Enormous efforts have been invested in the development of biomarkers for prognosis of prostate cancer in order to address urgent questions regarding overtreatment by radical methods. Nevertheless, few accepted and clinically useful biomarkers have been developed. A possible barrier to biomarker discovery may be accumulated genetic alterations in tumor cells resulting in polyclonal/multifocal prostate tumors as well as cell-type heterogeneity of prostate cancer between patients. Tumor-adjacent stroma (tumor microenvironment) is less affected by genetic alteration and might therefore yield more consistent biomarkers for clinical tests. To this end we compared gene expression profiles in stroma near tumor from high-risk patients that chemically relapsed shortly after prostatectomy (< 1 year), and low-risk patients either relapsed later than 4 years after surgery or who did not relapse and had at least 4 years’ follow-up data available. We identified 131 differentially expressed genes in these two categories. We also identified another set of 115 genes of which the expression levels are significantly correlated with time-to-relapse for the relapsed patients. Using the 19 genes that overlapped between the two gene lists, we developed a PAM-based classifier by training on samples containing stroma near tumor: 9 high-risk patient samples and 9 low-risk patient samples. We then tested the classifier on 47 independent samples, including 38 samples containing stroma near tumor and 9 tumor-bearing samples containing at least 90% stroma near tumor. The classifier predicted the risk status of patients with an average accuracy of 87%. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4284. doi:1538-7445.AM2012-4284