Research Papers:
Treatment-induced cell cycle kinetics dictate tumor response to chemotherapy
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Abstract
Robin M. Hallett3, Cheng Huang1,3, Ali Motazedian1,3,6, Stefanie Auf der Mauer4, Gregory R. Pond5, John A. Hassell2,3, Robert E. Nordon4, Jonathan S. Draper1,2,3
1McMaster Stem Cell and Cancer Research Institute, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON L8N 3Z5, Canada
2Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8N 3Z5, Canada
3Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada
4Graduate School of Biomedical Engineering, University of New South Wales, Sydney 2052, Australia
5Department of Oncology, McMaster University, Hamilton, ON L8N 3Z5, Canada
6Murdoch Children's Research Institute, The Royal Children's Hospital, Parkville, Victoria 3052, Australia
Correspondence to:
Jonathan S. Draper, e-mail: [email protected]
Keywords: Breast cancer, chemotherapy, cell cycle, p53
Received: January 05, 2015 Accepted: January 11, 2015 Published: February 07, 2015
ABSTRACT
Chemotherapy fails to provide durable cure for the majority of cancer patients. To identify mechanisms associated with chemotherapy resistance, we identified genes differentially expressed before and after chemotherapeutic treatment of breast cancer patients. Treatment response resulted in either increased or decreased cell cycle gene expression. Tumors in which cell cycle gene expression was increased by chemotherapy were likely to be chemotherapy sensitive, whereas tumors in which cell cycle gene transcripts were decreased by chemotherapy were resistant to these agents. A gene expression signature that predicted these changes proved to be a robust and novel index that predicted the response of patients with breast, ovarian, and colon tumors to chemotherapy. Investigations in tumor cell lines supported these findings, and linked treatment induced cell cycle changes with p53 signaling and G1/G0 arrest. Hence, chemotherapy resistance, which can be predicted based on dynamics in cell cycle gene expression, is associated with TP53 integrity.
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