Identification of Diverse Adenosine-to-Inosine RNA Editing Subtypes in Colorectal Cancer.
- Author:
Si Hyun LEE
1
;
Hwang Phill KIM
;
Jun Kyu KANG
;
Sang Hyun SONG
;
Sae Won HAN
;
Tae You KIM
Author Information
- Publication Type:Original Article
- Keywords: RNA editing; Colorectal neoplasms; Transcriptome sequencing; GLI family zinc finger 1; Adenosine deaminase
- MeSH: Adenosine Deaminase; Base Sequence; Biomarkers; Clinical Coding; Colorectal Neoplasms*; Genome; Humans; Inosine; RNA Editing*; RNA*; Transcriptome
- From:Cancer Research and Treatment 2017;49(4):1077-1087
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: RNA editing generates protein diversity by altering RNA sequences in coding regions without changing the overall DNA sequence. Adenosine-to-inosine (A-to-I) RNA editing events have recently been reported in some types of cancer, but they are rare in human colorectal cancer (CRC). Therefore, this study was conducted to identify diverse RNA editing in CRC. MATERIALS AND METHODS: We compared transcriptome data of 39 CRC samples and paired adjacent tissues from The Cancer Genome Atlas database to identify RNA editing patterns in CRC, focusing on canonical A-to-I RNA edits in coding sequence regions. We investigated nonsynonymous RNA editing patterns by comparing tumor and normal tissue transcriptome data. RESULTS: The number of RNA edits varied from 12 to 42 per sample. We also observed that hypoand hyper-RNA editing patterns were distinguishable within the samples. We found 10 recurrent nonsynonymous RNA editing candidates in nine genes (PDLIM, NEIL1, SRP9, GLI1, APMAP, IGFBP7, ZNF358, COPA, and ZNF587B) and validated some by Sanger sequencing and the inosine chemical erasing assay. We further showed that editing at these positions was performed by the adenosine deaminase acting on RNA 1 enzyme. Most of these genes are hypoedited in CRC, but editing of GLI1 was increased in cancer tissues compared with normal tissues. CONCLUSION: Our results show that nonsynonymous RNA editing patterns can be used to identify CRC patients and could serve as novel biomarkers for CRC.
