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


Authors: Almendro, V.; Cheng, Y. K.; Randles, A.; Itzkovitz, S.; Marusyk, A.; Ametller, E.; Gonzalez-Farre, X.; Munoz, M.; Russnes, H. G.; Helland, A.; Rye, I. H.; Borresen-Dale, A. L.; Maruyama, R.; van Oudenaarden, A.; Dowsett, M.; Jones, R. L.; Reis, J.; Gascon, P.; Gonen, M.; Michor, F.; Polyak, K.
Article 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 post-treatment 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: chemotherapy; progression; esophageal adenocarcinoma; neoadjuvant; resistance; pathological complete response; heterogeneity; breast-cancer cells; preoperative chemotherapy; carcinomas; molecular portraits
Journal Title: Cell Reports
Volume: 6
Issue: 3
ISSN: 2211-1247
Publisher: Cell Press  
Date Published: 2014-02-13
Start Page: 514
End Page: 527
Language: English
ACCESSION: WOS:000331168400010
DOI: 10.1016/j.celrep.2013.12.041
PROVIDER: wos
PMCID: PMC3928845
PUBMED: 24462293
Notes: Article -- Source: Wos
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Mithat Gonen
    1030 Gonen