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      Comprehensive analysis of the MIR4435-2HG/miR-1-3p/MMP9/miR-29-3p/DUXAP8 ceRNA network axis in hepatocellular carcinoma

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          Abstract

          A growing number of studies have shown that competitive endogenous RNA (ceRNA) regulatory networks might play important roles during the process of hepatocellular carcinoma (HCC). This study assessed the role of the ceRNA network in immune cell infiltration in HCC. Immune-related gene sets were downloaded from Molecular Signatures Database, and differentially expressed genes were screened based on TCGA HCC transcriptome data. The corresponding miRNAs with low expression and good prognostic implications, and the corresponding lncRNAs with high expression and poor prognostic were identified to construct ceRNA networks. The networks were utilized for clinical correlation analysis and risk model construction, and the CIBERSORT algorithm was applied to assess immune cell infiltration. In this study, the mRNA-miRNA-lncRNA model was used to construct a ceRNA network in HCC using immune-related differentially expressed mRNAs. Assessment of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis in HCC showed that a high risk/poor prognosis was significantly correlated with tumor stage and invasion depth. MMP9 was positively correlated with resting M0 macrophages and NK cells and negatively correlated with activated mast cells, resting mast cells, monocytes and activated NK cells. DUXAP8 was positively correlated with M2 macrophages and negatively correlated with MIR4435-2HG, which was positively correlated with M2 macrophages and negatively correlated with activated mast cells, CD8 T cells and follicular helper T cells. The correlation of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis with immune cell infiltration provides further information on the mechanism of HCC development. The result might improve our understanding the interactions between immune related genes and non-coding RNAs in the occurrence and development of HCC, and the relevant RNAs might be used as diagnostic and prognostic biomarkers and molecular targets in HCC patients.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s12672-021-00436-3.

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          Most cited references37

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            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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                Author and article information

                Contributors
                gaoyu@bbmc.edu.cn
                Journal
                Discov Oncol
                Discov Oncol
                Discover. Oncology
                Springer US (New York )
                2730-6011
                7 October 2021
                7 October 2021
                December 2021
                : 12
                : 38
                Affiliations
                [1 ]GRID grid.252957.e, ISNI 0000 0001 1484 5512, Department of Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, , Bengbu Medical College, ; 233030 Bengbu, China
                [2 ]GRID grid.252957.e, ISNI 0000 0001 1484 5512, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, , Bengbu Medical College, ; 233030 Bengbu, China
                [3 ]GRID grid.252957.e, ISNI 0000 0001 1484 5512, Research Center of Clinical Laboratory Science, School of Laboratory Medicine, , Bengbu Medical College, ; Bengbu, 233030 China
                [4 ]GRID grid.252957.e, ISNI 0000 0001 1484 5512, School of Life Science, , Bengbu Medical College, ; No. 2600, Donghai Road, Bengbu, 233030 China
                [5 ]GRID grid.252957.e, ISNI 0000 0001 1484 5512, Anhui Province Key Laboratory of Translational Cancer Research, , Bengbu Medical College, ; Bengbu, 233030 China
                Author information
                http://orcid.org/0000-0002-4210-7338
                Article
                436
                10.1007/s12672-021-00436-3
                8777520
                35201491
                abafec74-f2fd-42b5-82b8-07f7f998b173
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 July 2021
                : 28 September 2021
                Funding
                Funded by: Science Research Project of Bengbu Medical College
                Award ID: 2020byzd080
                Award Recipient :
                Funded by: Research Foundation for Advanced Talents of Bengbu Medical College
                Award ID: 15190016
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                hepatocellular carcinoma,cerna,prognosis,mir4435-2hg,mmp9,duxap8

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