Project description:Background: Aldo-keto reductase (AKR) 1C family member 3 (AKR1C3), one of four identified human AKR enzymes, catalyzes steroid, prostaglandin, and xenobiotic metabolism. In the prostate, AKR1C3 is up-regulated in localized and advanced prostate adenocarcinoma, and is associated with prostate cancer (PCa) aggressiveness. Here we provide initial evidence for potential roles of AKR1C3 in PCa progression. Methods: Spatial distribution of AKR1C3 was analyzed using immunohistochemical staining in prostate adenocarcinoma tissue array. Human PCa PC-3 cells were stably transfected with AKR1C3 cDNA to establish PC3-AKR1C3 transfectants. Microarray and bioinformatics analyses were performed to identify pathways that are activated by elevated AKR1C3 expression in PCa cells. Functional confirmation of microarray and bioinformatics results was performed by immunoblot analysis and an in vitro Matrigel angiogenesis assay. Results: Elevated AKR1C3 expression was specifically limited to human prostate adenocarcinoma. Microarray and bioinformatics analysis suggested that elevated AKR1C3 expression in PC-3 cells modulates estradiol and androgen metabolism and activates insulin growth factor (IGF)-1 and Akt signaling pathways. Immunoblots confirmed that phosphorylated levels of IGF-1 receptor (IGF-1R) and Akt are significantly up-regulated in PC3-AKR1C3 as compared to mock transfectants. PC3-AKR1C3 transfectants promoted endothelial cell tube formation in Matrigel as compared to parental PC-3 cells and mock transfectants. Conclusion: Microarray and bioinformatics data followed by biological analyses suggest that elevated AKR1C3 expression in PC-3 cells promotes PCa angiogenesis and aggressiveness. These results suggest AKR1C3 can promote the aggressiveness of PCa through modulating estrogen and androgen metabolism with subsequent activation of growth factor IGF-1 and cytoplasmic Akt signaling pathways. Total RNA from mock- and ACR1C3 transfected PC-3 cells was isolated, with 2 or 3 biological replicates each. Gene expression data from AKR1C3 transfected PC-3 cells were compared with mock-transfected data.

Project description: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).

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Homo sapiens

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