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      LINC00261 and the Adjacent Gene FOXA2 Are Epithelial Markers and Are Suppressed during Lung Cancer Tumorigenesis and Progression

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          Abstract

          Lung cancer continues to be the leading cause of cancer-related deaths worldwide, with little improvement in patient survival rates in the past decade. Long non-coding RNAs (lncRNAs) are gaining importance as possible biomarkers with prognostic potential. By large-scale data mining, we identified LINC00261 as a lncRNA which was significantly downregulated in lung cancer. Low expression of LINC00261 was associated with recurrence and poor patient survival in lung adenocarcinoma. Moreover, the gene pair of LINC00261 and its neighbor FOXA2 were significantly co-regulated. LINC00261 as well as FOXA2 negatively correlated with markers for epithelial-to-mesenchymal transition (EMT) and were suppressed by the EMT inducer TGFβ. Hierarchical clustering of gene expression data from lung cancer cell lines could further verify the association of high LINC00261/ FOXA2 expression to an epithelial gene signature. Furthermore, higher expression of the LINC00261/ FOXA2 locus was associated with lung cancer cell lines with lower migratory capacity. All these data establish LINC00261 and FOXA2 as an epithelial-specific marker pair, downregulated during EMT and lung cancer progression, and associated with lower cell migration potential in lung cancer cells.

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          Most cited references15

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          Molecular networks that regulate cancer metastasis.

          Tumor metastases are responsible for approximately 90% of all cancer-related deaths. Although many patients can be cured, in the US and UK, cancer still causes 730,000 deaths every year, and it is second only to cardiovascular disease as a cause of death. The functional roles of many critical players involved in metastasis have been delineated in great detail in recent years, due to the draft of the human genome and to many associated discoveries. Here, we address several genetic events and critical factors that define the metastatic phenotype acquired during tumorigenesis. This involves molecular networks that promote local cancer-cell invasion, single-cell invasion, formation of the metastatic microenvironment of primary tumors, intravasation, lymphogenic metastasis, extravasation, and metastatic outgrowth. Altogether, these functional networks of molecules contribute to the development of a selective environment that promotes the seeding and malignant progression of tumorigenic cells in distant organs. We include here candidate target proteins and signaling pathways that are now under clinical investigation. Although many of these trials are still ongoing, they provide the basis for the development of new aspects in the treatment of metastatic cancers, which involves inhibition of these proteins and their molecular networks. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Prediction of recurrence-free survival in postoperative non-small cell lung cancer patients by using an integrated model of clinical information and gene expression.

            One of the main challenges of lung cancer research is identifying patients at high risk for recurrence after surgical resection. Simple, accurate, and reproducible methods of evaluating individual risks of recurrence are needed. Based on a combined analysis of time-to-recurrence data, censoring information, and microarray data from a set of 138 patients, we selected statistically significant genes thought to be predictive of disease recurrence. The number of genes was further reduced by eliminating those whose expression levels were not reproducible by real-time quantitative PCR. Within these variables, a recurrence prediction model was constructed using Cox proportional hazard regression and validated via two independent cohorts (n = 56 and n = 59). After performing a log-rank test of the microarray data and successively selecting genes based on real-time quantitative PCR analysis, the most significant 18 genes had P values of <0.05. After subsequent stepwise variable selection based on gene expression information and clinical variables, the recurrence prediction model consisted of six genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, and IFI44). Two pathologic variables, pStage and cellular differentiation, were developed. Validation by two independent cohorts confirmed that the proposed model is significantly accurate (P = 0.0314 and 0.0305, respectively). The predicted median recurrence-free survival times for each patient correlated well with the actual data. We have developed an accurate, technically simple, and reproducible method for predicting individual recurrence risks. This model would potentially be useful in developing customized strategies for managing lung cancer.
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              Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer

              Background Previous studies identified microRNAs (miRNAs) and messenger RNAs with significantly different expression between normal pancreas and pancreatic cancer (PDAC) tissues. Due to technological limitations of microarrays and real-time PCR systems these studies focused on a fixed set of targets. Expression of other RNA classes such as long intergenic non-coding RNAs or sno-derived RNAs has rarely been examined in pancreatic cancer. Here, we analysed the coding and non-coding transcriptome of six PDAC and five control tissues using next-generation sequencing. Results Besides the confirmation of several deregulated mRNAs and miRNAs, miRNAs without previous implication in PDAC were detected: miR-802, miR-2114 or miR-561. SnoRNA-derived RNAs (e.g. sno-HBII-296B) and piR-017061, a piwi-interacting RNA, were found to be differentially expressed between PDAC and control tissues. In silico target analysis of miR-802 revealed potential binding sites in the 3′ UTR of TCF4, encoding a transcription factor that controls Wnt signalling genes. Overexpression of miR-802 in MiaPaCa pancreatic cancer cells reduced TCF4 protein levels. Using Massive Analysis of cDNA Ends (MACE) we identified differential expression of 43 lincRNAs, long intergenic non-coding RNAs, e.g. LINC00261 and LINC00152 as well as several natural antisense transcripts like HNF1A-AS1 and AFAP1-AS1. Differential expression was confirmed by qPCR on the mRNA/miRNA/lincRNA level and by immunohistochemistry on the protein level. Conclusions Here, we report a novel lncRNA, sncRNA and mRNA signature of PDAC. In silico prediction of ncRNA targets allowed for assigning potential functions to differentially regulated RNAs. Electronic supplementary material The online version of this article (doi:10.1186/s12943-015-0358-5) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Noncoding RNA
                Noncoding RNA
                ncrna
                Non-Coding RNA
                MDPI
                2311-553X
                28 December 2018
                March 2019
                : 5
                : 1
                : 2
                Affiliations
                [1 ]Division of Cancer Research, Department of Thoracic Surgery, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany; s.dhamija@ 123456dkfz.de (S.D.); andrea.becker@ 123456uniklinik-freiburg.de (A.C.B.); yogita.sharma@ 123456med.lu.se (Y.S.); ksenia.myacheva@ 123456uniklinik-freiburg.de (K.M.)
                [2 ]German Cancer Consortium (DKTK), Partner Site Freiburg, 79106 Freiburg, Germany
                [3 ]Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; jeanette.seiler@ 123456dkfz-heidelberg.de
                [4 ]CellNetworks Excellence Cluster, University of Heidelberg, 69120 Heidelberg, Germany
                Author notes
                [* ]Correspondence: s.diederichs@ 123456dkfz.de
                Author information
                https://orcid.org/0000-0001-7901-4752
                Article
                ncrna-05-00002
                10.3390/ncrna5010002
                6468413
                30597925
                48b9e7fc-2c93-40e3-a2b6-2d519fc87b48
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 November 2018
                : 17 December 2018
                Categories
                Article

                lncrna,non-coding rna,metastasis,emt,lung cancer,foxa2,cell migration

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