Abstract

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. 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). 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. 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.

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