Literature DB >> 27655283

Untargeted LC-HRMS-Based Metabolomics for Searching New Biomarkers of Pancreatic Ductal Adenocarcinoma: A Pilot Study.

Sandra Ríos Peces1, Caridad Díaz Navarro1, Cristina Márquez López2, Octavio Caba3,4, Cristina Jiménez-Luna4,5, Consolación Melguizo4,6, José Carlos Prados4,6, Olga Genilloud1, Francisca Vicente Pérez1, José Pérez Del Palacio1.   

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.

Entities:  

Keywords:  biomarker; diagnosis; hydrophilic interaction liquid chromatography (HILIC); liquid chromatography–high-resolution mass spectrometry (LC-HRMS); pancreatic ductal adenocarcinoma (PDAC); reverse-phase liquid chromatography (RPLC)

Mesh:

Substances:

Year:  2016        PMID: 27655283     DOI: 10.1177/1087057116671490

Source DB:  PubMed          Journal:  SLAS Discov        ISSN: 2472-5552            Impact factor:   3.341


  7 in total

1.  A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer.

Authors:  Nguyen Phuoc Long; Sang Jun Yoon; Nguyen Hoang Anh; Tran Diem Nghi; Dong Kyu Lim; Yu Jin Hong; Soon-Sun Hong; Sung Won Kwon
Journal:  Metabolomics       Date:  2018-08-10       Impact factor: 4.290

2.  Discrimination of pancreatic cancer and pancreatitis by LC-MS metabolomics.

Authors:  Anna Lindahl; Rainer Heuchel; Jenny Forshed; Janne Lehtiö; Matthias Löhr; Anders Nordström
Journal:  Metabolomics       Date:  2017-04-01       Impact factor: 4.290

3.  LC-HRMS Metabolomics for Untargeted Diagnostic Screening in Clinical Laboratories: A Feasibility Study.

Authors:  Bertrand Rochat; Rayane Mohamed; Pierre-Edouard Sottas
Journal:  Metabolites       Date:  2018-06-15

4.  Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics.

Authors:  Guangxi Wang; Hantao Yao; Yan Gong; Zipeng Lu; Ruifang Pang; Yang Li; Yuyao Yuan; Huajie Song; Jia Liu; Yan Jin; Yongsu Ma; Yinmo Yang; Honggang Nie; Guangze Zhang; Zhu Meng; Zhe Zhou; Xuyang Zhao; Mantang Qiu; Zhicheng Zhao; Kuirong Jiang; Qiang Zeng; Limei Guo; Yuxin Yin
Journal:  Sci Adv       Date:  2021-12-22       Impact factor: 14.136

5.  Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma.

Authors:  Yingying Cao; Rui Zhao; Kai Guo; Shuai Ren; Yaping Zhang; Zipeng Lu; Lei Tian; Tao Li; Xiao Chen; Zhongqiu Wang
Journal:  Front Oncol       Date:  2022-01-19       Impact factor: 6.244

6.  Predicting dynamic response to neoadjuvant chemotherapy in breast cancer: a novel metabolomics approach.

Authors:  Caridad Díaz; Carmen González-Olmedo; Leticia Díaz-Beltrán; José Camacho; Patricia Mena García; Ariadna Martín-Blázquez; Mónica Fernández-Navarro; Ana Laura Ortega-Granados; Fernando Gálvez-Montosa; Juan Antonio Marchal; Francisca Vicente; José Pérez Del Palacio; Pedro Sánchez-Rovira
Journal:  Mol Oncol       Date:  2022-04-14       Impact factor: 7.449

7.  Untargeted LC-HRMS-based metabolomics to identify novel biomarkers of metastatic colorectal cancer.

Authors:  Ariadna Martín-Blázquez; Caridad Díaz; Encarnación González-Flores; Daniel Franco-Rivas; Cristina Jiménez-Luna; Consolación Melguizo; José Prados; Olga Genilloud; Francisca Vicente; Octavio Caba; José Pérez Del Palacio
Journal:  Sci Rep       Date:  2019-12-27       Impact factor: 4.379

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.