Abstract
Abstract The pre-clinical validation of prognostic gene candidates in large independent patient cohorts is a pre-requisite for the development of robust biomarkers. We earlier implemented an online tool to assess the prognostic or predictive value of the expression levels of all microarray quantified genes in breast cancer patients. In present study, we further expanded our database, added additional analytical options and implemented the tool for ovarian cancer patients. The database was set up using gene expression data and survival information of breast and ovarian cancer patients downloaded from GEO and TCGA (Affymetrix HGU133A, HGU133A 2.0 and HGU133+2 microarrays). After quality control and normalization only probes present on all three Affymetrix platforms were retained (n=22,277). Patients can be stratified into the various robust subtypes either by histology or by various gene expression profiling based methods. To analyze the prognostic value of the selected gene in the various cohorts the patients are divided into two groups according to the median expression of the gene. A Kaplan-Meier survival plot is generated and significance is computed. All together 2,472 breast cancer patients and 1,390 ovarian cancer patients were entered into the database. These groups can be compared using relapse free survival (n=2,414 in breast cancer and 1,090 in ovarian cancer) or overall survival (n=463 and n=1,290). Follow-up threshold has been implemented to exclude long-term effects. The combination of several probe sets can be employed to assess the mean of their expression as a multigene predictor of survival and therapy efficiency. In summary, we expanded our global online biomarker validation platform to mine all available microarray data to assess the prognostic power of 22,277 genes in 2,472 breast and 1,390 ovarian cancer patients. The tool can be accessed online at: www.kmplot.com/breast and www.kmplot.com/dev/ovar. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-07-18.
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