Cesaroni Matteo, Powell Jasmine, Sapienza Carmen
Authors' Affiliations: Fels Institute for Cancer Research and Molecular Biology; and.
Authors' Affiliations: Fels Institute for Cancer Research and Molecular Biology; and Department of Pathology and Laboratory Medicine, Temple University School of Medicine, Philadelphia, Pennsylvania
Cancer Prev Res (Phila). 2014 Jul;7(7):717-26. doi: 10.1158/1940-6207.CAPR-13-0407. Epub 2014 May 7.
We have validated differences in DNA methylation levels of candidate genes previously reported to discriminate between normal colon mucosa of patients with colon cancer and normal colon mucosa of individuals without cancer. Here, we report that CpG sites in 16 of the 30 candidate genes selected show significant differences in mean methylation level in normal colon mucosa of 24 patients with cancer and 24 controls. A support vector machine trained on these data and data for an additional 66 CpGs yielded an 18-gene signature, composed of ten of the validated candidate genes plus eight additional candidates. This model exhibited 96% sensitivity and 100% specificity in a 40-sample training set and classified all eight samples in the test set correctly. Moreover, we found a moderate-strong correlation (Pearson coefficients r = 0.253-0.722) between methylation levels in colon mucosa and methylation levels in peripheral blood for seven of the 18 genes in the support vector model. These seven genes, alone, classified 44 of the 48 patients in the validation set correctly and five CpGs selected from only two of the seven genes classified 41 of the 48 patients in the discovery set correctly. These results suggest that methylation biomarkers may be developed that will, at minimum, serve as useful objective and quantitative diagnostic complements to colonoscopy as a cancer-screening tool. These data also suggest that it may be possible to monitor biomarker methylation levels in tissues collected much less invasively than by colonoscopy.
我们已经验证了先前报道的候选基因的DNA甲基化水平差异,这些差异可用于区分结肠癌患者的正常结肠黏膜与无癌个体的正常结肠黏膜。在此,我们报告,在所选的30个候选基因中,有16个基因的CpG位点在24例癌症患者和24例对照的正常结肠黏膜中的平均甲基化水平存在显著差异。基于这些数据以及另外66个CpG的数据训练的支持向量机产生了一个由18个基因组成的特征图谱,其中包括10个经过验证的候选基因以及另外8个候选基因。该模型在40个样本的训练集中表现出96%的灵敏度和100%的特异性,并且正确分类了测试集中的所有8个样本。此外,我们发现支持向量模型中18个基因中的7个基因的结肠黏膜甲基化水平与外周血甲基化水平之间存在中度至强的相关性(皮尔逊系数r = 0.253 - 0.722)。仅这7个基因就正确分类了验证集中48例患者中的44例,并且仅从这7个基因中的2个基因中选择的5个CpG正确分类了发现集中48例患者中的41例。这些结果表明,至少可以开发出甲基化生物标志物,作为结肠镜检查作为癌症筛查工具的有用的客观和定量诊断补充。这些数据还表明,有可能监测比结肠镜检查侵入性小得多的组织中的生物标志物甲基化水平。