agent partly by inducing unscheduled re-replication through supraphysiologic accumulation of CDT1, an essential factor for replication initiation. Unlike the known DNA-targeting agents and AHPN/CD437 that recruit SLFN11 onto chromatin in 4 hours, pevonedistat recruited SLFN11 at late time points (24 hours). While pevonedistat induced unscheduled re-replication in SLFN11-deficient cells after 24 hours, the re-replication was largely blocked in SLFN11-proficient cells. The positive correlation between sensitivity to pevonedistat and SLFN11 expression was also observed in non-isogenic cancer cells in three independent cancer cell databases (NCI-60, CTRP: Cancer Therapeutics Response Portal and GDSC: Genomic of Drug Sensitivity in Cancer). The present study reveals that SLFN11 not only detects stressed replication but also inhibits unscheduled re-replication induced by pevonedistat, thereby enhancing its anticancer efficacy. It also suggests SLFN11 as a potential predictive biomarker for pevonedistat in ongoing and future clinical trials.

A High-Throughput Screening Platform Identifies Novel Combination Treatments for Malignant Peripheral Nerve Sheath Tumors

Malignant peripheral nerve sheath tumors (MPNST) are soft-tissue sarcomas that are the leading cause of mortality in patients with Neurofibromatosis type 1 (NF1). Single chemotherapeutic agents have shown response rates ranging from 18% to 44% in clinical trials, so there is still a high medical need to identify chemotherapeutic combination treatments that improve clinical prognosis and outcome. We screened a collection of compounds from the NCATS Mechanism Interrogation PlatE (MIPE) library in three MPNST cell lines, using cell viability and apoptosis assays. We then tested whether compounds that were active as single agents were synergistic when screened as pairwise combinations. Synergistic combinations in vitro were further evaluated in patient-derived orthotopic xenograft/orthoxenograft (PDOX) athymic models engrafted with primary MPNST matching with their paired primary-derived cell line where synergism was observed. The high-throughput screening identified 21 synergistic combinations, from which four exhibited potent synergies in a broad panel of MPNST cell lines. One of the combinations, MK-1775 with Doxorubicin, significantly reduced tumor growth in a sporadic PDOX model (MPNST-SP-01; sevenfold) and in an NF1-PDOX model (MPNST-NF1-09; fourfold) and presented greater effects in TP53 mutated MPNST cell lines. The other three combinations, all involving Panobinostat (combined with NVP-BGT226, Torin 2, or Carfilzomib), did not reduce the tumor volume in vivo at noncytotoxic doses. Our results support the utility of our screening platform of in vitro and in vivo models to explore new therapeutic approaches for MPNSTs and identified that combination MK-1775 with Doxorubicin could be a good pharmacologic option for the treatment of these tumors.

Automated Assessment of Cancer Drug Efficacy On Breast Tumor Spheroids in Aggrewell™400 Plates Using Image Cytometry

Tumor spheroid models have proven useful in the study of cancer cell responses to chemotherapeutic compounds by more closely mimicking the 3-dimensional nature of tumors in situ. Their advantages are often offset, however, by protocols that are long, complicated, and expensive. Efforts continue for the development of high-throughput assays that combine the advantages of 3D models with the convenience and simplicity of traditional 2D monolayer methods. Herein, we describe the development of a breast cancer spheroid image cytometry assay using T47D cells in Aggrewell™400 spheroid plates. Using the Celigo^® automated imaging system, we developed a method to image and individually track thousands of spheroids within the Aggrewell™400 microwell plate over time. We demonstrate the use of calcein AM and propidium iodide staining to study the effects of known anti-cancer drugs Doxorubicin, Everolimus, Gemcitabine, Metformin, Paclitaxel and Tamoxifen. We use the image cytometry results to quantify the fluorescence of calcein AM and PI as well as spheroid size in a dose dependent manner for each of the drugs. We observe a dose-dependent reduction in spheroid size and find that it correlates well with the viability obtained from the CellTiter96^® endpoint assay. The image cytometry method we demonstrate is a convenient and high-throughput drug-response assay for breast cancer spheroids under 400 μm in diameter, and may lay a foundation for investigating other three-dimensional spheroids, organoids, and tissue samples.

An OpenData portal to share COVID-19 drug repurposing data in real time

The National Center for Advancing Translational Sciences (NCATS) has developed an online open science data portal for its COVID-19 drug repurposing campaign - named OpenData - with the goal of making data across a range of SARS-CoV-2 related assays available in real-time. The assays developed cover a wide spectrum of the SARS-CoV-2 life cycle, including both viral and human (host) targets. In total, over 10,000 compounds are being tested in full concentration-response ranges from across multiple annotated small molecule libraries, including approved drug, repurposing candidates and experimental therapeutics designed to modulate a wide range of cellular targets. The goal is to support research scientists, clinical investigators and public health officials through open data sharing and analysis tools to expedite the development of SARS-CoV-2 interventions, and to prioritize promising compounds and repurposed drugs for further development in treating COVID-19.

How polypharmacologic is each chemogenomics library?

Aim:

High-throughput phenotypic screens have emerged as a promising avenue for small-molecule drug discovery. The challenge faced in high-throughput phenotypic screens is target deconvolution once a small molecule hit is identified. Chemogenomics libraries have emerged as an important tool for meeting this challenge. Here, we investigate their target-specificity by deriving a ‘polypharmacology index’ for broad chemogenomics screening libraries.

Methods:

All known targets of all the compounds in each library were plotted as a histogram and fitted to a Boltzmann distribution, whose linearized slope is indicative of the overall polypharmacology of the library.

Results & conclusion:

Comparison of libraries clearly distinguished the most target-specific library, which might be assumed to be more useful for target deconvolution in a phenotypic screen.

Target Deconvolution of a Multikinase Inhibitor with Antimetastatic Properties Identifies TAOK3 as a Key Contributor to a Cancer Stem Cell-Like Phenotype

Pancreatic cancer remains an incurable condition. Its progression is driven, in part, by subsets of cancer cells that evade the cytotoxic effects of conventional chemotherapies. These cells are often low-cycling, multidrug resistant, and adopt a stem cell-like phenotype consistent with the concept of cancer stem cells (CSC). To identify drugs impacting on tumor-promoting CSCs, we performed a differential high-throughput drug screen in pancreatic cancer cells cultured in traditional (2D) monolayers versus three-dimensional (3D) spheroids which replicate key elements of the CSC model. Among the agents capable of killing cells cultured in both formats was a 1H-benzo[d]imidazol-2-amine-based inhibitor of IL2-inducible T-cell kinase (ITK; NCGC00188382, inhibitor #1) that effectively mediated growth inhibition and induction of apoptosis in vitro, and suppressed cancer progression and metastasis formation in vivo An examination of this agent's polypharmacology via in vitro and in situ phosphoproteomic profiling demonstrated an activity profile enriched for mediators involved in DNA damage repair. Included was a strong inhibitory potential versus the thousand-and-one amino acid kinase 3 (TAOK3), CDK7, and aurora B kinases. We found that cells grown under CSC-enriching spheroid conditions are selectively dependent on TAOK3 signaling. Loss of TAOK3 decreases colony formation, expression of stem cell markers, and sensitizes spheroids to the genotoxic effect of gemcitabine, whereas overexpression of TAOK3 increases stem cell traits including tumor initiation and metastasis formation. By inactivating multiple components of the cell-cycle machinery in concert with the downregulation of key CSC signatures, inhibitor #1 defines a distinctive strategy for targeting pancreatic cancer cell populations.

Cancer-on-a-chip for Drug Screening

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The oncology pharmaceutical research spent a shocking amount of money on target validation and drug optimization in preclinical models because many oncology drugs fail during clinical trial phase III. One of the most important reasons for oncology drug failures in clinical trials may due to the poor predictive tool of existing preclinical models. Therefore, in cancer research and personalized medicine field, it is critical to improve the effectiveness of preclinical predictions of the drug response of patients to therapies and to reduce costly failures in clinical trials. Three dimensional (3D) tumor models combine micro-manufacturing technologies mimic critical physiologic parameters present in vivo, including complex multicellular architecture with multicellular arrangement and extracellular matrix deposition, packed 3D structures with cell–cell interactions, such as tight junctions, barriers to mass transport of drugs, nutrients and other factors, which are similar to in vivo tumor tissues. These systems provide a solution to mimic the physiological environment for improving predictive accuracy in oncology drug discovery.

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his review gives an overview of the innovations, development and limitations of different types of tumor-like construction techniques such as self-assemble spheroid formation, spheroids formation by micro-manufacturing technologies, micro-dissected tumor tissues and tumor organoid. Combination of 3D tumor-like construction and microfluidic techniques to achieve tumor on a chip for in vitro tumor environment modeling and drug screening were all included. Eventually, developmental directions and technical challenges in the research field are also discussed. We believe tumor on chip models have provided better sufficient clinical predictive power and will bridge the gap between proof-of-concept studies and a wider implementation within the oncology drug development for pathophysiological applications.

Drug Efficacy Comparison of 3D Forming and Preforming Sphere Models with a Micropillar and Microwell Chip Platform

Hepatocellular carcinoma (HCC), a major histological subtype of liver cancer, is the third most common cause of cancer-related death worldwide. Currently, many curative standard treatments using target-specific chemotherapeutic agents are being developed. However, drug efficacy tests based on the 2D monolayer cell culture model do not effectively screen the best drug candidates because they do not accurately reflect in vivo tumor microenvironments. Thus, to select the best drug candidates or repositioning drugs, we developed new 3D in vitro hepatic tumor models, including 3D forming and preformed sphere models. A micropillar and microwell chip platform was used for the 3D in vitro liver cell-based model for high-throughput screening. We measured the efficacy of 60 drugs and sorted the most efficacious drugs by comparing the drug response of the 2D monolayer model with the 3D forming and preformed sphere models. Among the 60 drugs, 17 drugs (28.3%) showed a significant high efficacy in the 3D preformed sphere model, while 45 drugs (75%) showed an efficacy in the 2D model. We also calculated the IC₅₀ values of the 17 drugs and found that 7 drugs exhibited a high sensitivity in HCC, which was in agreement with previous studies.

High-throughput screens identify HSP90 inhibitors as potent therapeutics that target inter-related growth and survival pathways in advanced prostate cancer

The development of new treatments for castrate resistant prostate cancer (CRPC) must address such challenges as intrinsic tumor heterogeneity and phenotypic plasticity. Combined PTEN/TP53 alterations represent a major genotype of CRPC (25–30%) and are associated with poor outcomes. Using tumor-derived, castration-resistant Pten/Tp53 null luminal prostate cells for comprehensive, high-throughput, mechanism-based screening, we identified several vulnerabilities among >1900 compounds, including inhibitors of: PI3K/AKT/mTOR, the proteasome, the cell cycle, heat shock proteins, DNA repair, NFκB, MAPK, and epigenetic modifiers. HSP90 inhibitors were one of the most active compound classes in the screen and have clinical potential for use in drug combinations to enhance efficacy and delay the development of resistance. To inform future design of rational drug combinations, we tested ganetespib, a potent second-generation HSP90 inhibitor, as a single agent in multiple CRPC genotypes and phenotypes. Ganetespib decreased growth of endogenous Pten/Tp53 null tumors, confirming therapeutic activity in situ. Fifteen human CRPC LuCaP PDX-derived organoid models were assayed for responses to 110 drugs, and HSP90 inhibitors (ganetespib and onalespib) were among the select group of drugs (<10%) that demonstrated broad activity (>75% of models) at high potency (IC50 <1 µM). Ganetespib inhibits multiple targets, including AR and PI3K pathways, which regulate mutually compensatory growth and survival signals in some forms of CRPC. Combined with castration, ganetespib displayed deeper PDX tumor regressions and delayed castration resistance relative to either monotherapy. In all, comprehensive data from near-patient models presents novel contexts for HSP90 inhibition in multiple CRPC genotypes and phenotypes, expands upon HSP90 inhibitors as simultaneous inhibitors of oncogenic signaling and resistance mechanisms, and suggests utility for combined HSP90/AR inhibition in CRPC.

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is exposed to in vivo. Solid tumors grow not as a sheet attached to plastic, but instead as a collection of clonal cells in a three-dimensional (3D) space interacting with their neighbors, and with distinct spatial properties such as the disruption of normal cellular polarity. These interactions cause 3D-cultured cells to acquire morphological and cellular characteristics which are more relevant to in vivo tumors. Additionally, a tumor mass is in direct contact with other cell types such as stromal and immune cells, as well as the extracellular matrix from all other cell types. The matrix deposited is comprised of macromolecules such as collagen and fibronectin. In an attempt to increase the translation of research findings in oncology from bench to bedside, many groups have started to investigate the use of 3D model systems in their drug development strategies. These systems are thought to be more physiologically relevant because they attempt to recapitulate the complex and heterogeneous environment of a tumor. These systems, however, can be quite complex, and, although amenable to growth in 96-well formats, and some now even in 384, they offer few choices for large-scale growth and screening. This observed gap has led to the development of the methods described here in detail to culture tumor spheroids in a high-throughput capacity in 1536-well plates. These methods represent a compromise to the highly complex matrix-based systems, which are difficult to screen, and conventional 2D assays. A variety of cancer cell lines harboring different genetic mutations are successfully screened, examining compound efficacy by using a curated library of compounds targeting the Mitogen-Activated Protein Kinase or MAPK pathway. The spheroid culture responses are then compared to the response of cells grown in 2D, and differential activities are reported. These methods provide a unique protocol for testing compound activity in a high-throughput 3D setting.

The Current Landscape of 3D In Vitro Tumor Models: What Cancer Hallmarks Are Accessible for Drug Discovery?

Cancer prognosis remains a lottery dependent on cancer type, disease stage at diagnosis, and personal genetics. While investment in research is at an all-time high, new drugs are more likely to fail in clinical trials today than in the 1970s. In this review, a summary of current survival statistics in North America is provided, followed by an overview of the modern drug discovery process, classes of models used throughout different stages, and challenges associated with drug development efficiency are highlighted. Then, an overview of the cancer hallmarks that drive clinical progression is provided, and the range of available clinical therapies within the context of these hallmarks is categorized. Specifically, it is found that historically, the development of therapies is limited to a subset of possible targets. This provides evidence for the opportunities offered by novel disease-relevant in vitro models that enable identification of novel targets that facilitate interactions between the tumor cells and their surrounding microenvironment. Next, an overview of the models currently reported in literature is provided, and the cancer biology they have been used to explore is highlighted. Finally, four priority areas are suggested for the field to accelerate adoption of in vitro tumour models for cancer drug discovery.

Assessing Drug Efficacy in a Miniaturized Pancreatic Cancer In Vitro 3D Cell Culture Model

Pancreatic cancer continues to have one of the poorest prognoses among all cancers. The drug discovery efforts for this disease have largely failed, with no significant improvement in survival outcomes for advanced pancreatic cancer patients over the past 20 years. Traditional in vitro cell culture techniques have been used extensively in both basic and early drug discovery; however, these systems offer poor models to assess emerging therapeutics. More predictive cell-based models, which better capture the cellular heterogeneity and complexities of solid pancreatic tumors, are urgently needed not only to improve drug discovery success but also to provide insight into the tumor biology. Pancreatic tumors are characterized by a unique micro-environment that is surrounded by a dense stroma. A complex network of interactions between extracellular matrix (ECM) components and the effects of cell-to-cell contacts may enhance survival pathways within in vivo tumors. This biological and physical complexity is lost in traditional cell monolayer models. To explore the predictive potential of a more complex cellular system, a three-dimensional (3D) micro-tumor assay was evaluated. Efficacy of six current chemotherapeutics was determined against a panel of primary and metastatic pancreatic tumor cell lines in a miniaturized ECM-based 3D cell culture system. Suitability for potential use in high-throughput screening applications was assessed, including ascertaining the effects that miniaturization and automation had on assay robustness. Cellular health was determined by utilizing an indirect population-based metabolic activity assay and a direct imaging-based cell viability assay.

Overview of Cancer Stem Cells and Stemness for Community Oncologists

Advances in cancer research in the past have led to an evolving understanding of cancer pathogenesis and the development of novel drugs that significantly improve patient outcomes. However, many patients still encounter treatment resistance, recurrence, or metastasis and eventually die from progressing disease. Experimental evidence indicates that a subpopulation of cancer cells, called cancer stem cells (CSCs), possess "stemness" properties similar to normal stem cells, including self-renewal, differentiation, and proliferative potential. These stemness properties are lost during differentiation and are governed by pathways such as STAT3, NANOG, NOTCH, WNT, and HEDGEHOG, which are highly dysregulated in CSCs due to genetic and epigenetic changes. Promising results have been observed in preclinical models targeting these CSCs through the disruption of stemness pathways in combination with current treatment modalities. This has led to anti-CSC-based clinical trials in multiple stages of development. In this review, we discuss the role of CSCs and stemness pathways in cancer treatment and how they relate to clinical observations. Because CSCs and the stemness pathways governing them may explain the negative clinical outcomes observed during treatment, it is important for oncologists to understand how they contribute to cancer progression and how they may be targeted to improve patient outcomes.

Methods: Using Three-Dimensional Culture (Spheroids) as an In Vitro Model of Tumour Hypoxia

Regions of hypoxia in tumours can be modelled in vitro in 2D cell cultures with a hypoxic chamber or incubator in which oxygen levels can be regulated. Although this system is useful in many respects, it disregards the additional physiological gradients of the hypoxic microenvironment, which result in reduced nutrients and more acidic pH. Another approach to hypoxia modelling is to use three-dimensional spheroid cultures. In spheroids, the physiological gradients of the hypoxic tumour microenvironment can be inexpensively modelled and explored. In addition, spheroids offer the advantage of more representative modelling of tumour therapy responses compared with 2D culture. Here, we review the use of spheroids in hypoxia tumour biology research and highlight the different methodologies for spheroid formation and how to obtain uniformity. We explore the challenge of spheroid analyses and how to determine the effect on the hypoxic versus normoxic components of spheroids. We discuss the use of high-throughput analyses in hypoxia screening of spheroids. Furthermore, we examine the use of mathematical modelling of spheroids to understand more fully the hypoxic tumour microenvironment.

Cancer drug discovery: recent innovative approaches to tumor modeling

INTRODUCTION

Cell culture models have been at the heart of anti-cancer drug discovery programs for over half a century. Advancements in cell culture techniques have seen the rapid evolution of more complex in vitro cell culture models investigated for use in drug discovery. Three-dimensional (3D) cell culture research has become a strong focal point, as this technique permits the recapitulation of the tumor microenvironment. Biologically relevant 3D cellular models have demonstrated significant promise in advancing cancer drug discovery, and will continue to play an increasing role in the future.

AREAS COVERED

In this review, recent advances in 3D cell culture techniques and their application in tumor modeling and anti-cancer drug discovery programs are discussed. The topics include selection of cancer cells, 3D cell culture assays (associated endpoint measurements and analysis), 3D microfluidic systems and 3D bio-printing.

EXPERT OPINION

Although advanced cancer cell culture models and techniques are becoming commonplace in many research groups, the use of these approaches has yet to be fully embraced in anti-cancer drug applications. Furthermore, limitations associated with analyzing information-rich biological data remain unaddressed.

Transcriptomic profiling and quantitative high-throughput (qHTS) drug screening of CDH1 deficient hereditary diffuse gastric cancer (HDGC) cells identify treatment leads for familial gastric cancer

BACKGROUND

Patients with hereditary diffuse gastric cancer (HDGC), a cancer predisposition syndrome associated with germline mutations of the CDH1 (E-cadherin) gene, have few effective treatment options. Despite marked differences in natural history, histopathology, and genetic profile to patients afflicted by sporadic gastric cancer, patients with HDGC receive, in large, identical systemic regimens. The lack of a robust preclinical in vitro system suitable for effective drug screening has been one of the obstacles to date which has hampered therapeutic advances in this rare disease.

METHODS

In order to identify therapeutic leads selective for the HDGC subtype of gastric cancer, we compared gene expression profiles and drug phenotype derived from an oncology library of 1912 compounds between gastric cancer cells established from a patient with metastatic HDGC harboring a c.1380delA CDH1 germline variant and sporadic gastric cancer cells.

RESULTS

Unsupervised hierarchical cluster analysis shows select gene expression alterations in c.1380delA CDH1 SB.mhdgc-1 cells compared to a panel of sporadic gastric cancer cell lines with enrichment of ERK1-ERK2 (extracellular signal regulated kinase) and IP3 (inositol trisphosphate)/DAG (diacylglycerol) signaling as the top networks in c.1380delA SB.mhdgc-1 cells. Intracellular phosphatidylinositol intermediaries were increased upon direct measure in c.1380delA CDH1 SB.mhdgc-1 cells. Differential high-throughput drug screening of c.1380delA CDH1 SB.mhdgc-1 versus sporadic gastric cancer cells identified several compound classes with enriched activity in c.1380 CDH1 SB.mhdgc-1 cells including mTOR (Mammalian Target Of Rapamycin), MEK (Mitogen-Activated Protein Kinase), c-Src kinase, FAK (Focal Adhesion Kinase), PKC (Protein Kinase C), or TOPO2 (Topoisomerase II) inhibitors. Upon additional drug response testing, dual PI3K (Phosphatidylinositol 3-Kinase)/mTOR and topoisomerase 2A inhibitors displayed up to >100-fold increased activity in hereditary c.1380delA CDH1 gastric cancer cells inducing apoptosis most effectively in cells with deficient CDH1 function.

CONCLUSION

Integrated pharmacological and transcriptomic profiling of hereditary diffuse gastric cancer cells with a loss-of-function c.1380delA CDH1 mutation implies various pharmacological vulnerabilities selective to CDH1-deficient familial gastric cancer cells and suggests novel treatment leads for future preclinical and clinical treatment studies of familial gastric cancer.

Large-scale pharmacological profiling of 3D tumor models of cancer cells

The discovery of chemotherapeutic agents for the treatment of cancer commonly uses cell proliferation assays in which cells grow as two-dimensional (2D) monolayers. Compounds identified using 2D monolayer assays often fail to advance during clinical development, most likely because these assays do not reproduce the cellular complexity of tumors and their microenvironment in vivo. The use of three-dimensional (3D) cellular systems have been explored as enabling more predictive in vitro tumor models for drug discovery. To date, small-scale screens have demonstrated that pharmacological responses tend to differ between 2D and 3D cancer cell growth models. However, the limited scope of screens using 3D models has not provided a clear delineation of the cellular pathways and processes that differentially regulate cell survival and death in the different in vitro tumor models. Here we sought to further understand the differences in pharmacological responses between cancer tumor cells grown in different conditions by profiling a large collection of 1912 chemotherapeutic agents. We compared pharmacological responses obtained from cells cultured in traditional 2D monolayer conditions with those responses obtained from cells forming spheres versus cells already in 3D spheres. The target annotation of the compound library screened enabled the identification of those key cellular pathways and processes that when modulated by drugs induced cell death in all growth conditions or selectively in the different cell growth models. In addition, we also show that many of the compounds targeting these key cellular functions can be combined to produce synergistic cytotoxic effects, which in many cases differ in the magnitude of their synergism depending on the cellular model and cell type. The results from this work provide a high-throughput screening framework to profile the responses of drugs both as single agents and in pairwise combinations in 3D sphere models of cancer cells.

Targeting Epithelial-Mesenchymal Transition for Identification of Inhibitors for Pancreatic Cancer Cell Invasion and Tumor Spheres Formation

Background

Pancreatic cancer has an enrichment of stem-like cancer cells (CSCs) that contribute to chemoresistant tumors prone to metastasis and recurrence. Drug screening assays based on cytotoxicity cannot identify specific CSC inhibitors, because CSCs comprise only a small portion of cancer cell population, and it is difficult to propagate stable CSC populations in vitro for high-throughput screening (HTS) assays. Based on the important role of cancer cell epithelial-to-mesenchymal transition (EMT) in promoting CSCs, we hypothesized that inhibition of EMT can be a useful strategy for inhibiting CSCs, and therefore a feasible approach for HTS can be built for identification of CSC inhibitors, based on assays detecting EMT inhibition.

Methods

An immunofluorescent assay was established and optimized for HTS to identify compounds that enhance E-cadherin expression, as a hallmark of inhibition of EMT. Four chemical libraries containing 41,472 compounds were screened in PANC-1 pancreatic cancer cell line. Positive hits were validated for EMT and CSC inhibition in vitro using sphere formation assay, western blotting, immune fluorescence, and scratch assay.

Results

Initial hits were refined to 73 compounds with a secondary screening, among which 17 exhibited concentration dependent induction of E-cadherin expression. Six compounds were selected for further study which belonged to 2 different chemical structural clusters. A novel compound 1-(benzylsulfonyl) indoline (BSI, Compound #38) significantly inhibited pancreatic cancer cell migration and invasion. BSI inhibited histone deacetylase, increased histone 4 acetylation preferably, resulting in E-cadherin up-regulation. BSI effectively inhibited tumor spheres formation. Six more analogues of BSI were tested for anti-migration and anti-CSC activities.

Conclusion

This study demonstrated a feasible approach for discovery of agents targeting EMT and CSCs using HTS, and identified a class of novel chemicals that could be developed as anti-EMT and anti-CSC drug leads.

Aurora B kinase is a potent and selective target in MYCN-driven neuroblastoma

Despite advances in multimodal treatment, neuroblastoma (NB) is often fatal for children with high-risk disease and many survivors need to cope with long-term side effects from high-dose chemotherapy and radiation. To identify new therapeutic targets, we performed an siRNA screen of the druggable genome combined with a small molecule screen of 465 compounds targeting 39 different mechanisms of actions in four NB cell lines. We identified 58 genes as targets, including AURKB, in at least one cell line. In the drug screen, aurora kinase inhibitors (nine molecules) and in particular the AURKB-selective compound, barasertib, were the most discriminatory with regard to sensitivity for MYCN-amplified cell lines. In an expanded panel of ten NB cell lines, those with MYCN-amplification and wild-type TP53 were the most sensitive to low nanomolar concentrations of barasertib. Inhibition of the AURKB kinase activity resulted in decreased phosphorylation of the known target, histone H3, and upregulation of TP53 in MYCN-amplified, TP53 wild-type cells. However, both wild-type and TP53 mutant MYCN-amplified cell lines arrested in G2/M phase upon AURKB inhibition. Additionally, barasertib induced endoreduplication and apoptosis. Treatment of MYCN-amplified/TP53 wild-type neuroblastoma xenografts resulted in profound growth inhibition and tumor regression. Therefore, aurora B kinase inhibition is highly effective in aggressive neuroblastoma and warrants further investigation in clinical trials.

Large-scale image-based screening and profiling of cellular phenotypes

Cellular phenotypes are observable characteristics of cells resulting from the interactions of intrinsic and extrinsic chemical or biochemical factors. Image-based phenotypic screens under large numbers of basal or perturbed conditions can be used to study the influences of these factors on cellular phenotypes. Hundreds to thousands of phenotypic descriptors can also be quantified from the images of cells under each of these experimental conditions. Therefore, huge amounts of data can be generated, and the analysis of these data has become a major bottleneck in large-scale phenotypic screens. Here, we review current experimental and computational methods for large-scale image-based phenotypic screens. Our focus is on phenotypic profiling, a computational procedure for constructing quantitative and compact representations of cellular phenotypes based on the images collected in these screens. © 2016 International Society for Advancement of Cytometry.

Ranking Differential Drug Activities from Dose-Response Synthetic Lethality Screens

Synthetic lethal screens are used to discover new combination treatments for cancer. In traditional high-throughput synthetic lethal screens, compounds are tested at a single dose, and hit selection is based on threshold activity values from the variance of the efficacy of the compounds tested. The limitation of the single-dose screening for synthetic lethal screens is that it does not allow for the robust detection of differential activities from compound collections with a broad range of potencies and efficacies. There is therefore a need to develop screening approaches that enable the identification of compounds with synthetic lethal effects based on changes in both potency and efficacy. Here we describe the implementation of a dose response-based synthetic lethal screen to find drugs that enhance or mitigate the cytotoxic effect of an immunotoxin protein (HA22). We developed a data analysis framework for the selection of compounds with enhancing or mitigating cytotoxic activities based on the use of dose-response parameters. The data analysis framework includes an ensemble ranking approach that allows the use of multiple dose-response parameters in a nonparametric fashion. Quantitative high-throughput screening (HTS) enables the identification of compounds with synthetic lethal activity not identified by single-dose HTS.

Cancer stem cells: a systems biology view of their role in prognosis and therapy

Evidence has accumulated that characterizes highly tumorigenic cancer cells residing in heterogeneous populations. The accepted term for such a subpopulation is cancer stem cells (CSCs). While many questions still remain about their precise role in the origin, progression, and drug resistance of tumors, it is clear they exist. In this review, a current understanding of the nature of CSC, their potential usefulness in prognosis, and the need to target them will be discussed. In particular, separate studies now suggest that the CSC is plastic in its phenotype, toggling between tumorigenic and nontumorigenic states depending on both intrinsic and extrinsic conditions. Because of this, a static view of gene and protein levels defined by correlations may not be sufficient to either predict disease progression or aid in the discovery and development of drugs to molecular targets leading to cures. Quantitative dynamic modeling, a bottom up systems biology approach whereby signal transduction pathways are described by differential equations, may offer a novel means to overcome the challenges of oncology today. In conclusion, the complexity of CSCs can be captured in mathematical models that may be useful for selecting molecular targets, defining drug action, and predicting sensitivity or resistance pathways for improved patient outcomes.

The cancer stem cell hypothesis: a guide to potential molecular targets

Common cancer theories hold that tumor is an uncontrolled somatic cell proliferation caused by the progressive addition of random mutations in critical genes that control cell growth. Nevertheless, various contradictions related to the mutation theory have been reported previously. These events may be elucidated by the persistence of residual tumor cells, called Cancer Stem Cells (CSCs) responsible for tumorigenesis, tumor maintenance, tumor spread, and tumor relapse. Herein, we summarize the current understanding of CSCs, with a focus on the possibility to identify specific markers of CSCs, and discuss the clinical application of targeting CSCs for cancer treatment.

Cancer stem cells as a target population for drug discovery

Cancer stem cells (CSCs) have been identified in a growing list of malignancies and are believed to be responsible for cancer initiation, metastasis and relapse following certain therapies, even though they may only represent a small fraction of the cells in a given cancer. Like somatic stem cells and embryonic stem cells, CSCs are capable of self-renewal and differentiation into more mature, less tumorigenic cells that make up the bulk populations of cancer cells. Elimination of CSCs promises intriguing therapeutic potential and this concept has been adopted in preclinical drug discovery programs. Herein we will discuss the progress of these efforts, general considerations in practice, major challenges and possible solutions.

Chemical signatures and new drug targets for gametocytocidal drug development

Control of parasite transmission is critical for the eradication of malaria. However, most antimalarial drugs are not active against P. falciparum gametocytes, responsible for the spread of malaria. Consequently, patients can remain infectious for weeks after the clearance of asexual parasites and clinical symptoms. Here we report the identification of 27 potent gametocytocidal compounds (IC50 < 1 μM) from screening 5,215 known drugs and compounds. All these compounds were active against three strains of gametocytes with different drug sensitivities and geographical origins, 3D7, HB3 and Dd2. Cheminformatic analysis revealed chemical signatures for P. falciparum sexual and asexual stages indicative of druggability and suggesting potential targets. Torin 2, a top lead compound (IC50 = 8 nM against gametocytes in vitro), completely blocked oocyst formation in a mouse model of transmission. These results provide critical new leads and potential targets to expand the repertoire of malaria transmission-blocking reagents.

Application of Titration-Based Screening for the Rapid Pilot Testing of High-Throughput Assays

Pilot testing of an assay intended for high-throughput screening (HTS) with small compound sets is a necessary but often time-consuming step in the validation of an assay protocol. When the initial testing concentration is less than optimal, this can involve iterative testing at different concentrations to further evaluate the pilot outcome, which can be even more time-consuming. Quantitative HTS (qHTS) enables flexible and rapid collection of assay performance statistics, hits at different concentrations, and concentration-response curves in a single experiment. Here we describe the qHTS process for pilot testing in which eight-point concentration-response curves are produced using an interplate asymmetric dilution protocol in which the first four concentrations are used to represent the range of typical HTS screening concentrations and the last four concentrations are added for robust curve fitting to determine potency/efficacy values. We also describe how these data can be analyzed to predict the frequency of false-positives, false-negatives, hit rates, and confirmation rates for the HTS process as a function of screening concentration. By taking into account the compound pharmacology, this pilot-testing paradigm enables rapid assessment of the assay performance and choosing the optimal concentration for the large-scale HTS in one experiment.