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Wouldn’t it be nice if a cancer patient was given therapy only if it was going to work? Although it seems like a no-brainer, many patients undergo therapy without knowing how good the chances are for a successful outcome. Reasons for this uncertainty depend on the type and developmental-stage of individual tumors, as well as various genetic and environmental factors that directly or indirectly influence tumor persistence in a patient. Thus, a major challenge faced by recent anti-cancer therapeutics is their low predictive value of success, which may seem impractical when we consider their high cost of production. For example, a certain drug that can theoretically block a tumor’s access to nutrients and metastasis by inhibiting blood vessel formation (anti-angiogenic drug) has surprisingly been demonstrated in practice to either block or promote tumor metastasis. Therefore in such contextual scenarios, it becomes important to select and screen patients that have a better chance of prognosis in order to avoid treating patients that would gain no benefit from such therapeutic regimens.
Although ideal, screening patients for appropriate therapeutics is an ongoing challenge faced by researchers and clinicians. Normally, various scientific analyses are used to determine the best possible drug for an individual, with the aim of providing personalized treatment. For example, a quick test that can predict an individual’s responses prior to treatment, including the effect on cancer progression or metastasis, proves to be of great value to guide treatment options and screen patients for personalized benefits. Considering the example of anti-angiogenic agents, it would be even better to be able to have a test that can detect the difference in responses that are observed in clinical settings, and be able to predict respective outcomes.
A recent research by Rebelo de Almeida and colleagues targets this central theme of developing a rapid test that can be used to screen patients based on their individual tumor type and determine the possibility of an individual to benefit from respective therapy. Focusing on differentiating the complex responses generated by anti-angiogenic drugs, Rebelo de Almeida and group used zebrafish xenografts (patient derived tumors introduced in zebrafish) to represent the individual’s tumor microenvironment. Such patient-representing zebrafishes were named zAvatars as they correspond to the tumor properties related to blood vessel formation and metastasis found originally in the patient. Treating these tumor-carrying zAvatars with bevacizumab (a clinically relevant anti-angiogenic drug), they could monitor in a short span of 4 days the diversity in the therapeutic effect on blood vessel formation and also on metastasis. In brief, they found that there were zebrafishes that responded positively to the treatment and had significant tumor reduction, however there were also zebrafishes that did not benefit at all. Interestingly they found that the positive responses from zebrafishes correlated with the clinical patient response from which the tumors were derived. Accordingly, it seems to represent a relevant model system that can be used for ‘pre-testing’ cancer responsiveness to certain drugs outside patients. As a result, such an assay system can potentially guide clinicians to choose the most applicable therapeutics for respective patients.
Research has shown that in lieu of human testing for angiogenesis related drugs, zebrafish are a good model organism. Many of the cancer-related genes are conserved between zebrafish and humans in terms of both structure and function. Moreover, various signaling pathways related to angiogenesis, cell migration, death, and even differentiation are conserved between zebrafish and humans. Even minor but important details like structure of vascular growth factors (chemical signals that promote blood vessel formation) and their respective receptors are also well conserved. Such features in addition to the fast generation time and short life-span of zebrafish make them an attractive model that can be used for a fast screening of various anti-cancer drug targets. The possibility of introducing patient-derived tumors in zebrafish and predicting clinical efficacy of a certain drug opens up multiple avenues in our struggle to find the right cancer treatment for individual patients.
Edited by MaryAnn Bowyer
Rebelo de Almeida C, Mendes RV, Pezzarossa A, et al. Zebrafish xenografts as a fast screening platform for bevacizumab cancer therapy. Commun Biol. 2020;3(1):299. Published 2020 Jun 10. doi:10.1038/s42003-020-1015-0
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