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Evolution of cellular morpho-phenotypes in cancer metastasis

Intratumoral heterogeneity greatly complicates the study of molecular mechanisms driving cancer progression and our ability to predict patient outcomes. Here we have developed an automated high-throughput cell-imaging platform (htCIP) that allows us to extract high-content information about individu...

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Autores principales: Wu, Pei-Hsun, Phillip, Jude M., Khatau, Shyam B., Chen, Wei-Chiang, Stirman, Jeffrey, Rosseel, Sophie, Tschudi, Katherine, Van Patten, Joshua, Wong, Michael, Gupta, Sonal, Baras, Alexander S., Leek, Jeffrey T., Maitra, Anirban, Wirtz, Denis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682070/
https://www.ncbi.nlm.nih.gov/pubmed/26675084
http://dx.doi.org/10.1038/srep18437
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author Wu, Pei-Hsun
Phillip, Jude M.
Khatau, Shyam B.
Chen, Wei-Chiang
Stirman, Jeffrey
Rosseel, Sophie
Tschudi, Katherine
Van Patten, Joshua
Wong, Michael
Gupta, Sonal
Baras, Alexander S.
Leek, Jeffrey T.
Maitra, Anirban
Wirtz, Denis
author_facet Wu, Pei-Hsun
Phillip, Jude M.
Khatau, Shyam B.
Chen, Wei-Chiang
Stirman, Jeffrey
Rosseel, Sophie
Tschudi, Katherine
Van Patten, Joshua
Wong, Michael
Gupta, Sonal
Baras, Alexander S.
Leek, Jeffrey T.
Maitra, Anirban
Wirtz, Denis
author_sort Wu, Pei-Hsun
collection PubMed
description Intratumoral heterogeneity greatly complicates the study of molecular mechanisms driving cancer progression and our ability to predict patient outcomes. Here we have developed an automated high-throughput cell-imaging platform (htCIP) that allows us to extract high-content information about individual cells, including cell morphology, molecular content and local cell density at single-cell resolution. We further develop a comprehensive visually-aided morpho-phenotyping recognition (VAMPIRE) tool to analyze irregular cellular and nuclear shapes in both 2D and 3D microenvironments. VAMPIRE analysis of ~39,000 cells from 13 previously sequenced patient-derived pancreatic cancer samples indicate that metastasized cells present significantly lower heterogeneity than primary tumor cells. We found the same morphological signature for metastasis for a cohort of 10 breast cancer cell lines. We further decipher the relative contributions to heterogeneity from cell cycle, cell-cell contact, cell stochasticity and heritable morphological variations.
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spelling pubmed-46820702015-12-18 Evolution of cellular morpho-phenotypes in cancer metastasis Wu, Pei-Hsun Phillip, Jude M. Khatau, Shyam B. Chen, Wei-Chiang Stirman, Jeffrey Rosseel, Sophie Tschudi, Katherine Van Patten, Joshua Wong, Michael Gupta, Sonal Baras, Alexander S. Leek, Jeffrey T. Maitra, Anirban Wirtz, Denis Sci Rep Article Intratumoral heterogeneity greatly complicates the study of molecular mechanisms driving cancer progression and our ability to predict patient outcomes. Here we have developed an automated high-throughput cell-imaging platform (htCIP) that allows us to extract high-content information about individual cells, including cell morphology, molecular content and local cell density at single-cell resolution. We further develop a comprehensive visually-aided morpho-phenotyping recognition (VAMPIRE) tool to analyze irregular cellular and nuclear shapes in both 2D and 3D microenvironments. VAMPIRE analysis of ~39,000 cells from 13 previously sequenced patient-derived pancreatic cancer samples indicate that metastasized cells present significantly lower heterogeneity than primary tumor cells. We found the same morphological signature for metastasis for a cohort of 10 breast cancer cell lines. We further decipher the relative contributions to heterogeneity from cell cycle, cell-cell contact, cell stochasticity and heritable morphological variations. Nature Publishing Group 2015-12-17 /pmc/articles/PMC4682070/ /pubmed/26675084 http://dx.doi.org/10.1038/srep18437 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Wu, Pei-Hsun
Phillip, Jude M.
Khatau, Shyam B.
Chen, Wei-Chiang
Stirman, Jeffrey
Rosseel, Sophie
Tschudi, Katherine
Van Patten, Joshua
Wong, Michael
Gupta, Sonal
Baras, Alexander S.
Leek, Jeffrey T.
Maitra, Anirban
Wirtz, Denis
Evolution of cellular morpho-phenotypes in cancer metastasis
title Evolution of cellular morpho-phenotypes in cancer metastasis
title_full Evolution of cellular morpho-phenotypes in cancer metastasis
title_fullStr Evolution of cellular morpho-phenotypes in cancer metastasis
title_full_unstemmed Evolution of cellular morpho-phenotypes in cancer metastasis
title_short Evolution of cellular morpho-phenotypes in cancer metastasis
title_sort evolution of cellular morpho-phenotypes in cancer metastasis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682070/
https://www.ncbi.nlm.nih.gov/pubmed/26675084
http://dx.doi.org/10.1038/srep18437
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