No abstract

Our study aimed to identify a urinary metabolite panel for the detection/diagnosis of pancreatic ductal adenocarcinoma (PDAC). PDAC continues to have poor survival outcomes. One of the major reasons for poor prognosis is the advanced stage of the disease at diagnosis. Hence, identification of a novel and cost‐effective biomarker signature for early detection/diagnosis of PDAC could lead to better survival outcomes. Untargeted metabolomics was employed to identify a novel metabolite‐based biomarker signature for PDAC diagnosis. Urinary metabolites from 92 PDAC patients (56 discovery cohort and 36 validation cohort) were compared with 56 healthy volunteers using 1H nuclear magnetic resonance spectroscopy. Multivariate (partial‐least squares discriminate analysis) and univariate (Mann‐Whitney's U‐test) analyses were performed to identify a metabolite panel which can be used to detect PDAC. The selected metabolites were further validated for their diagnostic potential using the area under the receiver operating characteristic (AUROC) curve. Statistical analysis identified a six‐metabolite panel (trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone), which demonstrated high potential to diagnose PDAC, with AUROC of 0.933 and 0.864 in the discovery and validation cohort, respectively. Notably, the identified panel also demonstrated very high potential to diagnose early‐stage (I and II) PDAC patients with AUROC of 0.897. These results demonstrate that the selected metabolite signature could be used to detect PDAC and will pave the way for the development of a urinary test for detection/diagnosis of PDAC.