Abstract The microenvironment of prostate cancer plays a major role in tumor initiation, growth, and metastatic spread. Using RNA expression data from fresh frozen human prostatectomies for which the clinical outcome was followed for over 5 years, we have developed a general approach to identify gene expression changes of the tumor-adjacent stroma that distinguishes aggressive prostate cancer cases from indolent cases. Highly significant gene associations were defined by correlating expression with Disease-free Survival (DFS) and also, separately, by comparing RNA expression between cases that remained disease free for at least 4 years following surgery with those cases that exhibited relapse within 1 year of surgery. A total of 193 highly significant genes were identified, of which 15 were common to the two approaches. These 15 genes were used to develop a PAM (Prediction Analysis for Microarrays)-based algorithm to classify new cases as indolent or aggressive and to provide a probability for each classification. The algorithm was tested on stroma-enriched samples from 47 new cases with known outcome with an accuracy of 87% [1]. A potential functional basis for some the genes associated with aggressive disease was suggested by the observation that p53 expression is decreased in aggressive disease whereas p53-target genes and cell cycle inhibitors including p21, GADD45A, and GADD45B are increased, which is a pattern others have noted as suggestive of senescence [2]. Increased IGFBP6, Tubulin alpha 1a, and Lamin A/C further suggest a senescence-associated secretory phenotype [3]. A potential secretory factor of known significance in the growth of prostate cancer (IGF-1/Somatomedin-C) has elevated RNA levels in the stroma of the same cases. These features argue that an accurate and general prediction of aggressiveness may be derived from the tumor microenvironment and may be composed of genes that have functional roles in bringing about aggressive disease. [1] Jia et al. 2012 PLoS ONE, 7(8):e41371 [2] Liebermann and Hoffman 2008 Journal of Molecular Signaling, 3:15 [3] Coppe et al. 2008 PLoS Biology, 6(12):e301 Citation Format: Zhenyu Jia, Farahnaz Rahmatpanah, Xin Chen, Michael McClelland, Dan Mercola. A prostate stroma-derived profile is predictive of early relapse and reflects potential mechanisms of aggressive disease. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2811. doi:10.1158/1538-7445.AM2013-2811 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.