Priority Research Papers:
Immunocompetent mouse allograft models for development of therapies to target breast cancer metastasis
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Yuan Yang1,*, Howard H. Yang2,*, Ying Hu2, Peter H. Watson3, Huaitian Liu2, Thomas R. Geiger1, Miriam R. Anver4, Diana C. Haines4, Philip Martin4, Jeffrey E. Green1, Maxwell P. Lee2,*, Kent W. Hunter1,* and Lalage M. Wakefield1,*
1 Lab of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
2 High Dimension Data Analysis Group, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
3 British Columbia Cancer Agency, Vancouver Island Center, Victoria, British Columbia, Canada
4 Pathology Histotechnology Lab, Leidos Biomedical Research Inc., Frederick National Laboratory for Cancer Research, Frederick MD, USA
* These authors have contributed equally to this work
Lalage M. Wakefield, email:
Keywords: metastasis, breast cancer, immunocompetent mouse models, genomics, experimental therapeutics
Received: December 02, 2016 Accepted: February 18, 2017 Published: February 25, 2017
Effective drug development to combat metastatic disease in breast cancer would be aided by the availability of well-characterized preclinical animal models that (a) metastasize with high efficiency, (b) metastasize in a reasonable time-frame, (c) have an intact immune system, and (d) capture some of the heterogeneity of the human disease. To address these issues, we have assembled a panel of twelve mouse mammary cancer cell lines that can metastasize efficiently on implantation into syngeneic immunocompetent hosts. Genomic characterization shows that more than half of the 30 most commonly mutated genes in human breast cancer are represented within the panel. Transcriptomically, most of the models fall into the luminal A or B intrinsic molecular subtypes, despite the predominance of an aggressive, poorly-differentiated or spindled histopathology in all models. Patterns of immune cell infiltration, proliferation rates, apoptosis and angiogenesis differed significantly among models. Inherent within-model variability of the metastatic phenotype mandates large cohort sizes for intervention studies but may also capture some relevant non-genetic sources of variability. The varied molecular and phenotypic characteristics of this expanded panel of models should aid in model selection for development of antimetastatic therapies in vivo, and serve as a useful platform for predictive biomarker identification.
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