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SLAS Discov ; 22(4): 348-359, 2017 04.
Article in English | MEDLINE | ID: mdl-27655283

ABSTRACT

Pancreatic ductal adenocarcinoma is one of the most lethal tumors since it is usually detected at an advanced stage in which surgery and/or current chemotherapy have limited efficacy. The lack of sensitive and specific markers for diagnosis leads to a dismal prognosis. The purpose of this study is to identify metabolites in serum of pancreatic ductal adenocarcinoma patients that could be used as diagnostic biomarkers of this pathology. We used liquid chromatography-high-resolution mass spectrometry for a nontargeted metabolomics approach with serum samples from 28 individuals, including 16 patients with pancreatic ductal adenocarcinoma and 12 healthy controls. Multivariate statistical analysis, which included principal component analysis and partial least squares, revealed clear separation between the patient and control groups analyzed by liquid chromatography-high-resolution mass spectrometry using a nontargeted metabolomics approach. The metabolic analysis showed significantly lower levels of phospholipids in the serum from patients with pancreatic ductal adenocarcinoma compared with serum from controls. Our results suggest that the liquid chromatography-high-resolution mass spectrometry-based metabolomics approach provides a potent and promising tool for the diagnosis of pancreatic ductal adenocarcinoma patients using the specific metabolites identified as novel biomarkers that could be used for an earlier detection and treatment of these patients.


Subject(s)
Biomarkers, Tumor/blood , Carcinoma, Pancreatic Ductal/diagnosis , Metabolome , Pancreatic Neoplasms/diagnosis , Phospholipids/blood , Adult , Aged , Aged, 80 and over , Carcinoma, Pancreatic Ductal/blood , Carcinoma, Pancreatic Ductal/pathology , Case-Control Studies , Chromatography, Liquid/methods , Early Diagnosis , Female , Humans , Male , Mass Spectrometry/methods , Metabolomics/methods , Middle Aged , Multivariate Analysis , Pancreatic Neoplasms/blood , Pancreatic Neoplasms/pathology , Principal Component Analysis
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