Yuan Tanwei, Edelmann Dominic, Moreno Víctor, Georgii Elisabeth, de Andrade E Sousa Lisa Barros, Pelin Helena, Jiang Xiaofeng, Kather Jakob Nikolas, Tagscherer Katrin E, Roth Wilfried, Bewerunge-Hudler Melanie, Brobeil Alexander, Kloor Matthias, Bläker Hendrik, Brenner Hermann, Hoffmeister Michael
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Transl Oncol. 2025 Apr 30;57:102405. doi: 10.1016/j.tranon.2025.102405.
Tailoring surveillance and treatment strategies for stage II colon cancer (CC) after curative surgery remains challenging, and personalized approaches are lacking. We aimed to identify a gene methylation panel capable of stratifying high-risk stage II CC patients for recurrence beyond traditional clinical variables.
Genome-wide tumor tissue DNA methylation data were analyzed from 562 stage II CC patients who underwent surgery in Germany (DACHS study). The cohort was divided into a training set (N = 395) and an internal validation set (N = 131), with external validation performed on 97 stage II CC patients from Spain. DNA methylation markers were primarily selected using the Elastic Net Cox model. The resulting prognostic index (PI), a combination of clinical factors and selected methylation markers, was compared to baseline models using clinical variables or microsatellite instability (MSI), with discrimination and prediction accuracy assessed through time-dependent receiver operating characteristic curves (AUC) and Brier scores.
The final PI incorporated age, sex, tumor stage, location, and 27 DNA methylation markers. The PI consistently outperformed the baseline model including age, sex, and tumor stage in time-dependent AUC across validation cohorts (e.g., 1-year AUC and 95 % confidence interval: internal validation set, PI: 0.66, baseline model: 0.52; external validation set, PI: 0.72, baseline model: 0.64). In internal validation, the PI also showed a consistently improved time-dependent AUC compared with a combination of MSI and tumor stage only. Nevertheless, the PI did not improve the prediction accuracy of CC recurrence compared to the baseline model.
This study identified 27 tumor tissue DNA methylation biomarkers that improved the discriminative power in classifying recurrence risk among stage II colon cancer patients. While this methylation panel alone lacks sufficient prediction accuracy for clinical application, its discriminative improvement suggests potential value as part of a multimodal risk-stratification tool.
为根治性手术后的II期结肠癌（CC）制定监测和治疗策略仍然具有挑战性，且缺乏个性化方法。我们旨在确定一个基因甲基化panel，能够在传统临床变量之外，对II期CC高危复发患者进行分层。
分析了德国562例接受手术的II期CC患者的全基因组肿瘤组织DNA甲基化数据（DACHS研究）。该队列分为训练集（N = 395）和内部验证集（N = 131），并对来自西班牙的97例II期CC患者进行了外部验证。DNA甲基化标记主要使用弹性网Cox模型进行选择。将所得的预后指数（PI），即临床因素和选定的甲基化标记的组合，与使用临床变量或微卫星不稳定性（MSI）的基线模型进行比较，并通过时间依赖的受试者工作特征曲线（AUC）和Brier评分评估鉴别力和预测准确性。
最终的PI纳入了年龄、性别、肿瘤分期、位置和27个DNA甲基化标记。在各验证队列中，PI在时间依赖的AUC方面始终优于包括年龄、性别和肿瘤分期的基线模型（例如，1年AUC和95%置信区间：内部验证集，PI：0.66，基线模型：0.52；外部验证集，PI：0.72，基线模型：0.64）。在内部验证中，与仅MSI和肿瘤分期的组合相比，PI在时间依赖的AUC方面也持续改善。然而，与基线模型相比，PI并未提高CC复发的预测准确性。
本研究确定了27个肿瘤组织DNA甲基化生物标志物，这些标志物提高了II期结肠癌患者复发风险分类的鉴别力。虽然单独使用这个甲基化panel缺乏足够的临床应用预测准确性，但其鉴别力的提高表明作为多模式风险分层工具的一部分具有潜在价值。
