Title |
The Genomic Landscape and Clinical Relevance of A-to-I RNA Editing in Human Cancers
|
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Published in |
Cancer Cell, October 2015
|
DOI | 10.1016/j.ccell.2015.08.013 |
Pubmed ID | |
Authors |
Leng Han, Lixia Diao, Shuangxing Yu, Xiaoyan Xu, Jie Li, Rui Zhang, Yang Yang, Henrica M.J. Werner, A. Karina Eterovic, Yuan Yuan, Jun Li, Nikitha Nair, Rosalba Minelli, Yiu Huen Tsang, Lydia W.T. Cheung, Kang Jin Jeong, Jason Roszik, Zhenlin Ju, Scott E. Woodman, Yiling Lu, Kenneth L. Scott, Jin Billy Li, Gordon B. Mills, Han Liang |
Abstract |
Adenosine-to-inosine (A-to-I) RNA editing is a widespread post-transcriptional mechanism, but its genomic landscape and clinical relevance in cancer have not been investigated systematically. We characterized the global A-to-I RNA editing profiles of 6,236 patient samples of 17 cancer types from The Cancer Genome Atlas and revealed a striking diversity of altered RNA-editing patterns in tumors relative to normal tissues. We identified an appreciable number of clinically relevant editing events, many of which are in noncoding regions. We experimentally demonstrated the effects of several cross-tumor nonsynonymous RNA editing events on cell viability and provide the evidence that RNA editing could selectively affect drug sensitivity. These results highlight RNA editing as an exciting theme for investigating cancer mechanisms, biomarkers, and treatments. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 30% |
United Kingdom | 5 | 25% |
Germany | 1 | 5% |
Mexico | 1 | 5% |
Brazil | 1 | 5% |
Sweden | 1 | 5% |
Unknown | 5 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 13 | 65% |
Members of the public | 6 | 30% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | <1% |
United Kingdom | 2 | <1% |
Denmark | 2 | <1% |
Australia | 1 | <1% |
Sweden | 1 | <1% |
Canada | 1 | <1% |
Norway | 1 | <1% |
China | 1 | <1% |
Chile | 1 | <1% |
Other | 0 | 0% |
Unknown | 371 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 93 | 24% |
Researcher | 81 | 21% |
Student > Master | 32 | 8% |
Student > Bachelor | 31 | 8% |
Other | 18 | 5% |
Other | 42 | 11% |
Unknown | 87 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 113 | 29% |
Agricultural and Biological Sciences | 100 | 26% |
Medicine and Dentistry | 31 | 8% |
Computer Science | 8 | 2% |
Engineering | 7 | 2% |
Other | 33 | 9% |
Unknown | 92 | 24% |