Gastrointestinal Surgical Center, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Center of Gastric Cancer, Sun Yat-Sen University, Guangzhou, China.
Clin Cancer Res. 2019 Apr 1;25(7):2127-2135. doi: 10.1158/1078-0432.CCR-18-3696. Epub 2019 Jan 22.
Barrett's esophagus is the only known precursor of esophageal adenocarcinoma (EAC). Although endoscopy and biopsy are standard methods for Barrett's esophagus diagnosis, their high cost and risk limit their use as a screening modality. Here, we sought to develop a Barrett's esophagus detection method based on methylation status in cytology samples captured by EsophaCap using a streamlined sensitive technique, methylation on beads (MOB).
We conducted a prospective cohort study on 80 patients (52 in the training set; 28 in the test set). We used MOB to extract and bisulfite-convert DNA, followed by quantitative methylation-specific PCR to assess methylation levels of 8 previously selected candidate markers. Lasso regression was applied to establish a prediction model in the training set, which was then tested on the independent test set.
In the training set, five of eight candidate methylation biomarkers (6, , and ) were significantly higher in Barrett's esophagus patients than in controls. We built a four-biomarker-plus-age lasso regression model for Barrett's esophagus diagnosis. The AUC was 0.894, with sensitivity 94.4% [95% confidence interval (CI), 71%-99%] and specificity 62.2% (95% CI, 44.6%-77.3%) in the training set. This model also performed with high accuracy for Barrett's esophagus diagnosis in an independent test set: AUC = 0.929 ( < 0.001; 95% CI, 0.810%-1%), with sensitivity=78.6% (95% CI, 48.8%-94.3%) and specificity = 92.8% (95% CI, 64.1%-99.6%).
EsophaCap, in combination with an epigenetic biomarker panel and the MOB method, is a promising, well-tolerated, low-cost esophageal sampling strategy for Barrett's esophagus diagnosis. This approach merits further prospective studies in larger populations.
巴雷特食管是食管腺癌（EAC）唯一已知的前体。尽管内镜检查和活检是巴雷特食管诊断的标准方法，但由于其成本高且风险大，限制了其作为筛查手段的应用。在这里，我们试图开发一种基于 EsophaCap 捕获的细胞学样本中甲基化状态的巴雷特食管检测方法，该方法使用简化的敏感技术——珠子上的甲基化（MOB）。
我们对 80 名患者（训练集 52 例；测试集 28 例）进行了前瞻性队列研究。我们使用 MOB 提取和亚硫酸氢盐转化 DNA，然后使用定量甲基化特异性 PCR 评估 8 个先前选择的候选标志物的甲基化水平。应用套索回归在训练集中建立预测模型，然后在独立测试集中进行测试。
在训练集中，巴雷特食管患者的 8 个候选甲基化生物标志物中的 5 个（、和）明显高于对照组。我们建立了一个四标志物加年龄的套索回归模型用于巴雷特食管诊断。该模型在训练集中的 AUC 为 0.894，灵敏度为 94.4%（95%CI，71%-99%），特异性为 62.2%（95%CI，44.6%-77.3%）。该模型在独立测试集中也具有很高的巴雷特食管诊断准确性：AUC = 0.929（<0.001；95%CI，0.810%-1%），灵敏度=78.6%（95%CI，48.8%-94.3%），特异性=92.8%（95%CI，64.1%-99.6%）。
EsophaCap 联合表观遗传生物标志物组和 MOB 方法是一种很有前途、耐受性好、成本低的食管采样策略，用于巴雷特食管的诊断。这种方法值得在更大的人群中进行进一步的前瞻性研究。
