Abstract C47: Inference of tumor evolution during chemotherapy by computational modeling and single cell analysis of diversity.

Abstract

Abstract Cancer therapy exerts a strong selection that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here we report the analysis of single-cell heterogeneity of genetic and phenotypic features and their spatial distribution in breast tumors pre and post neoadjuvant therapy. We found that broad intratumor genetic diversity is tumor subtype specific but does not change significantly during treatment. However, we observed significant alterations in the spatial distribution of cells after chemotherapy whereas adjacent tumor cells were more likely to be genetically divergent yet phenotypically similar. We then developed a stochastic computational model to infer tumor growth patterns and evolutionary dynamics from these topologic features. Lastly, we found that lower pretreatment genetic diversity is associated with a better response, emphasizing the clinical utility of our study. Our results highlight the importance of an integrated analysis of genotype and phenotype of single cells in intact tissue to predict how tumors evolve. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C47. Citation Format: Vanessa Almendro, Yu-Kang Cheng, Mithat Gönen, Shalev Itzkovitz, Andriy Marusyk, Elisabet Ametller, Xavier Gonzalez-Farre, Montse Muñoz, Hege Russnes, Åslaug Helland, Inga Rye, Anne Lise Borresen-Dale, Reo Maruyama, Alexander van Oudenaarden, Mitchell Dowsett, Robin L. Jones, Jorge Reis-Filho, Pere Gascon, Franziska Michor, Kornelia Polyak. Inference of tumor evolution during chemotherapy by computational modeling and single cell analysis of diversity. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C47.