Successful prediction of prostate cancer recurrence by gene profiling in combination with clinical data: a 5-year follow-up study

Abstract

We show here that gene expression profiling, performed with conventional techniques and focused on a selected group of genes, when used in combination with standard clinical information, provides reliable prognostic prediction of prostate cancer (CaP). We showed previously that changes in the expression of metabolically related genes are involved in CaP progression. We then proceeded to search further for correlations between patients' gene profiling and recurrence with a 5-year follow-up study conducted on the same cohort of patients in which the molecular data were obtained. CaP prognosis was first assessed on the basis of gene expression profiling alone; then the result was compared with the prediction obtained using clinical and pathological information (Gleason score, Tumor-Node-Metastasis staging, prostate volume, or prostate-specific antigen levels at the time of diagnosis). The best result was obtained with a selected combination of gene profiling and clinical/pathological parameters, which resulted in prediction of recurrence in 95.7% of patients.