This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Berchuck, A. Articles by Marks, J. R. Search for Related Content PubMed PubMed Citation Articles by Berchuck, A. Articles by Marks, J. R.

Patterns of Gene Expression That Characterize Long-term Survival in Advanced Stage Serous Ovarian Cancers

Authors' Affiliations: Departments of ¹ Obstetrics and Gynecology/Division of Gynecologic Oncology, ² Department of Biostatistics and Bioinformatics, ³ Institute of Statistics and Decision Sciences, ⁴ Center for Applied Genomics and Technology, Departments of ⁵ Medicine and Molecular Genetics and Microbiology, and ⁶ Department of Surgery, Duke University Medical Center, Institute for Genome Sciences and Policy, Durham, North Carolina

Requests for reprints: Andrew Berchuck, Division of Gynecologic Oncology, Duke University Medical Center, Box 3079, Durham, NC 27710. Phone: 919-684-3765; Fax: 919-684-8719; E-mail: berch001{at}mc.duke.edu.

Purpose: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival.

Experimental Design: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays. This included 54 stage III/IV cases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models.

Results: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype.

Conclusions: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that early-stage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.

Key Words: ovarian cancer • serous • microarray • gene expression

This article has been cited by other articles:

				D. Mezzanzanica, M. Fabbi, M. Bagnoli, S. Staurengo, M. Losa, E. Balladore, P. Alberti, L. Lusa, A. Ditto, S. Ferrini, et al. Subcellular Localization of Activated Leukocyte Cell Adhesion Molecule Is a Molecular Predictor of Survival in Ovarian Carcinoma Patients Clin. Cancer Res., March 15, 2008; 14(6): 1726 - 1733. [Abstract] [Full Text] [PDF]

				K. A. Baggerly, K. R. Coombes, and E. S. Neeley Run Batch Effects Potentially Compromise the Usefulness of Genomic Signatures for Ovarian Cancer J. Clin. Oncol., March 1, 2008; 26(7): 1186 - 1187. [Full Text] [PDF]

				R. S. N. Fehrmann, X.-y. Li, A. G. J. van der Zee, S. de Jong, G. J. te Meerman, E. G. E. de Vries, and A. P. G. Crijns Profiling Studies in Ovarian Cancer: A Review Oncologist, August 1, 2007; 12(8): 960 - 966. [Abstract] [Full Text] [PDF]

				L. Song, J. Bedo, K. M. Borgwardt, A. Gretton, and A. Smola Gene selection via the BAHSIC family of algorithms Bioinformatics, July 1, 2007; 23(13): i490 - i498. [Abstract] [Full Text] [PDF]

				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]

				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]

				D. Seo, G. S. Ginsburg, and P. J. Goldschmidt-Clermont Gene Expression Analysis of Cardiovascular Diseases: Novel Insights Into Biology and Clinical Applications J. Am. Coll. Cardiol., July 18, 2006; 48(2): 227 - 235. [Abstract] [Full Text] [PDF]

				S. K. Murphy, Z. Huang, Y. Wen, M. A. Spillman, R. S. Whitaker, L. R. Simel, T. D. Nichols, J. R. Marks, and A. Berchuck Frequent IGF2/H19 Domain Epigenetic Alterations and Elevated IGF2 Expression in Epithelial Ovarian Cancer Mol. Cancer Res., April 1, 2006; 4(4): 283 - 292. [Abstract] [Full Text] [PDF]

				M. Komatsu, K. Hiyama, K. Tanimoto, M. Yunokawa, K. Otani, M. Ohtaki, E. Hiyama, J. Kigawa, M. Ohwada, M. Suzuki, et al. Prediction of individual response to platinum/paclitaxel combination using novel marker genes in ovarian cancers. Mol. Cancer Ther., March 1, 2006; 5(3): 767 - 775. [Abstract] [Full Text] [PDF]

				Z. Huang, Y. Wen, R. Shandilya, J. R. Marks, A. Berchuck, and S. K. Murphy High throughput detection of M6P/IGF2R intronic hypermethylation and LOH in ovarian cancer Nucleic Acids Res., January 23, 2006; 34(2): 555 - 563. [Abstract] [Full Text] [PDF]

				D. Spentzos, D. A. Levine, S. Kolia, H. Otu, J. Boyd, T. A. Libermann, and S. A. Cannistra Unique Gene Expression Profile Based on Pathologic Response in Epithelial Ovarian Cancer J. Clin. Oncol., November 1, 2005; 23(31): 7911 - 7918. [Abstract] [Full Text] [PDF]