A pathway-based approach to identify molecular biomarkers in cancer.

Published

Journal Article

Many examples highlight the power of gene expression profiles, or signatures, to provide an understanding of biological phenotypes. This is best seen in the context of cancer, where expression signatures have tremendous power to identify new cancer subtypes and to predict clinical outcomes. Gene expression profiles have been developed to personalize medicine, accurately predicting disease recurrence and tumor response to therapy. The use of these signatures as surrogate phenotypes allows us to link diverse experimental systems, which dissect the complexity of biological systems, with the in vivo setting in a way that was not previously feasible. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual cancer patient.

Full Text

Duke Authors

Cited Authors

  • Stevenson, M; Potti, A

Published Date

  • July 2012

Published In

Volume / Issue

  • 19 Suppl 3 /

Start / End Page

  • S620 - S624

PubMed ID

  • 22048630

Pubmed Central ID

  • 22048630

Electronic International Standard Serial Number (EISSN)

  • 1534-4681

Digital Object Identifier (DOI)

  • 10.1245/s10434-011-1855-4

Language

  • eng

Conference Location

  • United States