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      LncACTdb 3.0: an updated database of experimentally supported ceRNA interactions and personalized networks contributing to precision medicine

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          Abstract

          LncACTdb 3.0 is a comprehensive database of experimentally supported interactions among competing endogenous RNA (ceRNA) and the corresponding personalized networks contributing to precision medicine. LncACTdb 3.0 is freely available at http://bio-bigdata.hrbmu.edu.cn/LncACTdb or http://www.bio-bigdata.net/LncACTdb. We have updated the LncACTdb 3.0 database with several new features, including (i) 5669 experimentally validated ceRNA interactions across 25 species and 537 diseases/phenotypes through manual curation of published literature, (ii) personalized ceRNA interactions and networks for 16 228 patients from 62 datasets in TCGA and GEO, (iii) sub-cellular and extracellular vesicle locations of ceRNA manually curated from literature and data sources, (iv) more than 10 000 experimentally supported long noncoding RNA (lncRNA) biomarkers associated with tumor diagnosis and therapy, and (v) lncRNA/mRNA/miRNA expression profiles with clinical and pathological information of thousands of cancer patients. A panel of improved tools has been developed to explore the effects of ceRNA on individuals with specific pathological backgrounds. For example, a network tool provides a comprehensive view of lncRNA-related, patient-specific, and custom-designed ceRNA networks. LncACTdb 3.0 will provide novel insights for further studies of complex diseases at the individual level and will facilitate the development of precision medicine to treat such diseases.

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          Most cited references33

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          Hallmarks of Cancer: The Next Generation

          Douglas Hanahan, Robert A. Weinberg (2011)
          The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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            A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language?

            Leonardo Salmena, Laura Poliseno, Yvonne Tay … (2011)
            Here, we present a unifying hypothesis about how messenger RNAs, transcribed pseudogenes, and long noncoding RNAs "talk" to each other using microRNA response elements (MREs) as letters of a new language. We propose that this "competing endogenous RNA" (ceRNA) activity forms a large-scale regulatory network across the transcriptome, greatly expanding the functional genetic information in the human genome and playing important roles in pathological conditions, such as cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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              starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data

              Jun-Hao Li, Shun Liu, Hui Zhou … (2013)
              Although microRNAs (miRNAs), other non-coding RNAs (ncRNAs) (e.g. lncRNAs, pseudogenes and circRNAs) and competing endogenous RNAs (ceRNAs) have been implicated in cell-fate determination and in various human diseases, surprisingly little is known about the regulatory interaction networks among the multiple classes of RNAs. In this study, we developed starBase v2.0 (http://starbase.sysu.edu.cn/) to systematically identify the RNA–RNA and protein–RNA interaction networks from 108 CLIP-Seq (PAR-CLIP, HITS-CLIP, iCLIP, CLASH) data sets generated by 37 independent studies. By analyzing millions of RNA-binding protein binding sites, we identified ∼9000 miRNA-circRNA, 16 000 miRNA-pseudogene and 285 000 protein–RNA regulatory relationships. Moreover, starBase v2.0 has been updated to provide the most comprehensive CLIP-Seq experimentally supported miRNA-mRNA and miRNA-lncRNA interaction networks to date. We identified ∼10 000 ceRNA pairs from CLIP-supported miRNA target sites. By combining 13 functional genomic annotations, we developed miRFunction and ceRNAFunction web servers to predict the function of miRNAs and other ncRNAs from the miRNA-mediated regulatory networks. Finally, we developed interactive web implementations to provide visualization, analysis and downloading of the aforementioned large-scale data sets. This study will greatly expand our understanding of ncRNA functions and their coordinated regulatory networks.
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                Author and article information

                Contributors
                Peng Wang:
                ORCID: https://orcid.org/0000-0002-5716-9937
                Qiuyan Guo
                Yue Qi
                Yangyang Hao
                Yue Gao
                Hui Zhi:
                ORCID: https://orcid.org/0000-0001-9103-8642
                Yuanfu Zhang
                Yue Sun
                Yakun Zhang
                Mengyu Xin
                Yunpeng Zhang
                Shangwei Ning:
                ORCID: https://orcid.org/0000-0003-4079-8945
                Xia Li:
                ORCID: https://orcid.org/0000-0002-9794-2648
                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: 07 January 2022
                Publication date (Electronic): 26 November 2021
                Publication date PMC-release: 26 November 2021
                Volume: 50
                Issue: D1
                Pages: D183-D189
                Affiliations
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                Department of Gynecology, the First Affiliated Hospital of Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081, China
                Author notes
                To whom correspondence should be addressed. Tel: +86 451 86615922; Fax: +86 451 86615922; Email: lixia@ 123456hrbmu.edu.cn
                Correspondence may also be addressed to Shangwei Ning. Email: ningsw@ 123456ems.hrbmu.edu.cn
                Correspondence may also be addressed to YunPeng Zhang. Email: zhangyp@ 123456hrbmu.edu.cn

                The authors wish it to be known that, in their opinion, the first four authors should be regarded as joint First Authors.

                Author information
                https://orcid.org/0000-0002-5716-9937
                https://orcid.org/0000-0001-9103-8642
                https://orcid.org/0000-0003-4079-8945
                https://orcid.org/0000-0002-9794-2648
                Article
                Publisher ID: gkab1092
                DOI: 10.1093/nar/gkab1092
                PMC ID: 8728196
                PubMed ID: 34850125
                SO-VID: 34339ad5-8fe6-49a5-885a-0f933cfb5755
                Copyright © © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                Date accepted : 18 November 2021
                Date revision received : 10 October 2021
                Date received : 15 September 2021
                Page count
                Pages: 7
                Funding
                Funded by: National Key Research and Development Program of China, DOI 10.13039/501100012166;
                Award ID: 2018YFC2000100
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 32070673
                Award ID: 32070622
                Award ID: 32070672
                Award ID: 61873075
                Award ID: 62172131
                Award ID: 81902646
                Funded by: Heilongjiang Touyan Innovation Team Program;
                Funded by: Heilongjiang Provincial Natural Science Foundation;
                Award ID: YQ2021C026
                Funded by: Postdoctoral Science Foundation of China;
                Award ID: 2020M670922
                Funded by: Postdoctoral Foundation of Heilongjiang Province;
                Award ID: LBH-Z19077
                Award ID: LBH-Q20047
                Categories
                Subject: AcademicSubjects/SCI00010
                Subject: Database Issue

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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