TY - JOUR

T1 - Gene expression profiles as prognostic markers in women with ovarian cancer

AU - Jochumsen, Kirsten M

AU - Tan, Qihua

AU - Høgdall, Estrid V

AU - Høgdall, Claus

AU - Kjaer, Susanne K

AU - Blaakaer, Jan

AU - Kruse, Torben A

AU - Mogensen, Ole

N1 - Keywords: Adult; Aged; Algorithms; Female; Gene Expression Profiling; Humans; Individualized Medicine; Middle Aged; Neoplasm Staging; Neoplasms, Glandular and Epithelial; Oligonucleotide Array Sequence Analysis; Ovarian Neoplasms; Predictive Value of Tests; Prognosis; Survival Analysis; Survivors; Tumor Markers, Biological

PY - 2009

Y1 - 2009

N2 - 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 x 10 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.

AB - 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 x 10 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.

U2 - 10.1111/IGC.0b013e3181a3cf55

DO - 10.1111/IGC.0b013e3181a3cf55

M3 - Journal article

C2 - 19823056

VL - 19

SP - 1205

EP - 1213

JO - International Journal of Gynecological Cancer

JF - International Journal of Gynecological Cancer

SN - 1048-891X

IS - 7

ER -