Gene expression profiles in prostate cancer: identification of candidate non-invasive diagnostic markers.

Abstract Objective To analyze gene expression profiles of prostate cancer (PCa) with the aim of determining the relevant differentially expressed genes and subsequently ascertaining whether this differential expression is maintained in post-prostatic massage (PPM) urine samples. Materials and methods Forty-six tissue specimens (36 from PCa patients and 10 controls) and 158 urine PPM-urines (113 from PCa patients and 45 controls) were collected between December 2003 and May 2007. DNA microarrays were used to identify genes differentially expressed between tumor and control samples. Ten genes were technically validated in the same tissue samples by quantitative RT-PCR (RT-qPCR). Forty-two selected differentially expressed genes were validated in an independent set of PPM-urines by qRT-PCR. Results Multidimensional scaling plot according to the expression of all the microarray genes showed a clear distinction between control and tumor samples. A total of 1047 differentially expressed genes (FDR ≤ 0.1) were identified between both groups of samples. We found a high correlation in the comparison of microarray and RT-qPCR gene expression levels ( r  = 0.928, p HOXC6 , PCA3 , PDK4 and TMPRSS2-ERG ), these differences were statistically significant ( p Conclusion The analysis of PCa by DNA microarrays provides new putative mRNA markers for PCa diagnosis that, with caution, can be extrapolated to PPM-urines.