ABSTRACT
The TMPRSS2:ERG gene fusion is common in androgen receptor (AR) positive prostate cancers, yet its function remains poorly understood. From a screen for functionally relevant ERG interactors, we identify the arginine methyltransferase PRMT5. ERG recruits PRMT5 to AR-target genes, where PRMT5 methylates AR on arginine 761. This attenuates AR recruitment and transcription of genes expressed in differentiated prostate epithelium. The AR-inhibitory function of PRMT5 is restricted to TMPRSS2:ERG-positive prostate cancer cells. Mutation of this methylation site on AR results in a transcriptionally hyperactive AR, suggesting that the proliferative effects of ERG and PRMT5 are mediated through attenuating AR's ability to induce genes normally involved in lineage differentiation. This provides a rationale for targeting PRMT5 in TMPRSS2:ERG positive prostate cancers. Moreover, methylation of AR at arginine 761 highlights a mechanism for how the ERG oncogene may coax AR towards inducing proliferation versus differentiation.
Subject(s)
Epithelial Cells/metabolism , Gene Expression Regulation, Neoplastic , Oncogene Proteins, Fusion/genetics , Protein-Arginine N-Methyltransferases/genetics , Receptors, Androgen/genetics , Serine Endopeptidases/genetics , Base Sequence , Cell Differentiation , Cell Line, Tumor , Cell Proliferation , Epithelial Cells/pathology , Humans , Male , Methylation , Models, Molecular , Mutation , Oncogene Proteins, Fusion/metabolism , Prostate/metabolism , Prostate/pathology , Protein Binding , Protein Interaction Domains and Motifs , Protein Multimerization , Protein Structure, Secondary , Protein-Arginine N-Methyltransferases/antagonists & inhibitors , Protein-Arginine N-Methyltransferases/metabolism , RNA, Small Interfering/genetics , RNA, Small Interfering/metabolism , Receptors, Androgen/chemistry , Receptors, Androgen/metabolism , Serine Endopeptidases/metabolism , Signal Transduction , Transcriptional Regulator ERG/genetics , Transcriptional Regulator ERG/metabolismABSTRACT
5-Methylthioadenosine phosphorylase (MTAP) is a key enzyme in the methionine salvage pathway. The MTAP gene is frequently deleted in human cancers because of its chromosomal proximity to the tumor suppressor gene CDKN2A. By interrogating data from a large-scale short hairpin RNA-mediated screen across 390 cancer cell line models, we found that the viability of MTAP-deficient cancer cells is impaired by depletion of the protein arginine methyltransferase PRMT5. MTAP-deleted cells accumulate the metabolite methylthioadenosine (MTA), which we found to inhibit PRMT5 methyltransferase activity. Deletion of MTAP in MTAP-proficient cells rendered them sensitive to PRMT5 depletion. Conversely, reconstitution of MTAP in an MTAP-deficient cell line rescued PRMT5 dependence. Thus, MTA accumulation in MTAP-deleted cancers creates a hypomorphic PRMT5 state that is selectively sensitized toward further PRMT5 inhibition. Inhibitors of PRMT5 that leverage this dysregulated metabolic state merit further investigation as a potential therapy for MTAP/CDKN2A-deleted tumors.
Subject(s)
Cyclin-Dependent Kinase Inhibitor p16/metabolism , Methionine/metabolism , Neoplasms/metabolism , Protein-Arginine N-Methyltransferases/metabolism , Purine-Nucleoside Phosphorylase/metabolism , Cell Line, Tumor , Cell Survival , Cyclin-Dependent Kinase Inhibitor p16/genetics , Deoxyadenosines/metabolism , Gene Deletion , Humans , Neoplasms/drug therapy , Neoplasms/genetics , Protein-Arginine N-Methyltransferases/genetics , Purine-Nucleoside Phosphorylase/genetics , RNA, Small Interfering/genetics , Thionucleosides/metabolismABSTRACT
The increasing availability of genomic data for pathogens that cause tropical diseases has created new opportunities for drug discovery and development. However, if the potential of such data is to be fully exploited, the data must be effectively integrated and be easy to interrogate. Here, we discuss the development of the TDR Targets database (http://tdrtargets.org), which encompasses extensive genetic, biochemical and pharmacological data related to tropical disease pathogens, as well as computationally predicted druggability for potential targets and compound desirability information. By allowing the integration and weighting of this information, this database aims to facilitate the identification and prioritization of candidate drug targets for pathogens.
