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      Expression patterns and the prognostic value of the EMILIN/Multimerin family members in low-grade glioma

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          Abstract

          Managing low-grade gliomas (LGG) remains a major medical challenge due to the infiltrating nature of the tumor and failure of surgical resection to eliminate the disease. EMILIN/Multimerins contain the gC1q signature, which is involved in many tumor processes. However, the expression and prognostic value of EMILIN/Multimerins in LGG remains unclear. This study used integrated bioinformatics analysis to investigate the expression pattern, prognostic value and function of EMILIN/Multimerins in patients with LGG. We analyzed the transcription levels and prognostic value EMILIN/Multimerins in LGG using the ONCOMINE, Gene Expression Profiling Interactive Analysis (GEPIA) and UALCAN databases. The mutation and co-expression rates of neighboring genes in EMILIN/Multimerins were studied using cBioPortal. TIMER and Metascape were used to reveal the potential function of EMILIN/Multimerins in LGG. According to our analysis, most EMILIN/Multimerins were overexpressed in LGG and shared a clear association with immune cells. GEPIA analysis confirmed that high levels of EMILIN/Multimerins, not including MMRN2, were associated with a poor prognosis in disease-free survival of patients with LGG. Additionally, we discovered that EMILIN/Multimerins may regulate LGG and we found a correlation between their expression patterns and distinct pathological grades. We found that EMILIN/Multimerins serve as possible prognostic biomarkers and high-priority therapeutic targets patients with LGG.

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          Most cited references28

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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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            Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma.

            Comprehensive knowledge of the genomic alterations that underlie cancer is a critical foundation for diagnostics, prognostics, and targeted therapeutics. Systematic efforts to analyze cancer genomes are underway, but the analysis is hampered by the lack of a statistical framework to distinguish meaningful events from random background aberrations. Here we describe a systematic method, called Genomic Identification of Significant Targets in Cancer (GISTIC), designed for analyzing chromosomal aberrations in cancer. We use it to study chromosomal aberrations in 141 gliomas and compare the results with two prior studies. Traditional methods highlight hundreds of altered regions with little concordance between studies. The new approach reveals a highly concordant picture involving approximately 35 significant events, including 16-18 broad events near chromosome-arm size and 16-21 focal events. Approximately half of these events correspond to known cancer-related genes, only some of which have been previously tied to glioma. We also show that superimposed broad and focal events may have different biological consequences. Specifically, gliomas with broad amplification of chromosome 7 have properties different from those with overlapping focalEGFR amplification: the broad events act in part through effects on MET and its ligand HGF and correlate with MET dependence in vitro. Our results support the feasibility and utility of systematic characterization of the cancer genome.
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              Functional network analysis reveals extended gliomagenesis pathway maps and three novel MYC-interacting genes in human gliomas.

              Gene expression profiling has proven useful in subclassification and outcome prognostication for human glial brain tumors. The analysis of biological significance of the hundreds or thousands of alterations in gene expression found in genomic profiling remains a major challenge. Moreover, it is increasingly evident that genes do not act as individual units but collaborate in overlapping networks, the deregulation of which is a hallmark of cancer. Thus, we have here applied refined network knowledge to the analysis of key functions and pathways associated with gliomagenesis in a set of 50 human gliomas of various histogenesis, using cDNA microarrays, inferential and descriptive statistics, and dynamic mapping of gene expression data into a functional annotation database. Highest-significance networks were assembled around the myc oncogene in gliomagenesis and around the integrin signaling pathway in the glioblastoma subtype, which is paradigmatic for its strong migratory and invasive behavior. Three novel MYC-interacting genes (UBE2C, EMP1, and FBXW7) with cancer-related functions were identified as network constituents differentially expressed in gliomas, as was CD151 as a new component of a network that mediates glioblastoma cell invasion. Complementary, unsupervised relevance network analysis showed a conserved self-organization of modules of interconnected genes with functions in cell cycle regulation in human gliomas. This approach has extended existing knowledge about the organizational pattern of gene expression in human gliomas and identified potential novel targets for future therapeutic development.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                2 March 2020
                2020
                : 8
                : e8696
                Affiliations
                Department of Neurosurgery, Cangzhou Central Hospital , Cangzhou, Hebei Province, China
                Author information
                http://orcid.org/0000-0002-9419-6766
                Article
                8696
                10.7717/peerj.8696
                7058105
                32175193
                e717f44b-7801-4998-9fd9-b56d4c62c33d
                © 2020 Zhao et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 4 October 2019
                : 5 February 2020
                Funding
                The authors received no funding for this work.
                Categories
                Bioinformatics
                Genetics
                Neuroscience
                Neurology
                Oncology

                low-grade glioma,emilin/multimerin family,prognosis,genetic mutation,bioinformatics

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