Next Article in Journal
Protein Kinases C-Mediated Regulations of Drug Transporter Activity, Localization and Expression
Next Article in Special Issue
Molecular Drivers of Pancreatic Cancer Pathogenesis: Looking Inward to Move Forward
Previous Article in Journal
Visualization of Alternative Functional Configurations of Influenza Virus Hemagglutinin Facilitates Rapid Selection of Complementing Vaccines in Emergency Situations
Previous Article in Special Issue
Serum Concentrations of Angiopoietin-2 and Soluble fms-Like Tyrosine Kinase 1 (sFlt-1) Are Associated with Coagulopathy among Patients with Acute Pancreatitis
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Int. J. Mol. Sci. 2017, 18(4), 767; doi:10.3390/ijms18040767

Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

1
Division of Gastroenterology and Hepatology, Tokyo Medical University, Shinjuku, Tokyo 160-0023, Japan
2
Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
3
Third Department of Surgery, Tokyo Medical University, Shinjuku, Tokyo 160-0023, Japan
4
Fourth Department of Surgery, Tokyo Medical University Hachioji Medical Center, Hachioji,Tokyo 193-0998, Japan
*
Author to whom correspondence should be addressed.
Academic Editors: Srikumar Chellappan and Jaya Padmanabhan
Received: 25 February 2017 / Revised: 22 March 2017 / Accepted: 27 March 2017 / Published: 4 April 2017
(This article belongs to the Special Issue Pancreatic Disorders)
View Full-Text   |   Download PDF [1478 KB, uploaded 7 April 2017]   |  

Abstract

This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC) from malignant diseases, such as biliary tract cancer (BTC), intraductal papillary mucinous carcinoma (IPMC), and various benign pancreaticobiliary diseases. Capillary electrophoresismass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41) of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140). Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test). Four multiple logistic regression models (MLR) were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC) of 0.970 (95% confidential interval (CI), 0.946–0.994, p < 0.0001). Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020) with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), pancreatic cancer-associated antigen (DUPAN2) and s-pancreas-1 antigen (SPAN1). Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases. View Full-Text
Keywords: pancreatic cancer; biliary tract cancers; metabolomics; capillary electrophoresis mass spectrometry pancreatic cancer; biliary tract cancers; metabolomics; capillary electrophoresis mass spectrometry
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary materials

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Itoi, T.; Sugimoto, M.; Umeda, J.; Sofuni, A.; Tsuchiya, T.; Tsuji, S.; Tanaka, R.; Tonozuka, R.; Honjo, M.; Moriyasu, F.; Kasuya, K.; Nagakawa, Y.; Abe, Y.; Takano, K.; Kawachi, S.; Shimazu, M.; Soga, T.; Tomita, M.; Sunamura, M. Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination. Int. J. Mol. Sci. 2017, 18, 767.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top