Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

CiteULike is a free service for managing and discovering scholarly references - click here to get started.

Sign In to gain access to subscriptions and/or personal tools.
Journal of the Society for Gynecologic Investigation
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Lancaster, J. M.
Right arrow Articles by Berchuck, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lancaster, J. M.
Right arrow Articles by Dressman, H. K.
Right arrow Articles by Whitaker, R. S.
Right arrow Articles by Havrilesky, L.
Right arrow Articles by Gray, J.
Right arrow Articles by Marks, J. R.
Right arrow Articles by Nevins, J. R.
Right arrow Articles by Berchuck, A.
Right arrowPubmed/NCBI databases
*Compound via MeSH
*Substance via MeSH
Medline Plus Health Information
*Ovarian Cancer
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Gene Expression Patterns That Characterize Advanced Stage Serous Ovarian Cancers

Johnathan M. Lancaster, MD

Holly K. Dressman, PhD

Regina S. Whitaker

Laura Havrilesky, MD

Jonathan Gray, PhD, FRCP

Jeffrey R. Marks, PhD

Joseph R. Nevins, PhD

Departments of Obstetrics and Gynecology, Division of Gynecologic Oncology, Genetics, and Surgery, Duke University Medical Center, Durham, North Carolina, and Institute of Medical Genetics, University Hospital of Wales, Cardiff, United Kingdom

Andrew Berchuck, MD

Departments of Obstetrics and Gynecology, Division of Gynecologic Oncology, Genetics, and Surgery, Duke University Medical Center, Durham, North Carolina, and Institute of Medical Genetics, University Hospital of Wales, Cardiff, United Kingdom; berch001{at}mc.duke.edu

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 we 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 sutdies are possible to fully characterize genetic signatures fthat predict survival that may ultimately be used to guide therapeutic decision-making.

Key Words: Ovarian cancer • microarray analysis • immune function • survival

Journal of the Society for Gynecologic Investigation, Vol. 11, No. 1, 51-59 (2004)
DOI: 10.1016/j.jsgi.2003.07.004


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
JCOHome page
H. K. Dressman, A. Berchuck, G. Chan, J. Zhai, A. Bild, R. Sayer, J. Cragun, J. Clarke, R. S. Whitaker, L. Li, et al.
An Integrated Genomic-Based Approach to Individualized Treatment of Patients With Advanced-Stage Ovarian Cancer
J. Clin. Oncol., February 10, 2007; 25(5): 517 - 525.
[Abstract] [Full Text] [PDF]


Home page
Cancer Res.Home page
G. Castellano, J. F. Reid, P. Alberti, M. L. Carcangiu, A. Tomassetti, and S. Canevari
New Potential Ligand-Receptor Signaling Loops in Ovarian Cancer Identified in Multiple Gene Expression Studies
Cancer Res., November 15, 2006; 66(22): 10709 - 10719.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
A. Berchuck, E. S. Iversen, J. M. Lancaster, J. Pittman, J. Luo, P. Lee, S. Murphy, H. K. Dressman, P. G. Febbo, M. West, et al.
Patterns of Gene Expression That Characterize Long-term Survival in Advanced Stage Serous Ovarian Cancers
Clin. Cancer Res., May 15, 2005; 11(10): 3686 - 3696.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
L. C. Hartmann, K. H. Lu, G. P. Linette, W. A. Cliby, K. R. Kalli, D. Gershenson, R. C. Bast, J. Stec, N. Iartchouk, D. I. Smith, et al.
Gene Expression Profiles Predict Early Relapse in Ovarian Cancer after Platinum-Paclitaxel Chemotherapy
Clin. Cancer Res., March 15, 2005; 11(6): 2149 - 2155.
[Abstract] [Full Text] [PDF]