Exosomal ROR1 in peritoneal fluid identifies peritoneal disseminated PDAC and is associated with poor survival.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest forms of cancer and peritoneal dissemination is one major cause for this poor prognosis. Exosomes have emerged as promising biomarkers for gastrointestinal cancers and can be found in all kinds of bodily fluids, also in peritoneal fluid (PF). This is a unique sample due to its closeness to gastrointestinal malignancies. The receptor tyrosine kinase-like orphan receptor 1 (ROR1) has been identified as a potential biomarker in human cancers and represents a promising target for an immunotherapy approach, which could be considered for future treatment strategies. Here we prospectively analyzed the exosomal surface protein ROR1 (exo-ROR1) in PF in localized PDAC patients (PER-) on the one hand and peritoneal disseminated tumor stages (PER+) on the other hand followed by the correlation of exo-ROR1 with clinical-pathological parameters. Methods: Exosomes were isolated from PF and plasma samples of non-cancerous (NC) (n = 15), chronic pancreatitis (CP) (n = 4), localized PDAC (PER-) (n = 18) and peritoneal disseminated PDAC (PER+) (n = 9) patients and the surface protein ROR1 was detected via FACS analysis. Additionally, soluble ROR1 in PF was analyzed. ROR1 expression in tissue was investigated using western blots (WB), qPCR, and immunohistochemistry (IHC). Exosome isolation was proven by Nano Tracking Analysis (NTA), WB, Transmission electron microscopy (TEM), and BCA protein assay. The results were correlated with clinical data and survival analysis was performed. Results: PDAC (PER+) patients have the highest exo-ROR1 values in PF and can be discriminated from NC (p <0.0001), PDAC (PER-) (p <0.0001), and CP (p = 0.0112). PDAC (PER-) can be discriminated from NC (p = 0.0003). In plasma, exo-ROR1 is not able to distinguish between the groups. While there is no expression of ROR1 in the exocrine pancreatic tissue, PDAC and peritoneal metastasis show expression of ROR1. High exo-ROR1 expression in PF is associated with lower overall survival (p = 0.0482). Conclusion: With exo-ROR1 in PF we found a promising diagnostic and prognostic biomarker possibly discriminating between NC, PDAC (PER-) and PDAC (PER+) and might shed light on future diagnostic and therapeutic concepts in PDAC.

Discrimination of pancreato-biliary cancer and pancreatitis patients by non-invasive liquid biopsy.

BACKGROUND: Current diagnostics for the detection of pancreato-biliary cancers (PBCs) need to be optimized. We therefore propose that methylated cell-free DNA (cfDNA) derived from non-invasive liquid biopsies serves as a novel biomarker with the ability to discriminate pancreato-biliary cancers from non-cancer pancreatitis patients. METHODS: Differentially methylated regions (DMRs) from plasma cfDNA between PBCs, pancreatitis and clinical control samples conditions were identified by next-generation sequencing after enrichment using methyl-binding domains and database searches to generate a discriminatory panel for a hybridization and capture assay with subsequent targeted high throughput sequencing. RESULTS: The hybridization and capture panel, covering around 74 kb in total, was applied to sequence a cohort of 25 PBCs, 25 pancreatitis patients, 25 clinical controls, and seven cases of Intraductal Papillary Mucinous Neoplasia (IPMN). An unbiased machine learning approach identified the 50 most discriminatory methylation markers for the discrimination of PBC from pancreatitis and controls resulting in an AUROC of 0.85 and 0.88 for a training (n = 45) and a validation (n = 37) data set, respectively. The panel was also able to distinguish high grade from low grade IPMN samples. CONCLUSIONS: We present a proof of concept for a methylation biomarker panel with better performance and improved discriminatory power than the current clinical marker CA19-9 for the discrimination of pancreato-biliary cancers from non-cancerous pancreatitis patients and clinical controls. This workflow might be used in future diagnostics for the detection of precancerous lesions, e.g. the identification of high grade IPMNs vs. low grade IPMNs.