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Citations to this article

Modeling metastasis biology and therapy in real time in the mouse lung
Arnulfo Mendoza, … , Lalage M. Wakefield, Chand Khanna
Arnulfo Mendoza, … , Lalage M. Wakefield, Chand Khanna
Published July 19, 2010
Citation Information: J Clin Invest. 2010;120(8):2979-2988. https://doi.org/10.1172/JCI40252.
View: Text | PDF | Corrigendum
Technical Advance Oncology Article has an altmetric score of 4

Modeling metastasis biology and therapy in real time in the mouse lung

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Abstract

Pulmonary metastasis remains the leading ca use of death for cancer patients. Opportunities to improve treatment outcomes for patients require new methods to study and view the biology of metastatic progression. Here, we describe an ex vivo pulmonary metastasis assay (PuMA) in which the metastatic progression of GFP-expressing cancer cells, from a single cell to the formation of multicellular colonies, in the mouse lung microenvironment was assessed in real time for up to 21 days. The biological validity of this assay was confirmed by its prediction of the in vivo behavior of a variety of high- and low-metastatic human and mouse cancer cell lines and the discrimination of tumor microenvironments in the lung that were most permissive to metastasis. Using this approach, we provide what we believe to be new insights into the importance of tumor cell interactions with the stromal components of the lung microenvironment. Finally, the translational utility of this assay was demonstrated through its use in the evaluation of therapeutics at discrete time points during metastatic progression. We believe that this assay system is uniquely capable of advancing our understanding of both metastasis biology and therapeutic strategies.

Authors

Arnulfo Mendoza, Sung-Hyeok Hong, Tanasa Osborne, Mohammed A. Khan, Kirk Campbell, Joseph Briggs, Ananth Eleswarapu, Lauren Buquo, Ling Ren, Stephen M. Hewitt, El-H. Dakir, Susan Garfield, Renard Walker, Glenn Merlino, Jeffrey E. Green, Kent W. Hunter, Lalage M. Wakefield, Chand Khanna

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Total citations by year

Year: 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2009 Total
Citations: 6 4 2 7 3 3 6 4 6 8 3 5 3 5 1 66
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