Inference of Tumor Evolution during Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity
Name
Almendro-2014-Inference of Tumor E.pdf
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Author(s)
Almendro, Vanessa
Cheng, Yu-Kang
Randles, Amanda
Itzkovitz, Shalev
Marusyk, Andriy
Ametller, Elisabet
Gonzalez-Farre, Xavier
Russnes, Hege G.
Rye, Inga H.
Borresen-Dale, Anne-Lise
Date Issued
January 2014
Journal
Cell Reports
Publisher
Elsevier
Citation
Almendro, Vanessa, Yu-Kang Cheng, Amanda Randles, Shalev Itzkovitz, Andriy Marusyk, Elisabet Ametller, Xavier Gonzalez-Farre, et al. “Inference of Tumor Evolution During Chemotherapy by Computational Modeling and In Situ Analysis of Genetic and Phenotypic Cellular Diversity.” Cell Reports 6, no. 3 (February 2014): 514–527.
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Physics
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1016/j.celrep.2013.12.041
