American Association for Cancer Research
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00085472can143319-sup-138915_1_supp_2987685_ndnd5l.xlsx (11.65 kB)

Supplemental Table 1 from A Quantitative System for Studying Metastasis Using Transparent Zebrafish

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posted on 2023-03-30, 23:25 authored by Silja Heilmann, Kajan Ratnakumar, Erin M. Langdon, Emily R. Kansler, Isabella S. Kim, Nathaniel R. Campbell, Elizabeth B. Perry, Amy J. McMahon, Charles K. Kaufman, Ellen van Rooijen, William Lee, Christine A. Iacobuzio-Donahue, Richard O. Hynes, Leonard I. Zon, Joao B. Xavier, Richard M. White

Supplemental Table 1. This is data on the number of attempted zebrafish cell lines and our success rates in terms of long term propagation and weaning off fibronectin.

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ARTICLE ABSTRACT

Metastasis is the defining feature of advanced malignancy, yet remains challenging to study in laboratory environments. Here, we describe a high-throughput zebrafish system for comprehensive, in vivo assessment of metastatic biology. First, we generated several stable cell lines from melanomas of transgenic mitfa-BRAFV600E;p53−/− fish. We then transplanted the melanoma cells into the transparent casper strain to enable highly quantitative measurement of the metastatic process at single-cell resolution. Using computational image analysis of the resulting metastases, we generated a metastasis score, μ, that can be applied to quantitative comparison of metastatic capacity between experimental conditions. Furthermore, image analysis also provided estimates of the frequency of metastasis-initiating cells (∼1/120,000 cells). Finally, we determined that the degree of pigmentation is a key feature defining cells with metastatic capability. The small size and rapid generation of progeny combined with superior imaging tools make zebrafish ideal for unbiased high-throughput investigations of cell-intrinsic or microenvironmental modifiers of metastasis. The approaches described here are readily applicable to other tumor types and thus serve to complement studies also employing murine and human cell culture systems. Cancer Res; 75(20); 4272–82. ©2015 AACR.