title: Metabolic system alterations in pancreatic cancer patient serum: potential for early detection.
abstract: BACKGROUND
  The prognosis of pancreatic cancer (PC) is one of the poorest among all cancers, due largely to the lack of methods for screening and early detection. New biomarkers for identifying high-risk or early-stage subjects could significantly impact PC mortality. The goal of this study was to find metabolic biomarkers associated with PC by using a comprehensive metabolomics technology to compare serum profiles of PC patients to healthy control subjects.
  
  
  METHODS
  A non-targeted metabolomics approach based on high-resolution, flow-injection Fourier transform ion cyclotron resonance mass spectrometry (FI-FTICR-MS) was used to generate comprehensive metabolomic profiles containing 2478 accurate mass measurements from the serum of Japanese PC patients (n=40) and disease-free subjects (n=50). Targeted flow-injection tandem mass spectrometry (FI-MS/MS) assays for specific metabolic systems were developed and used to validate the FI-FTICR-MS results. A FI-MS/MS assay for the most discriminating metabolite discovered by FI-FTICR-MS (PC-594) was further validated in two USA Caucasian populations; one comprised 14 PCs, six intraductal papillary mucinous neoplasms (IPMN) and 40 controls, and a second comprised 1000 reference subjects aged 30 to 80, which was used to create a distribution of PC-594 levels among the general population.
  
  
  RESULTS
  FI-FTICR-MS metabolomic analysis showed significant reductions in the serum levels of metabolites belonging to five systems in PC patients compared to controls (all p<0.000025). The metabolic systems included 36-carbon ultra long-chain fatty acids, multiple choline-related systems including phosphatidylcholines, lysophosphatidylcholines and sphingomyelins, as well as vinyl ether-containing plasmalogen ethanolamines. ROC-AUCs based on FI-MS/MS of selected markers from each system ranged between 0.93 ±0.03 and 0.97 ±0.02. No significant correlations between any of the systems and disease-stage, gender, or treatment were observed. Biomarker PC-594 (an ultra long-chain fatty acid), was further validated using an independently-collected US Caucasian population (blinded analysis, n=60, p=9.9E-14, AUC=0.97 ±0.02). PC-594 levels across 1000 reference subjects showed an inverse correlation with age, resulting in a drop in the AUC from 0.99 ±0.01 to 0.90 ±0.02 for subjects aged 30 to 80, respectively. A PC-594 test positivity rate of 5.0% in low-risk reference subjects resulted in a PC sensitivity of 87% and a significant improvement in net clinical benefit based on decision curve analysis.
  
  
  CONCLUSIONS
  The serum metabolome of PC patients is significantly altered. The utility of serum metabolite biomarkers, particularly PC-594, for identifying subjects with elevated risk of PC should be further investigated.
authors.affiliation: Phenomenome Discoveries, Inc,, Saskatoon, SK, Canada. s.ritchie@phenomenome.com.
authors.forename: Shawn A
authors.initials: SA
authors.lastname: Ritchie
authors.forename: Hirofumi
authors.initials: H
authors.lastname: Akita
authors.forename: Ichiro
authors.initials: I
authors.lastname: Takemasa
authors.forename: Hidetoshi
authors.initials: H
authors.lastname: Eguchi
authors.forename: Elodie
authors.initials: E
authors.lastname: Pastural
authors.forename: Hiroaki
authors.initials: H
authors.lastname: Nagano
authors.forename: Morito
authors.initials: M
authors.lastname: Monden
authors.forename: Yuichiro
authors.initials: Y
authors.lastname: Doki
authors.forename: Masaki
authors.initials: M
authors.lastname: Mori
authors.forename: Wei
authors.initials: W
authors.lastname: Jin
authors.forename: Tolulope T
authors.initials: TT
authors.lastname: Sajobi
authors.forename: Dushmanthi
authors.initials: D
authors.lastname: Jayasinghe
authors.forename: Bassirou
authors.initials: B
authors.lastname: Chitou
authors.forename: Yasuyo
authors.initials: Y
authors.lastname: Yamazaki
authors.forename: Thayer
authors.initials: T
authors.lastname: White
authors.forename: Dayan B
authors.initials: DB
authors.lastname: Goodenowe
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood; D016022:Case-Control Studies; D016000:Cluster Analysis; D055088:Early Detection of Cancer; D005260:Female; D006801:Humans; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods; D008875:Middle Aged; D009367:Neoplasm Staging; D010190:Pancreatic Neoplasms / Q000097:blood / Q000175:diagnosis / Q000378:metabolism*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D053719:Tandem Mass Spectrometry; D014481:United States; D044465:White People
chemical_list: D014408:Biomarkers, Tumor
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