Gene expression patterns that characterize advanced stage serous ovarian cancers.

Journal Article (Journal Article)

OBJECTIVE: To identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis. METHODS: Using genome-wide expression analysis, we compared a series of 31 advanced stage (III or IV) serous ovarian cancers from patients who survived either less than 2 years or more than 7 years with three normal ovarian epithelial samples. Array findings were validated by analysis of expression of the insulin-like growth factor binding protein 2 (IGFBP2) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) genes using quantitative real-time polymerase chain reaction (QRT-PCR). RESULTS: Hierarchical clustering identified patterns of gene expression that distinguished cancer from normal ovarian epithelium. We also identified gene expression patterns that distinguish cancers on the basis of patient survival. These genes include many that are associated with immune function. Expression of IGFBP2 and TRAIL genes measured by array and QRT-PCR analysis demonstrated correlation coefficients of 0.63 and 0.78, respectively. CONCLUSION: Global expression analysis can identify expression patterns and individual genes that contribute to ovarian cancer development and outcome. Many of the genes that determine ovarian cancer survival are associated with the immune response, suggesting that immune function influences ovarian cancer virulence. With the generation of newer arrays with more transcripts, larger studies are possible to fully characterize genetic signatures that predict survival that may ultimately be used to guide therapeutic decision-making.

Full Text

Duke Authors

Cited Authors

  • Lancaster, JM; Dressman, HK; Whitaker, RS; Havrilesky, L; Gray, J; Marks, JR; Nevins, JR; Berchuck, A

Published Date

  • January 2004

Published In

Volume / Issue

  • 11 / 1

Start / End Page

  • 51 - 59

PubMed ID

  • 14706684

International Standard Serial Number (ISSN)

  • 1071-5576

Digital Object Identifier (DOI)

  • 10.1016/j.jsgi.2003.07.004


  • eng

Conference Location

  • United States