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Cancer Spheroid and Organoid eLearning Course
This free course comprises two interactive modules that were developed to provide a succinct, contextual overview of spheroid and organoid culture model techniques and applications as well as various imaging modalities including high-content analysis.
Overview
The terms spheroid and organoid both refer to culture models with three-dimensional (3D) conformation that have a specific organization and architecture that cannot be achieved in 2D monolayer cell culture. This course covers the history and basic information about the applications and limitations of 3D culture models—including spheroids and organoids—that model organ physiology and disease. Throughout the course, you will have an opportunity to evaluate your learning experience using a series of interactive knowledge checks.
Topics in this course include:
Module 1: Experimental approaches
- Historical perspectives pertaining to 3D culture model development
- Cell sources
- Various 3D culture features
- Applications and methods for in vitro manipulation of 3D cultures
- Technical aspects for culturing and modeling physiology and disease
Module 2: Imaging modalities
- Fluorescence fundamentals
- Fluorescent reporters
- Sample preparation
- Imaging modalities for 3D cultures
- Principles of high-content analysis (HCA)
- Other topics
Modeling organs in physiology and disease
3D Culture Systems
This is the first in a two-part series describing spheroid and organoid culture methods and applications.
Upon completion of this module, you will be able to:
- Discuss events involving the history of 3D culture models
- Understand the properties of 3D cultures relating to applications and limitations
- Describe the various cell sources and approaches for the growth of 3D culture models
- Discuss the manipulation of 3D cultures to model physiology and disease
- Describe technical aspects of 3D culture
Technical content excerpt
Historical perspective
- Advantages of growing 3D cultures from stem cell sources:
- Does not require immortalized cell lines
- Does not require animal models/tissue
- Personalized medicine: Using pluripotent stem cells derived from adult somatic cells to generate iPSCs
Organoid culture technology has significantly advanced in the past decade, leading to the successful development of culture models that recapitulate multiple adult organs, including intestine, stomach, pancreas, colon, liver, and other organs, and can be used to study development and disease.
Growing organoid models from stem cell sources avoids the use of immortalized cell lines which often do not represent disease states adequately, and avoids the use of animal tissues. Furthermore, patient-specific organoids can be grown for personalized medicine approaches by reprogramming somatic cells to a pluripotent stem cell-like state, resulting in induced pluripotent cells or iPSCs.
Historical perspective
- Current culture systems incorporate technology and knowledge accumulated in >100 years of research
- Development of culture tools and reagents
- Insight into mechanisms of tissue morphogenesis, function, stem cell biology
Examples of stem cell derived organoids include in vitro formed epithelial organoids, or mini-guts, that are clonally derived from single intestinal stem cells. Remarkable PSC-derived organoids include those mimicking brain structures such as polarized cortical tissues from embryonic stem cells (ESCs), and cerebral organoids from induced pluripotent stem cells (iPSCs), as well as optic cup structures from ESC. These intricate culture models provide the microenvironment and developmental and spatial cues required to reproduce tissue morphogenesis and function from stem cells entirely in vitro.
Modeling organs in physiology and disease
Imaging modalities
This is the second in a two-part series describing various imaging modalities.
Upon completion of this module, you will be able to:
- Describe the main principles of the fluorescence process and explain how and why different fluorophores can be used simultaneously to distinguish features in the same sample
- Discuss fluorescent reporter types (fluorescent stains and conjugates, antibody-based IF, proteins) and their suitability to study different biological questions (growth, intracellular processes)
- Distinguish different types of optical illumination of 3D objects and name key features of 3D imaging modalities
- Explain causes of phototoxicity and list visible and subtle manifestations in live cells
- Discuss approaches to minimize phototoxicity during live imaging and their rationale
- Explain principles of high-content screening and its components
- Describe an example of a multiplex assay to inform on drug activity in 3D cancer cultures
Technical content excerpt
Principles of high-content analysis (HCA)
HCA stages
- Assay development
- Image acquisition
- Image analysis
- Data analysis
HCA experiments consist of four major stages that are assay development, image acquisition, image analysis, and data analysis.
During assay development, the configuration of a multi-parameter assay, including cellular target, reporter characteristics including fluorophore emission and mode of action, and measurable assay output need to be defined and validated by testing each assay by traditional methods.
HCA relies on a set of integrated tools. These include reagent kits and protocols that are optimized for performance in high-content cell-based assays. Automated imaging instrumentation systems may be adapted for live cell analyses and kinetic assays, for fixed endpoint assays, and incorporate acquisition algorithms. Automated imaging analysis algorithms are designed to process and analyze images to extract quantitative information. Data storage and management must allow for rapid retrieval of data and measurements. HCA requires software tools for visualization and analysis of image data. These can be placed into context with published data using bioinformatics tools.
Modeling organs in physiology and disease
3D Culture Systems
This is the first in a two-part series describing spheroid and organoid culture methods and applications.
Upon completion of this module, you will be able to:
- Discuss events involving the history of 3D culture models
- Understand the properties of 3D cultures relating to applications and limitations
- Describe the various cell sources and approaches for the growth of 3D culture models
- Discuss the manipulation of 3D cultures to model physiology and disease
- Describe technical aspects of 3D culture
Technical content excerpt
Historical perspective
- Advantages of growing 3D cultures from stem cell sources:
- Does not require immortalized cell lines
- Does not require animal models/tissue
- Personalized medicine: Using pluripotent stem cells derived from adult somatic cells to generate iPSCs
Organoid culture technology has significantly advanced in the past decade, leading to the successful development of culture models that recapitulate multiple adult organs, including intestine, stomach, pancreas, colon, liver, and other organs, and can be used to study development and disease.
Growing organoid models from stem cell sources avoids the use of immortalized cell lines which often do not represent disease states adequately, and avoids the use of animal tissues. Furthermore, patient-specific organoids can be grown for personalized medicine approaches by reprogramming somatic cells to a pluripotent stem cell-like state, resulting in induced pluripotent cells or iPSCs.
Historical perspective
- Current culture systems incorporate technology and knowledge accumulated in >100 years of research
- Development of culture tools and reagents
- Insight into mechanisms of tissue morphogenesis, function, stem cell biology
Examples of stem cell derived organoids include in vitro formed epithelial organoids, or mini-guts, that are clonally derived from single intestinal stem cells. Remarkable PSC-derived organoids include those mimicking brain structures such as polarized cortical tissues from embryonic stem cells (ESCs), and cerebral organoids from induced pluripotent stem cells (iPSCs), as well as optic cup structures from ESC. These intricate culture models provide the microenvironment and developmental and spatial cues required to reproduce tissue morphogenesis and function from stem cells entirely in vitro.
Modeling organs in physiology and disease
Imaging modalities
This is the second in a two-part series describing various imaging modalities.
Upon completion of this module, you will be able to:
- Describe the main principles of the fluorescence process and explain how and why different fluorophores can be used simultaneously to distinguish features in the same sample
- Discuss fluorescent reporter types (fluorescent stains and conjugates, antibody-based IF, proteins) and their suitability to study different biological questions (growth, intracellular processes)
- Distinguish different types of optical illumination of 3D objects and name key features of 3D imaging modalities
- Explain causes of phototoxicity and list visible and subtle manifestations in live cells
- Discuss approaches to minimize phototoxicity during live imaging and their rationale
- Explain principles of high-content screening and its components
- Describe an example of a multiplex assay to inform on drug activity in 3D cancer cultures
Technical content excerpt
Principles of high-content analysis (HCA)
HCA stages
- Assay development
- Image acquisition
- Image analysis
- Data analysis
HCA experiments consist of four major stages that are assay development, image acquisition, image analysis, and data analysis.
During assay development, the configuration of a multi-parameter assay, including cellular target, reporter characteristics including fluorophore emission and mode of action, and measurable assay output need to be defined and validated by testing each assay by traditional methods.
HCA relies on a set of integrated tools. These include reagent kits and protocols that are optimized for performance in high-content cell-based assays. Automated imaging instrumentation systems may be adapted for live cell analyses and kinetic assays, for fixed endpoint assays, and incorporate acquisition algorithms. Automated imaging analysis algorithms are designed to process and analyze images to extract quantitative information. Data storage and management must allow for rapid retrieval of data and measurements. HCA requires software tools for visualization and analysis of image data. These can be placed into context with published data using bioinformatics tools.
For Research Use Only. Not for use in diagnostic procedures.