Tumor Growth Dynamics
Tumor Growth Dynamics - Related Videos
08:11
Measuring Growth and Gene Expression Dynamics of Tumor-Targeted S. Typhimurium Bacteria
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Cited by 22 •
2013
The goal of these experiments is to generate quantitative time-course data on the growth and gene expression dynamics of attenuated S. typhimurium bacterial colonies growing inside tumors. This video covers tumor cell preparation and implantation, bacteria preparation and injection, whole-animal luminescence imaging, tumor excision, and bacterial colony counting.
12:09
A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics
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Cited by 14 •
2013
We describe a novel in vivo imaging technique that couples fluorescent chimeric mice with intracranial windows and high-resolution 2-photon microscopy. This imaging platform aids studies of dynamic changes in brain tissue and microvasculature, at a single-cell level, following pathological insults and is adaptable to assess intracranial drug delivery and distribution.
07:55
The Influence of Liver Resection on Intrahepatic Tumor Growth
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Cited by 6 •
2016
A high incidence of tumor recurrence after resection of liver metastases remains an unsolved problem. The illustrated mouse model may be useful to investigate the reasons for such recurrences. It combines a liver resection model with intrahepatic tumor cell injection for the first time.
10:45
In Situ Visualization of Axon Growth and Growth Cone Dynamics in Acute Ex Vivo Embryonic Brain Slice Cultures
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Cited by 4 •
2021
This protocol demonstrates a straightforward and robust method to study in situ axon growth and growth cone dynamics. It describes how to prepare ex vivo physiologically relevant acute brain slices and provides a user-friendly analysis pipeline.
09:14
An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth
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Cited by 39 •
2011
A modified 3-D in vitro system is presented in which growth characteristics of several tumor cell lines in reconstituted basement membrane correlate with the dormant or proliferative behavior of the tumor cells at a metastatic secondary site in vivo.
FAQs
The net change in tumor burden depends on how rapidly cancer cells are produced relative to how many are eliminated through apoptosis or other forms of cell death. A tumor may therefore enlarge, stabilize, or regress without changes in a single process alone. Tracking this balance helps researchers interpret whether altered size reflects expansion, increased loss, or both.
These conditions can determine whether malignant cells continue expanding or enter less active states. Angiogenesis affects vascular support, whereas limited nutrients and hypoxia create pressures within the tumor microenvironment. Such influences help explain why different cell populations can coexist in one tumor and why some cells remain dormant while others acquire behavior associated with local invasion.
Tumor size alone does not capture how a malignancy is changing. Shifts in cellular composition may indicate differences in proliferation, cell death, dormancy, or invasive potential. Examining composition alongside size gives cancer researchers a more informative view of progression, because two tumors with similar dimensions may differ substantially in their biological behavior and expected response to treatment.
Researchers combine longitudinal measurements, imaging, and mathematical models to follow changes across multiple time points. Repeated observations reveal growth patterns rather than relying on a single measurement, while models help characterize those patterns and estimate how the tumor may respond to treatment. Together, these approaches connect visible changes in tumor size with underlying biological behavior.
These tools can show whether tumor changes after therapy are consistent with continued expansion, reduced growth, or increased cell loss. Longitudinal analysis is especially useful because response is evaluated as a pattern over time rather than as an isolated observation. The resulting estimates help researchers compare treatment effects and investigate changes associated with resistance.
Growth analyses support prognosis and can contribute to therapy selection by linking tumor behavior with expected clinical outcomes. They also provide a framework for studying tumor evolution, vascularization, and treatment resistance. In research, this perspective helps evaluate strategies aimed not only at reducing tumor burden but also at influencing the conditions and evolutionary processes that sustain malignancy.