Prostate Tumor Model
Prostate Tumor Model - Related Videos
08:03
Generation of Prostate Cancer Patient Derived Xenograft Models from Circulating Tumor Cells
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Cited by 59 •
2015
This manuscript details a method used to generate prostate cancer patient derived xenografts (PDXs) from circulating tumor cells (CTCs). The generation of PDX models from CTCs provides an alternative experimental model to study prostate cancer; the most commonly diagnosed tumor and a frequent cause of death from cancer in men.
06:48
An Orthotopic Murine Model of Human Prostate Cancer Metastasis
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Cited by 30 •
2013
This orthotopic model of human prostate cancer allows for quantification of tumor size, circulating tumor cells, and formation of distinct metastasis to the lung. As cells must escape the primary organ, enter the blood stream, and implant into a secondary site, this model effectively recapitulates the scenario in humans.
08:30
MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR (qPCR)
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Cited by 18 •
2012
Quantitative Real Time polymerase chain reaction (qPCR) is a rapid and sensitive method to investigate the expression levels of various microRNA (miRNA) molecules in tumor samples. Using this method expression of hundreds of different miRNA molecules can be amplified, quantified, and analyzed from the same cDNA template.
07:01
Pre-clinical Orthotopic Murine Model of Human Prostate Cancer
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Cited by 17 •
2016
Prostate cancer is the second most common cause of cancer-related deaths in the United States. An orthotopic cancer model provides a useful approach to understand the biology of prostate cancer and to evaluate the efficacy of therapeutic regimens. This protocol describes detailed steps necessary to establish an orthotopic prostate cancer mouse model.
04:12
Renal Capsule Tumor Xenografting: A Technique to Generate an Experimental Animal Model to Evaluate Prostate Carcinogenesis
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2023
In this video, we demonstrate the implantation of human-derived prostate cancer tissue grafts into the renal capsule of an immunocompromised recipient mouse. This technique can be used to assess tumor progression and develop novel therapeutic strategies.
FAQs
These model formats emphasize different aspects of prostate cancer research. Cultured cancer cells provide a system for examining tumor biology, whereas patient-derived organoids preserve features from an individual tumor. Tumors implanted in animals allow researchers to assess tumor growth in a living experimental setting. Comparing these formats helps investigators select a system that matches the biological question and desired outcome.
Androgen receptor signaling and genetic alterations connect molecular events with prostate tumor behavior. A model that represents these features can help researchers examine how changes in signaling or tumor genetics influence growth and treatment response. This molecular-to-behavioral link is especially useful when comparing disease mechanisms or evaluating whether a candidate treatment affects the relevant biology.
Therapy resistance can be investigated by relating molecular changes to measurable differences in tumor behavior after treatment. Prostate tumor models also provide a setting for examining interactions with the tumor microenvironment, which may influence how tumors respond. Studying these factors together helps researchers identify mechanisms associated with reduced treatment effectiveness and supports comparisons among experimental treatment strategies.
A typical research workflow begins by selecting a model that represents the tumor feature under study, such as androgen receptor signaling, genetic alterations, or microenvironmental interactions. Researchers then expose the system to candidate treatments, measure tumor-related behavior, and connect those observations with molecular changes. The resulting comparison can guide interpretation before studies advance toward clinical investigation.
Researchers use these models when they need to compare drug responses under controlled experimental conditions before clinical studies. The systems can reveal differences in treatment effectiveness by linking exposure to measurable tumor behavior and molecular changes. This makes them useful for prioritizing candidate treatments, investigating therapy resistance, and determining which biological features may influence the observed response.
Patient-derived organoids can preserve features from an individual tumor, allowing researchers to examine treatment responses in a model connected to that patient-derived material. When molecular characteristics are compared with experimental outcomes, the approach can support precision medicine by helping relate tumor-specific biology to candidate treatment effects. The broader goal is to develop more predictive research approaches.