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The functional status of the tumor suppressor p53 is a critical component in determining the sensitivity of cancer cells to many chemotherapeutic agents. DNA topoisomerase II (Top2) plays essential roles in DNA metabolism and is the target of FDA approved chemotherapeutic agents. Topoisomerase targeting drugs convert the enzyme into a DNA damaging agent and p53 influences cellular responses to these agents. We assessed the impact of the loss of p53 function on the formation of DNA damage induced by the Top2 poison etoposide. Using human HCT116 cells, we found resistance to etoposide in cell growth assays upon the functional loss of p53. Nonetheless, cells lacking fully functional p53 were etoposide hypersensitive in clonogenic survival assays. This complex role of p53 led us to directly examine the effects of p53 status on topoisomerase-induced DNA damage. A deficiency in functional p53 resulted in elevated levels of the Top2 covalent complexes (Top2cc) in multiple cell lines. Employing genome-wide siRNA screens, we identified a set of genes for which reduced expression resulted in enhanced synthetic lethality upon etoposide treatment of p53 defective cells. We focused on one hit from this screen, ATR, and showed that decreased expression sensitized the p53-defective cells to etoposide in all assays and generated elevated levels of Top2cc in both p53 proficient and deficient cells. Our findings suggest that a combination of etoposide treatment with functional inactivation of DNA repair in p53 defective cells could be used to enhance the therapeutic efficacy of Top2 targeting agents.

Age-related Macular Degeneration (AMD), a blinding eye disease, is characterized by pathological protein- and lipid-rich drusen deposits underneath the retinal pigment epithelium (RPE) and atrophy of the RPE monolayer in advanced disease stages - leading to photoreceptor cell death and vision loss. Currently, there are no drugs that stop drusen formation or RPE atrophy in AMD. Here we provide an iPSC-RPE AMD model that recapitulates drusen and RPE atrophy. Drusen deposition is dependent on AMD-risk-allele CFH(H/H) and anaphylatoxin triggered alternate complement signaling via the activation of NF-κB and downregulation of autophagy pathways. Through high-throughput screening we identify two drugs, L-745,870, a dopamine receptor antagonist, and aminocaproic acid, a protease inhibitor that reduce drusen deposits and restore RPE epithelial phenotype in anaphylatoxin challenged iPSC-RPE with or without the CFH(H/H) genotype. This comprehensive iPSC-RPE model replicates key AMD phenotypes, provides molecular insight into the role of CFH(H/H) risk-allele in AMD, and discovers two candidate drugs to treat AMD., Age-related macular degeneration is characterized by lipid-rich drusen deposits underneath the retinal pigment epithelium (RPE). Here the authors report an in vitro iPSC-RPE model for AMD that recapitulates drusen and RPE atrophy, and identify two drugs that reduce drusen deposits and restore RPE epithelial phenotype.

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

Modified vaccinia virus Ankara (MVA) is an approved smallpox vaccine and a promising vaccine vector for other pathogens as well as for cancer therapeutics with more than 200 current or completed clinical trials. MVA was derived by passaging the parental Ankara vaccine virus hundreds of times in chick embryo fibroblasts during which it lost the ability to replicate in human and most other mammalian cells. Although this replication deficiency is an important safety feature, the genetic basis of the host restriction is not understood. Here, an unbiased human genome-wide RNAi screen in human A549 cells revealed that the zinc-finger antiviral protein (ZAP), previously shown to inhibit certain RNA viruses, is a host restriction factor for MVA, a DNA virus. Additional studies demonstrated enhanced MVA replication in several human cell lines following knockdown of ZAP. Furthermore, CRISPR-Cas9 knockout of ZAP in human A549 cells increased MVA replication and spread by more than one log but had no effect on a non-attenuated strain of vaccinia virus. The intact viral C16 protein, which had been disrupted in MVA, antagonized ZAP by binding and sequestering the protein in cytoplasmic punctate structures. Studies aimed at exploring the mechanism by which ZAP restricts MVA replication in the absence of C16 showed that knockout of ZAP had no discernible effect on viral DNA or individual mRNA or protein species as determined by droplet digital polymerase chain reaction, deep RNA sequencing and mass spectrometry, respectively. Instead, inactivation of ZAP reduced the number of aberrant, dense, spherical particles that typically form in MVA-infected human cells, suggesting that ZAP has a novel role in interfering with a late step in the assembly of infectious MVA virions in the absence of the C16 protein., Author summary The attenuated vaccine vector known as modified vaccinia virus Ankara (MVA) was derived by extensively passaging the parental strain of vaccinia virus Ankara in chick embryo fibroblasts and is unable to replicate in most mammalian cells. The MVA host range restriction is exceptional in that synthesis of the abundant viral proteins appears unaffected but morphogenesis of virus particles is abortive. Despite the importance of the host range restriction for vaccine safety, the basis for this antiviral effect has remained an enigma. Here we demonstrate that the zinc finger antiviral protein (ZAP), previously shown to be an inhibitor of RNA viruses, is a specific host restriction factor for replication of MVA in human cells. Moreover, the intact vaccinia virus C16 protein, which was disrupted during the attenuation of MVA, sequesters ZAP in cytoplasmic punctae and effectively counteracts the inhibitory effects of ZAP.

The zika virus (ZIKV) and dengue virus (DENV) flaviviruses exhibit similar replicative processes but have distinct clinical outcomes. A systematic understanding of virus-host protein-protein interaction networks can reveal cellular pathways critical to viral replication and disease pathogenesis. Here we employed three independent systems biology approaches toward this goal. First, protein array analysis of direct interactions between individual ZIKV/DENV viral proteins and 20,240 human proteins revealed multiple conserved cellular pathways and protein complexes, including proteasome complexes. Second, an RNAi screen of 10,415 druggable genes identified the host proteins required for ZIKV infection and uncovered that proteasome proteins were crucial in this process. Third, high-throughput screening of 6016 bioactive compounds for ZIKV inhibition yielded 134 effective compounds, including six proteasome inhibitors that suppress both ZIKV and DENV replication. Integrative analyses of these orthogonal datasets pinpoint proteasomes as critical host machinery for ZIKV/DENV replication. Our study provides multi-omics datasets for further studies of flavivirus-host interactions, disease pathogenesis, and new drug targets.

The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.

Three-dimensional (3D) cell culture models are thought to mimic the physiological and pharmacological properties of tissues in vivo more accurately than two-dimensional cultures on plastic dishes. For the development of cancer therapies, 3D spheroid models are being created to reflect the complex histology and physiology of primary tumors with the hopes that drug responses will be more similar to and as predictive as those obtained in vivo. The effect of additional cell types in tumors, such as stromal cells, and the resulting heterotypic cell-cell crosstalk can be investigated in these heterotypic 3D cell cultures. Here, a high-throughput screening-compatible drug testing platform based on 3D multicellular spheroid models is described that enables the parallel assessment of toxicity on stromal cells and efficacy on cancer cells by drug candidates. These heterotypic microtissue tumor models incorporate NIH3T3 fibroblasts as stromal cells that are engineered with a reporter gene encoding secreted NanoLUC luciferase. By tracking the NanoLUC signal in the media over time, a time-related measurement of the cytotoxic effects of drugs on stromal cells over the cancer cells was possible, thus enabling the identification of a therapeutic window. An in vitro therapeutic index parameter is proposed to help distinguish and classify those compounds with broad cytotoxic effects versus those that are more selective at targeting cancer cells.

The tumor microenvironment (TME) is a key determinant of metastatic efficiency. We performed a quantitative high-throughput screen (qHTS) of diverse medicinal chemistry tractable scaffolds (44,420 compounds) and pharmacologically active small molecules (386 compounds) using a layered organotypic, robust assay representing the ovarian cancer metastatic TME. This 3D model contains primary human mesothelial cells, fibroblasts, and extracellular matrix, to which fluorescently labeled ovarian cancer cells are added. Initially, 100 compounds inhibiting ovarian cancer adhesion/invasion to the 3D model in a dose-dependent manner were identified. Of those, eight compounds were confirmed active in five high-grade serous ovarian cancer cell lines and were further validated in secondary in vitro and in vivo biological assays. Two tyrosine kinase inhibitors, PP-121 and milciclib, and a previously unreported compound, NCGC00117362, were selected because they had potency at 1 μmol/L in vitro. Specifically, NCGC00117362 and PP-121 inhibited ovarian cancer adhesion, invasion, and proliferation, whereas milciclib inhibited ovarian cancer invasion and proliferation. Using in situ kinase profiling and immunoblotting, we found that milciclib targeted Cdk2 and Cdk6, and PP-121 targeted mTOR. In vivo, all three compounds prevented ovarian cancer adhesion/invasion and metastasis, prolonged survival, and reduced omental tumor growth in an intervention study. To evaluate the clinical potential of NCGC00117362, structure–activity relationship studies were performed. Four close analogues of NCGC00117362 efficiently inhibited cancer aggressiveness in vitro and metastasis in vivo. Collectively, these data show that a complex 3D culture of the TME is effective in qHTS. The three compounds identified have promise as therapeutics for prevention and treatment of ovarian cancer metastasis.

High-throughput siRNA screens were only recently applied to cell factories to identify novel engineering targets which are able to boost cells towards desired phenotypes. While siRNA libraries exist for model organisms such as mice, no CHO-specific library is publicly available, hindering the application of this technique to CHO cells. The optimization of these cells is of special interest, as they are the main host for the production of therapeutic proteins. Here, we performed a cross-species approach by applying a mouse whole-genome siRNA library to CHO cells, optimized the protocol for suspension cultured cells, as this is the industrial practice for CHO cells, and developed an in silico method to identify functioning siRNAs, which also revealed the limitations of using cross-species libraries. With this method, we were able to identify several genes that, upon knockdown, enhanced the total productivity in the primary screen. A second screen validated two of these genes, Rad21 and Chd4, whose knockdown was tested in additional CHO cell lines, confirming the induced high productivity phenotype, but also demonstrating the cell line/clone specificity of engineering effects.

Summary Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER+ breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.

Excess lipid storage is an epidemic problem in human populations. Thus, the identification of small molecules to treat or prevent lipid storage-related metabolic complications is of great interest. Here we screened > 320.000 compounds for their ability to prevent a cellular lipid accumulation phenotype. We used fly cells because the multifarious tools available for this organism should facilitate unraveling the mechanism-of-action of active small molecules. Of the several hundred lipid storage inhibitors identified in the primary screen we concentrated on three structurally diverse and potent compound classes active in cells of multiple species (including human) and negligible cytotoxicity. Together with Drosophila in vivo epistasis experiments, RNA-Seq expression profiles suggested that the target of one of the small molecules was diacylglycerol acyltransferase 1 (DGAT1), a key enzyme in the production of triacylglycerols and prominent human drug target. We confirmed this prediction by biochemical and enzymatic activity tests., Highlights • We identified > 600 potent small molecule inhibitors of cellular lipid storage deposition. • RNA-Seq expression profiling discriminated the activity of three lead scaffolds and guided subsequent functional studies. • We discovered a class of DGAT1 inhibitors, which is active in fly and mammalian cell lines as well as whole flies. Obesity and other lipid storage associated diseases are a growing health threat of human populations. In an undirected phenotypic screen, we identified pharmacologically active small molecules that reduce or enhance lipid storage. Our work focuses on three lead structures that prevent lipid storage in diverse cellular systems including cells from a diabetes patient. In order to elucidate the compound mechanisms-of-action and cellular targets, we used a combination of RNA-Seq transcriptional profiling and diverse functional assays. Our results strongly suggest that one of our lead structures represents a class of inhibitors targeting the key lipogenic enzyme diacylglycerol acyltransferase 1.

As we witness steady progress towards the development of robust, scalable, and reproducible 3D tissue models for preclinical drug testing, there is a need for systematic physiological and pharmacological validation and benchmarking. Ongoing and future studies should generate evidence as to whether 3D tissue models are more predictive, help reduce the risk of failure rate, and can be used for decision making in the drug discovery and development pipeline. Here, we discuss the importance of harmonizing the validation of these models based on throughput capacity and physiological complexity as a requirement to establish their true translational capacity. We also outline our strategy for a novel 3D-tailored holistic drug discovery concept rather than piecemeal integration of 3D models into the current process.

Aldehyde dehydrogenases (ALDHs) are responsible for the metabolism of aldehydes (exogenous and endogenous) and possess vital physiological and toxicological functions in areas such as CNS, inflammation, metabolic disorders, and cancers. Overexpression of certain ALDHs (e.g., ALDH1A1) is an important biomarker in cancers and cancer stem cells (CSCs) indicating the potential need for the identification and development of small molecule ALDH inhibitors. Herein, a newly designed series of quinoline-based analogs of ALDH1A1 inhibitors is described. Extensive medicinal chemistry optimization and biological characterization led to the identification of analogs with significantly improved enzymatic and cellular ALDH inhibition. Selected analogs, e.g., 86 (NCT-505) and 91 (NCT-506), demonstrated target engagement in a cellular thermal shift assay (CETSA), inhibited the formation of 3D spheroid cultures of OV-90 cancer cells, and potentiated the cytotoxicity of paclitaxel in SKOV-3-TR, a paclitaxel resistant ovarian cancer cell line. Lead compounds also exhibit high specificity over other ALDH isozymes and unrelated dehydrogenases. The in vitro ADME profiles and pharmacokinetic evaluation of selected analogs are also highlighted.

With an increasing number of blockbuster drugs being recombinant mammalian proteins, protein production platforms that focus on mammalian proteins have had a profound impact in many areas of basic and applied research. Many groups, both academic and industrial, have been focusing on developing cost-effective methods to improve the production of mammalian proteins that would support potential therapeutic applications. As it stands, while a wide range of platforms have been successfully developed for laboratory use, the majority of biologicals are still produced in mammalian cell lines due to the requirement for posttranslational modification and the biosynthetic complexity of target proteins. An unbiased high-throughput RNAi screening approach can be an efficient tool to identify target genes involved in recombinant protein production. Here we describe the process of optimizing the transfection conditions, performing the genome-wide siRNA screen, the activity and cell viability assays and the validation transfection to identify genes involved with protein expression.

Emerging evidence links exosomes to cancer progression by the trafficking of oncogenic factors and neoplastic reprogramming of stem cells. This necessitates identification and integration of functionally validated exosome-targeting therapeutics into current cancer management regimens. We employed quantitative high throughput screen on two libraries to identify exosome-targeting drugs; a commercially available collection of 1280 pharmacologically active compounds and a collection of 3300 clinically approved compounds. Manumycin-A (MA), a natural microbial metabolite, was identified as an inhibitor of exosome biogenesis and secretion by castration-resistant prostate cancer (CRPC) C4-2B, but not the normal RWPE-1, cells. While no effect was observed on cell growth, MA attenuated ESCRT-0 proteins Hrs, ALIX and Rab27a and exosome biogenesis and secretion by CRPC cells. The MA inhibitory effect is primarily mediated via targeted inhibition of the Ras/Raf/ERK1/2 signaling. The Ras-dependent MA suppression of exosome biogenesis and secretion is partly mediated by ERK-dependent inhibition of the oncogenic splicing factor hnRNP H1. Our findings suggest that MA is a potential drug candidate to suppress exosome biogenesis and secretion by CRPC cells.

Alveolar rhabdomyosarcoma is a life-threatening myogenic cancer of children and adolescent young adults, driven primarily by the chimeric transcription factor PAX3–FOXO1. The mechanisms by which PAX3–FOXO1 dysregulates chromatin are unknown. We find PAX3–FOXO1 reprograms the cis-regulatory landscape by inducing de novo super enhancers. PAX3–FOXO1 uses super enhancers to set up autoregulatory loops in collaboration with the master transcription factors MYOG, MYOD, and MYCN. This myogenic super enhancer circuitry is consistent across cell lines and primary tumors. Cells harboring the fusion gene are selectively sensitive to small-molecule inhibition of protein targets induced by, or bound to, PAX3–FOXO1-occupied super enhancers. Furthermore, PAX3–FOXO1 recruits and requires the BET bromodomain protein BRD4 to function at super enhancers, resulting in a complete dependence on BRD4 and a significant susceptibility to BRD inhibition. These results yield insights into the epigenetic functions of PAX3–FOXO1 and reveal a specific vulnerability that can be exploited for precision therapy. Significance: PAX3–FOXO1 drives pediatric fusion-positive rhabdomyosarcoma, and its chromatin-level functions are critical to understanding its oncogenic activity. We find that PAX3–FOXO1 establishes a myoblastic super enhancer landscape and creates a profound subtype-unique dependence on BET bromodomains, the inhibition of which ablates PAX3–FOXO1 function, providing a mechanistic rationale for exploring BET inhibitors for patients bearing PAX-fusion rhabdomyosarcoma. Cancer Discov; 7(8); 884–99. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 783

The tumor microenvironment plays an important role in the processes of tumor growth, metastasis and drug resistance. We have utilized a multilayered 3D primary cell culture model that reproduces the human ovarian cancer metastatic microenvironment to study the effect of the microenvironment on the pharmacological responses of cancer cells proliferation to different classes of drugs. A collection of oncology drugs was screened to identify compounds that inhibited the proliferation of ovarian cancer cells growing as monolayers or forming spheroids, on plastic and on a 3D microenvironment culture model of the omentum metastatic site, and also cells already in pre-formed spheroids. Target-based analysis of the pharmacological responses revealed that several classes of targets were more efficacious in cancer cells growing in the absence of the metastatic microenvironment, and other target classes were less efficacious in cancer cells in pre-formed spheres compared to forming spheroids cultures. These findings show that both the cellular context of the tumor microenvironment and cell adhesion mode have an essential role in cancer cell drug resistance. Therefore it is important to perform screens for new drugs using model systems that more faithfully recapitulate the tissue composition at the site of tumor growth and metastasis

Viruses and their hosts can reach balanced states of evolution ensuring mutual survival, which makes it difficult to appreciate the underlying dynamics. To uncover hidden interactions, virus mutants that have lost defense genes may be used. Deletion of the gene that encodes serine protease inhibitor 1 (SPI-1) of rabbitpox virus and vaccinia virus, two closely related orthopoxviruses, prevents their efficient replication in human cells, whereas certain other mammalian cells remain fully permissive. Our high-throughput genome-wide siRNA screen identified host factors that prevent reproduction and spread of the mutant viruses in human cells. More than 20,000 genes were interrogated with individual siRNAs and those that prominently increased replication of the SPI-1 deletion mutant were subjected to a secondary screen. The top hits based on the combined data-replication factor C3 (RFC3), FAM111A, and interferon regulatory factor 2 (IRF2)-were confirmed by custom assays. The siRNAs to RFC1, RFC2, RFC4, and RFC5 mRNAs also enhanced spread of the mutant virus, strengthening the biological significance of the RFC complex as a host restriction factor for poxviruses. Whereas association with proliferating cell nuclear antigen and participation in processive genome replication are common features of FAM111A and RFC, IRF2 is a transcriptional regulator. Microarray analysis, quantitative RT-PCR, and immunoblotting revealed that IRF2 regulated the basal level expression of FAM111A, suggesting that the enhancing effect of depleting IRF2 on replication of the SPI-1 mutant was indirect. Thus, the viral SPI-1 protein and the host IRF2, FAM111A, and RFC complex likely form an interaction network that influences the ability of poxviruses to replicate in human cells.

Two-dimensional monolayer cell proliferation assays for cancer drug discovery have made the implementation of large-scale screens feasible but only seem to reflect a simplified view that oncogenes or tumor suppressor genes are the genetic drivers of cancer cell proliferation. However, there is now increased evidence that the cellular and physiological context in which these oncogenic events occur play a key role in how they drive tumor growth in vivo and, therefore, in how tumors respond to drug treatments. In vitro 3D spheroid tumor models are being developed to better mimic the physiology of tumors in vivo, in an attempt to improve the predictability and efficiency of drug discovery for the treatment of cancer. Here we describe the establishment of a real-time 3D spheroid growth, 384-well screening assay. The cells used in this study constitutively expressed green fluorescent protein (GFP), which enabled the real-time monitoring of spheroid formation and the effect of chemotherapeutic agents on spheroid size at different time points of sphere growth and drug treatment. This real-time 3D spheroid assay platform represents a first step toward the replication in vitro of drug dosing regimens being investigated in vivo. We hope that further development of this assay platform will allow the investigation of drug dosing regimens, efficacy, and resistance before preclinical and clinical studies.

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.

The tumour microenvironment contributes to cancer metastasis and drug resistance. However, most high throughput screening (HTS) assays for drug discovery use cancer cells grown in monolayers. Here we show that a multilayered culture containing primary human fibroblasts, mesothelial cells and extracellular matrix can be adapted into a reliable 384- and 1,536-multi-well HTS assay that reproduces the human ovarian cancer (OvCa) metastatic microenvironment. We validate the identified inhibitors in secondary in vitro and in vivo biological assays using three OvCa cell lines: HeyA8, SKOV3ip1 and Tyk-nu. The active compounds directly inhibit at least two of the three OvCa functions: adhesion, invasion and growth. In vivo, these compounds prevent OvCa adhesion, invasion and metastasis, and improve survival in mouse models. Collectively, these data indicate that a complex three-dimensional culture of the tumour microenvironment can be adapted for quantitative HTS and may improve the disease relevance of assays used for drug screening.

Protein expression from human embryonic kidney cells (HEK 293) is an important tool for structural and clinical studies. It is previously shown that microRNAs (small, noncoding RNAs) are effective means for improved protein expression from these cells, and by conducting a high-throughput screening of the human microRNA library, several microRNAs are identified as potential candidates for improving expression. From these, miR-22-3p is chosen for further study since it increased the expression of luciferase, two membrane proteins and a secreted fusion protein with minimal effect on the cells' growth and viability. Since each microRNA can interact with several gene targets, it is of interest to identify the repressed genes for understanding and exploring the improved expression mechanism for further implementation. Here, the authors describe a novel approach for identification of the target genes by integrating the differential gene expression analysis with information obtained from our previously conducted high-throughput siRNA screening. The identified genes were validated as being involved in improving luciferase expression by using siRNA and qRT-PCR. Repressing the target gene, HIPK1, is found to increase luciferase and GPC3 expression 3.3- and 2.2-fold, respectively.

Claudins are crucial components of tight junctions and are important in regulating permeability and maintaining cell polarity in cell sheets., The claudin multigene family encodes tetraspan membrane proteins that are crucial structural and functional components of tight junctions, which have important roles in regulating paracellular permeability and maintaining cell polarity in epithelial and endothelial cell sheets. In mammals, the claudin family consists of 24 members, which exhibit complex tissue-specific patterns of expression. The extracellular loops of claudins from adjacent cells interact with each other to seal the cellular sheet and regulate paracellular transport between the luminal and basolateral spaces. The claudins interact with multiple proteins and are intimately involved in signal transduction to and from the tight junction. Several claudin mouse knockout models have been generated and the diversity of phenotypes observed clearly demonstrates their important roles in the maintenance of tissue integrity in various organs. In addition, mutation of some claudin genes has been causatively associated with human diseases and claudin genes have been found to be deregulated in various cancers. The mechanisms of claudin regulation and their exact roles in normal physiology and disease are being elucidated, but much work remains to be done. The next several years are likely to witness an explosion in our understanding of these proteins, which may, in turn, provide new approaches for the targeted therapy of various diseases.