Literature DB >> 21715563

Adenosine-to-inosine RNA editing meets cancer.

Dan Dominissini1, Sharon Moshitch-Moshkovitz, Ninette Amariglio, Gideon Rechavi.   

Abstract

The role of epigenetics in tumor onset and progression has been extensively addressed. Discoveries in the last decade completely changed our view on RNA. We now realize that its diversity lies at the base of biological complexity. Adenosine-to-inosine (A-to-I) RNA editing emerges a central generator of transcriptome diversity and regulation in higher eukaryotes. It is the posttranscriptional deamination of adenosine to inosine in double-stranded RNA catalyzed by enzymes of the adenosine deaminase acting on RNA (ADAR) family. Thought at first to be restricted to coding regions of only a few genes, recent bioinformatic analyses fueled by high-throughput sequencing revealed that it is a widespread modification affecting mostly non-coding repetitive elements in thousands of genes. The rise in scope is accompanied by discovery of a growing repertoire of functions based on differential decoding of inosine by the various cellular machineries: when recognized as guanosine, it can lead to protein recoding, alternative splicing or altered microRNA specificity; when recognized by inosine-binding proteins, it can result in nuclear retention of the transcript or its degradation. An imbalance in expression of ADAR enzymes with consequent editing dysregulation is a characteristic of human cancers. These alterations may be responsible for activating proto-oncogenes or inactivating tumor suppressors. While unlikely to be an early initiating 'hit', editing dysregulation seems to contribute to tumor progression and thus should be considered a 'driver mutation'. In this review, we examine the contribution of A-to-I RNA editing to carcinogenesis.

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Year:  2011        PMID: 21715563     DOI: 10.1093/carcin/bgr124

Source DB:  PubMed          Journal:  Carcinogenesis        ISSN: 0143-3334            Impact factor:   4.944


  44 in total

Review 1.  Detecting RNA modifications in the epitranscriptome: predict and validate.

Authors:  Mark Helm; Yuri Motorin
Journal:  Nat Rev Genet       Date:  2017-02-20       Impact factor: 53.242

2.  miR-EdiTar: a database of predicted A-to-I edited miRNA target sites.

Authors:  Alessandro Laganà; Alessio Paone; Dario Veneziano; Luciano Cascione; Pierluigi Gasparini; Stefania Carasi; Francesco Russo; Giovanni Nigita; Valentina Macca; Rosalba Giugno; Alfredo Pulvirenti; Dennis Shasha; Alfredo Ferro; Carlo M Croce
Journal:  Bioinformatics       Date:  2012-10-07       Impact factor: 6.937

3.  Splicing variants of ADAR2 and ADAR2-mediated RNA editing in glioma.

Authors:  Yao Fu; Xingli Zhao; Zhaohui Li; Jun Wei; Yu Tian
Journal:  Oncol Lett       Date:  2016-06-15       Impact factor: 2.967

Review 4.  Alu elements: know the SINEs.

Authors:  Prescott Deininger
Journal:  Genome Biol       Date:  2011-12-28       Impact factor: 13.583

5.  RNA editing of SLC22A3 drives early tumor invasion and metastasis in familial esophageal cancer.

Authors:  Li Fu; Yan-Ru Qin; Xiao-Yan Ming; Xian-Bo Zuo; Yu-Wen Diao; Li-Yi Zhang; Jiaoyu Ai; Bei-Lei Liu; Tu-Xiong Huang; Ting-Ting Cao; Bin-Bin Tan; Di Xiang; Chui-Mian Zeng; Jing Gong; Qiangfeng Zhang; Sui-Sui Dong; Juan Chen; Haibo Liu; Jian-Lin Wu; Robert Z Qi; Dan Xie; Li-Dong Wang; Xin-Yuan Guan
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-22       Impact factor: 11.205

6.  Clinical Relevance of Noncoding Adenosine-to-Inosine RNA Editing in Multiple Human Cancers.

Authors:  Tongjun Gu; Audrey Q Fu; Michael J Bolt; Kevin P White
Journal:  JCO Clin Cancer Inform       Date:  2019-06

7.  RED-ML: a novel, effective RNA editing detection method based on machine learning.

Authors:  Heng Xiong; Dongbing Liu; Qiye Li; Mengyue Lei; Liqin Xu; Liang Wu; Zongji Wang; Shancheng Ren; Wangsheng Li; Min Xia; Lihua Lu; Haorong Lu; Yong Hou; Shida Zhu; Xin Liu; Yinghao Sun; Jian Wang; Huanming Yang; Kui Wu; Xun Xu; Leo J Lee
Journal:  Gigascience       Date:  2017-05-01       Impact factor: 6.524

8.  Detection of murine leukemia virus in the Epstein-Barr virus-positive human B-cell line JY, using a computational RNA-Seq-based exogenous agent detection pipeline, PARSES.

Authors:  Zhen Lin; Adriane Puetter; Joseph Coco; Guorong Xu; Michael J Strong; Xia Wang; Claire Fewell; Melody Baddoo; Christopher Taylor; Erik K Flemington
Journal:  J Virol       Date:  2012-01-11       Impact factor: 5.103

9.  Micro-editing mistake translates into a devastating brain tumor.

Authors:  Dan Dominissini; Ninette Amariglio; Gideon Rechavi
Journal:  J Clin Invest       Date:  2012-10-24       Impact factor: 14.808

10.  Whole-genome sequencing of the Akata and Mutu Epstein-Barr virus strains.

Authors:  Zhen Lin; Xia Wang; Michael J Strong; Monica Concha; Melody Baddoo; Guorong Xu; Carl Baribault; Claire Fewell; William Hulme; Dale Hedges; Christopher M Taylor; Erik K Flemington
Journal:  J Virol       Date:  2012-11-14       Impact factor: 5.103

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