4.7 Article

Zebrafish xenografts as a fast screening platform for bevacizumab cancer therapy

Journal

COMMUNICATIONS BIOLOGY
Volume 3, Issue 1, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s42003-020-1015-0

Keywords

-

Funding

  1. FCT/Lisboa2020 [LISBOA-01-0145-FEDER-022170]
  2. [FCT-PTDC/MEC-ONC/31627/2017]

Ask authors/readers for more resources

Rebelo de Almeida et al. describe the application of zebrafish tumor xenografts (zAvatars) to analyse the efficacy of bevacizumab (FDA approved drug) to treat cancer patients with highly variable outcomes. The authors suggest that these zAvatars could be used as a predictive model to determine whether or not bevacizumab treatment would be efficient for individual patients. Despite promising preclinical results, average response rates to anti-VEGF therapies, such as bevacizumab, are reduced for most cancers, while incurring in remarkable costs and side effects. Currently, there are no biomarkers available to select patients that can benefit from this therapy. Depending on the individual tumor, anti-VEGF therapies can either block or promote metastasis. In this context, an assay able to predict individual responses prior to treatment, including the impact on metastasis would prove of great value to guide treatment options. Here we show that zebrafish xenografts are able to reveal different responses to bevacizumab in just 4 days, evaluating not only individual tumor responses but also the impact on angiogenesis and micrometastasis. Importantly, we perform proof-of-concept experiments where clinical responses in patients were compared with their matching zebrafish Patient-Derived Xenografts - zAvatars, opening the possibility of using the zebrafish model to screen bevacizumab therapy in a personalized manner.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available