Abstract

Abstract Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. Barriers to biomarker discover include the polyclonal/multifocal nature of prostate tumors and the cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment) is much less affected by these problems but exhibit hundreds of gene expression changes compared to normal stroma (1). We performed Affymetrix gene expression profiles of tumor-adjacent stroma for asymptomatic organ-confined disease with negative surgical margins. We identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse following prostatectomy. Next, we compared expression in patients that chemically relapsed shortly after prostatectomy (< 1 year) versus patients that did not relapse in the first four years after prostatectomy. This comparison yielded 131 differentially expressed microarray probe sets. 19 probe sets (15 genes) were common between the two approaches, a significant degree of overlap (p < 0.0001). Using these 19 probe sets as input, we developed a PAM (Predicative Analysis of Microarrays)-based classifier by training on the expression profiles of samples containing stroma near tumor; 9 rapid relapse patient samples and 9 indolent patient samples. We then tested (validated) the classifier on array data from 47 independent samples containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. Notably of the 19 probe sets, 15 are down-regulated in poor outcome disease. Moreover of the 4 upregulated probe sets in poor outcome disease are transcripts of p53 (2) and its target genes, p21 and GADD45A. These features suggest an increased proportion of senescent cells with increased gene silencing (2,3) in the stroma, consistent with a substantially increased stressful environment in the tumor-adjacent microenvironment of of the subset of prostate cancers with poor outcome. 1. Jia, . et al. Canc. Res. 2011;71 :2476-2487. 2. Gabai, V. et al. Oncogene. 2010 ;2129 :1952-1962. 3. Banerjee, J. et al. Oncogene 2013 ; Epub., PMC accession no. 24141771. Citation Format: Zhenyu Jia, Farah Rahmatpanah, Xin Chen, Waldemar Lernhardt, Yipeng Wang, Xiao-Qin Xia, Anne Sawyers, Michael McClelland, Dan Mercola. A stroma-based 15 gene profile for prostate cancer suggests increased DNA methylation and senescence in the stroma of patients with poor prognosis. [abstract]. In: Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; 2014 Feb 26-Mar 1; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(1 Suppl):Abstract nr A63. doi:10.1158/1538-7445.CHTME14-A63

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call