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 novel biomarkers 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, including FAT3, KAZN, TLE4, and DUSP3. The prognostic value of the classifier was evaluated in two 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 CpG-depleted region. In multivariate analysis, the MePEC classifier was independently and significantly associated with time to recurrence in the validation cohort one (HR 2.35, 95% CI 1.47-3.76, p < 0.001) and cohort two (HR 3.20, 95% CI 1.92-5.33, p < 0.001). All results were further confirmed after each cohort was stratified by clinicopathological variables and molecular subtypes.
CONCLUSIONS
We demonstrated the prognostic significance of DNA methylation profile in 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.