DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer.
Journal
Journal of the National Cancer Institute
ISSN: 1460-2105
Titre abrégé: J Natl Cancer Inst
Pays: United States
ID NLM: 7503089
Informations de publication
Date de publication:
10 01 2023
10 01 2023
Historique:
received:
16
06
2022
revised:
27
07
2022
accepted:
23
08
2022
pubmed:
30
9
2022
medline:
12
1
2023
entrez:
29
9
2022
Statut:
ppublish
Résumé
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.
Sections du résumé
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.
Identifiants
pubmed: 36171645
pii: 6726193
doi: 10.1093/jnci/djac183
pmc: PMC10089593
doi:
Substances chimiques
2-methylphenyl 4-ethoxycinnamate
0
Biomarkers, Tumor
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
52-61Subventions
Organisme : NIH HHS
ID : U01 CA167551
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA220004
Pays : United States
Organisme : NIH HHS
ID : RO1CA194663
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA206110
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA167551
Pays : United States
Organisme : NCI NIH HHS
ID : U2C CA271902
Pays : United States
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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