Abstract

Abstract Prostate cancer (PCa) is a disease conferred by gene mutations, numerous alternations in gene expression and aberrant changes in genome composition/architecture. An area of research that continues to garner attention is PCa health disparities, wherein the African American (AA) population exhibits higher incidence and mortality rates compared to Caucasian Americans (CA). To identify the genetic predispositions and oncogenic networks associated with the observed PCa disparities, we applied a systems biology approach by integrating exon, microRNA and SNP information from PCa specimens of AA and CA patients. RNA and DNA purified from PCa (with Gleason score ≥6) and patient-matched normal prostate needle biopsies from AAs and CAs were processed and hybridized onto Affymetrix human Exon 1.0 ST, SNP 6.0 arrays or Agilent human microRNA arrays. A 4-way statistical design (10% FDR, >1.5 fold-change) was employed to identify differentially expressed mRNAs in the following comparisons: AA normal vs. CA normal, AA cancer vs. CA cancer, AA cancer vs. AA normal, and CA cancer vs. CA normal. Pathway analyses of the differentially expressed genes have revealed several critical network-level rewiring of gene interactions accounting for PCa disparities between AA and CA. For example, the mis-regulated testosterone metabolism network in normal AA prostate tissues may represent a genetic predisposition factor in the AA population. Whereas, the inflammatory response (NF-?B network), activated oncogenic signaling pathways (ERK, JNK and p38), and up-regulated cancer promoting genes (RHOA and STAT1) may be associated with the higher recurrence and death rates in AA patients. Moreover, our exon and SNP profiling results have identified hundreds of genes exhibiting differential splicing patterns and/or copy number variations (CNVs) in AA and CA patients. Notably, at least 13 genes residing within the 5 oncogenic signaling pathways have been identified as exhibiting either differential splicing (in FGFR3, PDGFRA, MET, EPHA1, NF1, RASGRP2, GSK3, TSC2, ATM, RAF and RB1) or CNVs (at EPHA, PTEN and APQ between AA and CA PCa specimens. In addition, micro RNA profiling further revealed that 14 micro RNAs (e.g. miR-125b-2∗, miR-34a, miR-100, miR-99a, miR-200a) were differentially expressed in AA and CA cancer samples, potentially related to cell proliferation, anti-apoptosis, cell cycle regulation in AA cancers. Taken together, our data suggest that mRNA splicing, CNVs, deregulated microRNA expression and gene-network rewiring may be critical in PCa health disparities between the AA and CA populations. These findings should advance our knowledge on the molecular mechanisms underlying PCa disparities, and may facilitate the development of novel strategies for PCa detection, diagnosis, prognosis, and therapy in AA population. This work was supported by NCI grant 5U01-CA-116937. Citation Information: Cancer Epidemiol Biomarkers Prev 2010;19(10 Suppl):B55.

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