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About the Authors:
Sol Efroni
Contributed equally to this work with: Sol Efroni, Rotem Ben-Hamo
Affiliation: The Mina & Everard Faculty of Life Science, Bar Ilan University, Ramat Gan, Israel
Rotem Ben-Hamo
Contributed equally to this work with: Sol Efroni, Rotem Ben-Hamo
Affiliation: The Mina & Everard Faculty of Life Science, Bar Ilan University, Ramat Gan, Israel
Michael Edmonson
Affiliation: Laboratory of Population Genetics, National Institutes of Health, Bethesda, Maryland, United States of America
Sharon Greenblum
Affiliation: Laboratory of Population Genetics, National Institutes of Health, Bethesda, Maryland, United States of America
Carl F. Schaefer
Affiliation: National Cancer Institute Center for Biomedical Informatics and Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America
Kenneth H. Buetow
* E-mail: [email protected]
Affiliations Laboratory of Population Genetics, National Institutes of Health, Bethesda, Maryland, United States of America, National Cancer Institute Center for Biomedical Informatics and Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America
Introduction
Biologic phenotypes emerge as a consequence of genes interacting through complex networks. Oncogenesis has been shown to be dependent on biologic networks that control processes such as apoptosis, senescence, proliferation, and angiogenesis [1], [2]. However, it is clear that current knowledge of which processes influence diverse cancer phenotypes is incomplete. This is especially true when it comes to understanding processes associated with disease outcome.
A complex collection of genomic alterations occur during tumor cell evolution, including mutations, translocations, and copy number alterations. For example, genome-wide analysis of breast tumors by numerous techniques have reproducibly demonstrated recurrent patterns of copy number alteration (CNA) [3], [4], [5], [6], [7], [8], [9], [10], [11]. The expression of genes within these altered segments has been demonstrated to be correlated with the copy number state of the region [3], [9], [12], [13], [14], [15], [16], [17], [18], [19]. However, it is unclear whether these recurrent patterns represent the most important set of CNAs or represent only a subset of key regions.
Patterns of copy number alteration have proven valuable in classification of cancer subtypes and can serve as predictors of patient outcome [19]. These alterations target genes that influence networks that provide the tumors with a selective advantage over cells of normal composition. Given their association with outcome, it is likely they also...