Comprehensive analysis identifying aberrant DNA methylation in rectal mucosa from ulcerative colitis patients with neoplasia
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Yuji Toiyama1, Yoshinaga Okugawa1, Satoru Kondo1, Yoshiki Okita1, Toshimitsu Araki1, Kurando Kusunoki2, Motoi Uchino2, Hiroki Ikeuchi2, Seiichi Hirota3, Akira Mitsui4, Kenji Takehana5, Tsutomu Umezawa5 and Masato Kusunoki1
1Department of Gastrointestinal and Pediatric Surgery, Division of Reparative Medicine, Institute of Life Sciences, Graduate School of Medicine, Mie University, Mie, Japan
2Department of Inflammatory Bowel Disease, Hyogo College of Medicine, Hyogo, Japan
3Department of Surgical Pathology, Hyogo College of Medicine, Hyogo, Japan
4Institute for Innovation, Ajinomoto Co., Inc., Kawasaki, Japan
5R&D Planning Department, EA Pharma Co., Ltd., Tokyo, Japan
Yuji Toiyama, email: [email protected]
Keywords: colitis-associated cancer; methylation; ulcerative colitis
Abbreviations: AUC: area under the ROC curve; CRC: colorectal cancer; FFPE: formalin-fixed paraffin-embedded; ROC: received operating characteristic; UC: ulcerative colitis
Received: June 19, 2018 Accepted: August 10, 2018 Published: September 04, 2018
Background: There are no biomarkers to facilitate the identification of patients with ulcerative colitis (UC) who are at high risk for developing colorectal cancer (CRC). In our current study, we used rectal tissues from UC patients to identify aberrant DNA methylations and evaluated whether they could be used to identify UC patients with coexisting colorectal neoplasia.
Results: Using a training set, we identified 484 differentially methylated regions (DMRs) with absolute delta beta-values > 0.1 in rectal mucosa by using the ChAMP algorithm. Next, pathway enrichment analysis was performed using 484 DMRs to select coordinately methylated DMRs, resulting in the selection of 187 aberrant DMRs in rectal tissues from UC-CRC. Then, the Elastic Net classification algorithm was performed to narrow down optimal aberrant DMRs, and we finally selected 11 DMRs as biomarkers for identification of UC-CRC patients. The 11 chosen DMRs could discriminate UC patients with or without CRC in a training set (area under the curve, 0.96) and the validation set (area under the curve, 0.81).
Conclusions: In conclusion, we identified 11 DMRs that could identify UC patients with CRC complications. Prospective studies should further confirm the validity of these biomarkers.
Methods: We performed genome-wide DNA methylation profiles in rectal mucosal tissues (n = 48) from 24 UC-CRC and 24 UC patients in a training set. Next, we performed comprehensive DNA methylation analysis using rectal mucosal tissues (n = 16) from 8 UC-CRC and 8 UC patients for validation.
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