Tumor Organoids
Tumor Organoids - Related Videos
03:17
Preparing Organoids from Tumors: A 3D In Vitro Tumor Model
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2023
Organoids derived from tumors are a type of 3D cell culture model that can maintain the pathological features and organ-specific cell lineage of tumors. In the example protocol, we will see scientists generate organoids from a prostate tumor from a genetically engineered mouse model.
07:33
In vitro Organoid Culture of Primary Mouse Colon Tumors
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Cited by 44 •
2013
A simple method to establish primary murine colon tumor organoid is described. This method utilizes the feature that colon tumor cells survive and grow into organoids in media containing limited growth factors, whereas normal colon epithelial do not.
04:15
Bladder Tumor Organoid Model: A Method for Orthotopic Transplantation of Bladder Organoids into Recipient Murine Bladder
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2023
In this video, we describe the orthotopic transplantation of cultured bladder tumor organoids into the murine bladder to study the role of the organ environment on developing tumors.
03:19
Generating an Organoid Culture from a Brain Tumor Cell Suspension
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2025
This video describes the preparation and cultivation of brain tumor organoids from single-cell suspension. Using a laminin-rich extracellular matrix as a scaffold and culture media for nutrients, cells are facilitated to multiply and self-organize within the organoid. Consequently, ex vivo organoids are generated, mimicking cellular diversity and the microenvironment of brain tumors.
12:41
Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
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Cited by 14 •
2022
This protocol describes a semi-automated method for medium- to high-throughput organoid drug screenings and microscope-agnostic, automated image analysis software to quantify and visualize multiparametric, single-organoid drug responses to capture intratumor heterogeneity.
FAQs
The extracellular matrix provides a supportive environment, while defined culture conditions regulate the setting in which tumor cells proliferate and organize. Together, these factors help preserve structural and molecular characteristics associated with the patient’s cancer. Their controlled nature also allows researchers to examine tumor behavior and treatment responses without the variability of a less defined experimental setting.
Self-organization allows cancer cells to form three-dimensional structures rather than remaining as a simple collection of cells. This organization helps maintain aspects of tumor heterogeneity, meaning the presence of diverse cellular and molecular features within a cancer. Preserving that complexity can give researchers a more informative system for investigating how different tumor characteristics relate to cancer behavior.
These models connect observable tumor characteristics with responses measured under controlled conditions. Researchers can examine how organoids derived from cancer samples behave and then investigate how treatments affect them. Comparing those results across organoids can reveal relationships between tumor features and drug sensitivity, supporting studies of cancer mechanisms, response variability, and potential biomarkers.
A typical study begins with tumor-derived cells, places them in a supportive extracellular matrix, and maintains them under defined culture conditions that permit proliferation and self-organization. Researchers then examine the resulting organoid characteristics or expose the models to treatments and assess responses. The workflow links model behavior with the originating clinical samples for interpretation.
Tumor organoids are especially useful when the research question depends on structural organization, molecular features, or heterogeneity that may be difficult to represent in a simpler cell setting. Their three-dimensional organization provides a controlled platform for studying cancer development, tumor cell behavior, and treatment interactions while retaining relevant characteristics of the patient’s cancer.
Researchers can expose tumor organoids to treatments and measure how the models respond in a controlled laboratory setting. When those responses are interpreted alongside the characteristics of the corresponding clinical samples, the results may help identify treatment-associated biomarkers and support preclinical evaluation. This approach can also contribute to more individualized strategies by connecting model behavior with patient-specific cancer features.