In Vivo Tumor Regression
In Vivo Tumor Regression - Related Videos
01:52
Regression Toward the Mean
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2020
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
14:04
Viral Nanoparticles for In vivo Tumor Imaging
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Cited by 45 •
2012
Plant viral nanoparticles (VNPs) are promising platforms for applications in biomedicine. Here, we describe the procedures for plant VNP propagation, purification, characterization, and bioconjugation. Finally, we show the application of VNPs for tumor homing and imaging using a mouse xenograft model and fluorescence imaging.
12:42
Paramyxoviruses for Tumor-targeted Immunomodulation: Design and Evaluation Ex Vivo
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Cited by 17 •
2019
This protocol describes a detailed workflow for the generation and ex vivo characterization of oncolytic viruses for expression of immunomodulators, using measles viruses encoding bispecific T cell engagers as an example. Application and adaptation to other vector platforms and transgenes will accelerate the development of novel immunovirotherapeutics for clinical translation.
12:03
In Vivo Model for Testing Effect of Hypoxia on Tumor Metastasis
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Cited by 6 •
2016
This manuscript describes the development of an animal model that allows for the direct testing of the effects of tumor hypoxia on metastasis and the deciphering the mechanisms of its action. Although the experiments described here focus on Ewing sarcoma, a similar approach can be applied to other tumor types.
04:13
A Technique to Assess the In Vivo Localization of Tumor-Specific Antibodies
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2025
This video demonstrates a technique to study the in vivo localization of tumor-specific antibodies in a mouse tumor xenograft model. Upon subcutaneously injecting cancer cells into mice for tumor formation, fluorescently-labeled antibodies are injected that bind to tumor-specific receptors, enabling in vivo assessment of antibody localization via imaging.
FAQs
The key determinant is the balance between tumor-cell loss and the cells’ continued proliferation and survival. Regression becomes measurable when treatment or immune activity produces enough cell loss to outweigh those opposing processes. This balance provides a mechanistic basis for interpreting a reduced tumor burden: the observed change reflects competing effects on cancer-cell persistence and expansion, not simply one isolated event.
Therapeutic effects and immune activity represent two supported sources of cancer-cell loss, but they need not be interpreted as identical mechanisms. Evaluating regression in relation to these sources helps cancer researchers examine how an intervention works and whether immune activity contributes to the response. That distinction is useful when comparing anticancer strategies with different intended modes of action.
A smaller tumor does not eliminate the need to examine resistant disease. If cancer cells retain the ability to survive or proliferate despite an intervention, the remaining disease can provide evidence that the response is incomplete or that resistance is present. For this reason, regression is interpreted alongside other study outcomes rather than treated as the sole indicator of treatment success.
No single measurement captures every aspect of the response. Imaging and physical measurements support assessment of tumor volume or burden, while pathology and survival analyses add complementary evidence for evaluating the outcome. Using these approaches in animal models or clinical studies allows investigators to compare responses more systematically and to interpret regression in the broader context of cancer treatment research.
Studies assess tumor response in a living organism, using animal models or clinical studies as the research setting. Investigators then apply one or more evaluation approaches, including imaging, physical measurements, pathology, or survival analyses. Together, these assessments characterize changes in tumor volume or burden and support treatment evaluation without relying on one type of evidence alone.
In cancer research, this outcome supports several decisions: investigators can compare anticancer strategies, examine treatment mechanisms, identify resistant disease, and judge whether an experimental therapy merits further development. Its value therefore extends beyond documenting a smaller tumor. Regression data help connect an observed response with questions about biological action, comparative performance, and the next stage of therapy evaluation.