| Literature DB >> 36167824 |
Qinying Wang1,2, Fanying Guo3, Yutao Jin1,2, Yanlei Ma4,5.
Abstract
Digestive system diseases arise primarily through the interplay of genetic and environmental influences; there is an urgent need in elucidating the pathogenic mechanisms of these diseases and deploy personalized treatments. Traditional and long-established model systems rarely reproduce either tissue complexity or human physiology faithfully; these shortcomings underscore the need for better models. Organoids represent a promising research model, helping us gain a more profound understanding of the digestive organs; this model can also be used to provide patients with precise and individualized treatment and to build rapid in vitro test models for drug screening or gene/cell therapy, linking basic research with clinical treatment. Over the past few decades, the use of organoids has led to an advanced understanding of the composition of each digestive organ and has facilitated disease modeling, chemotherapy dose prediction, CRISPR-Cas9 genetic intervention, high-throughput drug screening, and identification of SARS-CoV-2 targets, pathogenic infection. However, the existing organoids of the digestive system mainly include the epithelial system. In order to reveal the pathogenic mechanism of digestive diseases, it is necessary to establish a completer and more physiological organoid model. Combining organoids and advanced techniques to test individualized treatments of different formulations is a promising approach that requires further exploration. This review highlights the advancements in the field of organoid technology from the perspectives of disease modeling and personalized therapy.Entities:
Mesh:
Year: 2022 PMID: 36167824 PMCID: PMC9513303 DOI: 10.1038/s41392-022-01194-6
Source DB: PubMed Journal: Signal Transduct Target Ther ISSN: 2059-3635
Fig. 1Schematic diagram summarizing the generation of digestive organoids and the manner of cell differentiation. Organoids derived from isolated epithelial stem cells and tissue samples, reprogramming of skin fibroblasts and blood cells into pluripotent stem cells (PSCs). (Induction involves germ-layer specification (endoderm) and subsequent induction and maturation by specific growth factor combinations.)
Fig. 2Potential applications of organoid models in precision medicine. As a versatile in vitro model, organoids can cover many applications from disease modeling to clinical trials and achieve the purpose of precise and personalized treatment. The scope of organoid research includes (1) Disease modeling. (2) Pathogenic infection. (3) Biobanking of organoids. (4) Clinical trials. (5) Stem cell function and regeneration (delivery of organoids to repair intestinal epithelium or activate the repair program of endogenous stem cells). (6) Drug screening (patient-specific high-throughput screening and discovery). (7) Immunotherapy. (8) Gene therapy and FMT
Fig. 3Using gut organoids to study the impact of microbiota. Methods of infecting organoids with bacteria: (1) Microinjection. (2) Transwell/Plate-based 2D monolayer cultures of organoids. (3) Reversal of cell polarity of organoids. (4) Organoids-on-a-chip
Comparison of methods for introducing microorganisms into organoids
| Method | Description | Advantages | Disadvantages |
|---|---|---|---|
| Microinjection[ | Injecting microorganisms into the lumen of organoids using a microinjection device. | 1. The method preserves the structural integrity of the organoids, and microorganisms only contact the apical side of organoids, providing a more realistic gastrointestinal simulation environment, especially for the anaerobic bacteria. 2. The entire process of microbe-organoid interactions can be observed, including initial interactions and early host responses. 3. Quantitative experiments can be performed by controlling the MOI. 4. This method has no special requirements for organoid culture conditions and can be applied for most 3D organoids. | 1. This method requires a very specialized setup and is lacking of a standard procedure for different organoids. 2. The manual nature of the microinjection process makes it difficult to apply to high-throughput experiments, and the sequential injections resulted in asynchrony of experimental exposures. 3. The leakage of injected microorganisms toward the basolateral side can influence the readout, and the closed lumen may cause nutrient and oxygen consumption and metabolites accumulation. 4. Injections of small volumes of material are often imprecise, and differences in organoid size as well as luminal contents may cause uneven distribution of the injected material. |
| Organoid-derived fragment or epithelial monolayers[ | Linearizing 3D Organoids into 2D Systems such as extracellular matrix-coated dish. The organoid-derived monolayer contains various epithelial cell lineages and enables the introduction of microorganisms via direct addition to the culture media. | 1. The accessibility of the apical side of organoids is enhanced and the introduction of microorganisms can be achieved with an easily applicable setup. 2. This method can be applied to high-throughput experiments and can effectively reduce group differences caused by irrelevant variables in comparison or screening experiments. 3. Long-term co-culture with anaerobic bacteria can be achieved by incubating organoids in an aerobic environment while maintaining the apical chamber of a Transwell insert in an anaerobic environment. 4. Combined with the air-liquid interface or the microfabricated collagen scaffold array of crypt-like invaginations, this method can partially reconstruct epithelial-mesenchymal interactions and the crypt-like and villus-like structures. | 1. The inoculation process caused mechanical damage to the organoids, and 2D organoids cannot reflect the structural features of lumen. 2. Certain bacterial media such as tryptone-yeast extract-glucose (TYG) and brain heart infusion may be toxic to the monolayers during introduction. 3. The success rate of establishing functional epithelial monolayers varies between different donors, which may limit its applicability. 4. Optimization measures such as providing continuous nutrient replenishment, creating an anaerobic chamber for obligate anaerobic bacteria, combining the air-liquid interface and collagen scaffold technology are costly and time-consuming. |
| 3D organoids with growing reversed polarity[ | Making the apical surface evert to face the media and introducing microorganisms by adding them directly to the culture medium. | 1. This method simplifies the introduction of microorganisms while maintaining the 3D structure of organoids. 2. Without extracellular matrix affecting distribution, suspended apical-out organoids can be synchronously exposed to experimental agents and microorganisms. 3. Suspended organoid culture can be divided into multiple wells for different experimental conditions, which is more suitable for high-throughput experiments. | 1. This method does not guarantee complete polarity reversion, so it is difficult to distinguish between the apical and basolateral interactions. 2. The mucus can be easily washed out, making it easier for foreign substances to enter the organoids. 3. Transferring apical-out organoids to new media is a time-consuming and iterative process. 4. Apical-out organoids exhibit slower proliferation and accelerated differentiation, suggesting that some of the pathways have been altered and may interfere with host-microbe interactions. |
| Microfluidic platforms[ | Microfluidic platforms, including organ-on-a-chip, HuMiX and GuMI, are micro-engineered systems generated based on industrial computer microchips by microfabrication methods. Microfluidic platforms can provide organoids with precisely programmed biomimetic microenvironments and introduce microorganisms into organoids with ease and precision. | 1. This method enables microbial diversity in organoids by tuning chemical gradients, oxygen gradients, dynamic mechanical stress and even incorporating multiple cell types and connecting multiple tissue platforms. 2. Simulation of key characteristics of the human gut and reconstruction of the mucus layer provides a better model for studying microbe-host interactions. 3. Standardized and automated organoid-on-a-chip enables high-throughput experiments. 4. Long-term coculture can be achieved through the continuous supply of nutrients and scavenging of metabolites via the microfluidic platform. | 1. The complexity of organ structures and the heterogeneity of individuals determine that this method cannot fully simulate the real situation, so the applicability of this method needs to be discussed. 2. This method integrates programming, biochemistry, biomechanics, materials science and other disciplines and requires the cooperation of multiple teams and platforms, thus greatly increasing the experimental threshold and cost. |
Summary of organoid-based clinical trails
| Application | Condition or disease | Research title | ClinicalTrials.gov Identifier |
|---|---|---|---|
| Drug Screening | Pancreatic Cancer | A Prospective, Randomized, Controlled Trial of Chemotherapy for Advanced Pancreatic Cancer Based on Organoid Drug Sensitivity Test | NCT04931381 |
| Guidance of Standard of Care Treatment for Metastatic Pancreatic Cancer by Drug Screening in Patient-derived Organoids: A Single Centre, Open-label, Single Arm, Phase II Trial With Feasibility Endpoint | NCT05351983 | ||
| A Prospective, Randomized, Controlled Trial of Adjuvant Chemotherapy for Pancreatic Cancer Based on Organoid Drug Sensitivity Test | NCT04931394 | ||
| Drug Screening of Pancreatic Cancer Organoids Developed From EUS-FNA Guided Biopsy Tissues | NCT03544255 | ||
| Pharmacotyping of Patient-derived Pancreatic Cancer Organoids from Endoscopic Ultrasound-guided Biopsy as a Tool for Predicting Oncological Response | NCT05196334 | ||
| Colorectal Cancer | Prospective Observation on the Accuracy of in Vitro Screening of Colorectal Cancer Chemotherapy Drugs Based on Organoids-on-a-chip | NCT04996355 | |
| Patient-derived Organoids of RAS/RAF Wild-type Metastatic Right Colon Cancer to Test the Sensitivity and Clinical Consistency of Combined Treatment of Cetuximab. | NCT04906733 | ||
| A Prospective Multicenter Randomized Controlled Trial of the Clinical Efficacy of Neoadjuvant Therapy Based on Organoids Drug Sensitivity Versus Empirical Neoadjuvant Therapy in the Treatment of Advanced Rectal Cancer | NCT05352165 | ||
| The Culture of Advanced/Recurrent/Metastatic Colorectal Cancer Organoids and Drug Screening | NCT05304741 | ||
| Pilot Study for Ex Vivo Tailoring of Treatment in Colorectal Cancer | NCT05401318 | ||
| Gastric Cancer | The Clinical Efficacy of Patient-derived Organoid-based Drug Sensitive Neoadjuvant Chemotherapy Versus Traditional Neoadjuvant Chemotherapy in Advanced Gastric Cancer: A Prospective Multi-center Randomized Controlled Study | NCT05351398 | |
| Consistency Between Treatment Responses in Patient-Derived Organoid (PDO) Models and Clinical Outcomes of Neoadjuvant Therapy, Conversion Therapy and Palliative Therapy in Gastric Cancer | NCT05203549 | ||
| A Prospective Observational Study on the Potential Benefit of Neoadjuvant Therapy for Advanced Gastric Cancer Based on Organoid Drug Susceptibility Screening | NCT05442138 | ||
| Q-GAIN (Using Qpop to Predict Treatment for GAstroIntestinal caNcer) | NCT04611035 | ||
| Cystic Fibrosis | Response to CFTR-modulators in Intestinal Organoids of Patients with CF Having at Least One R334W Mutation | NCT04254705 | |
| Biliary Tract Cancer | A Prospective Feasibility Study of Multi-Platform Profiling Using Biospecimens From Patients With Resected Biliary Tract Cancer | NCT04561453 | |
| Preclinical Evaluation | Pancreatic Cancer | Establishing Organoids from Metastatic Pancreatic Cancer Patients, the OPT-I Study | NCT03500068 |
| Development of a Prediction Platform for Neoadjuvant Treatment and Prognosis in Pancreatic Cancer Using Ex Vivo Analysis of Organoid Culture | NCT04777604 | ||
| Development of a Prediction Platform for Adjuvant Treatment and Prognosis in Pancreatic Cancer Using Ex Vivo Analysis of Organoid Culture | NCT04736043 | ||
| Colorectal Cancer | Validation of Organoids Potential Use as a Companion Diagnostic in Predicting Neoadjuvant Chemoradiation Sensitivity in Locally Advanced Rectal Cancer | NCT03577808 | |
| Systemic Neoadjuvant and Adjuvant Control by Precision Medicine in Rectal Cancer (SYNCOPE) - Approach on High-risk Group to Reduce Metastases | NCT04842006 | ||
| Radiation Enteritis, Inflammatory Bowel Diseases | Preclinical Evaluation of Multimodal Therapeutic Strategies in Intestinal Irradiation and Inflammatory Bowel Disease from Organoids | NCT05425901 | |
| Esophageal Cancer | Chemoradioresistance in Prospectively Isolated Cancer Stem Cells in Esophageal Cancer-Organoid: RARE STEM-Organoid | NCT03283527 | |
| Esophagogastric Carcinoma | Molecular Outcome Prediction of Neoadjuvant Systemic Treatment in Esophagogastric Carcinoma | NCT03429816 | |
| Colorectal Cancer | The Exploratory Study of Patient-derived Organoids for the Prediction and Evaluation of Clinical Efficiency Effect of Colorectal Cancer Liver Metastasis | NCT05183425 | |
| Validation of the Three-dimensional Bioprinted Tumor Models as a Predictive Method of the Response to Chemotherapy for Colorectal Cancer With or Without Liver Metastases | NCT04755907 | ||
| Living biobanks | Inflammatory Bowel Disease | Prospective, monocentric cohort aiming at generating 3D organoids from human digestive samples | NCT05294107 |
| Colorectal Cancer | Feasibility of Establishing Patient-Derived Organoids for Rectal Cancer: A Biospecimen Collection Protocol | NCT04371198 | |
| Tumor Immune Microenvironment Involvement in Colorectal Cancer Chemoresistance Mechanisms: a Patient-derived Tumoroids Prospective Collection From Systemic Treatment Naive Tumors | NCT05038358 | ||
| Colorectal Cancer Metastases and Hepatocellular Carcinomas | Next Generation “ of Liver Derived-organoïd Biobank: Case of Colorectal Cancer Metastases and Hepatocellular Carcinomas | NCT05384184 | |
| Liver, Biliary and Pancreatic Cancer | A Study Designed to Develop in Vitro Models of Liver, Biliary and Pancreatic Cancer for the Investigation of Tumour Biology and Potential Therapies | NCT02436564 | |
| Primary Sclerosing Cholangitis | Characterization of Biliary Cell-derived Organoids From Bile of PSC and Non-PSC Patients | NCT04753996 | |
| Pancreatic Cancer | EUS-guided Biopsy of Pancreatic Mass Lesions for Developing Patient -Derived Cancer Models | NCT03140592 | |
| Mechanism exploration | Host-microbiota Interactions | Establishment of Human Organoid Lines as a Tool to Dissect Molecular Pathways of Host-microbiota Interactions | NCT05323357 |
| Allergy and Gastrointestinal Disorders | Establishment of Small Intestinal Human Organoids to Check the Influence of Nutrient Antigens or Therapeutic Agents | NCT03256266 | |
| Improving the Diagnosis of Food Allergy and Food Intolerance by Determining Mucosal IgE and Inflammatory Markers and Validating With Intestinal in Vitro Organoids | NCT05259826 | ||
| Bestimmung Des Einflusses Von Nahrungsmitteln Auf Die Darmschleimhaut Mit Der Konfokalen Laserendomikroskopie Und Humanen in Vitro Organoiden | NCT05056610 | ||
| Intestinal Stem Cells Characterization | Intestinal Stem Cells Characterization in Intestinal Organoid Culture from Inflammatory Bowel Disease and Intestinal Polyposis Patients | NCT02874365 | |
| Specimen acquisition | Evaluation and Comparison of the Growth Rate of Pancreatic Cancer Patient-derived Organoids Generated from Matched Fine Needle Aspirations (FNA) and Fine Needle Biopsies (FNB) | NCT03990675 | |
| The biology of innervated sensory epithelial cells | The Innervation of Human Gut Sensory Epithelial Cells | NCT02888587 | |
| The physiopathology of Necrotizing Enterocolitis | Development and Use of a Tissue and Human Enteroid Biorepository to Study the Pathophysiology of Neonatal Necrotizing Enterocolitis | NCT04549727 | |
| The gut epithelium properties in hypertension | Gut Inflammation and Gut-Gut Microbiome Interactions in the Pathogenesis of Hypertension | NCT04497727 |
Fig. 4Advancements in organoid cellular and functional integrity. Advancement of organoid models: improving organoid complexity by adding mesenchymal cells, immune cells, endothelial cells, nerve cells, etc.; combining organoids with 3D bioprinting, biological materials and chip technology to develop organoid models that closely resemble the physiology of the human digestive system
Fig. 5Future trends in the development of multi-organoid models. Organoids of the esophagus, pancreas, stomach, and intestines can be generated in vitro and combined to form a multi-organoid model on a microarray to test multiorgan diseases and cancer metastasis as well as drug toxicity and efficacy
Fig. 6The prospect of combining high-technology approaches and digestive organoids. Gene editing and omics (epigenetics, transcriptomics, proteomics, metabolomics, and single-cell sequencing) technologies are used in combination with organoid models to systematically and comprehensively analyze molecular, cellular, and histological changes mediated by gene mutations or environmental interventions. Starting from basic research, the in vivo phenotypes and molecular targets corresponding to organoids under different conditions are continuously explored to guide the selection and testing of clinical treatment strategies