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Cell Rep. 2014 Feb 13;6(3):514-27. doi: 10.1016/j.celrep.2013.12.041. Epub 2014 Jan 23.

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

Author information

1
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Department of Medical Oncology, Hospital Clinic, Institut d'Investigacions Biomediques August Pi i Sunyer, Barcelona 08036, Spain.
2
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.
3
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA; Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA.
4
Departments of Physics and Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
5
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
6
Department of Medical Oncology, Hospital Clinic, Institut d'Investigacions Biomediques August Pi i Sunyer, Barcelona 08036, Spain.
7
Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, Norway; K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0316, Norway; Department of Pathology, Oslo University Hospital, Oslo 0424, Norway.
8
Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, Norway; Department of Oncology, Oslo University Hospital, Oslo 0424, Norway; Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0316, Norway.
9
Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo 0424, Norway; K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0316, Norway.
10
Departments of Physics and Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT, Utrecht, the Netherlands.
11
The Royal Marsden Hospital, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London SW3 6JJ, UK.
12
The Royal Marsden Hospital, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London SW3 6JJ, UK; Seattle Cancer Care Alliance, Seattle, WA 98109-1023, USA.
13
The Royal Marsden Hospital, The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London SW3 6JJ, UK; Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
14
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
15
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. Electronic address: michor@jimmy.harvard.edu.
16
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute, Cambridge, MA 02142, USA. Electronic address: kornelia_polyak@dfci.harvard.edu.

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.

PMID:
24462293
PMCID:
PMC3928845
DOI:
10.1016/j.celrep.2013.12.041
[Indexed for MEDLINE]
Free PMC Article
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