| Literature DB >> 29717485 |
Xiang Shu1, Wei Zheng1, Danxia Yu1, Hong-Lan Li2, Qing Lan3, Gong Yang1, Hui Cai1, Xiao Ma2, Nathaniel Rothman3, Yu-Tang Gao2, Wei Jia4,5, Yong-Bing Xiang2, Xiao-Ou Shu1.
Abstract
Using a metabolomics approach, we systematically searched for circulating metabolite biomarkers for pancreatic cancer risk in a case-control study nested within two prospective Shanghai cohorts. Included in our study were 226 incident pancreatic cancer cases and their individually-matched controls. Untargeted mass spectrometry platforms were used to measure metabolites in blood samples collected prior to cancer diagnosis. Conditional logistic regression was performed to assess the associations of metabolites with pancreatic cancer risk. We identified 10 metabolites associated with pancreatic cancer, after accounting for multiple comparisons (the Benjamini-Hochberg false discovery rate <0.05). The majority of the identified metabolites were glycerophospholipids (ORs per SD increase: 0.44-2.32; p values: 7.2 × 10-4 to 1.0 × 10-6 ), six of which were associated with decreased risk and one with increased risk. Additionally, levels of coumarin (OR = 1.96, p = 3.7 × 10-6 ) and picolinic acid (OR = 2.53, p = 5.0 × 10-5 ) were positively associated with pancreatic cancer risk, while tetracosanoic acid was inversely associated with risk (OR = 0.48, p = 7.16 × 10-7 ). Four metabolites remained statistically significant after mutual adjustment. Our study provides novel evidence that the dysregulation of glycerophospholipids may play an important role in pancreatic cancer development.Entities:
Keywords: biomarkers; metabolomics; nested case-control study; pancreatic cancer
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Year: 2018 PMID: 29717485 PMCID: PMC6195470 DOI: 10.1002/ijc.31574
Source DB: PubMed Journal: Int J Cancer ISSN: 0020-7136 Impact factor: 7.396