BMC cancer · 2026
Multi-gene DNA methylation profiles of tumor suppressor genes for prognostic prediction in gastric cancer.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Nam Soo Kyung, Park Juhyeong, Kwak Yoonjin, Batochir Chinbayar, Kim Eun-Bi, Kong Seong-Ho, Park Do Joong, Lee Hyuk-Joon, Yang Han-Kwang, Lee Hye Seung
Аннотация
BACKGROUND: This study aimed to identify prognostic biomarkers for gastric cancer (GC) by analyzing the methylation status of multiple tumor suppressor genes. METHODS: 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. RESULT: 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. CONCLUSION: 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.