A Quantitative System for Studying Metastasis Using Transparent Zebrafish.
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-BRAF(V600E);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.
Memorial Sloan Kettering Cancer Center, Computational Biology.
Silja
S
Heilmann
Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
Kajan
K
Ratnakumar
Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
Erin
E
Langdon
Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
Emily
E
Kansler
Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
Isabella
I
Kim
Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program.
Nathaniel R
NR
Campbell
Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
Elizabeth
E
Perry
Massachusetts Institute of Technology, David Koch Institute for Integrated Cancer Biology.|Howard Hughes Medical Institute.
Amy
A
McMahon
Children's Hospital Boston.|Harvard Medical School.|Dana Farber Cancer Institute.|Howard Hughes Medical Institute.
Charles
C
Kaufman
Children's Hospital Boston.|Harvard Medical School.|Howard Hughes Medical Institute.
Ellen
E
van Rooijen
Memorial Sloan Kettering Cancer Center, Computational Biology.
William
W
Lee
Memorial Sloan Kettering Cancer Center, Pathology.
Christine
C
Iacobuzio-Donahue
Massachusetts Institute of Technology, David Koch Institute for Integrated Cancer Biology.|Howard Hughes Medical Institute.
Richard
R
Hynes
Children's Hospital Boston.|Harvard Medical School.|Dana Farber Cancer Institute.|Howard Hughes Medical Institute.
Leonard
L
Zon
Memorial Sloan Kettering Cancer Center, Computational Biology.
Joao
J
Xavier
Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.|Weill Cornell Medical College.
Richard
RM
White
D000465:Algorithms; D000818:Animals; D030801:Animals, Genetically Modified; D045744:Cell Line, Tumor; D004195:Disease Models, Animal; D020869:Gene Expression Profiling; D008545:Melanoma / Q000235:genetics / Q000378:metabolism / Q000473:pathology; D008954:Models, Biological; D009154:Mutation; D009362:Neoplasm Metastasis; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism / Q000473:pathology*; D059467:Transcriptome; D015027:Zebrafish