Posters presented at the 2023 Building Biology in 3D Symposium
3D cell culture taking into account the extracellular matrix for bridging the gap between in vitro & in vivo: focus on cancer models
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Open to download resource. In oncology, 97% of drug candidate fail in clinical trials. That highlights a lake of relevance of preclinical models used upstream to select therapeutic molecules. Indeed, human in vitro models don’t take into account the microenvironment of the cancerous cells, in particular the Extracellular Matrix (ECM). However, more and more studies demonstrate that both the composition and the stiffness of the ECM are modified in tumors and are strongly linked to cancer initiation, progression, and propagation, as well as in drug resistance. BIOMIMESYS® is a hyaluronic acid-based matrix bio-functionalized with structural and adhesion molecules of the ECM, which forms a relevant microenvironment for in vitro 3-dimensional cell culture. This ECM-like hydroscaffold™ combines both the advantages of solid scaffold (porosity and structure maintenance) and of hydrogels (cell-matrix interactions). This matrix is chemically defined, translucent and provided ready-to-used in multi-well plate format (96 and 384 well plates). It can be therefore used for High Content Screening. Moreover, its composition, porosity and stiffness can be modified, in the aim to reproduce the organ-specificity of the native ECM, or to mimic a pathological microenvironment like in cancer. Cancer cells can be advantageously grown in BIOMIMESYS® for several weeks in multi-well plates and in microfluidic chips for more advanced models. We observed that modifications in the matrix composition and stiffness modify the cell behavior. Moreover, we have demonstrated that the exposition of colon cancer cells cultured in BIOMIMESYS® Oncology matrix to an anti-proliferative drug showed a closer in vitro/in vivo correlation in the EC50 curve compared to 2D culture. In addition, thanks to collaborations with academic laboratories, we demonstrated that BIOMIMESYS® allows to reproduce in vitro the behavior of cancerous cells in vivo, like mutation effects and metastasis propagation, and could be a relevant alternative to animal models. These results showed that the matricial microenvironment modifies the behavior of cancerous cells in vitro and should be considered carefully both in fundamental research and in drug discovery. BIOMIMESYS® hydroscaffold™ offers a good in vitro/in vivo correlation, and is adapted to High Content Screening; it represents a powerful tool to better select drug candidate in preclinical trials and to increase the success rate in clinical trials.
3D cell model generation and immunofluorescence phenotypic profiling for immuno-oncology drug discovery
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Open to download resource. Three-dimensional cell models have gained popularity, compared with traditional 2D models, because they better reproduce key aspects of human tissues and are amenable to a wide range of applications from basic research to pharmaceutical drug safety and efficacy testing. Immunofluorescence (IF) staining and high-content imaging of 3D cell models are important tools that allow evaluation of the expression and localization of specific proteins within cells, as well as the distribution and interaction of different cell types, in response to treatments. Image-based phenotypic profiling is a validated strategy by which data-rich biological images are mined for patterns, revealing disease-associated phenotypes. This process helps to understand disease mechanisms and to assess novel therapies more effectively. However, the transition from 2D to 3D cell models has resulted in challenges related to sample handling and assay development and requires more sophisticated protocols and instrumentation. Here we present our novel automated workflow for phenotypic profiling of 3D models using microfluidic low attachment flowchips and the new Pu·MA system EC (Environmental Control). The Pu·MA System EC can precisely control temperature, carbon dioxide levels and relative humidity in the flowchip chamber. The system enables generation of 3D cell models combined with automated 3D cell-based assays. The Pu·MA System EC workflow consists of 1) 3D cell model formation from a cell suspension with automated media exchanges, 2) incubation with compounds, 3) sample fixation and automated washes at room temperature, and 4) automated IF staining at room temperature. The samples can then be imaged and analzyed on confocal microscopes or high-content imaging systems. We used this workflow to analyze the cell marker expressions for proliferation and epithelial-mesenchymal transition (EMT) phenotype in two triple-negative breast cancer models: MCF7 spheroids and patient-derived tumoroids from aggressive tumor explant primary cells TU-BcX-4IC (4IC). 3D cell models were formed from 5000 cells per well over 2 days within the flowchip with high cell viability. Automated media exchanges were performed every 12 hours. Formed spheroids and tumoroids were fixed, washed, and stained for Ki67 (proliferation), pan-cytokeratin, E-cadherin (epithelial markers), N-cadherin, Vimentin (mesenchymal markers) and F-actin in the flowchip. Confocal images were acquired using CellVoyager CQ1 High-Content Analysis System. A 150-200 μm Z-stack of images with 5 μm Z-step was acquired in the flowchip. MCF7 spheroids showed strong signals for epithelial markers (E-Cadherin, cyto-keratins). In comparison, 4IC patient-derived tumoroids showed marked downregulation of epithelial markers but had strong Vimentin and N-cadherin expression. This suggests that these highly aggressive 4IC cells have acquired a mesenchymal phenotype. This completely automated Pu·MA System EC workflow for 3D cell model formation, assay and phenotypic profiling eliminates sample disturbance, manual handling errors and provides consistent reproducible high-quality data. This platform is a valuable tool in a wide range of research areas including disease modeling, drug discovery and personalized medicine.
3D human iPSC derived small intestinal organoids as a relevant model for infection and antiviral studies
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Open to download resource. Enteroviruses are a leading cause of upper respiratory tract, gastrointestinal and neurological infections. Management of enterovirus-related diseases has been hindered by the lack of specific antiviral treatment. The pre-clinical and clinical development of such antivirals has been challenging, calling for novel model systems and strategies to identify suitable pre-clinical candidates. Organoids represent a new and outstanding opportunity to test antiviral agents in a more physiologically relevant system. However, dedicated studies addressing the validation and direct comparison of organoids versus commonly used cell lines are lacking. Here, we described the use of human small intestinal organoids (HIOs) as a model to study antiviral treatment against human enterovirus 71 (EV-A71) infection and compare this model to EV-A71-infected RD cells. We used reference antiviral compounds such as enviroxime, rupintrivir and 2’-C-methylcytidine (2’CMC) to assess their effects on cell viability, virus-induced cytopathic effect (CPE), and viral RNA yield in EV-A71-infected HIOs and cell line. The derived HIOs consisted of intestinal epithelial cell lineages and efficiently supported EV-A71 replication, even higher than that was detected in RD cells. All compounds showed almost similar toxicity between HIOs and RD cells, except for 2’CMC showed toxicity in HIOs (CC50 = 48 ± 1 µM) but not in RD cells. The calculated EC50 for antiviral activity of enviroxime in HIOs (EC50 = 0.4 ± 0.2 μM and 1.4 ± 0.3 μM) was 10-fold lower in the RD cells (EC50 = 0.06 ± 0.001 µM and 0.2 ± 0.04 μM), as determined by CPE inhibition and RNA yield reduction, respectively. Rupintrivir showed a strong antiviral activity in both HIOs and RD cells, resulting in full protection from EV-A71-induced CPE at the lowest concentration tested of 0.15 μM and 0.035 μM, respectively. Still, by looking at virus yield data, there was a rupintrivir concentration dependent reduction in virus RNA level in HIOs (EC50 = 1.7 ± 0.4 μM), while in RD cells RNA levels were lowered to 10 ± 3 % at all tested concentrations (EC50 < 0.035 μM). 2’CMC reduced HIOs from virus-induced CPE of up to 66 ± 17 % (EC50 = 1.0 ± 0.3), while there was a complete protection from virus-induced CPE in RD cells (EC50 = 1.3 ± 0.04 μM). Furthermore, 2’CMC treatment showed a concentration-response reduction of the detected viral RNA in HIOs and RD cells. While the calculated EC50 values of 2’CMC in HIOs and RD cells were comparable, the antiviral showed poorer selectivity index in the HIO model. These results indicate a difference in the activity of the tested compounds between the two models, with HIOs being more sensitive to the infection and drug treatment. In conclusion, the outcome reveals the value added by using organoid model in virus and antiviral studies.
Assessing efficacy therapies in human colorectal cancer organoids using a standardized screening workflow
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Open to download resource. Precision medicine for cancer patients promises the tailoring of targeted therapies to specific genetic alterations. Currently, alterations in 43 oncogenes can be targeted based on Level 1 clinical evidence. Still, the majority of cancer patients lack efficient targeted therapy options with lasting benefits. Ex vivo assays, such as tumor tissue explants, hold the promise to directly measure the impact of anticancer compounds and their combinations. However, a significant challenge for ex vivo drug testing lies in the efficient establishment of fresh primary cell cultures for testing, within clinically actionable timeframe, and in the available tumour volume. To this end, patient-derived organoids (PDOs) have been proposed as viable and efficient alternatives for ex vivo testing. PDOs show long-term expansion potential while retaining tumor histopathology as well as cancer gene mutations. We have shown how homogenous reproducible PDOs based on Gri3D® hydrogel microwell arrays could be generated for high-throughput drug testing of single and combination therapies. Here we show on human colorectal cancer organoids the ability to perform dose-response analysis of multiple anti-cancer drugs, which can be used to guide the selection of optimal drug selection for a patient. We compare the results to those found in cell line-derived spheroids and report unique responses found only in organoids. In addition, we demonstrate how a combination of anti-cancer drugs could enhance efficacy compared to single-therapy approaches. By targeting pathways in a synergistic or additive manner, a lower therapeutic dosage of each individual drug is required, potentially also reducing toxic side effects.
Automated Analysis and Sorting of 3D cell based Models
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Open to download resource. 3D cell based models show promising potential to be a gold standard for many fields of applied life sciences. Due to the inherited complexity of the biological system, individuals may vary dramatically between different production batches and even within the same batch. Screening for specific morphological structures is inevitable to determine the suitability for further culturing or assay preparation. We developed a novel analysis and sorting technology using image recognition to assess specific morphological properties during culture and select them based on the desired profile. We optimized our technology for different biological systems and applications, ranging from fertility determination of Zebrafish eggs to determination of the differentiation state of neural hiPSC-derived cerebral organoids. In summary, we demonstrate a technology development process for quality control and sorting of 3D cell based models, according to their morphology. In the future, we aim to further adapt and test this workflow with other model systems and introduce a machine learning algorithm to fully-automate the process of decision making. Quality 3D sorting feasibility is a major interest for robust and unbiased high-throughput downstream applications such as biomanufacturing, drug testing or toxicology.
Automating high-throughput screens using patient-derived colorectal cancer organoids
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Open to download resource. Most potential oncology drugs fail at the later stages of the drug development pipeline and in clinical trials, despite having promising data for their efficacy in vitro. This high failure rate is partly due to insufficient predictive models being used to screen drug candidates in the early stages of drug discovery. As such, there is a need to develop and utilize more representative models that are amendable for efficient testing of drug efficacy to discover new therapeutic targets. 3D cell models, specifically patient-derived organoids (PDOs), offer a promising solution to this problem. Studies show that patients and their derived organoids respond similarly to drugs, suggesting the therapeutic value of using PDOs to improve therapeutic outcomes. However, challenges commonly associated with using these organoids, such as assay reproducibility, ability to scale up, and cost have limited their widespread adoption as a primary screening method in drug discovery. To address some of the hurdles associated with the use of PDOs in large scale screens, a semi-automated bioprocess has been developed for the controlled production of standardized PDOs at scale. Cultured PDOs were uniform in size, show high viability and were produced in repeatable batches in an assay-ready format. Here, we develop an end-end, automated workflow starting with assay-ready CRC organoids.
Customized inkjet-printed 3D in vitro microelectrode arrays for 3D cell models
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Open to download resource. In 2D, microelectrode array (MEA) is the standard tool to electrically stimulate and to record electrophysiological signals from electrically active in vitro cell cultures, e.g. neuronal cells, retinas or cardiomyocytes. However, 3D cell models based on e.g. organoids, spheroids or cells in hydrogel are getting more and more common as they are thought to mimic real organs better than just 2D cell models. It is obvious that the 2D MEAs have very limited capability in recording 3D cell cultures. Instead, 3D MEAs that can penetrate inside the 3D cell construct or be wrapped around it are needed. In in vivo use, 3D MEAs like e.g., so-called Utah array have a long history, but they are all too bulky to be integrated into Organ-on-Chips or any other in vitro 3D cell model platforms. Surprising but true, still in 2023 there are no real 3D in vitro MEAs commercially available. However, various mainly academic 3D in vitro MEA demonstrations with many different approaches exist in the literature. Just like some other research groups, we have chosen 3D pillar electrodes as our 3D in vitro MEA approach and inkjet printing as the method to fabricate the electrodes. The benefit of the inkjet printing is that it allows easy and fast customization of pillar heights and other array design and thus easy customization of the 3D MEAs for different 3D cell models. The major challenge, on the other hand, is the biocompatibility concern related to the ink materials, including both the main component, the solvents and possible additives. Because of that, the biocompatibility is typically secured by coating the pillars either with a conductive coating like electroplated gold or some insulator material. In the latter case the tip of the pillar must be opened to enable the electrophysiological recordings. In collaboration with the Technical University of Munich, we are developing the printing process and studying novel thin film coatings for 3D pillar electrodes at Tampere University (TAU). The aim of the coatings is not only to secure the biocompatibility but also to improve the long-term stability of the pillar electrodes. Preliminary coating trials and cytotoxicity tests with neuronal cells have already been done in 2D. We will perform cell trials with our 3D pillar electrodes in collaboration with cell research groups at TAU, but we are also constantly looking for new partners to co-operate in developing and, especially, to use our 3D in vitro MEA technology.
3D cell culture taking into account the extracellular matrix for phenotypic screening in the frame of Parkinson’s disease
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Open to download resource. Aim: About 90% of drug candidates fail in clinical trials, for efficacy- and toxicity-related reasons, which often involve the Central Nervous System (CNS). This high failure rate highlights a lack of relevance of experimental models used upstream, including human in vitro models. Indeed, they do not take into account the complexity of the CNS, in which neurons are organized in 3 dimensions (3D) and interact with their microenvironment, composed of other cell types like glial cells, and the extracellular matrix (ECM). The objectives of this work were i) to study the influence of the microenvironment on neuronal cells in cerebral in vitro models by automatized cellular imaging, and ii) to develop more relevant cerebral in vitro models for phenotypic screening, to assess neurotoxic or therapeutic effects, in the frame of Parkinson’s Disease (PD). Methods: In this purpose, we developed BIOMIMESYS®, a hyaluronic acid-based matrix bio-functionalized with structural and adhesion molecules of the ECM, which forms a physiological microenvironment for in vitro 3 dimensional cell culture. This ECM-like hydroscaffold™ combines both the advantages of solid scaffold (porosity and structure maintain) and of hydrogels (cell-matrix interactions). Its composition, porosity and stiffness can be modified, in the aim to reproduce the organ-specificity of the native ECM, including the brain. This matrix is chemically defined, translucent and provided ready-to-used in 96 well plate format. It can be therefore used for High Content Screening. First, the sensitivity of Luhmes cells, a dopaminergic neuronal cell line, to PD inducers has been studied in this model. Then, we performed a co-culture of Luhmes cells and primary human astrocytes in this matrix, to form a complex model including both the glial and the matricial microenvironments. All the results were acquired by automated confocal fluorescent microscopy and quantitative image analysis. Results: In the hydroscaffold, the neuronal cells were organized in clusters and exhibited neurites. They displayed a lower sensitivity in 3D compared to cells cultured in 2 dimensions (2D). This difference was explained by two phenomena: a partial retention of toxic molecules in the matrix, and a difference in neuronal protein expression compared to cells cultured in 2D. In the co-culture, we observed spheroids containing both neurons and astrocytes. The analysis of matrix component expression in the co-culture, in healthy and pathological conditions, is ongoing. Conclusions: This work highlighted that the microenvironment of neurons can modify the neuronal response in vitro, and should thus be considered carefully in academic research and as early as possible in the drug discovery industrial process.
High content image analysis of human cortical adherent organoids: 3D MICro-brains
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Open to download resource. Scalable high-throughput screening approaches for human brain organoids remain a challenge for disease modeling and drug discovery. Using induced pluripotent stem cells (iPSC), we have established a robust 3D miniaturized format of the cerebral cortex neurodevelopmental architecture. These 3D MICro-brains demonstrate layered radial organization in functional neuronal networks containing all major brain cell types: neurons, astrocytes, myelin-producing oligodendrocytes and microglia. One of the major objectives of our consortium is to further establish 3D MICro-brains as a standardized model that is amenable to high content (HC) screening to assess disease phenotypes and therapeutic agents on human neurodevelopment. Adherent cortical organoids were fixed and stained with various markers and HC image acquisition was performed in z-stacks. Images were subsequently analyzed using two different methods. Maximum intensity projection was performed on z-stacks and the resulting images were segmented to extract whole organoid and cellular marker measures. Moreover, z-stack images were segmented in a 3D way based on whole organoids and the same cellular markers. We compared the results from 2D and 3D methods to determine the added value of volumetric segmentation. We extracted over 100+ multi-parametric features from cellular markers and organoids, including volume and topography, spatial orientation, intensity and co-localization scores. Image quantification data was subsequently analyzed using a defined and reproducible data analytics workflow. The numerical dataset was automatically scanned for feature redundancy based on: binary vs. continuous data type, variation, amount of missing values and Spearman's rho correlation coefficient. Heavily skewed variables were detected and transformed. All data were scaled using a robust Z-score to account for feature-to-feature variation. Due to the large number of features, principal component analysis was performed to reduce complexity. This revealed that 3D-related features had a high contribution in variance within our dataset, which indicates the advantage of performing volumetric image analysis in HC screening. Preliminary observations indicate differences in whole organoid structure when comparing two different microglia seeding time points. Hence, we aim to quantify the effects of sequential seeding of microglia on structure formation, cell proliferation and differentiation by using our volumetric analysis pipeline. Our results demonstrate the feasibility and reproducibility of using 3D MICro-brain platform for high throughput screening to support the discovery of therapeutics for a wide array of neurological diseases, with the goal of making a practical workflow to deploy a modern drug discovery environment using animal-free in vitro scalable models for screening.
Implementation of the MANTIS® Automated Liquid Dispenser for Efficient, Scalable Organoid Culture and High-Throughput Quality Control Assessment
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Open to download resource. Organoids are three-dimensional in vitro models that mimic the physiological conditions of a specific organ, providing valuable insights into tissue biology and disease. Creation of diverse organoid biobanks is crucial for advancing research in disease modelling, drug screening, personalized medicine, and regenerative therapies. In Cellular Operations at the Wellcome Trust Sanger Institute, researchers are constructing biobanks and developing customized downstream application assays utilizing organoid disease models to investigate a diverse range of human pathologies, including endometriosis, inflammatory bowel disease, and multiple types of human malignancies. Establishment of large biobanks necessitates dependable organoid culture and analysis methodology, with incorporated quality control assays to assess the fundamental attributes of the disease model generated. Evaluation and refinement of such assays have typically been constrained in throughput and dependent on qualitative assessments. Consequently, there is need for a solution that is reproducible, quantifiable, and amenable to high-throughput processing. Here we demonstrate use of the automated liquid dispenser MANTIS® (Formulatrix) for bench-scale automation of organoid culture. Utilizing cancer and intestinal organoid models, we validated the application of the MANTIS® in dispensing extracellular matrix droplets across a variety of plate formats, significantly improving the efficiency and scalability of organoid culture for large biobank generation. Further, the miniaturization capabilities provided by the MANTIS® were effectively demonstrated for quality control evaluation purposes by plating organoids for high-throughput growth kinetic and morphology quantification assays on the IncuCyte SX5 (Sartorius) live-cell imaging system. MANTIS® considerably shortened plating times with improved accuracy and precision over manual plating, resulting in high intra- and inter-assay reproducibility.
Morphometric analysis of 3D cellular models in the context of Rab GTPases
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Open to download resource. In mammalian cells, membrane trafficking is responsible for the transport of proteins, lipids, and various other macromolecules between membrane compartments. The Rab family of small GTPases are considered as the main coordinators of this process as they govern the direction and specificity of membrane trafficking. With over 60 members identified in humans, many of the Rabs have been implicated in disease progression, including cancer. Most experimental approaches so far have studied Rabs in cells grown as two-dimensional monolayers. However, these models do not mimic the complexity of in vivo conditions as do three-dimensional (3D) cell culture models. 3D cell culture models, such as spheroids, are aggregates of cells that are increasingly being used in preclinical studies for drug development and disease studies, and offer a new system for the study of biological networks. Here, we used High Content Analysis (HCA) to study Rab GTPases in a 3D context. We performed a comprehensive RNA interference-mediated depletion of Rab GTPases in HeLa Kyoto cell spheroids and observed the morphological changes to the spheroids. We quantified these changes at two levels; whole spheroid level and cellular level. We developed a fully automated HCA pipeline for segmentation and morphometric analysis on the images generated using automated confocal microscopy. The HCA pipeline addresses a number of important challenges in 3D image segmentation, including high noise to signal ratios and over-segmentation. The analysis of morphological properties at whole spheroid level showed significant changes in the size and compactness of spheroids after the knock-down of various Rab proteins. At the cellular level, changes in cellular morphology and altered radial distances from the centroid of the spheroid were also observed. In conclusion, the morphometric analysis revealed the importance of Rab proteins in cell growth, maintenance, and cell-cell interactions. The HCA pipeline that we have developed shows promising results, and can be further modified for detecting and quantifying wider cellular as well as subcellular structures.