DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer. (28th September 2022)
- Record Type:
- Journal Article
- Title:
- DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer. (28th September 2022)
- Main Title:
- DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer
- Authors:
- Yu, Huichuan
Wang, Xiaolin
Bai, Liangliang
Tang, Guannan
Carter, Kelly T
Cui, Ji
Huang, Pinzhu
Liang, Li
Ding, Yanqing
Cai, Muyan
Huang, Meijin
Liu, Huanliang
Cao, Guangwen
Gallinger, Steven
Pai, Rish K
Buchanan, Daniel D
Win, Aung Ko
Newcomb, Polly A
Wang, Jianping
Grady, William M
Luo, Yanxin - Abstract:
- Abstract: Background: The current risk stratification system defined by clinicopathological features does not identify the risk of recurrence in early-stage (stage I-II) colorectal cancer (CRC) with sufficient accuracy. We aimed to investigate whether DNA methylation could serve as a novel biomarker for predicting prognosis in early-stage CRC patients. Methods: We analyzed the genome-wide methylation status of CpG loci using Infinium MethylationEPIC array run on primary tumor tissues and normal mucosa of early-stage CRC patients to identify potential methylation markers for prognosis. The machine-learning approach was applied to construct a DNA methylation–based prognostic classifier for early-stage CRC (MePEC) using the 4 gene methylation markers FAT3, KAZN, TLE4, and DUSP3 . The prognostic value of the classifier was evaluated in 2 independent cohorts (n = 438 and 359, respectively). Results: The comprehensive analysis identified an epigenetic subtype with high risk of recurrence based on a group of CpG loci in the CpG-depleted region. In multivariable analysis, the MePEC classifier was independently and statistically significantly associated with time to recurrence in validation cohort 1 (hazard ratio = 2.35, 95% confidence interval = 1.47 to 3.76, P < .001) and cohort 2 (hazard ratio = 3.20, 95% confidence interval = 1.92 to 5.33, P < .001). All results were further confirmed after each cohort was stratified by clinicopathological variables and molecular subtypes.Abstract: Background: The current risk stratification system defined by clinicopathological features does not identify the risk of recurrence in early-stage (stage I-II) colorectal cancer (CRC) with sufficient accuracy. We aimed to investigate whether DNA methylation could serve as a novel biomarker for predicting prognosis in early-stage CRC patients. Methods: We analyzed the genome-wide methylation status of CpG loci using Infinium MethylationEPIC array run on primary tumor tissues and normal mucosa of early-stage CRC patients to identify potential methylation markers for prognosis. The machine-learning approach was applied to construct a DNA methylation–based prognostic classifier for early-stage CRC (MePEC) using the 4 gene methylation markers FAT3, KAZN, TLE4, and DUSP3 . The prognostic value of the classifier was evaluated in 2 independent cohorts (n = 438 and 359, respectively). Results: The comprehensive analysis identified an epigenetic subtype with high risk of recurrence based on a group of CpG loci in the CpG-depleted region. In multivariable analysis, the MePEC classifier was independently and statistically significantly associated with time to recurrence in validation cohort 1 (hazard ratio = 2.35, 95% confidence interval = 1.47 to 3.76, P < .001) and cohort 2 (hazard ratio = 3.20, 95% confidence interval = 1.92 to 5.33, P < .001). All results were further confirmed after each cohort was stratified by clinicopathological variables and molecular subtypes. Conclusions: We demonstrated the prognostic statistical significance of a DNA methylation profile in the CpG-depleted region, which may serve as a valuable source for tumor biomarkers. MePEC could identify an epigenetic subtype with high risk of recurrence and improve the prognostic accuracy of current clinical variables in early-stage CRC. … (more)
- Is Part Of:
- Journal of the National Cancer Institute. Volume 115:Number 1(2023)
- Journal:
- Journal of the National Cancer Institute
- Issue:
- Volume 115:Number 1(2023)
- Issue Display:
- Volume 115, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 115
- Issue:
- 1
- Issue Sort Value:
- 2023-0115-0001-0000
- Page Start:
- 52
- Page End:
- 61
- Publication Date:
- 2022-09-28
- Subjects:
- Cancer -- Periodicals
Cancer -- Research -- Periodicals
616.994 - Journal URLs:
- https://jnci.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/jnci/djac183 ↗
- Languages:
- English
- ISSNs:
- 0027-8874
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4830.000000
British Library DSC - BLDSS-3PM
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- 25201.xml