bioRxivBiochemistry
Multiple-biological matrices metabolomics identified new metabolite biomarkers for the precise diagnosis of pancreatic cancer and associated tissue metastasis
Abstract
PurposeTo improve clinical diagnosis and enhance therapeutic outcome, we figure out to identify and validate metabolite biomarkers from the plasma samples of patients with pancreatic cancer that can easily, sensitively and efficiently diagnose the onsite progression, and metastasis of the disease. Experimental DesignWe employed the newly developed precision-targeted metabolomics method to validate that many differential metabolites have the capacity to markedly distinguish patients with pancreatic cancer from healthy controls. 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. ResultsWe 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, we characterized succinic acid and gluconic acid as having a great capability to monitor the progression and metastasis of pancreatic cancer at different stages. ConclusionsTaken 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 efficiently therapeutic interventions, which could largely improve the five-year survival rate of PC patients.
- organism: human
- assay: metabolomics
- research focus: differential expression
- approach: experimental assay
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