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A metastasis map of human cancer cell lines

Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical owing to the complexity of in vivo models. Here we introduce an in vivo barcoding strategy that is capable of determining the metastatic potential of human cancer cell lines in mouse xen...

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Autores principales: Jin, Xin, Demere, Zelalem, Nair, Karthik, Ali, Ahmed, Ferraro, Gino B., Natoli, Ted, Deik, Amy, Petronio, Lia, Tang, Andrew A., Zhu, Cong, Wang, Li, Rosenberg, Danny, Mangena, Vamsi, Roth, Jennifer, Chung, Kwanghun, Jain, Rakesh K., Clish, Clary B., Vander Heiden, Matthew G., Golub, Todd R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8439149/
https://www.ncbi.nlm.nih.gov/pubmed/33299191
http://dx.doi.org/10.1038/s41586-020-2969-2
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author Jin, Xin
Demere, Zelalem
Nair, Karthik
Ali, Ahmed
Ferraro, Gino B.
Natoli, Ted
Deik, Amy
Petronio, Lia
Tang, Andrew A.
Zhu, Cong
Wang, Li
Rosenberg, Danny
Mangena, Vamsi
Roth, Jennifer
Chung, Kwanghun
Jain, Rakesh K.
Clish, Clary B.
Vander Heiden, Matthew G.
Golub, Todd R.
author_facet Jin, Xin
Demere, Zelalem
Nair, Karthik
Ali, Ahmed
Ferraro, Gino B.
Natoli, Ted
Deik, Amy
Petronio, Lia
Tang, Andrew A.
Zhu, Cong
Wang, Li
Rosenberg, Danny
Mangena, Vamsi
Roth, Jennifer
Chung, Kwanghun
Jain, Rakesh K.
Clish, Clary B.
Vander Heiden, Matthew G.
Golub, Todd R.
author_sort Jin, Xin
collection PubMed
description Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical owing to the complexity of in vivo models. Here we introduce an in vivo barcoding strategy that is capable of determining the metastatic potential of human cancer cell lines in mouse xenografts at scale. We validated the robustness, scalability and reproducibility of the method and applied it to 500 cell lines(1,2) spanning 21 types of solid tumour. We created a first-generation metastasis map (MetMap) that reveals organ-specific patterns of metastasis, enabling these patterns to be associated with clinical and genomic features. We demonstrate the utility of MetMap by investigating the molecular basis of breast cancers capable of metastasizing to the brain—a principal cause of death in patients with this type of cancer. Breast cancers capable of metastasizing to the brain showed evidence of altered lipid metabolism. Perturbation of lipid metabolism in these cells curbed brain metastasis development, suggesting a therapeutic strategy to combat the disease and demonstrating the utility of MetMap as a resource to support metastasis research.
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spelling pubmed-84391492021-09-14 A metastasis map of human cancer cell lines Jin, Xin Demere, Zelalem Nair, Karthik Ali, Ahmed Ferraro, Gino B. Natoli, Ted Deik, Amy Petronio, Lia Tang, Andrew A. Zhu, Cong Wang, Li Rosenberg, Danny Mangena, Vamsi Roth, Jennifer Chung, Kwanghun Jain, Rakesh K. Clish, Clary B. Vander Heiden, Matthew G. Golub, Todd R. Nature Article Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical owing to the complexity of in vivo models. Here we introduce an in vivo barcoding strategy that is capable of determining the metastatic potential of human cancer cell lines in mouse xenografts at scale. We validated the robustness, scalability and reproducibility of the method and applied it to 500 cell lines(1,2) spanning 21 types of solid tumour. We created a first-generation metastasis map (MetMap) that reveals organ-specific patterns of metastasis, enabling these patterns to be associated with clinical and genomic features. We demonstrate the utility of MetMap by investigating the molecular basis of breast cancers capable of metastasizing to the brain—a principal cause of death in patients with this type of cancer. Breast cancers capable of metastasizing to the brain showed evidence of altered lipid metabolism. Perturbation of lipid metabolism in these cells curbed brain metastasis development, suggesting a therapeutic strategy to combat the disease and demonstrating the utility of MetMap as a resource to support metastasis research. Nature Publishing Group UK 2020-12-09 2020 /pmc/articles/PMC8439149/ /pubmed/33299191 http://dx.doi.org/10.1038/s41586-020-2969-2 Text en © The Author(s), under exclusive licence to Springer Nature Limited 2020, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jin, Xin
Demere, Zelalem
Nair, Karthik
Ali, Ahmed
Ferraro, Gino B.
Natoli, Ted
Deik, Amy
Petronio, Lia
Tang, Andrew A.
Zhu, Cong
Wang, Li
Rosenberg, Danny
Mangena, Vamsi
Roth, Jennifer
Chung, Kwanghun
Jain, Rakesh K.
Clish, Clary B.
Vander Heiden, Matthew G.
Golub, Todd R.
A metastasis map of human cancer cell lines
title A metastasis map of human cancer cell lines
title_full A metastasis map of human cancer cell lines
title_fullStr A metastasis map of human cancer cell lines
title_full_unstemmed A metastasis map of human cancer cell lines
title_short A metastasis map of human cancer cell lines
title_sort metastasis map of human cancer cell lines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8439149/
https://www.ncbi.nlm.nih.gov/pubmed/33299191
http://dx.doi.org/10.1038/s41586-020-2969-2
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