ABSTRACT: Following androgen ablation treatment for advanced prostate cancer, almost all men relapse after a period of initial response to therapy, which eventually is life threatening. We have previously found that purine-rich element binding protein, PUR alpha, was significantly repressed in androgen-independent prostate cancer cell lines in comparison to an androgen-dependent line. Moreover, over-expressing PURa in androgen-independent prostate cancer cells attenuated their cell proliferation. The aim of the studies described here was to uncover some of the mechanisms by which over-expression of PURa attenuates cell proliferation. A set of common genes induced by over-expressing PURa both in PC3 and LNCaP cells was analyzed by DNA microarray. The results were then validated utilizing quantitative reverse transcription-PCR. Using a 5.3-kb region of the PSA promoter containing androgen response elements, the participation of PURa in androgen regulated gene expression was determined. Genes involved in stress response and cell differentiation were induced in cells over-expressing PURa. Some of the genes that are targets of androgen regulation are also induced. Most strikingly, ectopic expression of PURa induced transcriptional activity of the 5.3-kb PSA promoter containing androgen response elements, without androgen stimulation. Based upon the consideration that some of the genes involved in cell stress and differentiation are also regulated by androgens our data suggest that PURa shares some common pathway regulated by the androgen receptor. These findings suggest that regulation of PURa expression in prostate cancer cells may serve as a therapeutic target for hormone refractory prostate cancer. Experiment Overall Design: PC3 cells (low in PURa expression) was stably over-expressed PURa. Total RNA of the cells was collected simultaneously with that of PC3 transfected with mock vector. Experiment Overall Design: LNCaP cells (Express PURa more than PC3 cells) was PURa-over-expressed with retrovirus vector (MSCV-PIG) and selected with puromycin for 72hr. Total RNA of the cells was collected simultaneously with that of LNCaP cells infected with mock vector. Experiment Overall Design: One set of RNA derived from PC3 cells and two independent RNA derived from LNCaP cells retrovirus infection were used for DNA microarray. Quality and concentration of total RNA was verified using Agilent Bioanalyzer and Nanodrop Spectrophotometer, respectively. T7 oligo(dT) primer (Sigma-Proligo, Boulder, CO) and 5ug total RNA are combined for first strand cDNA synthesis. Following second strand cDNA synthesis and cDNA cleanup (Phase Lock Gel Light, Eppendorf, Hamburg, Germany) an in vitro transcription reaction was performed overnight using T7 RNA transcript labeling kit provided by Enzo Life Sciences, Inc. (Farmingdale, NY). IVT reactions were cleaned using RNeasy Mini Kit (Qiagen) and concentration determined by Nanodrop Spectrophotometer. 15ug cRNA was fragmented using 5X fragmentation buffer (made in-house). Hybridization cocktail was made in accordance with Affymetrix eukaryotic expression array protocol (Affymetrix, Santa Clara, CA) and combined with fragmented cRNA. 10ug cRNA was loaded onto Human U133Plus 2.0 genome arrays (Affymetrix, Santa Clara, CA) and hybridized overnight for 16 hours. After hybridization, staining and washing of the arrays was performed following the Affymetrix eukaryotic expression array protocol, including staining with streptavidin-phycoerythrin, antibody stain, and a second streptavidin-phycoerythrin stain. After washing and staining, all arrays were scanned with the Affymetrix GeneChip Scanner and data collected with GeneChip Operating System 1.4 (GCOS, Affymetrix, Santa Clara, CA). Experiment Overall Design: The quality of the microarray experiments was assessed with affyPLM and Affy, two Bioconductor packages for statistical analysis of microarray data. To estimate the gene expression signals, data analysis was conducted on the chipsâ CEL file probe signal values at the Affymetrix probe pair (perfect match (PM) probe and mismatch (MM) probe) level, using the statistical algorithm Robust Multiarray Analysis (RMA) expression measure (Irizarry RA et al. 2003) with Affy. This probe level data processing includes a normalization procedure utilizing the quantile normalization method (Bolstad BM et al. 2003) to reduce the obscuring variation between microarrays, which might be introduced during the processes of sample preparation, manufacture, fluorescence labeling, hybridization and/or scanning. Exploratory data analysis (EDA) was performed with the preprocessed data above. Between-treatment and between-replicate variations were examined with the pair-wise MvA plots, in which the base 2 log ratios (M) between two samples are plotted against their averaged base 2 log signals (A). With the signal estimates, Principal Component analysis (PCA) was also performed to assess sample variability. Experiment Overall Design: With the signal intensities obtained above, an empirical Bayes method with the Gamma-Gamma modeling, as implemented in the bioconductor package EBarrays, was used to estimate the posterior probabilities of the differential expression of genes between PURA and Vector only sample conditions (Newton MA et al. 2001, Kendziorski Cm et al. 2003, Newton MA et al. 2004). The criterion of the posterior probability > 0.5, which means the posterior odds favoring change, was used to produce the differentially expressed gene list. Experiment Overall Design: All Bioconductor packages are available at http://www.bioconductor.org and all computation was performed under R environment (http://www.r-project.org).
