154 research outputs found

    The RNA-binding protein Sam68 regulates expression and transcription function of the androgen receptor splice variant AR-V7.

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    Castration-resistant (CR) prostate cancer (PCa) partly arises due to persistence of androgen receptor (AR) transcriptional activity in the absence of cognate ligand. An emerging mechanism underlying the CRPCa phenotype and predicting response to therapy is the expression of the constitutively-active AR-V7 splice variant generated by AR cryptic exon 3b inclusion. Here, we explore the role of the RNA-binding protein (RBP) Sam68 (encoded by KHDRBS1), which is over-expressed in clinical PCa, on AR-V7 expression and transcription function. Using a minigene reporter, we show that Sam68 controls expression of exon 3b resulting in an increase in endogenous AR-V7 mRNA and protein expression in RNA-binding-dependent manner. We identify a novel protein-protein interaction between Sam68 and AR-V7 mediated by a common domain shared with full-length AR, and observe these proteins in the cell nucleoplasm. Using a luciferase reporter, we demonstrate that Sam68 co-activates ligand-independent AR-V7 transcriptional activity in an RNA-binding-independent manner, and controls expression of the endogenous AR-V7-specific gene target UBE2C. Our data suggest that Sam68 has separable effects on the regulation of AR-V7 expression and transcriptional activity, through its RNA-binding capacity. Sam68 and other RBPs may control expression of AR-V7 and other splice variants as well as their downstream functions in CRPCa

    CRIPTO and its signaling partner GRP78 drive the metastatic phenotype in human osteotropic prostate cancer

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    CRIPTO (CR-1, TDGF1) is a cell surface/secreted oncoprotein actively involved in development and cancer. Here, we report that high expression of CRIPTO correlates with poor survival in stratified risk groups of prostate cancer (PCa) patients. CRIPTO and its signaling partner glucose-regulated protein 78 (GRP78) are highly expressed in PCa metastases and display higher levels in the metastatic ALDHhigh sub-population of PC-3M-Pro4Luc2 PCa cells compared with non-metastatic ALDHlow. Coculture of the osteotropic PC-3M-Pro4Luc2 PCa cells with differentiated primary human osteoblasts induced CRIPTO and GRP78 expression in cancer cells and increases the size of the ALDHhigh sub-population. Additionally, CRIPTO or GRP78 knockdown decreases proliferation, migration, clonogenicity and the size of the metastasis-initiating ALDHhigh sub-population. CRIPTO knockdown reduces the invasion of PC-3M-Pro4Luc2 cells in zebrafish and inhibits bone metastasis in a preclinical mouse model. These results highlight a functional role for CRIPTO and GRP78 in PCa metastasis and suggest that targeting CRIPTO/GRP78 signaling may have significant therapeutic potential.Oncogene advance online publication, 10 April 2017; doi:10.1038/onc.2017.87

    TGF-β Regulates DNA Methyltransferase Expression in Prostate Cancer, Correlates with Aggressive Capabilities, and Predicts Disease Recurrence

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    DNA methyltransferase (DNMT) is one of the major factors mediating the methylation of cancer related genes such as TGF-β receptors (TβRs). This in turn may result in a loss of sensitivity to physiologic levels of TGF-β in aggressive prostate cancer (CaP). The specific mechanisms of DNMT's role in CaP remain undetermined. In this study, we describe the mechanism of TGF-β-mediated DNMT in CaP and its association with clinical outcomes following radical prostatectomy.We used human CaP cell lines with varying degrees of invasive capability to describe how TGF-β mediates the expression of DNMT in CaP, and its effects on methylation status of TGF-β receptors and the invasive capability of CaP in vitro and in vivo. Furthermore, we determined the association between DNMT expression and clinical outcome after radical prostatectomy. We found that more aggressive CaP cells had significantly higher TGF-β levels, increased expression of DNMT, but reduced TβRs when compared to benign prostate cells and less aggressive prostate cancer cells. Blockade of TGF-β signaling or ERK activation (p-ERK) was associated with a dramatic decrease in the expression of DNMT, which results in a coincident increase in the expression of TβRs. Blockade of either TGF-β signaling or DNMT dramatically decreased the invasive capabilities of CaP. Inhibition of TGF-β in an TRAMP-C2 CaP model in C57BL/6 mice using 1D11 was associated with downregulation of DNMTs and p-ERK and impairment in tumor growth. Finally, independent of Gleason grade, increased DNMT1 expression was associated with biochemical recurrence following surgical treatment for prostate cancer.Our findings demonstrate that CaP derived TGF-β may induce the expression of DNMTs in CaP which is associated with methylation of its receptors and the aggressive potential of CaP. In addition, DNMTs is an independent predictor for disease recurrence after prostatectomy, and may have clinical implications for CaP prognostication and therapy

    iTRAQ Identification of Candidate Serum Biomarkers Associated with Metastatic Progression of Human Prostate Cancer

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    A major challenge in the management of patients with prostate cancer is identifying those individuals at risk of developing metastatic disease, as in most cases the disease will remain indolent. We analyzed pooled serum samples from 4 groups of patients (n = 5 samples/group), collected prospectively and actively monitored for a minimum of 5 yrs. Patients groups were (i) histological diagnosis of benign prostatic hyperplasia with no evidence of cancer ‘BPH’, (ii) localised cancer with no evidence of progression, ‘non-progressing’ (iii) localised cancer with evidence of biochemical progression, ‘progressing’, and (iv) bone metastasis at presentation ‘metastatic’. Pooled samples were immuno-depleted of the 14 most highly abundant proteins and analysed using a 4-plex iTRAQ approach. Overall 122 proteins were identified and relatively quantified. Comparisons of progressing versus non-progressing groups identified the significant differential expression of 25 proteins (p<0.001). Comparisons of metastatic versus progressing groups identified the significant differential expression of 23 proteins. Mapping the differentially expressed proteins onto the prostate cancer progression pathway revealed the dysregulated expression of individual proteins, pairs of proteins and ‘panels’ of proteins to be associated with particular stages of disease development and progression. The median immunostaining intensity of eukaryotic translation elongation factor 1 alpha 1 (eEF1A1), one of the candidates identified, was significantly higher in osteoblasts in close proximity to metastatic tumour cells compared with osteoblasts in control bone (p = 0.0353, Mann Whitney U). Our proteomic approach has identified leads for potentially useful serum biomarkers associated with the metastatic progression of prostate cancer. The panels identified, including eEF1A1 warrant further investigation and validation

    Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.

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    Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa
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