A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer
Metabolomics is an emerging approach for early detection of cancer. Along with the development of metabolomics, high-throughput technologies and statistical learning, the integration of multiple biomarkers has significantly improved clinical diagnosis and management for patients.
In this study, we conducted a systematic review to examine recent advancements in the oncometabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer.
PubMed, Scopus, and Web of Science were searched for relevant studies published before September 2017. We examined the study designs, the metabolomics approaches, and the reporting methodological quality following PRISMA statement.
Results and Conclusion
The included 25 studies primarily focused on the identification rather than the validation of predictive capacity of potential biomarkers. The sample size ranged from 10 to 8760. External validation of the biomarker panels was observed in nine studies. The diagnostic area under the curve ranged from 0.68 to 1.00 (sensitivity: 0.43–1.00, specificity: 0.73–1.00). The effects of patients’ bio-parameters on metabolome alterations in a context-dependent manner have not been thoroughly elucidated. The most reported candidates were glutamic acid and histidine in seven studies, and glutamine and isoleucine in five studies, leading to the predominant enrichment of amino acid-related pathways. Notably, 46 metabolites were estimated in at least two studies. Specific challenges and potential pitfalls to provide better insights into future research directions were thoroughly discussed. Our investigation suggests that metabolomics is a robust approach that will improve the diagnostic assessment of pancreatic cancer. Further studies are warranted to validate their validity in multi-clinical settings.
KeywordsPancreatic cancer Metabolomics Diagnostic biomarkers Systematic review
Area under the curve
Branched-chain amino acids
Gas chromatography–mass spectrometry
Liquid chromatography–mass spectrometry
Magnetic resonance imaging
Tandem mass spectrometry
Nuclear magnetic resonance
Orthogonal projections to latent structures discriminant analysis
Principal component analysis
Pancreatic ductal adenocarcinoma
Partial least squares discriminant analysis
Partial least squares discriminant function
Cross-validated coefficient of determination
Coefficient of determination
Receiver operating characteristic curve
Supercritical fluid extraction-supercritical fluid chromatography coupled with tandem mass spectrometry
SWK and SSH supervised the project. SWK, SSH, and NPL contributed to the study design. NPL, SJY, NHA, TDN, DKL, and YJH searched and collected the data. NPL, SJY, NHA, TDN, DKL, and YJH performed data processing and interpretation. NPL, SJY, NHA, and TDN prepared the first draft of the manuscript. All authors have read, revised critically, and approved the final manuscript.
The Bio-Synergy Research Project of the Ministry of Science, ICT and Future Planning through the National Research Foundation of Korea (NRF-2012M3A9C4048796), the National Research Foundation of Korea (NRF-2017R1E1A2A02022658, NRF-2018R1A5A2024425), and the BK21 Plus Program in 2017.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no competing interests.
This article does not contain any studies with human participants performed by any of the authors.
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