Abstract 4414: Genome-wide DNA methylation classifier diagnoses pancreatic ductal adenocarcinoma in CUP setting
Authors: Teodor G. Calina, Eilís Perez, Simon Schallenberg, Horst David, Erik Knutsen, David Capper, Mihnea P. Dragomir
Journal: Cancer Research (2024)

Abstract Introduction: The metastasis of a pancreatic ductal adenocarcinoma (PAAD) is a diagnosis of exclusion and one of the most common causes of cancer of unknown primary (CUP). We have recently developed a genome-wide DNA methylation-based neural network classifier that can accurately differentiate between liver metastasis of a PAAD and intrahepatic cholangiocarcinoma (iCCA) (PAAD-iCCA-Classifier). Therefore, the aim of our study was to test whether our PAAD-iCCA-Classifier can be extended to be used to correctly diagnose PAAD metastases from other sites in CUP setting. Methods: For this purpose, we enhanced the anomaly detection layer of the classifier by incorporating ten mimicker carcinomas to be excluded by this layer. We used a validation set 1 (n=3786) including primary PAAD (n=242), PAAD liver metastases (n=20), iCCA (n=151) and 10 other mimicker carcinomas (n=3373) and a validation set 2 (n=26) including primary PAAD from a real-life clinical cohort from an independent institution to validate the classifier. Next, we tested the classifier on 16 PAAD initially considered CUP samples (test set) from different sites: peritoneum, lung, liver, and lymph node. The clinical history and diagnostic imaging of these samples were used to confirm PAAD as the most probable origin. We further performed differentially methylated probes (DMP) and copy number alterations (CNA) analysis of primary PAAD and metastatic PAAD from different locations. Results: The improved version of the PAAD-iCCA-Classifier achieved an accuracy of 98.43% on the validation set 1 and was able to exclude most of the mimicker carcinomas. On validation set 2, the classifier achieved an accuracy of 88.46%. Medical history, imaging and immunohistochemical analysis of the test set samples confirmed the diagnosis of PAAD. The DNA methylation classifier correctly labeled 15/16 PAAD metastatic samples as PAAD (93.75% accuracy). We observed that the classifier performance was negatively affected by a high CD3+ immune infiltrate and positively affected by high tumor purity and high proliferation rate. CNA revealed that PAAD liver metastases have a distinct CNA profile characterized by chromosome 6, 9 (CDKN2A/B) and 18q (SMAD4) deletions. DMP analysis showed that PAAD liver metastases have global hypomethylation of both promoter- and enhancer-associated CpGs compared to primary PAAD and PAAD peritoneal carcinomatosis. Finally, gene ontology analysis revealed that different epithelial-mesenchymal transition pathways are activated in PAAD liver metastases compared to PAAD peritoneal carcinomatosis. Conclusion: Our tool performs well in classifying metastatic PAAD samples and could be of great clinical use when a PAAD origin is suspected in the case of a CUP. DMP and CNA profiles show that PAAD liver metastases may have a distinct DNA methylation and copy number profile compared to primary and peritoneal carcinomatosis PAAD. Citation Format: Teodor G. Calina, Eilís Perez, Simon Schallenberg, Horst David, Erik Knutsen, David Capper, Mihnea P. Dragomir. Genome-wide DNA methylation classifier diagnoses pancreatic ductal adenocarcinoma in CUP setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4414.