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Downregulation of PRMT1, a histone arginine methyltransferase, by sodium propionate induces cell apoptosis in colon cancer.

Oncology reports | 2019

The microbiota and bacterial metabolites in the colon are regarded as alternative targets for colon cancer prevention and therapy. Among these metabolites, short-chain fatty acids (SCFAs) exhibit anticancer effects and suppress inflammation in the colon. However, the molecular mechanisms and target development of SCFAs require additional study. In the present study, using RNA-seq results from colon cancer samples derived from the Cancer Genome Atlas (TCGA) portal, overexpressed epigenetic modifiers were identified and RT-PCR and qRT-PCR analysis was performed to select target genes that responded to treatment with propionate in HCT116 cells. Downregulation of protein arginine methyltransferase 1 (PRMT1), a histone arginine methyltransferase, was observed after sodium propionate (SP) treatment. Moreover, phospho-array analysis demonstrated that the mTOR pathway was involved in propionate and siPRMT1 treatment, and regulation of this pathway was associated with apoptosis in HCT116 cells. The present study, to the best of our knowledge, was the first to demonstrate that PRMT1 levels were reduced by propionate treatment in HCT116 cells and that downregulation of PRMT1 induced cell apoptosis. Thus, this novel mechanism of sodium propionate treatment for colon cancer therapy may indicate more effective approaches, such as dietary therapy, for CRC patients.

Pubmed ID: 30569144 RIS Download

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GraphPad Prism (tool)

RRID:SCR_002798

Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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The Cancer Genome Atlas (tool)

RRID:SCR_003193

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).

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Cell Signaling Technology (tool)

RRID:SCR_004431

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RRID:SCR_013575

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Agilent AriaMx Real-time PCR System (tool)

RRID:SCR_019469

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HCT 116 (tool)

RRID:CVCL_0291

Cell line HCT 116 is a Cancer cell line with a species of origin Homo sapiens (Human)

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SW480 (tool)

RRID:CVCL_0546

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