Pancreatic cancer (PC) is one of the most aggressive
malignancies with high mortality due to a complex and latent pathogenesis leading to the severe lack of early diagnosis methods. To improve clinical diagnosis and enhance therapeutic outcome, we employed the newly developed precision-targeted metabolomics method to identify and validate metabolite
biomarkers from the plasma samples of patients with
pancreatic cancer that can sensitively and efficiently diagnose the onsite progression of the disease. Many differential metabolites have the capacity to markedly distinguish patients with
pancreatic cancer (n = 60) from healthy controls (n = 60). To further enhance the specificity and selectivity of metabolite
biomarkers, a dozen
tumor tissues from PC patients and paired normal tissues were used to clinically validate the
biomarker performance. We eventually verified five new metabolite
biomarkers in plasma (
creatine,
inosine,
beta-sitosterol,
sphinganine and
glycocholic acid), which can be used to readily diagnose
pancreatic cancer in a clinical setting. Excitingly, we proposed a panel
biomarker by integrating these five individual metabolites into one pattern, demonstrating much higher accuracy and specificity to precisely diagnose
pancreatic cancer than conventional
biomarkers (CA125, CA19-9, CA242 and CEA); moreover, this plasma panel
biomarker used for PC diagnosis is also quite convenient to implement in clinical practice. Using the same metabolomics method, we characterized
succinic acid and
gluconic acid as having a great capability to monitor the progression and
metastasis of
pancreatic cancer at different stages. Taken together, this metabolomics method was used to identify and validate metabolite
biomarkers that can precisely and sensitively diagnose the onsite progression and
metastasis of
pancreatic cancer in a clinical setting. Furthermore, such effort should leave clinicians with the correct time frame to facilitate early and efficient therapeutic interventions, which could largely improve the five-year survival rate of PC patients by significantly lowering clinical mortality.