An assessment of 6,226 samples from patients with 17 different cancer types taken from The Cancer Genome Atlas has revealed new information about RNA editing events in tumors versus normal tissue, and provided evidence that RNA editing could selectively affect drug sensitivity. RNA editing is the process where genetic information is altered in the RNA molecule. Once thought rare in humans and other vertebrates, RNA editing is now recognized as widespread in the human genome.
Results from the study are published in the Oct. 1 online edition of Cancer Cell.
“These results highlight RNA editing as an exciting theme for investigating cancer mechanisms, biomarkers and treatments,” said Han Liang, Ph.D., associate professor of Bioinformatics and Computational Biology. “In this study, we identified an appreciable number of clinically relevant editing events, many of which are in non-coding regions.”
Liang said that specific RNA editing processes, adenosine-to-inosine (A-to-I), are plentiful in the human genome but have not been investigated in depth. The study provided new detail on this little understood biological phenomenon that may have significant clinical relevance.
“If a protein is only highly edited in the tumor proteins, but not in normal proteins, then it’s possible that a specific drug could be designed to inhibit the edited mutant protein,” said Liang. “Previous studies have focused on DNA mutations and mainly focused on RNA editing in normal tissues. The role of RNA editing in human cancers is only beginning to emerge from those early studies of individual patient samples in a few cancer types.”
The larger scale Cancer Genome Atlas study provided the information needed to alter proteins or RNA sequences that may act as “drivers” for prognostic biomarkers or therapeutic targets. RNA editing adds another layer of complexity in the quest to predict patient survivability and suggest new therapies, said Liang.
MD Anderson study participants included Leng Han, Ph.D., Lixia Diao, Ph.D., Yang Yang, Ph.D., Yuan Yuan, Ph.D., Jun Li, Ph.D. and Zhenlin Ju, Ph.D., all of Bioinformatics and Computational Biology; Shuangxing Yu, M.D., Jie Li, Karina Eterovic, Ph.D., Lydia Cheung, Ph.D., Kang Jin Jeong, Ph.D., Yiling Lu, M.D. and Gordon Mills, M.D., Ph.D., Systems Biology; and Jason Roszik, Ph.D. and Scott Woodman, M.D., Ph.D., Melanoma Medical Oncology.
Other participating institutions included China Medical University, Shenyang City, China; Stanford University, Stanford, Calif.; The University of Texas Health Science Center at Houston School of Public Health; Haukeland University Hospital, Bergen, Norway; Baylor College of Medicine, Houston; and Sun Yat-Sen University, Guangzhou, China.
The study was funded by the National Institutes of Health (CA168394, CA098258, U24CA143883, R01CA175486, CA016672 and R01GM102484), the Cancer Prevention and Research Institute of Texas (RP140462), The Jeanne F. Shelby Scholarship Fund, the Lorraine Dell Program in Bioinformatics for Personalization of Cancer Medicine, the Adelson Medical Research Foundation, and AstraZeneca.
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