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About the Authors:
Ying Hu
Affiliation: Center for Biomedical Informatics and Information Technology, Bethesda, Maryland, United States of America
Ling Bai
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Thomas Geiger
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Natalie Goldberger
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Renard C. Walker
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Jeffery E. Green
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Lalage M. Wakefield
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Kent W. Hunter
* E-mail: [email protected]
Affiliation: Laboratory of Cancer Biology and Genetics, CCR, NCI, NIH, Bethesda, Maryland, United States of America
Introduction
The past decades have seen significant advances in our understanding of and ability to model breast cancer. The advent of genome-wide expression profiling has led to the development of prognostic gene signatures [1] and improved molecular subtyping [2] that can stratify tumors into groups with different clinical outcomes. These molecular subtypes express signatures similar to those of different cellular components of the mammary duct, including both luminal and basal cell types, and are thought to reflect contributions from the tumor cell type of origin and somatic mutations. The subtyping tools have also been applied to mouse models to gain better understanding of the particular class of breast tumors that the models may represent [3]. Investigators can thus better focus on appropriate models for further characterization or translational studies of breast cancer subtypes of interest. This improved understanding of breast cancer may also permit more sophisticated targeting of particular somatic events associated with the different breast cancer subtypes [4] to the presumptive cell of origin in future mouse models to further improve our understanding of this pervasive disease.
In addition to cell of origin and somatic mutation events, studies over the past 10 years have demonstrated that genetic polymorphism can significantly affect gene expression. Studies in a variety of species have shown that the expression of a significant fraction of the genome can...