Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity
Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-...
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Elsevier
2014-02-01
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Series: | Cell Reports |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2211124713007997 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Vanessa Almendro Yu-Kang Cheng Amanda Randles Shalev Itzkovitz Andriy Marusyk Elisabet Ametller Xavier Gonzalez-Farre Montse Muñoz Hege G. Russnes Åslaug Helland Inga H. Rye Anne-Lise Borresen-Dale Reo Maruyama Alexander van Oudenaarden Mitchell Dowsett Robin L. Jones Jorge Reis-Filho Pere Gascon Mithat Gönen Franziska Michor Kornelia Polyak |
spellingShingle |
Vanessa Almendro Yu-Kang Cheng Amanda Randles Shalev Itzkovitz Andriy Marusyk Elisabet Ametller Xavier Gonzalez-Farre Montse Muñoz Hege G. Russnes Åslaug Helland Inga H. Rye Anne-Lise Borresen-Dale Reo Maruyama Alexander van Oudenaarden Mitchell Dowsett Robin L. Jones Jorge Reis-Filho Pere Gascon Mithat Gönen Franziska Michor Kornelia Polyak Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity Cell Reports |
author_facet |
Vanessa Almendro Yu-Kang Cheng Amanda Randles Shalev Itzkovitz Andriy Marusyk Elisabet Ametller Xavier Gonzalez-Farre Montse Muñoz Hege G. Russnes Åslaug Helland Inga H. Rye Anne-Lise Borresen-Dale Reo Maruyama Alexander van Oudenaarden Mitchell Dowsett Robin L. Jones Jorge Reis-Filho Pere Gascon Mithat Gönen Franziska Michor Kornelia Polyak |
author_sort |
Vanessa Almendro |
title |
Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity |
title_short |
Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity |
title_full |
Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity |
title_fullStr |
Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity |
title_full_unstemmed |
Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity |
title_sort |
inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity |
publisher |
Elsevier |
series |
Cell Reports |
issn |
2211-1247 |
publishDate |
2014-02-01 |
description |
Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. |
url |
http://www.sciencedirect.com/science/article/pii/S2211124713007997 |
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doaj-9aab389303f9453b895d7dc8459382532020-11-24T21:55:28ZengElsevierCell Reports2211-12472014-02-016351452710.1016/j.celrep.2013.12.041Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular DiversityVanessa Almendro0Yu-Kang Cheng1Amanda Randles2Shalev Itzkovitz3Andriy Marusyk4Elisabet Ametller5Xavier Gonzalez-Farre6Montse Muñoz7Hege G. Russnes8Åslaug Helland9Inga H. Rye10Anne-Lise Borresen-Dale11Reo Maruyama12Alexander van Oudenaarden13Mitchell Dowsett14Robin L. Jones15Jorge Reis-Filho16Pere Gascon17Mithat Gönen18Franziska Michor19Kornelia Polyak20Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USADepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USADepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USADepartments of Physics and Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USADepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USADepartment of Medical Oncology, Hospital Clinic, Institut d’Investigacions Biomediques August Pi i Sunyer, Barcelona 08036, SpainDepartment of Medical Oncology, Hospital Clinic, Institut d’Investigacions Biomediques August Pi i Sunyer, Barcelona 08036, SpainDepartment of Medical Oncology, Hospital Clinic, Institut d’Investigacions Biomediques August Pi i Sunyer, Barcelona 08036, SpainDepartment of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, NorwayDepartment of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, NorwayDepartment of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, NorwayDepartment of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, NorwayDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USADepartments of Physics and Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USAThe Royal Marsden Hospital, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London SW3 6JJ, UKThe Royal Marsden Hospital, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London SW3 6JJ, UKThe Royal Marsden Hospital, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London SW3 6JJ, UKDepartment of Medical Oncology, Hospital Clinic, Institut d’Investigacions Biomediques August Pi i Sunyer, Barcelona 08036, SpainDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USADepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USADepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USACancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.http://www.sciencedirect.com/science/article/pii/S2211124713007997 |