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      Molecular mechanisms of pathogenesis in hepatocellular carcinoma revealed by RNA-sequencing

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          Abstract

          The present study aimed to explore the underlying molecular mechanisms of hepatocellular carcinoma (HCC). RNA-sequencing profiles GSM629264 and GSM629265, from the GSE25599 data set, were downloaded from the Gene Expression Omnibus database and processed by quality evaluation. GSM629264 and GSM629265 were from HCC and adjacent non-cancerous tissues, respectively. TopHat software was used for alignment analysis, followed by the detection of novel splicing sites. In addition, the Cufflinks software package was used to analyze gene expressions, and the Cuffdiff program was used to screen for differently expressed genes (DEGs) and differentially expressed splicing variants. Gene ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs were also performed. Transcription factors (TFs) and microRNAs (miRNAs) that regulate DEGs were identified, and a protein-protein interaction (PPI) network was constructed. The hub node in the PPI network was obtained, and the TFs and miRNAs that regulated the hub node were further predicted. The quality of the sequencing data met the standards for analysis, and the clean reads were ~65%. Most sequencing reads mapped into coding sequence exons (CDS_exons), whereas other reads mapped into exon 3′ untranslated regions (UTR_Exons), 5′UTR_Exons and Introns. Upregulated and downregulated DEGs between HCC and adjacent non-cancerous tissues were screened. Genes of differentially expressed splicing variants were identified, including vesicle-associated membrane protein 4, phosphatidylinositol glycan anchor biosynthesis class C, protein disulfide isomerase family A member 4 and growth arrest specific 5. Screened DEGs were enriched in the complement pathway. In the PPI network, ubiquitin C (UBC) was the hub node. UBC was predicted to be regulated by several TFs, including specificity protein 1 (SP1), FBJ murine osteosarcoma viral oncogene homolog (FOS), proto-oncogene c-JUN (JUN), FOS-like antigen 2 (FOSL2) and SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A, member 4 (SMARCA4), and several miRNAs, including miR-30 and miR-181. Results from the present study demonstrated that UBC, SP1, FOS, JUN, FOSL2, SMARCA4, miR-30 and miR-181 may participate in the development of HCC.

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          Most cited references28

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          A concordance correlation coefficient to evaluate reproducibility.

          L Lin (1989)
          A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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            Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma.

            Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. Here, we performed high-resolution copy-number analysis on 125 HCC tumors and whole-exome sequencing on 24 of these tumors. We identified 135 homozygous deletions and 994 somatic mutations of genes with predicted functional consequences. We found new recurrent alterations in four genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses showed tumor suppressor properties for IRF2, whose inactivation, exclusively found in hepatitis B virus (HBV)-related tumors, led to impaired TP53 function. In contrast, inactivation of chromatin remodelers was frequent and predominant in alcohol-related tumors. Moreover, association of mutations in specific genes (RPS6KA3-AXIN1 and NFE2L2-CTNNB1) suggested that Wnt/β-catenin signaling might cooperate in liver carcinogenesis with both oxidative stress metabolism and Ras/mitogen-activated protein kinase (MAPK) pathways. This study provides insight into the somatic mutational landscape in HCC and identifies interactions between mutations in oncogene and tumor suppressor gene mutations related to specific risk factors.
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              Statistical design and analysis of RNA sequencing data.

              Next-generation sequencing technologies are quickly becoming the preferred approach for characterizing and quantifying entire genomes. Even though data produced from these technologies are proving to be the most informative of any thus far, very little attention has been paid to fundamental design aspects of data collection and analysis, namely sampling, randomization, replication, and blocking. We discuss these concepts in an RNA sequencing framework. Using simulations we demonstrate the benefits of collecting replicated RNA sequencing data according to well known statistical designs that partition the sources of biological and technical variation. Examples of these designs and their corresponding models are presented with the goal of testing differential expression.
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                Author and article information

                Journal
                Mol Med Rep
                Mol Med Rep
                Molecular Medicine Reports
                D.A. Spandidos
                1791-2997
                1791-3004
                November 2017
                11 September 2017
                11 September 2017
                : 16
                : 5
                : 6674-6682
                Affiliations
                Department of Infectious Diseases, Baoji Municipal Central Hospital, Baoji, Shaanxi 721008, P.R. China
                Author notes
                Correspondence to: Dr Feng Du, Department of Infectious Diseases, Baoji Municipal Central Hospital, 8 Jiang Tan Road, Baoji, Shaanxi 721008, P.R. China, E-mail: dufengdhdh@ 123456hotmail.com
                Article
                mmr-16-05-6674
                10.3892/mmr.2017.7457
                5865798
                28901494
                649ebace-5f19-49ee-a262-1cf2b07ecb5d
                Copyright: © Liu et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 22 February 2016
                : 22 February 2017
                Categories
                Articles

                hepatic carcinoma,rna-sequencing,transcription factor,mirna

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