DNA methylation classifier to diagnose pancreatic ductal adenocarcinoma metastases from different anatomical sites.

IF 4.8 2区 医学 Q1 GENETICS & HEREDITY
Teodor G Calina, Eilís Perez, Elena Grafenhorst, Jamal Benhamida, Simon Schallenberg, Adrian Popescu, Ines Koch, Tobias Janik, BaoQing Chen, Jana Ihlow, Stephanie Roessler, Benjamin Goeppert, Bruno Sinn, Marcus Bahra, George A Calin, Eliane T Taube, Uwe Pelzer, Christopher C M Neumann, David Horst, Erik Knutsen, David Capper, Mihnea P Dragomir
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引用次数: 0

Abstract

Background: We have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.

Methods: For this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.

Results: The updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.

Conclusions: The updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/ ) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.

DNA 甲基化分类器诊断来自不同解剖部位的胰腺导管腺癌转移。
背景:我们最近构建了一种DNA甲基化分类器(PAAD-iCCA-Classifier),该分类器能准确区分胰腺导管腺癌(PAAD)肝转移瘤和肝内胆管癌(iCCA)。PAAD 是原发灶不明癌症的主要病因之一,诊断的基础是排除其他恶性肿瘤。因此,我们的重点是研究 PAAD-iCCA 分类器是否可用于诊断其他部位的 PAAD 转移:方法:在此范围内,初始分类器的异常检测过滤器增加了 8 个模拟癌,使阴性类别中的癌总数达到 10 个。我们在验证集上对更新版分类器进行了验证,验证集包括生物组群(n = 3579)和技术组群(n = 15)。然后,我们在测试集上评估了分类器的性能,测试集包括一个由来自不同部位的 16 个 PAAD 转移灶组成的阳性对照组,以及一个由来自 18 个解剖部位的 96 个乳腺癌转移灶和 28 个脑癌转移灶组成的 124 个阴性对照样本组:更新后的 PAAD-iCCA 分类器对生物验证样本的准确率达到 98.21%,对技术验证样本的准确率达到 100%。该分类器还将阳性对照中的 15/16 例(93.75%)转移瘤正确识别为 PAAD,并对阴性对照中的 122/124 例样本(98.39%)进行了正确分类,测试集的总体准确率为 97.85%。我们利用该DNA甲基化数据集探索了PAAD转移瘤的器官性,并观察到PAAD肝转移瘤有别于PAAD腹膜癌和原发性PAAD,其特点是特定的拷贝数改变和参与上皮-间质转化的增强子的低甲基化:更新后的 PAAD-iCCA 分类器(可在 https://classifier.tgc-research.de/ 上获取)可对来自不同转移部位的 PAAD 样本进行准确分类,并可作为诊断辅助工具。
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来源期刊
自引率
5.30%
发文量
150
期刊介绍: Clinical Epigenetics, the official journal of the Clinical Epigenetics Society, is an open access, peer-reviewed journal that encompasses all aspects of epigenetic principles and mechanisms in relation to human disease, diagnosis and therapy. Clinical trials and research in disease model organisms are particularly welcome.
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