胰导管腺癌（PDAC）是一种致命的恶性肿瘤。区分慢性胰腺炎（CP）目前在约三分之一的病例中不准确。然而，两者误诊都对患者造成严重后果。我们旨在找到区分PDAC和CP的分子标记。我们分析了345个组织样本的DNA甲基化、信使RNA和微RNA水平的全基因组变异以及它们的组合来确定标记。为了提高诊断性能，我们建立了一种随机森林机器学习方法。结果在另外的48个样本上得到了验证，并在16个液体活组织样本中得到了进一步的证实。机器学习成功地确定了用于区分PDAC和CP患者的标记，而低维嵌入和聚类分析未能做到。DNA甲基化明显优于转录水平，在诊断准确性方面表现最佳。所确定的变化已在公共数据库中的数据中得到了确认，并在独立样本集中得到了验证。蛋白激酶C beta型基因的CpG岛中的六个DNA甲基化位点的签名在组织和患者血浆中分离的循环自由DNA中实现了经验证的100%的诊断准确性。机器学习成功地确定了有效的标记签名，这证明了这种方法的威力。将PDAC与CP区分开的高诊断准确性可能对治疗成功产生巨大影响，一旦仍然有限的液体活组织样本的结果得到了在怀疑患有胰腺癌的更大一组患者中得到了验证后。© 作者（或其雇主）2023。CC BY-NC许可下允许重新使用。商业再利用受限。详见权利和权限。由BMJ出版。

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy. Differentiation from chronic pancreatitis (CP) is currently inaccurate in about one-third of cases. Misdiagnoses in both directions, however, have severe consequences for patients. We set out to identify molecular markers for a clear distinction between PDAC and CP.Genome-wide variations of DNA-methylation, messenger RNA and microRNA level as well as combinations thereof were analysed in 345 tissue samples for marker identification. To improve diagnostic performance, we established a random-forest machine-learning approach. Results were validated on another 48 samples and further corroborated in 16 liquid biopsy samples.Machine-learning succeeded in defining markers to differentiate between patients with PDAC and CP, while low-dimensional embedding and cluster analysis failed to do so. DNA-methylation yielded the best diagnostic accuracy by far, dwarfing the importance of transcript levels. Identified changes were confirmed with data taken from public repositories and validated in independent sample sets. A signature of six DNA-methylation sites in a CpG-island of the protein kinase C beta type gene achieved a validated diagnostic accuracy of 100% in tissue and in circulating free DNA isolated from patient plasma.The success of machine-learning to identify an effective marker signature documents the power of this approach. The high diagnostic accuracy of discriminating PDAC from CP could have tremendous consequences for treatment success, once the result from still a limited number of liquid biopsy samples would be confirmed in a larger cohort of patients with suspected pancreatic cancer.© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.