Division of Molecular Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Molecular Biology of Breast Cancer, Department of Gynecology and Obstetrics, University of Heidelberg, Heidelberg, Germany.
Gut. 2019 Jan;68(1):101-110. doi: 10.1136/gutjnl-2017-314711. Epub 2017 Nov 3.
Pathological staging used for the prediction of patient survival in colorectal cancer (CRC) provides only limited information.
Here, a genome-wide study of DNA methylation was conducted for two cohorts of patients with non-metastatic CRC (screening cohort (n=572) and validation cohort (n=274)). A variable screening for prognostic CpG sites was performed in the screening cohort using marginal testing based on a Cox model and subsequent adjustment of the p-values via independent hypothesis weighting using the methylation difference between 34 pairs of tumour and normal mucosa tissue as auxiliary covariate. From the 1000 CpG sites with the smallest adjusted p-value, 20 CpG sites with the smallest Brier score for overall survival (OS) were selected. Applying principal component analysis, we derived a prognostic methylation-based classifier for patients with non-metastatic CRC (ProMCol classifier).
This classifier was associated with OS in the screening (HR 0.51, 95% CI 0.41 to 0.63, p=6.2E-10) and the validation cohort (HR 0.61, 95% CI 0.45 to 0.82, p=0.001). The independent validation of the ProMCol classifier revealed a reduction of the prediction error for 3-year OS from 0.127, calculated only with standard clinical variables, to 0.120 combining the clinical variables with the classifier and for 4-year OS from 0.153 to 0.140. All results were confirmed for disease-specific survival.
The ProMCol classifier could improve the prognostic accuracy for patients with non-metastatic CRC.
用于预测结直肠癌(CRC)患者生存情况的病理分期仅提供了有限的信息。
本研究对两组无转移 CRC 患者(筛查队列(n=572)和验证队列(n=274))进行了全基因组 DNA 甲基化研究。在筛查队列中,使用基于 Cox 模型的边缘检验和通过使用肿瘤和正常黏膜组织之间的甲基化差异作为辅助协变量对 p 值进行独立假设加权调整,对预后 CpG 位点进行了可变筛选。从具有最小调整后 p 值的 1000 个 CpG 位点中,选择了 20 个用于总体生存(OS)的最小 Brier 评分的 CpG 位点。通过主成分分析,我们为非转移性 CRC 患者推导了一个基于甲基化的预后分类器(ProMCol 分类器)。
该分类器与筛查队列(HR 0.51,95%CI 0.41 至 0.63,p=6.2E-10)和验证队列(HR 0.61,95%CI 0.45 至 0.82,p=0.001)的 OS 相关。ProMCol 分类器的独立验证表明,仅使用标准临床变量计算的 3 年 OS 预测误差从 0.127 降低到将临床变量与分类器结合后的 0.120,4 年 OS 从 0.153 降低到 0.140。所有结果均确认了疾病特异性生存。
ProMCol 分类器可以提高非转移性 CRC 患者的预后准确性。