In silico validation of a prostate cancer recurrence prognostic signature based on pathways related to stem cells.

e23205 Background: Prostate cancer has the highest incidence in Peruvian male population with mortality close to 50% as opposed to countries with strong preventative programs were mortality is between 10-15%. Early detection and close follow up to avoid or detect recurrence as soon as possible is considered to be the best strategy to reduce this high mortality. However, this is not always the case due to limitations in prevention programs and cultural characteristics of male behavior. Therefore, there is a need to develop better biomarkers and targets. We hypothesize that recurrence occur due to the existence of cells that have acquired stem cell behavior that we denominate prostate cancer stem cell, which are not affected by first-line therapies. Methods: We curated a list of stem-cell genes meshing the WNT Signaling Pathway (KEGG entry: hsa04310) and the Signaling Pathways Regulating Pluripotency of Stem Cells (KEGG entry: hsa04550). We used data from 497 samples of primary tumors whose expression for 231 genes was quantified with NanoString from a public genomic information database (TCGA, provisional). The validation set (GSE21032) consisted of 131 primary tumors cases of prostate cancer. The stepwise multivariate survival analysis performed by the Cox proportional hazards mode selected FZD3, PLCB2, PLCB3 and TP53 as independent prognostic factors for distant recurrence-free survival (DRFS). We developed a four-genes signature using the regression coefficients for each gene. Results: The signature was: -0.363 × FZD3 + 0.432 × PLCB2 + 1.313 × PLCB3 - 0.237 × TP53. The percentile seventy-five score in the discovery set (0.6734) identified two subgroups with different DFRS (P < 0.05). The same score we used in the validation set and was also able to discriminate patients with different DRFS (P = 0.000003). Conclusions: Our in silico validation of a prostate cancer recurrence prognostic signature supports the involvement of stem cell-related pathways in prostate cancer genomics.