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A Quantitative System for Studying Metastasis Using Transparent Zebrafish.
Heilmann, Silja; Ratnakumar, Kajan; Langdon, Erin; Kansler, Emily; Kim, Isabella; Campbell, Nathaniel R; Perry, Elizabeth; McMahon, Amy; Kaufman, Charles; van Rooijen, Ellen; Lee, William; Iacobuzio-Donahue, Christine; Hynes, Richard; Zon, Leonard; Xavier, Joao; White, Richard.
Afiliação
  • Heilmann S; Memorial Sloan Kettering Cancer Center, Computational Biology.
  • Ratnakumar K; Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
  • Langdon E; Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
  • Kansler E; Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
  • Kim I; Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
  • Campbell NR; Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program.
  • Perry E; Memorial Sloan Kettering Cancer Center, Cancer Biology & Genetics.
  • McMahon A; Massachusetts Institute of Technology, David Koch Institute for Integrated Cancer Biology.
  • Kaufman C; Howard Hughes Medical Institute.
  • van Rooijen E; Children's Hospital Boston.
  • Lee W; Harvard Medical School.
  • Iacobuzio-Donahue C; Dana Farber Cancer Institute.
  • Hynes R; Howard Hughes Medical Institute.
  • Zon L; Children's Hospital Boston.
  • Xavier J; Harvard Medical School.
  • White RM; Howard Hughes Medical Institute.
Cancer Res ; 75(20): 4272-4282, 2015 10 15.
Article em En | MEDLINE | ID: mdl-26282170
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-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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peixe-Zebra / Modelos Biológicos / Neoplasias Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peixe-Zebra / Modelos Biológicos / Neoplasias Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2015 Tipo de documento: Article