Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer - Liu, Chang; Qin, Henan; Liu, Huiying; Wei, Tianfu; Wu, Zeming; Shang, Mengxue; Liu, Haihua; Wang, Aman; Liu, Jiwei; Shang, Dong; Yin, Peiyuan (Frontiers in Oncology, 2022)
Pancreatic cancer (PC) is burdened with a low five-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using an ultra-high performance liquid chromatography with high-resolution mass spectrometer (UHPLC-HRMS) to identify and validate metabolite biomarkers from paired tissue samples of PC patients. Results showed that the metabolic reprogramming of PC was mainly featured with enhanced amino acid metabolism and inhibited sphingolipid metabolism, which satisfied the energy and biomass requirements for tumorigenesis and progression. And the altered metabolism results were confirmed by the significantly changed gene expressions in PC tissues from online database. A metabolites biomarker panel (six metabolites) was identified for the differential diagnosis between PC tumors and normal pancreatic tissues. The panel biomarker distinguished tumors from normal pancreatic tissues in the discovery group with an area under the curve (AUC) of 1.0 (95%CI: 1.000−1.000). The biomarker panel cut-off was 0.776. In the validation group, an AUC of 0.9000 (95%CI = 0.782-1.000) using the same cut-off, successfully validated the biomarker signature. Moreover, this metabolites panel biomarker had a great capability to predict the overall survival (OS) of PC. Taken together, this metabolomics method identifies and validate metabolite biomarkers that can diagnose the onsite progression and prognosis of PC precisely and sensitively in a clinical setting. It may also help clinicians to choose proper therapeutic interventions for different PC patients, and improve the survival of PC patients.