91 research outputs found

    The β2-adrenergic receptor is a molecular switch for neuroendocrine transdifferentiation of prostate cancer cells

    Get PDF
    The incidence of treatment-related neuroendocrine (NE) prostate cancer (t-NEPC) is rising as more potent drugs targeting the androgen signaling axis are clinically implemented. Neuroendocrine transdifferentiation (NEtD), an putative initial step in t-NEPC development, is induced by androgen deprivation therapy (ADT) or anti-androgens, and by activation of the β2-adrenergic receptor (ADRB2) in prostate cancer cell lines. Thus, understanding whether ADRB2 is involved in ADT-initiated NEtD may assist in developing treatment strategies that can prevent or reverse t-NEPC emergence, thereby prolonging therapeutic responses. Here we found that in primary, treatment-naïve prostate cancers, ADRB2 mRNA was positively correlated with expression of luminal differentiation markers, and ADRB2 protein levels were inversely correlated with Gleason grade. ADRB2 mRNA was upregulated in metastatic prostate cancer, and progressively downregulated during androgen deprivation therapy (ADT) and t-NEPC emergence. In androgen-deprivated medium, high ADRB2 was required for LNCaP cells to undergo NEtD, measured as increased neurite outgrowth and expression of neuron differentiation and NE genes. ADRB2 overexpression induced an NE-like morphology in both AR positive and -negative prostate cancer cell lines. ADRB2 downregulation in LNCaP cells increased canonical Wnt signaling, and GSK3α/β inhibition reduced the expression of neuron differentiation and NE genes. In LNCaP xenografts, more pronounced castration-induced NEtD was observed in tumors derived from high than low-ADRB2 cells. In conclusion, high ADRB2 expression is required for ADT-induced NEtD, characterized by ADRB2 downregulation and t-NEPC emergence. Implications: This data suggest a potential application of β-blockers to prevent cancer cells committed to a neuroendocrine lineage from evolving into t-NEPC

    c-Myc antagonises the transcriptional activity of the androgen receptor in prostate cancer affecting key gene networks.

    Get PDF
    Prostate cancer (PCa) is the most common non-cutaneous cancer in men. The androgen receptor (AR), a ligand-activated transcription factor, constitutes the main drug target for advanced cases of the disease. However, a variety of other transcription factors and signaling networks have been shown to be altered in patients and to influence AR activity. Amongst these, the oncogenic transcription factor c-Myc has been studied extensively in multiple malignancies and elevated protein levels of c-Myc are commonly observed in PCa. Its impact on AR activity, however, remains elusive. In this study, we assessed the impact of c-Myc overexpression on AR activity and transcriptional output in a PCa cell line model and validated the antagonistic effect of c-MYC on AR-targets in patient samples. We found that c-Myc overexpression partially reprogrammed AR chromatin occupancy and was associated with altered histone marks distribution, most notably H3K4me1 and H3K27me3. We found c-Myc and the AR co-occupy a substantial number of binding sites and these exhibited enhancer-like characteristics. Interestingly, c-Myc overexpression antagonised clinically relevant AR target genes. Therefore, as an example, we validated the antagonistic relationship between c-Myc and two AR target genes, KLK3 (alias PSA, prostate specific antigen), and Glycine N-Methyltransferase (GNMT), in patient samples. Our findings provide unbiased evidence that MYC overexpression deregulates the AR transcriptional program, which is thought to be a driving force in PCa

    Bromodomain protein 4 discriminates tissue-specific super-enhancers containing disease-specific susceptibility loci in prostate and breast cancer.

    Get PDF
    Background Epigenetic information can be used to identify clinically relevant genomic variants single nucleotide polymorphisms (SNPs) of functional importance in cancer development. Super-enhancers are cell-specific DNA elements, acting to determine tissue or cell identity and driving tumor progression. Although previous approaches have been tried to explain risk associated with SNPs in regulatory DNA elements, so far epigenetic readers such as bromodomain containing protein 4 (BRD4) and super-enhancers have not been used to annotate SNPs. In prostate cancer (PC), androgen receptor (AR) binding sites to chromatin have been used to inform functional annotations of SNPs.Results Here we establish criteria for enhancer mapping which are applicable to other diseases and traits to achieve the optimal tissue-specific enrichment of PC risk SNPs. We used stratified Q-Q plots and Fisher test to assess the differential enrichment of SNPs mapping to specific categories of enhancers. We find that BRD4 is the key discriminant of tissue-specific enhancers, showing that it is more powerful than AR binding information to capture PC specific risk loci, and can be used with similar effect in breast cancer (BC) and applied to other diseases such as schizophrenia.Conclusions This is the first study to evaluate the enrichment of epigenetic readers in genome-wide associations studies for SNPs within enhancers, and provides a powerful tool for enriching and prioritizing PC and BC genetic risk loci. Our study represents a proof of principle applicable to other diseases and traits that can be used to redefine molecular mechanisms of human phenotypic variation

    FUS/TLS Is a Co-Activator of Androgen Receptor in Prostate Cancer Cells

    Get PDF
    Androgen receptor (AR) is a member of the nuclear receptor family of transcription factors. Upon binding to androgens, AR becomes transcriptionally active to regulate the expression of target genes that harbor androgen response elements (AREs) in their promoters and/or enhancers. AR is essential for the growth and survival of prostate cancer cells and is therefore a target for current and next-generation therapeutic modalities against prostate cancer. Pathophysiologically relevant protein-protein interaction networks involving AR are, however, poorly understood. In this study, we identified the protein FUsed/Translocated in LipoSarcoma (FUS/TLS) as an AR-interacting protein by co-immunoprecipitation of endogenous proteins in LNCaP human prostate cancer cells. The hormonal response of FUS expression in LNCaP cells was shown to resemble that of other AR co-activators. FUS displayed a strong intrinsic transactivation capacity in prostate cancer cells when tethered to basal promoters using the GAL4 system. Chromatin immunoprecipitation experiments showed that FUS was recruited to ARE III of the enhancer region of the PSA gene. Data from ectopic overexpression and “knock-down” approaches demonstrated that AR transcriptional activity was enhanced by FUS. Depletion of FUS reduced androgen-dependent proliferation of LNCaP cells. Thus, FUS is a novel co-activator of AR in prostate cancer cells

    Lipid degradation promotes prostate cancer cell survival

    Get PDF
    Prostate cancer is the most common male cancer and androgen receptor (AR) is the major driver of the disease. Here we show that Enoyl-CoA delta isomerase 2 (ECI2) is a novel AR-target that promotes prostate cancer cell survival. Increased ECI2 expression predicts mortality in prostate cancer patients (p = 0.0086). ECI2 encodes for an enzyme involved in lipid metabolism, and we use multiple metabolite profiling platforms and RNA-seq to show that inhibition of ECI2 expression leads to decreased glucose utilization, accumulation of fatty acids and down-regulation of cell cycle related genes. In normal cells, decrease in fatty acid degradation is compensated by increased consumption of glucose, and here we demonstrate that prostate cancer cells are not able to respond to decreased fatty acid degradation. Instead, prostate cancer cells activate incomplete autophagy, which is followed by activation of the cell death response. Finally, we identified a clinically approved compound, perhexiline, which inhibits fatty acid degradation, and replicates the major findings for ECI2 knockdown. This work shows that prostate cancer cells require lipid degradation for survival and identifies a small molecule inhibitor with therapeutic potential

    Cancer Biomarker Discovery: The Entropic Hallmark

    Get PDF
    Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases
    corecore