Abstract

Colorectal cancer (CRC) stands as a major contributor to cancer-related fatalities within China. There is an urgent need to identify accurate biomarkers for recurrence predicting in CRC. Reduced representation bisulfite sequencing was used to perform a comparative analysis of methylation profiles in tissue samples from 30 recurrence to 30 non-recurrence patients with CRC. Least absolute shrinkage and selection operator method was performed to select the differential methylation regions (DMRs) and built a DNA methylation classifier for predicting recurrence. Based on the identified top DMRs, a methylation classifier was built and consisted of eight hypermethylated DMRs in CRC. The DNA methylation classifier showed high accuracy for predicting recurrence with an area under the receiver operator characteristic curve of 0.825 (95% CI 0.680–0.970). The Kaplan–Meier survival analysis demonstrated that CRC patients with high methylation risk score, evaluated by the DNA methylation classifier, had poorer survival than low risk score (Hazard Ratio 4.349; 95% CI 1.783–10.61, P = 0.002). And only CRC patients with low methylation risk score could acquire benefit from adjuvant therapy. The DNA methylation classifier has been proved as crucial biomarkers for predicting recurrence and exhibited promising prognostic value after curative surgery in patients with CRC.

Details

Title
Genome wide identification of novel DNA methylation driven prognostic markers in colorectal cancer
Author
Ma, Yuhua 1 ; Li, Yuanxin 1 ; Wen, Zhahong 2 ; Lai, Yining 1 ; Kamila, Kulaixijiang 1 ; Gao, Jing 1 ; Xu, Wang-yang 2 ; Gong, Chengxiang 2 ; Chen, Feifan 2 ; Shi, Liuqing 2 ; Zhang, Yunzhi 2 ; Chen, Hanzhang 3 ; Zhu, Min 1 

 Karamay Central Hospital, Xinjiang Key Laboratory of Clinical Genetic Testing and Biomedical Information, Karamay, China (GRID:grid.459690.7); Karamay Central Hospital, Department of Pathology, Karamay, China (GRID:grid.459690.7) 
 Singlera Genomics (Shanghai) Ltd., Shanghai, China (GRID:grid.520179.8) 
 Zhabei Central Hospital of Shanghai, Department of Pathology, Shanghai, China (GRID:grid.520179.8) 
Pages
15654
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3076842283
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.