Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma

Background & ObjectivesPancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the lack of effective screening methods. In this study, we aimed to construct a novel metabolic model for stage-I PDAC detection, using both serum and tissue samples. MethodsWe employed an untargeted technique, UHPLC-Q-TOF-MS, to identify the potential metabolite, and then used a targeted technique, GC-TOF-MS, to quantitatively validate. Multivariate and univariate statistics were performed to analyze the metabolomic profiles between stage-I PDAC and healthy controls, including 90 serum and 53 tissue samples. 28 patients with stage-I PDAC and 62 healthy controls were included in this study. ResultsA total of 10 potential metabolites presented the same expression levels both in serum and in tissue. Among them, a 2-metabolites-model (isoleucine and adrenic acid) for stage-I PDAC was constructed. The area under the curve (AUC) value was 0.93 in the discovery set and 0.90 in the independent validation set. Especially, the serum metabolite model had a better diagnostic performance than CA19-9 (AUC = 0.79). Pathway analysis revealed 11 altered pathways in both serum and tissue of stage-I PDAC. ConclusionsThis study developed a novel serum metabolites model that could early separate stage-I PDAC from healthy controls.

Automated summary

This study developed a novel metabolic model using both serum and tissue samples for early detection of stage-I pancreatic ductal adenocarcinoma (PDAC). The model showed high diagnostic accuracy and outperformed the traditional CA19-9 marker.