Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, Minnesota, USA.
Am J Gastroenterol. 2019 Sep;114(9):1539-1549. doi: 10.14309/ajg.0000000000000284.
Pancreatic cystic lesions (PCLs) may be precancerous. Those likely to harbor high-grade dysplasia (HGD) or pancreatic cancer (PC) are targets for surgical resection. Current algorithms to predict advanced neoplasia (HGD/PC) in PCLs lack diagnostic accuracy. In pancreatic tissue and cyst fluid (CF) from PCLs, we sought to identify and validate novel methylated DNA markers (MDMs) that discriminate HGD/PC from low-grade dysplasia (LGD) or no dysplasia (ND).
From an unbiased whole-methylome discovery approach using predefined selection criteria followed by multistep validation on case (HGD or PC) and control (ND or LGD) tissues, we identified discriminant MDMs. Top candidate MDMs were then assayed by quantitative methylation-specific polymerase chain reaction on archival CF from surgically resected PCLs.
Of 25 discriminant MDMs identified in tissue, 13 were selected for validation in 134 CF samples (21 cases [8 HGD, 13 PC], 113 controls [45 ND, 68 LGD]). A tree-based algorithm using 2 CF-MDMs (TBX15, BMP3) achieved sensitivity and specificity above 90%. Discrimination was significantly better by this CF-MDM panel than by mutant KRAS or carcinoembryonic antigen, with areas under the receiver operating characteristic curve of 0.93 (95% confidence interval: 0.86-0.99), 0.71 (0.57-0.85), and 0.72 (0.60-0.84), respectively. Cutoffs for the MDM panel applied to an independent CF validation set (31 cases, 56 controls) yielded similarly high discrimination, areas under the receiver operating characteristic curve = 0.86 (95% confidence interval: 0.77-0.94, P = 0.2).
Novel MDMs discovered and validated in tissue accurately identify PCLs harboring HGD/PC. A panel of 2 MDMs assayed in CF yielded results with potential to enhance current risk prediction algorithms. Prospective studies are indicated to optimize and further evaluate CF-MDMs for clinical use.
胰腺囊性病变（PCL）可能具有癌前病变。那些可能存在高级别异型增生（HGD）或胰腺癌（PC）的病变是手术切除的目标。目前预测 PCL 中高级别肿瘤（HGD/PC）的算法缺乏诊断准确性。在胰腺组织和 PCL 的囊液（CF）中，我们试图鉴定和验证新的甲基化 DNA 标志物（MDM），以区分 HGD/PC 与低级别异型增生（LGD）或无异型增生（ND）。
采用基于预设选择标准的无偏全甲基化组学发现方法，对病例（HGD 或 PC）和对照（ND 或 LGD）组织进行多步验证，我们鉴定了具有判别能力的 MDM。然后，通过定量甲基化特异性聚合酶链反应，在手术切除的 PCL 存档 CF 中检测顶级候选 MDM。
在组织中鉴定出的 25 个有判别能力的 MDM 中，有 13 个在 134 个 CF 样本（21 例[8 例 HGD，13 例 PC]，113 例对照[45 例 ND，68 例 LGD]）中进行了验证。使用 2 个 CF-MDM（TBX15、BMP3）的基于树的算法实现了超过 90%的灵敏度和特异性。该 CF-MDM 面板的判别能力明显优于突变型 KRAS 或癌胚抗原，其受试者工作特征曲线下面积分别为 0.93（95%置信区间：0.86-0.99）、0.71（0.57-0.85）和 0.72（0.60-0.84）。在一个独立的 CF 验证集（31 例，56 例对照）中应用 MDM 面板的截止值也得到了类似的高判别能力，受试者工作特征曲线下面积=0.86（95%置信区间：0.77-0.94，P=0.2）。
在组织中发现和验证的新 MDM 能够准确识别存在 HGD/PC 的 PCL。在 CF 中检测 2 个 MDM 的组合可获得具有增强当前风险预测算法潜力的结果。需要前瞻性研究来优化和进一步评估 CF-MDM 的临床应用。
