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Single-cell morphology encodes metastatic potential
A central goal of precision medicine is to predict disease outcomes and design treatments based on multidimensional information from afflicted cells and tissues. Cell morphology is an emergent readout of the molecular underpinnings of a cell’s functions and, thus, can be used as a method to define t...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976289/ https://www.ncbi.nlm.nih.gov/pubmed/32010778 http://dx.doi.org/10.1126/sciadv.aaw6938 |
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author | Wu, Pei-Hsun Gilkes, Daniele M. Phillip, Jude M. Narkar, Akshay Cheng, Thomas Wen-Tao Marchand, Jorge Lee, Meng-Horng Li, Rong Wirtz, Denis |
author_facet | Wu, Pei-Hsun Gilkes, Daniele M. Phillip, Jude M. Narkar, Akshay Cheng, Thomas Wen-Tao Marchand, Jorge Lee, Meng-Horng Li, Rong Wirtz, Denis |
author_sort | Wu, Pei-Hsun |
collection | PubMed |
description | A central goal of precision medicine is to predict disease outcomes and design treatments based on multidimensional information from afflicted cells and tissues. Cell morphology is an emergent readout of the molecular underpinnings of a cell’s functions and, thus, can be used as a method to define the functional state of an individual cell. We measured 216 features derived from cell and nucleus morphology for more than 30,000 breast cancer cells. We find that single cell–derived clones (SCCs) established from the same parental cells exhibit distinct and heritable morphological traits associated with genomic (ploidy) and transcriptomic phenotypes. Using unsupervised clustering analysis, we find that the morphological classes of SCCs predict distinct tumorigenic and metastatic potentials in vivo using multiple mouse models of breast cancer. These findings lay the groundwork for using quantitative morpho-profiling in vitro as a potentially convenient and economical method for phenotyping function in cancer in vivo. |
format | Online Article Text |
id | pubmed-6976289 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-69762892020-01-31 Single-cell morphology encodes metastatic potential Wu, Pei-Hsun Gilkes, Daniele M. Phillip, Jude M. Narkar, Akshay Cheng, Thomas Wen-Tao Marchand, Jorge Lee, Meng-Horng Li, Rong Wirtz, Denis Sci Adv Research Articles A central goal of precision medicine is to predict disease outcomes and design treatments based on multidimensional information from afflicted cells and tissues. Cell morphology is an emergent readout of the molecular underpinnings of a cell’s functions and, thus, can be used as a method to define the functional state of an individual cell. We measured 216 features derived from cell and nucleus morphology for more than 30,000 breast cancer cells. We find that single cell–derived clones (SCCs) established from the same parental cells exhibit distinct and heritable morphological traits associated with genomic (ploidy) and transcriptomic phenotypes. Using unsupervised clustering analysis, we find that the morphological classes of SCCs predict distinct tumorigenic and metastatic potentials in vivo using multiple mouse models of breast cancer. These findings lay the groundwork for using quantitative morpho-profiling in vitro as a potentially convenient and economical method for phenotyping function in cancer in vivo. American Association for the Advancement of Science 2020-01-22 /pmc/articles/PMC6976289/ /pubmed/32010778 http://dx.doi.org/10.1126/sciadv.aaw6938 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Wu, Pei-Hsun Gilkes, Daniele M. Phillip, Jude M. Narkar, Akshay Cheng, Thomas Wen-Tao Marchand, Jorge Lee, Meng-Horng Li, Rong Wirtz, Denis Single-cell morphology encodes metastatic potential |
title | Single-cell morphology encodes metastatic potential |
title_full | Single-cell morphology encodes metastatic potential |
title_fullStr | Single-cell morphology encodes metastatic potential |
title_full_unstemmed | Single-cell morphology encodes metastatic potential |
title_short | Single-cell morphology encodes metastatic potential |
title_sort | single-cell morphology encodes metastatic potential |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976289/ https://www.ncbi.nlm.nih.gov/pubmed/32010778 http://dx.doi.org/10.1126/sciadv.aaw6938 |
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