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      Long Noncoding RNA MALAT1 Promotes Colorectal Cancer Progression by Acting as a ceRNA of miR-508-5p to Regulate RAB14 Expression

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          Abstract

          Accumulating evidence suggested that lncRNA MALAT1 plays critical roles in the commencement and progression of malignant cancers. Nevertheless, the function of MALAT1 in colorectal cancer (CRC) remains largely unknown. In the present study, we reported that MALAT1 expression is significantly upregulated in CRC and correlated with advanced TNM stage, lymph node metastasis, and worse prognosis in patients. Functional assays revealed that MALAT1 knockdown reduced CRC cell growth and invasion abilities in vitro. Mechanistically, we discovered that MALAT1 may serve as a competing endogenous RNA (ceRNA) to miR-508-5p in CRC progression. Bioinformatics analysis and luciferase assays confirmed that RAB14 acts as a target of miR-508-5p. In addition, downregulation of RAB14 reduced the progression of CRC. Collectively, our findings indicated that MALAT1 could promote CRC progress by sponging miR-508-5p and enhancing RAB14 expression, which provides a therapeutic target in CRC treatment.

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          Most cited references32

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

            Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
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              Long non-coding RNAs: insights into functions.

              In mammals and other eukaryotes most of the genome is transcribed in a developmentally regulated manner to produce large numbers of long non-coding RNAs (ncRNAs). Here we review the rapidly advancing field of long ncRNAs, describing their conservation, their organization in the genome and their roles in gene regulation. We also consider the medical implications, and the emerging recognition that any transcript, regardless of coding potential, can have an intrinsic function as an RNA.
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                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2020
                4 December 2020
                : 2020
                : 4157606
                Affiliations
                1First Department of Oncology, Xinxiang Central Hospital, Xinxiang, 453000 Henan, China
                2Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, 475000 Henan, China
                Author notes

                Academic Editor: Guangcun Huang

                Author information
                https://orcid.org/0000-0003-4776-0165
                https://orcid.org/0000-0001-8924-9061
                Article
                10.1155/2020/4157606
                7732393
                33344634
                39088581-bd0c-49af-99e8-e7fa7399dcc8
                Copyright © 2020 Chen Zhang et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 January 2020
                : 1 May 2020
                : 9 June 2020
                Funding
                Funded by: Henan Science and Technology Project
                Award ID: 182102310372
                Categories
                Research Article

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