Early growth response 3 (Egr3) is highly over-expressed in non-relapsing prostate cancer but not in relapsing prostate cancer.

Members of the early growth response (EGR) family of transcription factors play diverse functions in response to many cellular stimuli, including growth, stress, and inflammation. Egr3 has gone relatively unstudied, but here through use of the SPECS (Strategic Partners for the Evaluation of Predictive Signatures of Prostate Cancer) Affymetrix whole genome gene expression database we report that Egr3 mRNA is significantly over-expressed in prostate cancer compared to normal prostate tissue (5-fold). The Human Protein Atlas (http://www.proteinatlas.org), a database of tissue microarrays labeled with antibodies against over 11,000 human proteins, was utilized to quantify Egr3 protein expression in normal prostate and prostate cancer patients. In agreement with the SPECS data, we found that Egr3 protein is significantly increased in prostate cancer. The SPECS database has the benefit of extensive clinical follow up for the prostate cancer patients. Analysis of Egr3 mRNA expression in relation to the relapse status reveals that Egr3 mRNA expression is increased in tumor cells of non-relapsed samples (n = 63) compared to normal prostate cells, but is significantly lower in relapsed samples (n = 38) compared to non-relapse. The observations were confirmed using an independent data set. A list of genes correlating with this unique expression pattern was determined. These Egr3-correlated genes were enriched with Egr binding sites in their promoters. The gene list contains inflammatory genes such as IL-6, IL-8, IL1ß and COX-2, which have extensive connections to prostate cancer.

Diagnosis of prostate cancer using differentially expressed genes in stroma.

More than one million prostate biopsies are performed in the United States every year. A failure to find cancer is not definitive in a significant percentage of patients due to the presence of equivocal structures or continuing clinical suspicion. We have identified gene expression changes in stroma that can detect tumor nearby. We compared gene expression profiles of 13 biopsies containing stroma near tumor and 15 biopsies from volunteers without prostate cancer. About 3,800 significant expression changes were found and thereafter filtered using independent expression profiles to eliminate possible age-related genes and genes expressed at detectable levels in tumor cells. A stroma-specific classifier for nearby tumor was constructed on the basis of 114 candidate genes and tested on 364 independent samples including 243 tumor-bearing samples and 121 nontumor samples (normal biopsies, normal autopsies, remote stroma, as well as stroma within a few millimeters of tumor). The classifier predicted the tumor status of patients using tumor-free samples with an average accuracy of 97% (sensitivity = 98% and specificity = 88%) whereas classifiers trained with sets of 100 randomly generated genes had no diagnostic value. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorizing the presence of tumor in patients when a prostate sample is derived from near the tumor but does not contain any recognizable tumor.