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Although MIR516A has been reported to be downregulated and act as a tumor suppressor in multiple cancers, its expression and potential contribution to human bladder cancer (BC) remain unexplored. Unexpectedly, we showed here that MIR516A was markedly upregulated in human BC tissues and cell lines, while inhibition of MIR516A expression attenuated BC cell monolayer growth in vitro and xenograft tumor growth in vivo, accompanied with increased expression of PHLPP2. Further studies showed that MIR516A was able to directly bind to the 3'-untranslated region of PHLPP2 mRNA, which was essential for its attenuating PHLPP2 expression. The knockdown of PHLPP2 expression in MIR516A-inhibited cells could reverse BC cell growth, suggesting that PHLPP2 is a MIR516A downstream mediator responsible for MIR516A oncogenic effect. PHLPP2 was able to mediate BECN1/Beclin1 stabilization indirectly, therefore promoting BECN1-dependent macroautophagy/autophagy, and inhibiting BC tumor cell growth. In addition, our results indicated that the increased autophagy by attenuating MIR516A resulted in a dramatic inhibition of xenograft tumor formation in vivo. Collectively, our results reveal that MIR516A has a novel oncogenic function in BC growth by directing binding to PHLPP2 3'-UTR and inhibiting PHLPP2 expression, in turn at least partly promoting CUL4A-mediated BECN1 protein degradation, thereby attenuating autophagy and promoting BC growth, which is a distinct function of MIR516A identified in other cancers.Abbreviation: ATG3: autophagy related 3; ATG5: autophagy related 5; ATG7: autophagy related 7; ATG12: autophagy related 12; BAF: bafilomycin A1; BC: bladder cancer; CHX: cycloheximide; Co-IP: co-immunoprecipitation; CUL3: cullin 3; CUL4A: cullin 4A; CUL4B: cullin 4B; IF: immunofluorescence: IHC-p: immunohistochemistry-paraffin; MIR516A: microRNA 516a (microRNA 516a1 and microRNA 516a2); MS: mass spectrometry; PHLPP2: PH domain and leucine rich repeat protein phosphatase.
Pubmed ID: 32116109
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Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
View all literature mentionsA software package and server used to identify and characterize proteins from primary sequence databases using mass spectrometry data. Mascot integrates peptide mass fingerprinting, sequence querying, and MS/MS ion searching in order to search for proteins in databases like SwissProt, NCBInr, EMBL EST divisions, contaminants, and cRAP. If a license is purchased, users may: search data sets that exceed the 1200 spectrum limit of the free version; set up automated, high throughput work; add and edit proteins and quantification methods; and search a preferred collection of sequence databases. The software package works with instruments from AB Sciex, Agilent, Bruker, Jeol, Shimadzu, Thermo Scientific, and Waters.
View all literature mentionsCell line UM-UC-3 is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsMus musculus with name Crl:NU(NCr)-Foxn1nu from IMSR.
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