scholarly journals Advanced Development of Primary Pancreatic Organoid Tumor Models for High-Throughput Phenotypic Drug Screening

2018 ◽  
Vol 23 (6) ◽  
pp. 574-584 ◽  
Author(s):  
Shurong Hou ◽  
Hervé Tiriac ◽  
Banu Priya Sridharan ◽  
Louis Scampavia ◽  
Franck Madoux ◽  
...  
Keyword(s):  
High Throughput ◽  
Drug Screening ◽  
Anticancer Agents ◽  
High Throughput Screening ◽  
Large Scale ◽  
Ex Vivo ◽  
Cell Models ◽  
Tumor Models ◽  
Flat Bottom

Traditional high-throughput drug screening in oncology routinely relies on two-dimensional (2D) cell models, which inadequately recapitulate the physiologic context of cancer. Three-dimensional (3D) cell models are thought to better mimic the complexity of in vivo tumors. Numerous methods to culture 3D organoids have been described, but most are nonhomogeneous and expensive, and hence impractical for high-throughput screening (HTS) purposes. Here we describe an HTS-compatible method that enables the consistent production of organoids in standard flat-bottom 384- and 1536-well plates by combining the use of a cell-repellent surface with a bioprinting technology incorporating magnetic force. We validated this homogeneous process by evaluating the effects of well-characterized anticancer agents against four patient-derived pancreatic cancer KRAS mutant-associated primary cells, including cancer-associated fibroblasts. This technology was tested for its compatibility with HTS automation by completing a cytotoxicity pilot screen of ~3300 approved drugs. To highlight the benefits of the 3D format, we performed this pilot screen in parallel in both the 2D and 3D assays. These data indicate that this technique can be readily applied to support large-scale drug screening relying on clinically relevant, ex vivo 3D tumor models directly harvested from patients, an important milestone toward personalized medicine.

scholarly journals Identification of a juvenile-hormone signaling inhibitor via high-throughput screening of a chemical library

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Takumi Kayukawa ◽  
Kenjiro Furuta ◽  
Keisuke Nagamine ◽  
Tetsuro Shinoda ◽  
Kiyoaki Yonesu ◽  
...  
Keyword(s):  
Juvenile Hormone ◽  
Cell Line ◽  
Signaling Pathway ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Ex Vivo ◽  
Agricultural Field ◽  
Chemical Library ◽  
Field Development

Abstract Insecticide resistance has recently become a serious problem in the agricultural field. Development of insecticides with new mechanisms of action is essential to overcome this limitation. Juvenile hormone (JH) is an insect-specific hormone that plays key roles in maintaining the larval stage of insects. Hence, JH signaling pathway is considered a suitable target in the development of novel insecticides; however, only a few JH signaling inhibitors (JHSIs) have been reported, and no practical JHSIs have been developed. Here, we established a high-throughput screening (HTS) system for exploration of novel JHSIs using a Bombyx mori cell line (BmN_JF&AR cells) and carried out a large-scale screening in this cell line using a chemical library. The four-step HTS yielded 69 compounds as candidate JHSIs. Topical application of JHSI48 to B. mori larvae caused precocious metamorphosis. In ex vivo culture of the epidermis, JHSI48 suppressed the expression of the Krüppel homolog 1 gene, which is directly activated by JH-liganded receptor. Moreover, JHSI48 caused a parallel rightward shift in the JH response curve, suggesting that JHSI48 possesses a competitive antagonist-like activity. Thus, large-scale HTS using chemical libraries may have applications in development of future insecticides targeting the JH signaling pathway.

scholarly journals RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions

2017 ◽  
Vol 22 (5) ◽  
pp. 525-536 ◽  
Author(s):  
Jiaqi Fu ◽  
Daniel Fernandez ◽  
Marc Ferrer ◽  
Steven A. Titus ◽  
Eugen Buehler ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Attrition Rate ◽  
Three Dimensions ◽  
Cell Type ◽  
Tumor Spheroids ◽  
Flat Bottom ◽  
Cancer Subtypes

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.

Large-scale drug screening against Babesia divergens parasite using a fluorescence-based high-throughput screening assay

2016 ◽  
Vol 227 ◽  
pp. 93-97 ◽  
Author(s):  
Mohamed Abdo Rizk ◽  
Shimaa Abd El-Salam El-Sayed ◽  
Mahmoud AbouLaila ◽  
Bumduuren Tuvshintulga ◽  
Naoaki Yokoyama ◽  
...  
Keyword(s):  
High Throughput ◽  
Drug Screening ◽  
High Throughput Screening ◽  
Large Scale ◽  
Screening Assay ◽  
High Throughput Screening Assay ◽  
Babesia Divergens

scholarly journals Epileptic brain fluorescent imaging reveals apigenin can relieve the myeloperoxidase-mediated oxidative stress and inhibit ferroptosis

2020 ◽  
Vol 117 (19) ◽  
pp. 10155-10164 ◽  
Author(s):  
Chenwen Shao ◽  
Jiwen Yuan ◽  
Yani Liu ◽  
Yajuan Qin ◽  
Xueao Wang ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Real Time ◽  
High Throughput ◽  
High Throughput Screening ◽  
Fluorescence Probe ◽  
Ex Vivo ◽  
Fluorescent Imaging ◽  
Flavonoid Compound ◽  
Antiepileptic Agents

Myeloperoxidase (MPO)-mediated oxidative stress has been suggested to play an important role in the pathological dysfunction of epileptic brains. However, there is currently no robust brain-imaging tool to detect real-time endogenous hypochlorite (HClO) generation by MPO or a fluorescent probe for rapid high-throughput screening of antiepileptic agents that control the MPO-mediated chlorination stress. Herein, we report an efficient two-photon fluorescence probe (named HCP) for the real-time detection of endogenous HClO signals generated by MPO in the brain of kainic acid (KA)-induced epileptic mice, where HClO-dependent chlorination of quinolone fluorophore gives the enhanced fluorescence response. With this probe, we visualized directly the endogenous HClO fluxes generated by the overexpression of MPO activity in vivo and ex vivo in mouse brains with epileptic behaviors. Notably, by using HCP, we have also constructed a high-throughput screening approach to rapidly screen the potential antiepileptic agents to control MPO-mediated oxidative stress. Moreover, from this screen, we identified that the flavonoid compound apigenin can relieve the MPO-mediated oxidative stress and inhibit the ferroptosis of neuronal cells. Overall, this work provides a versatile fluorescence tool for elucidating the role of HClO generation by MPO in the pathology of epileptic seizures and for rapidly discovering additional antiepileptic agents to prevent and treat epilepsy.

scholarly journals Live Florescent Staining Platform Drug-Screening and Mechanism-Analysis in Zebrafish for Bone Mineralization

2017 ◽  
Author(s):  
Jung-Ren Chen ◽  
Yu-Heng Lai ◽  
Jhih-Jie Tsai ◽  
Chung-Der Hsiao
Keyword(s):  
High Throughput ◽  
Drug Screening ◽  
High Throughput Screening ◽  
Bone Mineralization ◽  
Biological Effects ◽  
Rapid Development ◽  
Toxicity Screening ◽  
Mechanism Analysis ◽  
Chemical Library

Currently, drug screening is primarily based on human cell culture for initial high-throughput screening, and subsequently, rodent model to confirm the biological effects. However, the mammalian system is known for time-consuming and highly-cost to be difficult to perform high-throughput drug screening, which exists a critical gap between in vitro cell-based models and the in vivo mammalian models. Therefore, the zebrafish could bridge this gap in preclinical toxicity screening along the drug development pipeline because of its efficiency. We aimed to develop an in vivo zebrafish platform for rapid drug screening. Zebrafish, due to its high genomic conservation with mammals and rapid development and differentiation, it has many advantages, such as short life span, large number of offspring and low cost, easy manipulation for generating transgenic species, to serve as animal model for disease-based research. In 96-well microplates, zebrafish embryos were incubated with small molecular compounds that affected bone mineralization. The level of osteogenic mineralization was evaluated by fluorescent dye staining and quantified by image analysis software. Quantitative real time-PCR (qRT-PCR) was performed to evaluate the biological pathways involved in bone metabolism at the molecular level. The system was validated by demonstrating that response to alendronate and Dorsomorphin in zebrafish. In our study, we screened for 24 compounds within the CYCU-1120~1152 chemical library and identified 3 compounds, pentamidine (CYCU-1140), BML-267 (CYCU-1147), and alendronate (CYCU-1152), increased embryonic mineralization; while 6 compounds, RWJ-60475 (CYCU-1126), levamisole HCL (CYCU-1128), tetramisole HCL (CYCU-1129), fenvalerate (CYCU-1132), NSC-663284 (CYCU-1138), and BML-267ester (CYCU-1148), were inhibitory to bone mineralization. We also found that alendronate enhanced the level of bone mineralization by inhibiting osteoclast-related genes. To sum up, our research showed that zebrafish may have potential to be a drug-screening and mechanism-analysis platform for bone mineralization.

scholarly journals Computationally guided high-throughput design of self-assembling drug nanoparticles

2019 ◽  
Author(s):  
Daniel Reker ◽  
Yulia Rybakova ◽  
Ameya R. Kirtane ◽  
Ruonan Cao ◽  
Jee Won Yang ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Ex Vivo ◽  
Drug Loading ◽  
Food Additives ◽  
Drug Nanoparticles ◽  
Self Assembling ◽  
Wide Range ◽  
Approved Drugs

AbstractNanoformulations are transforming our capacity to effectively deliver and treat a myriad of conditions. However, many nanoformulation approaches still suffer from high production complexity and low drug loading. One potential solution relies on harnessing co-assembly of drugs and small molecular excipients to facilitate nanoparticle formation through solvent exchange without the need for chemical synthesis, generating nanoparticles with up to 95% drug loading. However, there is currently no understanding which of the millions of possible combinations of small molecules can result in the formation of these nanoparticles. Here we report the development of a high-throughput screening platform coupled to machine learning to enable the rapid evaluation of such nanoformulations. Our platform identified 101 novel self-assembling drug nanoparticles from 2.1 million pairings derived from 788 candidate drugs with one of 2686 excipients, spanning treatments for multiple diseases and often harnessing well-known food additives, vitamins, or approved drugs as carrier materials – with potential for accelerated approval and translation. Given their long-term stability and potential for clinical impact, we further characterize novel sorafenib-glycyrrhizin and terbinafine-taurocholic acid nanoparticles ex vivo and in vivo. We anticipate that this platform could accelerate the development of safer and more efficacious nanoformulations with high drug loadings for a wide range of therapeutics.

scholarly journals A Cytotoxic Three-Dimensional-Spheroid, High-Throughput Assay Using Patient-Derived Glioma Stem Cells

2018 ◽  
Vol 23 (8) ◽  
pp. 842-849 ◽  
Author(s):  
Victor Quereda ◽  
Shurong Hou ◽  
Franck Madoux ◽  
Louis Scampavia ◽  
Timothy P. Spicer ◽  
...  
Keyword(s):  
Stem Cells ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Three Dimensional ◽  
Treatment Resistance ◽  
Small Population ◽  
Molecular Probes ◽  
Glioma Stem Cells

Glioblastoma (GBM) is the most aggressive primary brain cancer with an average survival time after diagnosis of only 12–14 months, with few (<5%) long-term survivors. A growing body of work suggests that GBMs contain a small population of glioma stem cells (GSCs) that are thought to be major contributors to treatment resistance and disease relapse. Identifying compounds that modulate GSC proliferation would provide highly valuable molecular probes of GSC-directed signaling. However, targeting GSCs pharmacologically has been challenging. Patient-derived GSCs can be cultured as neurospheres, and in vivo these cells functionally recapitulate the heterogeneity of the original tumor. Using patient-derived GSC-enriched cultures, we have developed a 1536-well spheroid-based proliferation assay and completed a pilot screen, testing ~3300 compounds comprising approved drugs. This cytotoxic and automation-friendly assay yielded a signal-to-background (S/B) ratio of 161.3 ± 7.5 and Z′ of 0.77 ± 0.02, demonstrating its robustness. Importantly, compounds were identified with anti-GSC activity, demonstrating the applicability of this assay for large-scale high-throughput screening (HTS).

scholarly journals CytoRADx: A High-Throughput, Standardized Biodosimetry Diagnostic System Based on the Cytokinesis-Block Micronucleus Assay

2021 ◽  
Author(s):  
Chris Capaccio ◽  
Jay R. Perrier ◽  
Lídia Cunha ◽  
Ryan C. Mahnke ◽  
Thomas Lörch ◽  
...  
Keyword(s):  
Radiation Dose ◽  
High Throughput ◽  
Large Scale ◽  
Ex Vivo ◽  
Micronucleus Assay ◽  
In Vivo Studies ◽  
Diverse Populations ◽  
Cell Nuclei ◽  
Cbmn Assay

In a large-scale catastrophe, such as a nuclear detonation in a major city, it will be crucial to accurately diagnose large numbers of people to direct scarce medical resources to those in greatest need. Currently no FDA-cleared tests are available to diagnose radiation exposures, which can lead to complex, life-threatening injuries. To address this gap, we have achieved substantial advancements in radiation biodosimetry through refinement and adaptation of the cytokinesis-block micronucleus (CBMN) assay as a high throughput, quantitative diagnostic test. The classical CBMN approach, which quantifies micronuclei (MN) resulting from DNA damage, suffers from considerable time and expert labor requirements, in addition to a lack of universal methodology across laboratories. We have developed the CytoRADx™ System to address these drawbacks by implementing a standardized reagent kit, optimized assay protocol, fully automated microscopy and image analysis, and integrated dose prediction. These enhancements allow the CytoRADx System to obtain high-throughput, standardized results without specialized labor or laboratory-specific calibration curves. The CytoRADx System has been optimized for use with both humans and non-human primates (NHP) to quantify radiation dose-dependent formation of micronuclei in lymphocytes, observed using whole blood samples. Cell nuclei and resulting MN are fluorescently stained and preserved on durable microscope slides using materials provided in the kit. Up to 1,000 slides per day are subsequently scanned using the commercially based RADxScan™ Imager with customized software, which automatically quantifies the cellular features and calculates the radiation dose. Using less than 1 mL of blood, irradiated ex vivo, our system has demonstrated accurate and precise measurement of exposures from 0 to 8 Gy (90% of results within 1 Gy of delivered dose). These results were obtained from 636 human samples (24 distinct donors) and 445 NHP samples (30 distinct subjects). The system demonstrated comparable results during in vivo studies, including an investigation of 43 NHPs receiving single-dose total-body irradiation. System performance is repeatable across laboratories, operators, and instruments. Results are also statistically similar across diverse populations, considering various demographics, common medications, medical conditions, and acute injuries associated with radiological disasters. Dose calculations are stable over time as well, providing reproducible results for at least 28 days postirradiation, and for blood specimens collected and stored at room temperature for at least 72 h. The CytoRADx System provides significant advancements in the field of biodosimetry that will enable accurate diagnoses across diverse populations in large-scale emergency scenarios. In addition, our technological enhancements to the well-established CBMN assay provide a pathway for future diagnostic applications, such as toxicology and oncology.

scholarly journals Development and Optimization of A High-Throughput 3D Rat Purkinje Neuron Culture to Study Paraneoplastic Cerebellar Degeneration

2022 ◽  
Author(s):  
Ida Margrethe Uggerud ◽  
Torbjorn Krakenes ◽  
Hirokazu Hirai ◽  
Christian Alexander Vedeler ◽  
Manja Schubert
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Ex Vivo ◽  
Purkinje Neuron ◽  
Cerebellar Degeneration ◽  
Paraneoplastic Cerebellar Degeneration ◽  
Purkinje Neurons ◽  
Branch Order ◽  
Cellular Models

Abstract Improved understanding of the mechanisms involved in neurodegenerative disease has been hampered by the lack of robust cellular models that faithfully replicate in vivo features. Here, we present a refined protocol for generating age-dependent, well-developed and synaptically active rat Purkinje neurons in a 3D cell network culture which are responsive to a disease inducer. Using our model, we found that the application of autoantibody Yo, a paraneoplastic cerebellar degeneration (PCD) inducer, alters the structure of the dendritic arbour of cultured Purkinje neurons. The numbers of dendrites per branch-order, the branch-order in itself and the dendritic length were reduced by anti-Yo, proving a functional role for anti-Yo in the pathogenesis of PCD. Our new ex-vivo model is flexible and can be used to investigate disease mechanisms that disturb Purkinje neuron function and communication in 3D. Since it is possible to use the approach in a multi-well format, this method also has high-throughput screening potential.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

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