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      The prognostic value of LINC01296 in pan-cancers and the molecular regulatory mechanism in hepatocellular carcinoma: a comprehensive study based on data mining, bioinformatics, and in vitro validation

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          Background and aims

          This study aimed to clarify the prognostic role of LINC01296 in various cancers, and to evaluate its effect on proliferation, metastasis, and the cell cycle in hepatocellular carcinoma (HCC) by data mining, bioinformatics, and in vitro validation.


          The prognostic role of LINC01296 in cancer patients was assessed by searching the PubMed, Embase, Web of Science, and Gene Expression Omnibus databases and calculating pooled hazard ratios (HRs) with 95% confidence intervals (CIs); this prognostic role was also evaluated using The Cancer Genome Atlas (TCGA). We detected LINC01296 expression in HCC cell lines, and lentivirus-mediated small interfering RNAs were used to silence LINC01296 in MHCC97H and Hep3B cells to explore the role of LINC01296 in cell proliferation, metastasis, and cell cycle progression with in vitro validation and bioinformatics.


          The results indicated that LINC01296 overexpression was associated with poor overall survival (OS) and disease-free survival (DFS) in various cancers; however, LINC01296 expression was not associated with recurrence-free survival (RFS). Similar results were found with TCGA, which showed that LINC01296 expression was associated with the pathologic stage, tumor size, and differentiation in Asian cancer patients. Additionally, bioinformatics analysis revealed expression of 394 related genes, which indicated that LINC01296 could be involved in the tumorigenesis and progression of HCC. In vitro gene silencing experiments indicated that LINC01296 downregulation repressed cell proliferation, cell cycle progression, and the metastatic potential of HCC through the regulation of BUB1, CCNA2, and CDK1 expression.


          This study demonstrated that LINC01296 expression is related to poor OS and DFS in a variety of cancer types and that LINC01296 has an oncogenic role in HCC.

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          Most cited references 24

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          DAVID: Database for Annotation, Visualization, and Integrated Discovery.

          Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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            New therapies for hepatocellular carcinoma.

            Hepatocellular carcinoma (HCC), one of the most common cancers worldwide, is often diagnosed at an advanced stage when most potentially curative therapies such as resection, transplantation or percutaneous and transarterial interventions are of limited efficacy. The fact that HCC is resistant to conventional chemotherapy, and is rarely amenable to radiotherapy, leaves this disease with no effective therapeutic options and a very poor prognosis. Therefore, the development of more effective therapeutic tools and strategies is much needed. HCCs are phenotypically and genetically heterogeneous tumors that commonly emerge on a background of chronic liver disease. However, in spite of this heterogeneity recent insights into the biology of HCC suggest that certain signaling pathways and molecular alterations are likely to play essential roles in HCC development by promoting cell growth and survival. The identification of such mechanisms may open new avenues for the prevention and treatment of HCC through the development of targeted therapies. In this review we will describe the new potential therapeutic targets and clinical developments that have emerged from progress in the knowledge of HCC biology, In addition, recent advances in gene therapy and combined cell and gene therapy, together with new radiotherapy techniques and immunotherapy in patients with HCC will be discussed.
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              Function of lncRNAs and approaches to lncRNA-protein interactions.

              Long non-coding RNAs (lncRNAs), which represent a new frontier in molecular biology, play important roles in regulating gene expression at epigenetic, transcriptional and post-transcriptional levels. More and more lncRNAs have been found to play important roles in normal cell physiological activities, and participate in the development of varieties of tumors and other diseases. Previously, we have only been able to determine the function of lncRNAs through multiple mechanisms, including genetic imprinting, chromatin remodeling, splicing regulation, mRNA decay, and translational regulation. Application of technological advances to research into the function of lncRNAs is extremely important. The major tools for exploring lncRNAs include microarrays, RNA sequencing (RNA-seq), Northern blotting, real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR), fluorescence in situ hybridization (FISH), RNA interference (RNAi), RNA-binding protein immunoprecipitation (RIP), chromatin isolation by RNA purification (ChIRP), crosslinking-immunopurification (CLIP), and bioinformatic prediction. In this review, we highlight the functions of lncRNAs, and advanced methods to research lncRNA-protein interactions.

                Author and article information

                Onco Targets Ther
                Onco Targets Ther
                OncoTargets and therapy
                19 July 2019
                : 12
                : 5861-5885
                [1 ]Department of General Surgery, First Hospital/First Clinical College of Shanxi Medical University , Taiyuan, Shanxi 030001, People’s Republic of China
                Author notes
                Correspondence: Zhigang Wei; Jiansheng Guo Department of General Surgery, First Hospital/First Clinical Medical College of Shanxi Medical University, Jiefangnan Road , Taiyuan, Shanxi030001, People’s Republic of ChinaTel +86 1 503 515 8467 Email sdyywzg2018@ 123456126.com ; sdyygjs2017@ 123456126.com

                These authors contributed equally to this work

                © 2019 Liang et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 13, Tables: 7, References: 37, Pages: 25
                Original Research

                Oncology & Radiotherapy

                bioinformatics, linc01296, hcc, cancers, lncrna


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