Department of Pathology, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1, Shuaifuyuan Wangfujing, Dongcheng District, Beijing, 100730, China.
Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Navy Medical, University (the Second Military Medical University), No.168, Changhai Road, Shanghai, 200433, China.
BMC Med. 2022 Nov 25;20(1):458. doi: 10.1186/s12916-022-02647-z.
Pancreatic ductal adenocarcinoma (PDAC) has the lowest overall survival rate primarily due to the late onset of symptoms and rapid progression. Reliable and accurate tests for early detection are lacking. We aimed to develop a noninvasive test for early PDAC detection by capturing the circulating tumour DNA (ctDNA) methylation signature in blood.
Genome-wide methylation profiles were generated from PDAC and nonmalignant tissues and plasma. Methylation haplotype blocks (MHBs) were examined to discover de novo PDAC markers. They were combined with multiple cancer markers and screened for PDAC classification accuracy. The most accurate markers were used to develop PDACatch, a targeted methylation sequencing assay. PDACatch was applied to additional PDAC and healthy plasma cohorts to train, validate and independently test a PDAC-discriminating classifier. Finally, the classifier was compared and integrated with carbohydrate antigen 19-9 (CA19-9) to evaluate and maximize its accuracy and utility.
In total, 90 tissues and 546 plasma samples were collected from 232 PDAC patients, 25 chronic pancreatitis (CP) patients and 323 healthy controls. Among 223 PDAC cases with known stage information, 43/119/38/23 cases were of Stage I/II/III/IV. A total of 171 de novo PDAC-specific markers and 595 multicancer markers were screened for PDAC classification accuracy. The top 185 markers were included in PDACatch, from which a 56-marker classifier for PDAC plasma was trained, validated and independently tested. It achieved an area under the curve (AUC) of 0.91 in both the validation (31 PDAC, 26 healthy; sensitivity = 84%, specificity = 89%) and independent tests (74 PDAC, 65 healthy; sensitivity = 82%, specificity = 88%). Importantly, the PDACatch classifier detected CA19-9-negative PDAC plasma at sensitivities of 75 and 100% during the validation and independent tests, respectively. It was more sensitive than CA19-9 in detecting Stage I (sensitivity = 80 and 68%, respectively) and early-stage (Stage I-IIa) PDAC (sensitivity = 76 and 70%, respectively). A combinatorial classifier integrating PDACatch and CA19-9 outperformed (AUC=0.94) either PDACatch (0.91) or CA19-9 (0.89) alone (p < 0.001).
The PDACatch assay demonstrated high sensitivity for early PDAC plasma, providing potential utility for noninvasive detection of early PDAC and indicating the effectiveness of methylation haplotype analyses in discovering robust cancer markers.
胰腺导管腺癌(PDAC)的总体存活率最低,主要是因为症状出现较晚且进展迅速。目前缺乏可靠和准确的早期检测方法。我们旨在通过捕获血液中循环肿瘤 DNA(ctDNA)甲基化特征来开发用于早期 PDAC 检测的非侵入性测试。
从 PDAC 和非恶性组织和血浆中生成全基因组甲基化谱。检查甲基化单倍型块(MHB)以发现新的 PDAC 标志物。它们与多种癌症标志物结合,并筛选用于 PDAC 分类准确性的标志物。使用最准确的标志物来开发 PDACatch,这是一种靶向甲基化测序检测。将 PDACatch 应用于其他 PDAC 和健康血浆队列中,以训练、验证和独立测试用于区分 PDAC 的分类器。最后,对分类器进行比较并与碳水化合物抗原 19-9(CA19-9)结合,以评估和最大化其准确性和实用性。
总共从 232 名 PDAC 患者、25 名慢性胰腺炎(CP)患者和 323 名健康对照中收集了 90 个组织和 546 个血浆样本。在有已知分期信息的 223 例 PDAC 病例中,43/119/38/23 例为 I/II/III/IV 期。筛选了 171 个新的 PDAC 特异性标志物和 595 个多癌标志物,以评估其对 PDAC 分类准确性的影响。前 185 个标志物被包含在 PDACatch 中,从这些标志物中训练、验证和独立测试了用于 PDAC 血浆的 56 个标志物分类器。它在验证(31 个 PDAC,26 个健康;灵敏度=84%,特异性=89%)和独立测试(74 个 PDAC,65 个健康;灵敏度=82%,特异性=88%)中均获得了 0.91 的曲线下面积(AUC)。重要的是,在验证和独立测试中,PDACatch 分类器分别以 75%和 100%的灵敏度检测到 CA19-9 阴性的 PDAC 血浆。它在检测 I 期(灵敏度分别为 80%和 68%)和早期(I-IIa 期)PDAC(灵敏度分别为 76%和 70%)方面比 CA19-9 更敏感。整合了 PDACatch 和 CA19-9 的组合分类器(AUC=0.94)优于单独使用 PDACatch(0.91)或 CA19-9(0.89)(p<0.001)。
PDACatch 检测法在检测早期 PDAC 血浆方面具有较高的灵敏度,为非侵入性检测早期 PDAC 提供了潜在的应用,并表明甲基化单倍型分析在发现稳健的癌症标志物方面的有效性。