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Gene Expression Profiles as Prognostic Markers in Women With Ovarian Cancer
  1. Kirsten M. Jochumsen, MD, PhD*,,
  2. Qihua Tan, PhD,,
  3. Estrid V. Høgdall, PhD§,
  4. Claus Høgdall, MD, DMSc,
  5. Susanne K. KjæR, MD, DMSc§,
  6. Jan BlaakæR, MD, DMSc,
  7. Torben A. Kruse, Lic Sc and
  8. Ole Mogensen, DMSc*
  1. *Department of Obstetrics and Gynecology, and
  2. Human MicroArray Centre, Department of Biochemistry, Pharmacology, and Genetics, Odense University Hospital; and
  3. Institute of Public Health, University of Southern Denmark, Odense;
  4. §Department of Virus, Hormones, and Cancer, Institute of Cancer Epidemiology, Danish Cancer Society; and
  5. The Juliane Marie Centre, Department of Gynecology, Rigshospitalet, Copenhagen; and
  6. Department of Obstetrics and Gynecology, Aarhus University Hospital, Skejby, Denmark.
  1. Address correspondence and reprint requests to Kirsten M. Jochumsen, Department of Obstetrics and Gynecology, Odense University Hospital, Sdr. Blvd 29, DK-5000 Odense C, Denmark. E-mail: kirsten.jochumsen{at}


The purpose was to find a gene expression profile that could distinguish short-term from long-term survivors in our collection of serous epithelial ovarian carcinomas. Furthermore, it should be able to stratify in an external validation set. Such a classifier profile will take us a step forward toward investigations for more individualized therapies and the use of gene expression profiles in the clinical practice. RNA from tumor tissue from 43 Danish patients with serous epithelial ovarian carcinoma (11 International Federation of Gynecology and Obstetrics [FIGO] stage I/II, 32 FIGO stage III/IV) was analyzed using Affymetrix U133 plus 2.0 microarrays. A multistep statistical procedure was applied to the data to find the gene set that optimally split the patients into short-term and long-term survivors in a Kaplan-Meier plot. A 14-gene prognostic profile with the ability to distinguish short-term survivors (median overall survival of 32 months) from long-term survivors (median overall survival not yet reached after a median follow-up of 76 months) with a P value of 3.4 × 10−9 was found. The prognostic gene set was also able to distinguish short-term from long-term survival in patients with advanced disease. Furthermore, its ability to classify in an external validation set was demonstrated. The identified 14-gene prognostic profile was able to predict survival (short- vs long-term survival) with a strength that is better than any other prognostic factor in epithelial ovarian cancer including FIGO stage. This stratification method may form the basis of determinations for new therapeutic approaches, as patients with poor prognosis could obtain the biggest advantage from new treatment modalities.

  • Epithelial ovarian cancer
  • Gene expression profiling
  • Microarray
  • Prognosis

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  • The Danish Cancer Society and The Danish Research Agency have financially supported the ongoing study on gene expression profiles and proteomic research in ovarian cancer. The Local Cancer Research Fund and Institute of Clinical Research at Odense University Hospital have given grants to this study.