Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Vanessa Almendro; Yu-Kang Cheng; Amanda Randles; Shalev Itzkovitz; Andriy Marusyk; Elisabet Ametller; Xavier Gonzalez-Farre; Montse Muñoz; Hege G Russnes; Aslaug 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

doi:10.1016/j.celrep.2013.12.041

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Vanessa Almendro, Yu-Kang Cheng, Amanda Randles, Shalev Itzkovitz, Andriy Marusyk, Elisabet Ametller, Xavier Gonzalez-Farre, Montse Muñoz, Hege G Russnes, Aslaug 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 MichorKornelia Polyak

Hubrecht Institute

Research output: Contribution to journal/periodical › Article › Scientific › peer-review

218 Citations (Scopus)

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.

Original language	English
Pages (from-to)	514-27
Number of pages	14
Journal	Cell Reports
Volume	6
Issue number	3
DOIs	https://doi.org/10.1016/j.celrep.2013.12.041
Publication status	Published - 13 Feb 2014

Keywords

Antineoplastic Agents
Breast Neoplasms
Cell Proliferation
Female
Genetic Heterogeneity
Genetic Variation
Genotype
Humans
Models, Biological
Phenotype

Access to Document

10.1016/j.celrep.2013.12.041

Cite this

Almendro, V., Cheng, Y.-K., Randles, A., Itzkovitz, S., Marusyk, A., Ametller, E., Gonzalez-Farre, X., Muñoz, M., Russnes, H. G., Helland, A., Rye, I. H., Borresen-Dale, A.-L., Maruyama, R., van Oudenaarden, A., Dowsett, M., Jones, R. L., Reis-Filho, J., Gascon, P., Gönen, M., ... Polyak, K. (2014). Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. Cell Reports, 6(3), 514-27. https://doi.org/10.1016/j.celrep.2013.12.041

@article{c4d5c535adb2491d8d799a81d948aefa,

title = "Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity",

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.",

keywords = "Antineoplastic Agents, Breast Neoplasms, Cell Proliferation, Female, Genetic Heterogeneity, Genetic Variation, Genotype, Humans, Models, Biological, Phenotype",

author = "Vanessa Almendro and Yu-Kang Cheng and Amanda Randles and Shalev Itzkovitz and Andriy Marusyk and Elisabet Ametller and Xavier Gonzalez-Farre and Montse Mu{\~n}oz and Russnes, {Hege G} and Aslaug Helland and Rye, {Inga H} and Anne-Lise Borresen-Dale and Reo Maruyama and {van Oudenaarden}, Alexander and Mitchell Dowsett and Jones, {Robin L} and Jorge Reis-Filho and Pere Gascon and Mithat G{\"o}nen and Franziska Michor and Kornelia Polyak",

year = "2014",

month = feb,

day = "13",

doi = "10.1016/j.celrep.2013.12.041",

language = "English",

volume = "6",

pages = "514--27",

journal = "Cell Reports",

issn = "2211-1247",

publisher = "Cell Press",

number = "3",

}

Almendro, V, Cheng, Y-K, Randles, A, Itzkovitz, S, Marusyk, A, Ametller, E, Gonzalez-Farre, X, Muñoz, M, Russnes, HG, Helland, A, Rye, IH, Borresen-Dale, A-L, Maruyama, R, van Oudenaarden, A, Dowsett, M, Jones, RL, Reis-Filho, J, Gascon, P, Gönen, M, Michor, F & Polyak, K 2014, 'Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity', Cell Reports, vol. 6, no. 3, pp. 514-27. https://doi.org/10.1016/j.celrep.2013.12.041

TY - JOUR

T1 - Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

AU - Almendro, Vanessa

AU - Cheng, Yu-Kang

AU - Randles, Amanda

AU - Itzkovitz, Shalev

AU - Marusyk, Andriy

AU - Ametller, Elisabet

AU - Gonzalez-Farre, Xavier

AU - Muñoz, Montse

AU - Russnes, Hege G

AU - Helland, Aslaug

AU - Rye, Inga H

AU - Borresen-Dale, Anne-Lise

AU - Maruyama, Reo

AU - van Oudenaarden, Alexander

AU - Dowsett, Mitchell

AU - Jones, Robin L

AU - Reis-Filho, Jorge

AU - Gascon, Pere

AU - Gönen, Mithat

AU - Michor, Franziska

AU - Polyak, Kornelia

PY - 2014/2/13

Y1 - 2014/2/13

N2 - 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.

AB - 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.

KW - Antineoplastic Agents

KW - Breast Neoplasms

KW - Cell Proliferation

KW - Female

KW - Genetic Heterogeneity

KW - Genetic Variation

KW - Genotype

KW - Humans

KW - Models, Biological

KW - Phenotype

U2 - 10.1016/j.celrep.2013.12.041

DO - 10.1016/j.celrep.2013.12.041

M3 - Article

C2 - 24462293

SN - 2211-1247

VL - 6

SP - 514

EP - 527

JO - Cell Reports

JF - Cell Reports

IS - 3

ER -

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Abstract

Keywords

Access to Document

Fingerprint

Cite this