title: Mining gene expression profiles: expression signatures as cancer phenotypes.
abstract: Many examples highlight the power of gene expression profiles, or signatures, to inform an understanding of biological phenotypes. This is perhaps best seen in the context of cancer, where expression signatures have tremendous power to identify new subtypes and to predict clinical outcomes. Although the ability to interpret the meaning of the individual genes in these signatures remains a challenge, this does not diminish the power of the signature to characterize biological states. The use of these signatures as surrogate phenotypes has been particularly important, linking diverse experimental systems that dissect the complexity of biological systems with the in vivo setting in a way that was not previously feasible.
authors.affiliation: Duke Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina 27710, USA. nevin001@mc.duke.edu
authors.forename: Joseph R
authors.initials: JR
authors.lastname: Nevins
authors.forename: Anil
authors.initials: A
authors.lastname: Potti
mesh_terms: D045744:Cell Line, Tumor; D043171:Chromosomal Instability; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data / Q000639:trends; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D010641:Phenotype