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      Identification of a long non-coding RNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

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          Abstract

          Long non-coding RNAs (lncRNAs) have a number of functions in various cellular processes and are potential prognostic factors for lung adenocarcinoma (LUAD). A gene risk model could provide novel evidence to improve the prediction of overall outcomes and provide more potential biomarkers. The present study aimed improve a previously published method of gene signature construction to make it more robust and accurate. The lncRNA expression profiles from 594 patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database and samples were divided into high- and low-risk groups based on median risk scores calculated using a prognosis-related risk score formula. Univariate Cox regression, least absolute shrinkage and selection operator algorithm and multivariate Cox regression were performed to construct a gene signature based on the differentially expressed lncRNAs in patients with LUAD. The robustness and accuracy of the present model was assessed using area under the calculated curves (AUC) and Kaplan-Meier (K-M) survival analysis of the high- and low-risk cohorts. Potential biomarkers associated with survival status were then identified using K-M survival analysis and potential biomarker functions were predicted using enrichment analysis of co-expressed mRNAs. The gene signature constructed contained 44 lncRNAs. The AUCs for 3- and 5-year survival with the model were 0.836 and 0.818, respectively, of a time-dependent receiver operator characteristic curve. Moreover, lncRNAs AC124804.1 and MIR34AHG were identified using K-M survival analysis and the potential function of these two lncRNAs was predicted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment. The present lncRNA model provides novel insight which may improve prediction of prognosis for patients with LUAD and identify potentially novel biomarkers for the diagnosis.

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          Most cited references31

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          Long non-coding RNAs in Oral squamous cell carcinoma: biologic function, mechanisms and clinical implications

          There is growing evidence that regions of the genome that cannot encode proteins play an important role in diseases. These regions are usually transcribed into long non-coding RNAs (lncRNAs). LncRNAs, little or no coding potential, are defined as capped transcripts longer than 200 nucleotides. New sequencing technologies have shown that a large number of aberrantly expressed lncRNAs are associated with multiple cancer types and indicated they have emerged as an important class of pervasive genes during the development and progression of cancer. However, the underlying mechanism in cancer is still unknown. Therefore, it is necessary to elucidate the lncRNA function. Notably, many lncRNAs dysregulation are associated with Oral squamous cell carcinoma (OSCC) and affect various aspects of cellular homeostasis, including proliferation, survival, migration or genomic stability. This review expounds the up- or down-regulation of lncRNAs in OSCC and the molecular mechanisms by which lncRNAs perform their function in the malignant cell. Finally, the potential of lncRNAs as non-invasive biomarkers for OSCC diagnosis are also described. LncRNAs hold promise as prospective novel therapeutic targets, but more research is needed to gain a better understanding of their biologic function.
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            HCP5 is a SMAD3-responsive long non-coding RNA that promotes lung adenocarcinoma metastasis via miR-203/SNAI axis

            Introduction: Transforming growth factor-beta (TGFβ) signaling plays a vital role in lung adenocarcinoma (LUAD) progression. However, the involvement of TGFβ-regulated long non-coding RNAs (lncRNAs) in metastasis of LUAD remains poorly understood. Methods: We performed bioinformatic analyses to identify putative lncRNAs regulated by TGF-β/SMAD3 and validated the results by quantitative PCR in LUAD cells. We performed luciferase reporter and chromatin immunoprecipitation assays to demonstrate the transcriptional regulation of the lncRNA histocompatibility leukocyte antigen complex P5 (HCP5) we decided to focus on. Stable HCP5 knockdown and HCP5-overexpressing A549 cell variants were generated respectively, to study HCP5 function and understand its mechanism of action. We also confirmed our findings in mouse xenografts and metastasis models. We analyzed the correlation between the level of lncRNA expression with EGFR, KRAS mutations, smoke state and prognostic of LUAD patients. Results: We found that the lncRNA HCP5 is induced by TGFβ and transcriptionally regulated by SMAD3, which promotes LUAD tumor growth and metastasis. Moreover, HCP5 is overexpressed in tumor tissues of patients with LUAD, specifically in patients with EGFR and KRAS mutations and current smoker. HCP5 high expression level is positively correlated with poor prognosis of patients with LUAD. Finally, we demonstrated that upregulation of HCP5 increases the expression of Snail and Slug by sponging the microRNA-203 (miR-203) and promoting epithelial-mesenchymal transition (EMT) in LUAD cells. Conclusions: Our work demonstrates that the lncRNA HCP5 is transcriptionally regulated by SMAD3 and acts as a new regulator in the TGFβ/SMAD signaling pathway. Therefore, HCP5 can serve as a potential therapeutic target in LUAD.
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              Long noncoding RNAs as novel predictors of survival in human cancer: a systematic review and meta-analysis

              Background Expression of various long noncoding RNAs (lncRNAs) may affect cancer prognosis. Here, we aim to gather and examine all evidence on the potential role of lncRNAs as novel predictors of survival in human cancer. Methods We systematically searched through PubMed, to identify all published studies reporting on the association between any individual lncRNA or group of lncRNAs with prognosis in human cancer (death or other clinical outcomes). Where appropriate, we then performed quantitative synthesis of those results using meta-analytic methods to identify the true effect size of lncRNAs on cancer prognosis. The reliability of those results was then examined using measures of heterogeneity and testing for selective reporting biases. Results Three hundred ninety-two studies were screened to eventually identify 111 eligible studies on 127 datasets. In total, these represented 16,754 independent participants pertaining to 53 individual and 6 grouped lncRNAs within a total of 19 cancer sites. Overall, 83 % of the studies we identified addressed overall survival and 32 % of the studies addressed recurrence-free survival. For overall survival, 96 % (88/92) of studies identified a statistically significant association of lncRNA expression to prognosis. Meta-analysis of 6 out of 7 lncRNAs for which three or more studies were available, identified statistically significant associations with overall survival. The lncRNA HOTAIR was by far the most broadly studied lncRNA (n = 29; of 111 studies) and featured a summary hazard ratio (HR) of 2.22 (95 % confidence interval (CI), 1.86–2.65) with modest heterogeneity (I2 = 49 %; 95 % CI, 14–79 %). Prominent excess significance was demonstrated across all meta-analyses (p-value = 0.0003), raising the possibility of substantial selective reporting biases. Conclusions Multiple lncRNAs have been shown to be strongly associated with prognosis in diverse cancers, but substantial bias cannot be excluded in this field and larger studies are needed to understand whether these prognostic information may eventually be useful. Electronic supplementary material The online version of this article (doi:10.1186/s12943-016-0535-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Oncol Lett
                Oncol Lett
                OL
                Oncology Letters
                D.A. Spandidos
                1792-1074
                1792-1082
                April 2020
                17 February 2020
                17 February 2020
                : 19
                : 4
                : 2793-2800
                Affiliations
                [1 ]Department of Internal Medicine of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100078, P.R. China
                [2 ]Department of Respiratory, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, P.R. China
                Author notes
                Correspondence to: Dr Yanxia Zhang, Department of Respiratory, Dongfang Hospital, Beijing University of Chinese Medicine, 6 Fangxingyuan 1st Block, Beijing 100078, P.R. China, E-mail: zhangyx929@ 123456126.com
                Article
                OL-0-0-11400
                10.3892/ol.2020.11400
                7068299
                2bb4d09c-b8eb-4dee-b5b1-f030b40351b4
                Copyright: © Yu 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
                : 26 July 2019
                : 16 January 2020
                Categories
                Articles

                Oncology & Radiotherapy
                long non-coding rna,lung adenocarcinoma,prognostic signature,risk score,overall survival,biomarkers

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