Related Experiment Video
Updated: Oct 26, 2025
Isolation of Proximal Fluids to Investigate the Tumor Microenvironment of Pancreatic Adenocarcinoma
Published on: November 5, 2020
Urinary metabolite prognostic biomarker panel for pancreatic ductal adenocarcinomas
Luke Hipperson1, William J Hadden2, Christopher B Nahm3
1Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Australia; Kolling Institute of Medical Research, University of Sydney, St Leonards, Sydney, Australia.
Background:
Patients with pancreatic ductal adenocarcinoma (PDAC) have a very low survival rate and surgical resection is the only curative intent treatment available. However, the majority of patients relapse after surgery and identification of biomarkers for accurate prognostication of PDAC patients is required. We have recently identified a six biomarker (i.e., trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone) urinary metabolite panel with very high potential to diagnose PDAC (Int J Cancer 2021;148:1508-18). This study aimed to assess the prognostic ability of these previously identified diagnostic metabolites in the urine of PDAC patients.
Methods:
Metabolite data from 88 PDAC patients was statistically assessed for their prognostic ability.
Results:
A panel of three metabolites (i.e., trigonelline, hippurate and myoinositol) was able to stratify patients with good- or poor-prognosis based on overall survival. The PDAC patients with abnormal levels of 2 or more metabolites in their urine demonstrated significantly lower survival compared to patients with abnormal levels of one or less metabolites.
Conclusion:
These results demonstrate that the selected three metabolite panel could be used to stratify patients based on their prognostic outcomes and if independently validated may lead to the development of a urinary prognostic biomarker test for PDAC.
General Significance:
This study highlights the potential of using 1H-nuclear magnetic resonance spectroscopy for the identification of novel metabolites which can prognosticate cancer patients.
