Cancer Res Treat.  2017 Oct;49(4):1077-1087. 10.4143/crt.2016.301.

Identification of Diverse Adenosine-to-Inosine RNA Editing Subtypes in Colorectal Cancer

• Lee SH
• Kim HP
• Kang JK
• Song SH
• Han SW
• Kim TY

• KMID: 2394826
• DOI: http://doi.org/10.4143/crt.2016.301

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.

Keyword

RNA editing; Colorectal neoplasms; Transcriptome sequencing; GLI family zinc finger 1; Adenosine deaminase

MeSH Terms

Adenosine Deaminase
Base Sequence
Biomarkers
Clinical Coding
Colorectal Neoplasms*
Genome
Humans
Inosine
RNA Editing*
RNA*
Transcriptome
Adenosine Deaminase
Biomarkers
Inosine
RNA

Figure

• 

  Fig. 1. The pattern of nonsynonymous RNA editing. (A) Overall number of nonsynonymous A-to-I RNA editing sites in each sample. The number of samples was 39. (B) Percentage of hyper- and hypo-RNA editing. Hyperediting was defined as editing in more than 10% in tumor than normal tissue. Hypoediting was defined as editing of less than 10% in tumor than normal tissue.

• 

  Fig. 2. Hypoediting sites in colorectal cancer. RNA editing detected among 39 paired specimens of colorectal tumor and adjacent normal tissues. The percentage of RNA editing was obtained from the The Cancer Genome Atlas transcriptome dataset. The p-value was calculated by a Student’s t test. (A, B) IGFBP7 (chr4:57976234, c.A284G, p.K95R) and (chr4:57976286, c.A232G, p.R78). (C) COPA (chr1:160302244, c.A490G, p.I164V). (D) ZNF358 (chr19:7585273, c.A1145G, p.K382R).

• 

  Fig. 3. RNA editing of GLI1 is hyperedited in colorectal cancer. (A) GLI1 RNA editing (chr12:57864624, c.A2101G:p.R701G) detected in The Cancer Genome Atlas transcriptome data. (B) GLI1 RNA editing validated in gDNA (top) and cDNA (bottom) by Sanger sequencing in SNU-254 cells. (C) cDNA of normal and tumor tissue was amplified, and sequencing was performed by Sanger sequencing. (D) GLI1 editing percentage; the percentage of editing was determined using pyrosequencing. n=10; the p-value was calculated by a Student’s t test (*p < 0.05).

• 

  Fig. 4. Validation of the editing candidates. (A) RNA editing of SRP9 (chr1:225974614) and NEIL1 (chr15:75646086) was validated in gDNA (top) and cDNA (bottom) by Sanger sequencing in SNU-81 cells. (B) The top panels show the chromatograms of regions amplified from gDNA in SNU-81 cells. The middle panels show the chromatograms of cDNA amplified from nontreated cyanoethylation. Cyanoethylation treated RNA was amplified and their chromatograms are displayed along the bottom line. (C) Sanger sequencing results of SRP9 and NEIL1 from siRNA control (top) and adenosine deaminase acting on RNA 1 (ADAR1; bottom) treated SNU-81 cells. (D) The siRNA knockdown efficiency of ADAR1 was tested by real-time quantitative reverse transcription–polymerase chain reaction (left) and western blot (right).

Reference

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