Multi-gene DNA methylation profiles of tumor suppressor genes for prognostic prediction in gastric cancer

This study aimed to identify prognostic biomarkers for gastric cancer (GC) by analyzing the methylation status of multiple tumor suppressor genes. Using the Epi-TOP™ methylation detection system, we analyzed 51 genes in 169 matched tumor and adjacent normal tissue samples. Methylation levels were quantified as Percent Methylated Reference (PMR) in tumor (PMR-T) and normal (PMR-N) tissues; the differential methylation (PMR-D) was also calculated. Tumor tissues exhibited significantly higher DNA methylation levels than matched normal tissues across 51 tumor suppressor genes (all p < 0.001). Clustering analysis based on PMR-T identified four epigenetic subtypes associated with known molecular classifications (epithelial–mesenchymal transition (EMT) and microsatellite instability–high (MSI-H)) and overall survival (p = 0.030). In contrast, clustering based on PMR-N showed no significant association with molecular subtypes or survival outcomes, suggesting limited prognostic relevance. Two prognostic gene panels were constructed: one PMR-T–based panel (ALX, BMP3, CDKN2A, MINT25, PTGDR) and another PMR-D-based panel (ADCYAP1, SOCS1, SEPTIN9, CDKN2B). Both panels independently predicted overall survival in multivariate Cox regression. The PMR-D panel demonstrated stronger prognostic performance (hazard ratio (HR) = 0.329, p = 0.002), while the PMR-T panel also demonstrated significant prognostic value (HR = 0.512, p = 0.012), highlighting that tumor methylation profiles alone may provide meaningful survival predictions for patients with GC. This study demonstrates that tumor-specific DNA methylation changes, particularly when evaluated using multi-gene panels can enhance prognostic stratification in GC. These findings support the potential use of methylation-based biomarkers for personalized management of GC.

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Journal
BMC Cancer
Published
2026-02-03
DOI
https://doi.org/10.1186/s12885-026-15620-3
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-gene DNA methylation profiles of tumor suppressor genes for prognostic prediction in gastric cancer

Seong-Ho Kong, Hye Seung Lee, Do Joong Park, Soo Kyung Nam et al.
BMC Cancer
Epigenetics and DNA Methylation
article

Multi-gene DNA methylation profiles of tumor suppressor genes for prognostic prediction in gastric cancer

Seong-Ho Kong, Hye Seung Lee, Do Joong Park, Soo Kyung Nam, Han-Kwang Yang, Yoonjin Kwak, Hyuk-Joon Lee, Eun-Bi Kim, Juhyeong Park, Chinbayar Batochir
article en

Abstract

This study aimed to identify prognostic biomarkers for gastric cancer (GC) by analyzing the methylation status of multiple tumor suppressor genes. Using the Epi-TOP™ methylation detection system, we analyzed 51 genes in 169 matched tumor and adjacent normal tissue samples. Methylation levels were quantified as Percent Methylated Reference (PMR) in tumor (PMR-T) and normal (PMR-N) tissues; the differential methylation (PMR-D) was also calculated. Tumor tissues exhibited significantly higher DNA methylation levels than matched normal tissues across 51 tumor suppressor genes (all p < 0.001). Clustering analysis based on PMR-T identified four epigenetic subtypes associated with known molecular classifications (epithelial–mesenchymal transition (EMT) and microsatellite instability–high (MSI-H)) and overall survival (p = 0.030). In contrast, clustering based on PMR-N showed no significant association with molecular subtypes or survival outcomes, suggesting limited prognostic relevance. Two prognostic gene panels were constructed: one PMR-T–based panel (ALX, BMP3, CDKN2A, MINT25, PTGDR) and another PMR-D-based panel (ADCYAP1, SOCS1, SEPTIN9, CDKN2B). Both panels independently predicted overall survival in multivariate Cox regression. The PMR-D panel demonstrated stronger prognostic performance (hazard ratio (HR) = 0.329, p = 0.002), while the PMR-T panel also demonstrated significant prognostic value (HR = 0.512, p = 0.012), highlighting that tumor methylation profiles alone may provide meaningful survival predictions for patients with GC. This study demonstrates that tumor-specific DNA methylation changes, particularly when evaluated using multi-gene panels can enhance prognostic stratification in GC. These findings support the potential use of methylation-based biomarkers for personalized management of GC.

BMC CancerVol. 26(1)
Daejeon University (KR), Seoul National University (KR), Cancer Research Institute (US), Seoul National University Hospital (KR), National University College (PR)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Good health and well-being
Openalex Percentile: Top 70%
Epigenetics and DNA Methylation
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