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      Deficiency of G9a Inhibits Cell Proliferation and Activates Autophagy via Transcriptionally Regulating c-Myc Expression in Glioblastoma

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          Abstract

          Glioblastoma is an aggressive and difficult to treat cancer. Recent data have emerged implicating that histone modification level may play a crucial role in glioma genesis. The histone lysine methyltransferase G9a is mainly responsible for the mono- and di-methylation of histone H3 lysine 9 (H3K9), whose overexpression is associated with a more aggressive phenotype in cancer. However, the detailed correlations between G9a and glioblastoma genesis remain to be further elucidated. Here, we show that G9a is essential for glioblastoma carcinogenesis and reveal a probable mechanism of it in cell proliferation control. We found that G9a was highly expressed in glioblastoma cells, and knockdown or inhibition of G9a significantly repressed cell proliferation and tumorigenesis ability both in vitro and in vivo. Besides, knockdown or inhibition of G9a led to a cell cycle arrest in G2 phase, as well as decreased the expression of CDK1, CDK2, Cyclin A2, and Cyclin B1, while it induced the activation of autophagy. Further investigation showed that G9a deficiency induced cell proliferation suppression, and activation of autophagy was rescued by overexpression of the full-length c-Myc. Chromatin immunoprecipitation (ChIP) assay showed that G9a was enriched on the −2267 to −1949 region of the c-Myc promoter in LN-229 cells and the −1949 to −1630 region of the c-Myc promoter in U-87 MG cells. Dual-luciferase reporter assay showed that c-Myc promoter activity was significantly reduced after knockdown or inhibition of G9a. Our study shows that G9a controls glioblastoma cell proliferation by transcriptionally modulating oncogene c-Myc and provides insight into the capabilities of G9a working as a potential therapeutic target in glioblastoma.

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses1

            Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.
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              Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition).

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                Author and article information

                Contributors
                Journal
                Front Cell Dev Biol
                Front Cell Dev Biol
                Front. Cell Dev. Biol.
                Frontiers in Cell and Developmental Biology
                Frontiers Media S.A.
                2296-634X
                27 November 2020
                2020
                : 8
                : 593964
                Affiliations
                [1] 1State Key Laboratory of Silkworm Genome Biology, College of Sericulture, Textile and Biomass Sciences, Southwest University , Chongqing, China
                [2] 2Cancer Center, Medical Research Institute, Southwest University , Chongqing, China
                [3] 3Chongqing Engineering and Technology Research Centre for Silk Biomaterials and Regenerative Medicine, Southwest University , Chongqing, China
                [4] 4Engineering Research Center for Cancer Biomedical and Translational Medicine, Southwest University , Chongqing, China
                Author notes

                Edited by: Uwe Knippschild, University of Ulm, Germany

                Reviewed by: Sang Beom Seo, Chung-Ang University, South Korea; Timo Burster, Nazarbayev University, Kazakhstan; Georg Karpel-Massler, Ulm University Medical Center, Germany

                This article was submitted to Cell Death and Survival, a section of the journal Frontiers in Cell and Developmental Biology

                †These authors have contributed equally to this work

                Article
                10.3389/fcell.2020.593964
                7729084
                33330479
                39c7bb62-87bc-45ca-a034-e1b5f9b4a54c
                Copyright © 2020 Ke, Zhang, Zhong, Zhang and Cui.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 August 2020
                : 30 October 2020
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 62, Pages: 14, Words: 9472
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Funded by: Chongqing Research Program of Basic Research and Frontier Technology 10.13039/501100013223
                Funded by: Natural Science Foundation of Chongqing 10.13039/501100005230
                Funded by: Fundamental Research Funds for the Central Universities 10.13039/501100012226
                Categories
                Cell and Developmental Biology
                Original Research

                glioblastoma,cell proliferation,autophagy,g9a,c-myc
                glioblastoma, cell proliferation, autophagy, g9a, c-myc

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