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

Research output: Contribution to journal/periodicalArticleScientificpeer-review

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 languageEnglish
Pages (from-to)514-27
Number of pages14
JournalCell Reports
Volume6
Issue number3
DOIs
Publication statusPublished - 13 Feb 2014

Keywords

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

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