Organoids in image-based phenotypic chemical screens

Basic models to advanced systems: harnessing the power of organoids-based microphysiological models of the human brain

Understanding the complexities of the human brain's function in health and disease is a formidable challenge in neuroscience. While traditional models like animals offer valuable insights, they often fall short in accurately mirroring human biology and drug responses. Moreover, recent legislation has underscored the need for more predictive models that more accurately represent human physiology. To address this requirement, human-derived cell cultures have emerged as a crucial alternative for biomedical research. However, traditional static cell culture models lack the dynamic tissue microenvironment that governs human tissue function. Advancedin vitrosystems, such as organoids and microphysiological systems (MPSs), bridge this gap by offering more accurate representations of human biology. Organoids, which are three-dimensional miniaturized organ-like structures derived from stem cells, exhibit physiological responses akin to native tissues, but lack essential tissue-specific components such as functional vascular structures and immune cells. Recent endeavors have focused on incorporating endothelial cells and immune cells into organoids to enhance vascularization, maturation, and disease modeling. MPS, including organ-on-chip technologies, integrate diverse cell types and vascularization under dynamic culture conditions, revolutionizing brain research by bridging the gap betweenin vitroandin vivomodels. In this review, we delve into the evolution of MPS, with a particular focus on highlighting the significance of vascularization in enhancing the viability, functionality, and disease modeling potential of organoids. By examining the interplay of vasculature and neuronal cells within organoids, we can uncover novel therapeutic targets and gain valuable insights into disease mechanisms, offering the promise of significant advancements in neuroscience and improved patient outcomes.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Morphological profiling for drug discovery in the era of deep learning

Morphological profiling is a valuable tool in phenotypic drug discovery. The advent of high-throughput automated imaging has enabled the capturing of a wide range of morphological features of cells or organisms in response to perturbations at the single-cell resolution. Concurrently, significant advances in machine learning and deep learning, especially in computer vision, have led to substantial improvements in analyzing large-scale high-content images at high throughput. These efforts have facilitated understanding of compound mechanism of action, drug repurposing, characterization of cell morphodynamics under perturbation, and ultimately contributing to the development of novel therapeutics. In this review, we provide a comprehensive overview of the recent advances in the field of morphological profiling. We summarize the image profiling analysis workflow, survey a broad spectrum of analysis strategies encompassing feature engineering- and deep learning-based approaches, and introduce publicly available benchmark datasets. We place a particular emphasis on the application of deep learning in this pipeline, covering cell segmentation, image representation learning, and multimodal learning. Additionally, we illuminate the application of morphological profiling in phenotypic drug discovery and highlight potential challenges and opportunities in this field.

A Decade in a Systematic Review: The Evolution and Impact of Cell Painting

High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction. Moreover, machine learning methods recently surpassed classical approaches in their ability to extract biologically useful information from Cell Painting images. Cell Painting data have been used alone or in combination with other -omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Overall, key methodological advances have expanded Cell Painting's ability to capture cellular responses to various perturbations. Future advances will likely lie in advancing computational and experimental techniques, developing new publicly available datasets, and integrating them with other high-content data types.

The application of brain organoid for drug discovery in mitochondrial diseases

Mitochondrial diseases are difficult to treat due to the complexity and multifaceted nature of mitochondrial dysfunction. Brain organoids are three-dimensional (3D) structures derived from human pluripotent stem cells designed to mimic brain-like development and function. Brain organoids have received a lot of attention in recent years as powerful tools for modeling human diseases, brain development, and drug screening. Screening compounds for mitochondrial diseases using brain organoids could provide a more physiologically relevant platform for drug discovery. Brain organoids offer the possibility of personalized medicine because they can be derived from patient-specific cells, allowing testing of drugs tailored to specific genetic mutations. In this article, we highlight how brain organoids offer a promising avenue for screening compounds for mitochondrial diseases and address the challenges and limitations associated with their use. We hope this review will provide new insights into the further progress of brain organoids for mitochondrial screening studies.

Selecting Monoclonal Cell Lineages from Somatic Reprogramming Using Robotic-Based Spatial-Restricting Structured Flow

Somatic cell reprogramming generates induced pluripotent stem cells (iPSCs), which serve as a crucial source of seed cells for personalized disease modeling and treatment in regenerative medicine. However, the process of reprogramming often causes substantial lineage manipulations, thereby increasing cellular heterogeneity. As a consequence, the process of harvesting monoclonal iPSCs is labor-intensive and leads to decreased reproducibility. Here, we report the first in-house developed robotic platform that uses a pin-tip-based micro-structure to manipulate radial shear flow for automated monoclonal iPSC colony selection (~1 s) in a non-invasive and label-free manner, which includes tasks for somatic cell reprogramming culturing, medium changes; time-lapse-based high-content imaging; and iPSCs monoclonal colony detection, selection, and expansion. Throughput-wise, this automated robotic system can perform approximately 24 somatic cell reprogramming tasks within 50 days in parallel via a scheduling program. Moreover, thanks to a dual flow-based iPSC selection process, the purity of iPSCs was enhanced, while simultaneously eliminating the need for single-cell subcloning. These iPSCs generated via the dual processing robotic approach demonstrated a purity 3.7 times greater than that of the conventional manual methods. In addition, the automatically produced human iPSCs exhibited typical pluripotent transcriptional profiles, differentiation potential, and karyotypes. In conclusion, this robotic method could offer a promising solution for the automated isolation or purification of lineage-specific cells derived from iPSCs, thereby accelerating the development of personalized medicines.

Multimodal spatiotemporal monitoring of basal stem cell-derived organoids reveals progression of olfactory dysfunction in Alzheimer's disease

Olfactory dysfunction (OD) is a highly prevalent symptom and an early sign of neurodegenerative diseases in humans. However, the roles of peripheral olfactory system in disease progression and the mechanisms behind neurodegeneration remain to be studied. Olfactory epithelium (OE) organoid is an ideal model to study pathophysiology in vitro, yet the reliance on 3D culture condition limits continual in situ monitoring of organoid development. Here, we combined impedance biosensors and live imaging for real-time spatiotemporal analysis of OE organoids morphological and physiological features during Alzheimer's disease (AD) progression. The impedance measurements showed that organoids generated from basal stem cells of APP/PS1 transgenic mice had lower proliferation rate than that from wild-type mice. In concert with the biosensor measurements, live imaging enabled to visualize the spatial and temporal dynamics of organoid morphology. Abnormal protein aggregation and accumulation, including amyloid plaques and neurofibrillary tangles, was found in AD organoids and increased as disease progressed. This multimodal in situ bioelectrical measurement and imaging provide a new platform for investigating onset mechanisms of OD, which would shed new light on early diagnosis and treatment of neurodegenerative disease.

MAGIC matrices: freeform bioprinting materials to support complex and reproducible organoid morphogenesis

Organoids are powerful models of tissue physiology, yet their applications remain limited due to a lack of complex tissue morphology and high organoid-to-organoid structural variability. To address these limitations we developed a soft, composite yield-stress extracellular matrix that supports freeform 3D bioprinting of cell slurries at tissue-like densities. Combined with a custom piezoelectric printhead, this platform allows more reproducible and complex morphogenesis from uniform and spatially organized organoid "seeds." At 4 °C the material exhibits reversible yield-stress behavior to support long printing times without compromising cell viability. When transferred to cell culture at 37 °C, the material cross-links and exhibits similar viscoelasticity and plasticity to basement membrane extracts such as Matrigel. We use this setup for high-throughput generation of intestinal and salivary gland organoid arrays that are morphologically indistinguishable from those grown in pure Matrigel, but exhibit dramatically improved homogeneity in organoid size, shape, maturation time, and budding efficiency. The reproducibility of organoid structure afforded by this approach increases the sensitivity of assays by orders of magnitude, requiring less input material and reducing analysis times. The flexibility of this approach additionally enabled the fabrication of perfusable intestinal organoid tubes. Combined, these advances lay the foundation for the efficient design of complex tissue morphologies in both space and time.

Inner Ear Organoids: Strengths and Limitations

Inner ear organoids derived from differentiation of human pluripotent stem cells have recently gained momentum as tools to study inner ear development and developmental defects. An additional exciting aspect about this technology is represented by its translational potential, specifically, the use of organoids to validate therapeutics for hearing and balance restoration on human/patient-specific cells. This latter aspect will be briefly discussed here including opportunities and current limitations.

AI-enabled organoids: Construction, analysis, and application

Organoids, miniature and simplified in vitro model systems that mimic the structure and function of organs, have attracted considerable interest due to their promising applications in disease modeling, drug screening, personalized medicine, and tissue engineering. Despite the substantial success in cultivating physiologically relevant organoids, challenges remain concerning the complexities of their assembly and the difficulties associated with data analysis. The advent of AI-Enabled Organoids, which interfaces with artificial intelligence (AI), holds the potential to revolutionize the field by offering novel insights and methodologies that can expedite the development and clinical application of organoids. This review succinctly delineates the fundamental concepts and mechanisms underlying AI-Enabled Organoids, summarizing the prospective applications on rapid screening of construction strategies, cost-effective extraction of multiscale image features, streamlined analysis of multi-omics data, and precise preclinical evaluation and application. We also explore the challenges and limitations of interfacing organoids with AI, and discuss the future direction of the field. Taken together, the AI-Enabled Organoids hold significant promise for advancing our understanding of organ development and disease progression, ultimately laying the groundwork for clinical application.

Automated, High-Throughput Phenotypic Screening and Analysis Platform to Study Pre- and Post-Implantation Morphogenesis in Stem Cell-Derived Embryo-Like Structures

Combining high-throughput generation and high-content imaging of embryo models will enable large-scale screening assays in the fields of (embryo) toxicity, drug development, embryogenesis, and reproductive medicine. This study shows the continuous culture and in situ (i.e., in microwell) imaging-based readout of a 3D stem cell-based model of peri-implantation epiblast (Epi)/extraembryonic endoderm (XEn) development with an expanded pro-amniotic cavity (PAC) (E3.5 E5.5), namely XEn/EPiCs. Automated image analysis and supervised machine learning permit the identification of embryonic morphogenesis, tissue compartmentalization, cell differentiation, and consecutive classification. Screens with signaling pathway modulators at different time windows provide spatiotemporal information on their phenotypic effect on developmental processes leading to the formation of XEn/EPiCs. Exposure of the biological model in the microwell platform to pathway modulators at two time windows, namely 0-72 h and 48-120 h, show that Wnt and Fgf/MAPK pathway modulators affect Epi differentiation and its polarization, while modulation of BMP and Tgfβ/Nodal pathway affects XEn specification and epithelialization. Further, their collective role is identified in the timing of the formation and expansion of PAC. The newly developed, scalable culture and analysis platform, thereby, provides a unique opportunity to quantitatively and systematically study effects of pathway modulators on early embryonic development.

Organoid assessment technologies

Despite enormous advances in the generation of organoids, robust and stable protocols of organoids are still a major challenge to researchers. Research for assessing structures of organoids and the evaluations of their functions on in vitro or in vivo is often limited by precision strategies. A growing interest in assessing organoids has arisen, aimed at standardizing the process of obtaining organoids to accurately resemble human-derived tissue. The complex microenvironment of organoids, intricate cellular crosstalk, organ-specific architectures and further complicate functions urgently quest for high-through schemes. By utilizing multi-omics analysis and single-cell analysis, cell-cell interaction mechanisms can be deciphered, and their structures can be investigated in a detailed view by histological analysis. In this review, we will conclude the novel approaches to study the molecular mechanism and cell heterogeneity of organoids and discuss the histological and morphological similarity of organoids in comparison to the human body. Future perspectives on functional analysis will be developed and the organoids will become mature models.

Modular 3D printed platform for fluidically connected human brain organoid culture

Brain organoid technology has transformed both basic and applied biomedical research and paved the way for novel insights into developmental processes and disease states of the human brain. While the use of brain organoids has been rapidly growing in the past decade, the accompanying bioengineering and biofabrication solutions have remained scarce. As a result, most brain organoid protocols still rely on commercially available tools and culturing platforms that had previously been established for different purposes, thus entailing suboptimal culturing conditions and excessive use of plasticware. To address these issues, we developed a 3D printing pipeline for the fabrication of tailor-made culturing platforms for fluidically connected but spatially separated brain organoid array culture. This all-in-one platform allows all culturing steps-from cellular aggregation, spheroid growth, hydrogel embedding, and organoid maturation-to be performed in a single well plate without the need for organoid manipulation or transfer. Importantly, the approach relies on accessible materials and widely available 3D printing equipment. Furthermore, the developed design principles are modular and highly customizable. As such, we believe that the presented technology can be easily adapted by other research groups and fuel further development of culturing tools and platforms for brain organoids and other 3D cellular systems.

Multiplexed live-cell imaging for drug responses in patient-derived organoid models of cancer

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to simultaneously quantitate cell health and apoptosis. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level

In this perspective we discuss how tumor heterogeneity and therapy resistance necessitate a focus on more personalized approaches, prompting a shift toward precision medicine. At the heart of the shift towards personalized medicine, omics-driven systems biology becomes a driving force as it leverages high-throughput technologies and novel bioinformatics tools. These enable the creation of systems-based maps, providing a comprehensive view of individual tumor's functional plasticity. We highlight the innovative PHENOSTAMP program, which leverages high-dimensional data to construct a visually intuitive and user-friendly map. This map was created to encapsulate complex transitional states in cancer cells, such as Epithelial-Mesenchymal Transition (EMT) and Mesenchymal-Epithelial Transition (MET), offering a visually intuitive way to understand disease progression and therapeutic responses at single-cell resolution in relation to EMT-related single-cell phenotypes. Most importantly, PHENOSTAMP functions as a reference map, which allows researchers and clinicians to assess one clinical specimen at a time in relation to their phenotypic heterogeneity, setting the foundation on constructing phenotypic maps for personalized medicine. This perspective argues that such dynamic predictive maps could also catalyze the development of personalized cancer treatment. They hold the potential to transform our understanding of cancer biology, providing a foundation for a future where therapy is tailored to each patient's unique molecular and cellular tumor profile. As our knowledge of cancer expands, these maps can be continually refined, ensuring they remain a valuable tool in precision oncology.

High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery

Measuring single cell responses to the universe of chemicals (drugs, natural products, environmental toxicants etc.) is of paramount importance to human health as phenotypic variability in sensing stimuli is a hallmark of biology that is considered during high throughput screening. One of the ways to approach this problem is via high throughput, microscopy-based assays coupled with multi-dimensional single cell analysis methods. Here, we will summarize some of the efforts in this vast and growing field, focusing on phenotypic screens (e.g., Cell Painting), single cell analytics and quality control, with particular attention to environmental toxicology and drug screening. We will discuss advantages and limitations of high throughput assays with various end points and levels of complexity.

Spectroscopic techniques for monitoring stem cell and organoid proliferation in 3D environments for therapeutic development

Spectroscopic techniques for monitoring stem cell and organoid proliferation have gained significant attention in therapeutic development. Spectroscopic techniques such as fluorescence, Raman spectroscopy, and infrared spectroscopy offer noninvasive and real-time monitoring of biochemical and biophysical changes that occur during stem cell and organoid proliferation. These techniques provide valuable insight into the underlying mechanisms of action of potential therapeutic agents, allowing for improved drug discovery and screening. This review highlights the importance of spectroscopic monitoring of stem cell and organoid proliferation and its potential impact on therapeutic development. Furthermore, this review discusses recent advances in spectroscopic techniques and their applications in stem cell and organoid research. Overall, this review emphasizes the importance of spectroscopic techniques as valuable tools for studying stem cell and organoid proliferation and their potential to revolutionize therapeutic development in the future.

Evolution and impact of high content imaging

The field of high content imaging has steadily evolved and expanded substantially across many industry and academic research institutions since it was first described in the early 1990's. High content imaging refers to the automated acquisition and analysis of microscopic images from a variety of biological sample types. Integration of high content imaging microscopes with multiwell plate handling robotics enables high content imaging to be performed at scale and support medium- to high-throughput screening of pharmacological, genetic and diverse environmental perturbations upon complex biological systems ranging from 2D cell cultures to 3D tissue organoids to small model organisms. In this perspective article the authors provide a collective view on the following key discussion points relevant to the evolution of high content imaging: • Evolution and impact of high content imaging: An academic perspective • Evolution and impact of high content imaging: An industry perspective • Evolution of high content image analysis • Evolution of high content data analysis pipelines towards multiparametric and phenotypic profiling applications • The role of data integration and multiomics • The role and evolution of image data repositories and sharing standards • Future perspective of high content imaging hardware and software.

Recent Advances in High-Content Imaging and Analysis in iPSC-Based Modelling of Neurodegenerative Diseases

In the field of neurodegenerative pathologies, the platforms for disease modelling based on patient-derived induced pluripotent stem cells (iPSCs) represent a valuable molecular diagnostic/prognostic tool. Indeed, they paved the way for the in vitro recapitulation of the pathological mechanisms underlying neurodegeneration and for characterizing the molecular heterogeneity of disease manifestations, also enabling drug screening approaches for new therapeutic candidates. A major challenge is related to the choice and optimization of the morpho-functional study designs in human iPSC-derived neurons to deeply detail the cell phenotypes as markers of neurodegeneration. In recent years, the specific combination of high-throughput screening with subcellular resolution microscopy for cell-based high-content imaging (HCI) screening allowed in-depth analyses of cell morphology and neurite trafficking in iPSC-derived neuronal cells by using specific cutting-edge microscopes and automated computational assays. The present work aims to describe the main recent protocols and advances achieved with the HCI analysis in iPSC-based modelling of neurodegenerative diseases, highlighting technical and bioinformatics tips and tricks for further uses and research. To this end, microscopy requirements and the latest computational pipelines to analyze imaging data will be explored, while also providing an overview of the available open-source high-throughput automated platforms.

A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids

Organoids are powerful experimental models for studying the ontogeny and progression of various diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, bulk-cultured organoids physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix properties make it difficult to assess whether observed phenotypic heterogeneity between organoids results from intrinsic cell differences or differences in the microenvironment. Here, we developed a microwell-based method that enables high-throughput quantification of image-based parameters for organoids grown from single cells, which can further be retrieved from their microwells for molecular profiling. Coupled with a deep learning image-processing pipeline, we characterized phenotypic traits including growth rates, cellular movement, and apical-basal polarity in two CRISPR-engineered human gastric organoid models, identifying genomic changes associated with increased growth rate and changes in accessibility and expression correlated with apical-basal polarity. A record of this paper's transparent peer review process is included in the supplemental information.

Flourishing tumor organoids: History, emerging technology, and application

Malignant tumors are one of the leading causes of death which impose an increasingly heavy burden on all countries. Therefore, the establishment of research models that closely resemble original tumor characteristics is crucial to further understanding the mechanisms of malignant tumor development, developing safer and more effective drugs, and formulating personalized treatment plans. Recently, organoids have been widely used in tumor research owing to their advantages including preserving the structure, heterogeneity, and cellular functions of the original tumor, together with the ease of manipulation. This review describes the history and characteristics of tumor organoids and the synergistic combination of three-dimensional (3D) culture approaches for tumor organoids with emerging technologies, including tissue-engineered cell scaffolds, microfluidic devices, 3D bioprinting, rotating wall vessels, and clustered regularly interspaced short palindromic repeats-CRISPR-associated protein 9 (CRISPR-Cas9). Additionally, the progress in research and the applications in basic and clinical research of tumor organoid models are summarized. This includes studies of the mechanism of tumor development, drug development and screening, precision medicine, immunotherapy, and simulation of the tumor microenvironment. Finally, the existing shortcomings of tumor organoids and possible future directions are discussed.

A Strainer-Based Platform for the Collection and Immunolabeling of Mouse Intestinal Organoids

Intestinal organoids have emerged as powerful model systems for studying the complex structure and function of the intestine. However, there is a lack of widely applicable methods for the collection, labeling, and imaging of intestinal organoids. In this study, we developed a novel method for loading and labeling intestinal organoids, a method that efficiently collects the organoids and facilitates imaging of their three-dimensional (3D) structure. Based on this strainer platform, mouse intestinal organoids were adequately collected and immobilized, facilitating the immunolabeling workflow to target proteins of the organoids. After evaluation, the strainer size of 40 μm was considered to be more conducive to the collection and labeling of mouse intestinal organoids. More extensive research on organoids of multiple types and species origins will contribute to broadening the applicability of the methodology. Overall, our study proposes an innovative workflow for loading and analyzing intestinal organoids. The combination of a strainer-based collection method, fluorescent labeling, and 3D reconstruction provides valuable insights into the organization and complexity of these tissue models, thereby offering new avenues for investigating intestinal development, disease modeling, and drug discovery.

Single-cell sequencing of individual retinal organoids reveals determinants of cell-fate heterogeneity

With a critical need for more complete in vitro models of human development and disease, organoids hold immense potential. Their complex cellular composition makes single-cell sequencing of great utility; however, the limitation of current technologies to a handful of treatment conditions restricts their use in screens or studies of organoid heterogeneity. Here, we apply sci-Plex, a single-cell combinatorial indexing (sci)-based RNA sequencing (RNA-seq) multiplexing method to retinal organoids. We demonstrate that sci-Plex and 10× methods produce highly concordant cell-class compositions and then expand sci-Plex to analyze the cell-class composition of 410 organoids upon modulation of critical developmental pathways. Leveraging individual organoid data, we develop a method to measure organoid heterogeneity, and we identify that activation of Wnt signaling early in retinal organoid cultures increases retinal cell classes up to 6 weeks later. Our data show sci-Plex's potential to dramatically scale up the analysis of treatment conditions on relevant human models.

Patient-Derived Ex Vivo Cultures and Endpoint Assays with Surrogate Biomarkers in Functional Testing for Prediction of Therapeutic Response

Prediction of therapeutic outcomes is important for cancer patients in order to reduce side effects and improve the efficacy of anti-cancer drugs. Currently, the most widely accepted method for predicting the efficacy of anti-cancer drugs is gene panel testing based on next-generation sequencing. However, gene panel testing has several limitations. For example, only 10% of cancer patients are estimated to have druggable mutations, even if whole-exome sequencing is applied. Additionally, even if optimal drugs are selected, a significant proportion of patients derive no benefit from the indicated drug treatment. Furthermore, most of the anti-cancer drugs selected by gene panel testing are molecularly targeted drugs, and the efficacies of cytotoxic drugs remain difficult to predict. Apart from gene panel testing, attempts to predict chemotherapeutic efficacy using ex vivo cultures from cancer patients have been increasing. Several groups have retrospectively demonstrated correlations between ex vivo drug sensitivity and clinical outcome. For ex vivo culture, surgically resected tumor tissue is the most abundant source. However, patients with recurrent or metastatic tumors do not usually undergo surgery, and chemotherapy may be the only option for those with inoperable tumors. Therefore, predictive methods using small amounts of cancer tissue from diagnostic materials such as endoscopic, fine-needle aspirates, needle cores and liquid biopsies are needed. To achieve this, various types of ex vivo culture and endpoint assays using effective surrogate biomarkers of drug sensitivity have recently been developed. Here, we review the variety of ex vivo cultures and endpoint assays currently available.

Balance between the cell viability and death in 3D

Cell death is a phenomenon, frequently perceived as an absolute event for cell, tissue and the organ. However, the rising popularity and complexity of such 3D multicellular 'tissue building blocks' as heterocellular spheroids, organoids, and 'assembloids' prompts to revise the definition and quantification of cell viability and death. It raises several questions on the overall viability of all the cells within 3D volume and on choosing the appropriate, continuous, and non-destructive viability assay enabling for a single-cell analysis. In this review, we look at cell viability and cell death modalities with attention to the intrinsic features of such 3D models as spheroids, organoids, and bioprints. Furthermore, we look at emerging and promising methodologies, which can help define and understand the balance between cell viability and death in dynamic and complex 3D environments. We conclude that the recent innovations in biofabrication, biosensor probe development, and fluorescence microscopy can help answer these questions.

Label-free imaging of 3D pluripotent stem cell differentiation dynamics on chip

Massive, parallelized 3D stem cell cultures for engineering in vitro human cell types require imaging methods with high time and spatial resolution to fully exploit technological advances in cell culture technologies. Here, we introduce a large-scale integrated microfluidic chip platform for automated 3D stem cell differentiation. To fully enable dynamic high-content imaging on the chip platform, we developed a label-free deep learning method called Bright2Nuc to predict in silico nuclear staining in 3D from confocal microscopy bright-field images. Bright2Nuc was trained and applied to hundreds of 3D human induced pluripotent stem cell cultures differentiating toward definitive endoderm on a microfluidic platform. Combined with existing image analysis tools, Bright2Nuc segmented individual nuclei from bright-field images, quantified their morphological properties, predicted stem cell differentiation state, and tracked the cells over time. Our methods are available in an open-source pipeline, enabling researchers to upscale image acquisition and phenotyping of 3D cell culture.

Single-cell sequencing of individual retinal organoids reveals determinants of cell fate heterogeneity

With a critical need for more complete in vitro models of human development and disease, organoids hold immense potential. Their complex cellular composition makes single-cell sequencing of great utility; however, the limitation of current technologies to a handful of treatment conditions restricts their use in screens or studies of organoid heterogeneity. Here, we apply sci-Plex, a single-cell combinatorial indexing (sci)-based RNA-seq multiplexing method to retinal organoids. We demonstrate that sci-Plex and 10x methods produce highly concordant cell class compositions and then expand sci-Plex to analyze the cell class composition of 410 organoids upon modulation of critical developmental pathways. Leveraging individual organoid data, we develop a method to measure organoid heterogeneity, and we identify that activation of Wnt signaling early in retinal organoid cultures increases retinal cell classes up to six weeks later. Our data show sci-Plex's potential to dramatically scale-up the analysis of treatment conditions on relevant human models.

Light-field tomographic fluorescence lifetime imaging microscopy

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging technique that enables the visualization of biological samples at the molecular level by measuring the fluorescence decay rate of fluorescent probes. This provides critical information about molecular interactions, environmental changes, and localization within biological systems. However, creating high-resolution lifetime maps using conventional FLIM systems can be challenging, as it often requires extensive scanning that can significantly lengthen acquisition times. This issue is further compounded in three-dimensional (3D) imaging because it demands additional scanning along the depth axis. To tackle this challenge, we developed a novel computational imaging technique called light field tomographic FLIM (LIFT-FLIM). Our approach allows for the acquisition of volumetric fluorescence lifetime images in a highly data-efficient manner, significantly reducing the number of scanning steps required compared to conventional point-scanning or line-scanning FLIM imagers. Moreover, LIFT-FLIM enables the measurement of high-dimensional data using low-dimensional detectors, which are typically low-cost and feature a higher temporal bandwidth. We demonstrated LIFT-FLIM using a linear single-photon avalanche diode array on various biological systems, showcasing unparalleled single-photon detection sensitivity. Additionally, we expanded the functionality of our method to spectral FLIM and demonstrated its application in high-content multiplexed imaging of lung organoids. LIFT-FLIM has the potential to open up new avenues in both basic and translational biomedical research.

Human epidermis organotypic cultures, a reproducible system recapitulating the epidermis in vitro

The translatability of research is highly dependent on models that recapitulate human tissues and organs. Here, we describe a procedure for the generation of human epidermis organotypic cultures (HEOCs) from primary keratinocytes isolated from foreskin and adult skin as well as from an immortalized keratinocyte cell line (KerTr). We tested several media conditions to develop a defined HEOC growing and expansion media. We characterized the HEOCs and show that in optimal culture conditions they express the proliferation marker Ki67, the basement membrane protein collagen 17 (col17) and the epidermal differentiation markers keratin 15 (K15), keratin 14 (K14), keratin 5 (K5), keratin 10 (K10), keratin 1 (K1), transglutaminase 1 (TGM1), transglutaminase 3 (TGM3) and filaggrin (FLG). Thus, they recapitulate the human epidermis and are stratified from the basal layer to the stratum corneum. These HEOC can be generated reproducibly on a large scale, making it an invaluable model for screening therapeutic compounds and also for the study of pathologies affecting the epidermis.

Morphological alterations in C57BL/6 mouse intestinal organoids as a tool for predicting chemical-induced toxicity

Intestinal organoid may serve as an alternative model for toxicity testing. However, the linkage between specific morphological alterations in organoids and chemical-induced toxicity has yet to be defined. Here, we generated C57BL/6 mouse intestinal organoids and conducted a morphology-based analysis on chemical-induced toxicity. Alterations in morphology were characterized by large spheroids, hyperplastic organoids, small spheroids, and protrusion-loss organoids, which responded in a concentration-dependent manner to the treatment of four metal(loid)s including cadmium (Cd), lead (Pb), hexavalent chromium (Cr-VI), and inorganic trivalent arsenic (iAs-III). Notably, alterations in organoid morphology characterized by abnormal morphology rate were correlated with specific intestinal toxic effects, including reduction in cell viability and differentiation, induction of apoptosis, dysfunction of mucus production, and damage to epithelial barrier upon repeated administration. The benchmark dose (BMDL₁₀) values of morphological alterations (0.007-0.195 μM) were lower than those of conventional bioassays (0.010-0.907 μM). We also established that the morphologic features of organoids upon Cd, Pb, Cr-VI, or iAs-III treatment were metal specific, and mediated by Wnt, bone morphogenetic protein, apoptosis induction, and Notch signaling pathways, respectively. Collectively, these findings provide novel insights into the relevance of morphological alterations in organoids to specific toxic endpoints and identify specific morphological alterations as potential indicators of enterotoxicity.

In Vitro Three-dimensional (3D) Cell Culture Tools for Spheroid and Organoid Models

Three-dimensional (3D) cell culture technology has been steadily studied since the 1990's due to its superior biocompatibility compared to the conventional two-dimensional (2D) cell culture technology, and has recently developed into an organoid culture technology that further improved biocompatibility. Since the 3D culture of human cell lines in artificial scaffolds was demonstrated in the early 90's, 3D cell culture technology has been actively developed owing to various needs in the areas of disease research, precision medicine, new drug development, and some of these technologies have been commercialized. In particular, 3D cell culture technology is actively being applied and utilized in drug development and cancer-related precision medicine research. Drug development is a long and expensive process that involves multiple steps-from target identification to lead discovery and optimization, preclinical studies, and clinical trials for approval for clinical use. Cancer ranks first among life-threatening diseases owing to intra-tumoral heterogeneity associated with metastasis, recurrence, and treatment resistance, ultimately contributing to treatment failure and adverse prognoses. Therefore, there is an urgent need for the development of efficient drugs using 3D cell culture techniques that can closely mimic in vivo cellular environments and customized tumor models that faithfully represent the tumor heterogeneity of individual patients. This review discusses 3D cell culture technology focusing on research trends, commercialization status, and expected effects developed until recently. We aim to summarize the great potential of 3D cell culture technology and contribute to expanding the base of this technology.

Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence

Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.

A Scalable 3D High-Content Imaging Protocol for Measuring a Drug Induced DNA Damage Response Using Immunofluorescent Subnuclear γH2AX Spots in Patient Derived Ovarian Cancer Organoids

The high morbidity rate of ovarian cancer has remained unchanged during the past four decades, partly due to a lack of understanding of disease mechanisms and difficulties in developing new targeted therapies. Defective DNA damage detection and repair is one of the hallmarks of cancer cells and is a defining characteristic of ovarian cancer. Most in vitro studies to date involve viability measurements at scale using relevant cancer cell lines; however, the translation to the clinic is often lacking. The use of patient derived organoids is closing that translational gap, yet the 3D nature of organoid cultures presents challenges for assay measurements beyond viability measurements. In particular, high-content imaging has the potential for screening at scale, providing a better understanding of the mechanism of action of drugs or genetic perturbagens. In this study we report a semiautomated and scalable immunofluorescence imaging assay utilizing the development of a 384-well plate based subnuclear staining and clearing protocol and optimization of 3D confocal image analysis for studying DNA damage dose response in human ovarian cancer organoids. The assay was validated in four organoid models and demonstrated a predictable response to etoposide drug treatment with the lowest efficacy observed in the clinically most resistant model. This imaging and analysis method can be applied to other 3D organoid and spheroid models for use in high content screening.

Pancreas organoid models of development and regeneration

Organoids have become one of the fastest progressing and applied models in biological and medical research, and various organoids have now been developed for most of the organs of the body. Here, we review the methods developed to generate pancreas organoids in vitro from embryonic, fetal and adult cells, as well as pluripotent stem cells. We discuss how these systems have been used to learn new aspects of pancreas development, regeneration and disease, as well as their limitations and potential for future discoveries.

Current and future approaches for in vitro hit discovery in diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a serious public health problem. In this review, we discuss current and promising future drugs, targets, in vitro assays and emerging omics technologies in T2DM. Importantly, we open the perspective to image-based high-content screening (HCS), with the focus of combining it with metabolomics or lipidomics. HCS has become a strong technology in phenotypic screens because it allows comprehensive screening for the cell-modulatory activity of small molecules. Metabolomics and lipidomics screen for perturbations at the molecular level. The combination of these data-intensive comprehensive technologies is enabled by the rapid development of artificial intelligence. It promises a deep cellular and molecular phenotyping directly linked to chemical information about the applied drug candidates or complex mixtures.

Application of Intelligent Image Matching and Visual Communication in Brand Design

In this paper, from the perspective of improving the visual communication of brand design, image texture intelligent matching processing is needed, proposing a brand design texture intelligent matching method based on visual communication, constructing a brand design texture intelligent information acquisition model under visual communication, using automatic image imaging technology for texture imaging and feature segmentation of brand design, and extracting typical brand design and ethnic design language of texture histogram, texture segmentation, and automatic matching under visual communication according to histogram distribution, brand design texture information enhancement and optimization detection by regularized feature fusion method, extraction of edge contour feature points of brand design, and texture matching with the extracted edge contour feature points of decorative patterns as input statistics. The adaptive performance of texture matching for a brand design using this method is better, and the texture discrimination ability is stronger, which improves the application research of better reflecting brand design in modern visual communication design and promotes the innovative combination of traditional cultural elements and modern design.

Patient-derived cancer organoids for drug screening: Basic technology and clinical application

Cancer organoids, a three-dimensional (3D) culture system of cancer cells derived from tumor tissues, recapitulate physiological structure of the parental tumor. Different tumor organoids have been established for a variety of tumor types, such as colorectal, liver, stomach, pancreatic and brain tumors. Some tumor organoid biobanks are built to screen and discover novel antitumor drug targets. Moreover, patients-derived tumor organoids (PDOs) could predict treatment response to chemoradiotherapy, targeted therapy and immunotherapy to provide guidance for personalized cancer therapy. In this review, we provide an updated overview of tumor organoid development, summarize general approach to establish tumor organoids, and discuss the application of anti-cancer drug screening based on tumor organoid and its application in personalized therapy. We also outline the opportunities and challenges for organoids to guide precision medicine.

Insights Into the Biogenesis and Emerging Functions of Lipid Droplets From Unbiased Molecular Profiling Approaches

Lipid droplets (LDs) are spherical, single sheet phospholipid-bound organelles that store neutral lipids in all eukaryotes and some prokaryotes. Initially conceived as relatively inert depots for energy and lipid precursors, these highly dynamic structures play active roles in homeostatic functions beyond metabolism, such as proteostasis and protein turnover, innate immunity and defense. A major share of the knowledge behind this paradigm shift has been enabled by the use of systematic molecular profiling approaches, capable of revealing and describing these non-intuitive systems-level relationships. Here, we discuss these advances and some of the challenges they entail, and highlight standing questions in the field.

Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification

Current imaging approaches limit the ability to perform multi-scale characterization of three-dimensional (3D) organotypic cultures (organoids) in large numbers. Here, we present an automated multi-scale 3D imaging platform synergizing high-density organoid cultures with rapid and live 3D single-objective light-sheet imaging. It is composed of disposable microfabricated organoid culture chips, termed JeWells, with embedded optical components and a laser beam-steering unit coupled to a commercial inverted microscope. It permits streamlining organoid culture and high-content 3D imaging on a single user-friendly instrument with minimal manipulations and a throughput of 300 organoids per hour. We demonstrate that the large number of 3D stacks that can be collected via our platform allows training deep learning-based algorithms to quantify morphogenetic organizations of organoids at multi-scales, ranging from the subcellular scale to the whole organoid level. We validated the versatility and robustness of our approach on intestine, hepatic, neuroectoderm organoids and oncospheres.

The Molecular Mechanisms of Intestinal Inflammation and Fibrosis in Crohn’s Disease

Crohn’s disease (CD) is an inflammatory bowel disease (IBD) with repeated remissions and relapses. As the disease progresses, fibrosis and narrowing of the intestine occur, leading to severe complications such as intestinal obstruction. Endoscopic balloon dilatation, surgical stricture plasty, and bowel resection have been performed to treat intestinal stenosis. The clinical issue is that some patients with CD have a recurrence of intestinal stenosis even after the medical treatments. On the other hand, there exist no established medical therapies to prevent stenosis. With the progressive intestinal inflammation, cytokines and growth factors, including transforming growth factor (TGF-β), stimulate intestinal myofibroblasts, contributing to fibrosis of the intestine, smooth muscle hypertrophy, and mesenteric fat hypertrophy. Therefore, chronically sustained inflammation has long been considered a cause of intestinal fibrosis and stenosis. Still, even after the advent of biologics and tighter control of inflammation, intestinal fibrosis’s surgical rate has not necessarily decreased. It is essential to elucidate the mechanisms involved in intestinal fibrosis in CD from a molecular biological level to overcome clinical issues. Recently, much attention has been paid to several key molecules of intestinal fibrosis: peroxisome proliferator-activating receptor gamma (PPARγ), toll-like receptor 4 (TLR4), adherent-invasive Escherichia coli (AIEC), Th17 immune response, and plasminogen activator inhibitor 1 (PAI-1). As a major problem in the treatment of CD, the pathophysiology of patients with CD is not the same and varies depending on each patient. It is necessary to integrate these key molecules for a better understanding of the mechanism of intestinal inflammation and fibrosis.