Gene panel model predictive of outcome in patients with prostate cancer

Abstract

In men at high risk for prostate cancer, established clinical and pathological parameters provide only limited prognostic information. Here we analyzed a French cohort of 103 prostate cancer patients and developed a gene panel model predictive of outcome in this group of patients. The model comprised of a 15-gene TaqMan Low-Density Array (TLDA) card, with gene expressions compared to a standardized reference. The RQ value for each gene was calculated, and a scoring system was developed. Summing all the binary scores (0 or 1) corresponding to the 15 genes, a global score is obtained between 0 and 15. This global score can be compared to Gleason score (0 to 10) by recalculating it into a 0-10 scaled score. A scaled score ≥2 suggested that the patient is suffering from a prostate cancer, and a scaled score ≥7 flagged aggressive cancer. Statistical analyses demonstrated a strongly significant linear correlation (p=3.50E-08) between scaled score and Gleason score for this prostate cancer cohort (N=103). These results support the capacity of this designed 15 target gene TLDA card approach to predict outcome in prostate cancer, opening up a new avenue for personalized medicine through future independent replication and applications for rapid identification of aggressive prostate cancer phenotypes for early intervention.

FIG. 1.

Fold changes of 15 studied genes differentiating controls and prostate cancer with different Gleason scores. Gene fold change values showing differential expression between prostate cancer and controls, were generated from RT-qPCR measurements, and represent the difference in means for prostate cancer versus control. The control corresponded to a pool of 32 normal prostate tissues from Caucasian subjects (Clontech). (A) shows prostate cancer patients with Gleason score≤5, (B) shows prostate cancer patients with Gleason score ≤7, (C) shows prostate cancer patients with Gleason score >7 (**p<0.01 and *p<0.05).