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Open AccessArticle

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

AMA 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. International Journal of Molecular Sciences. 2017; 18(4):767. https://doi.org/10.3390/ijms18040767

Chicago/Turabian Style

Itoi, Takao; Sugimoto, Masahiro; Umeda, Junko; Sofuni, Atsushi; Tsuchiya, Takayoshi; Tsuji, Shujiro; Tanaka, Reina; Tonozuka, Ryosuke; Honjo, Mitsuyoshi; Moriyasu, Fuminori; Kasuya, Kazuhiko; Nagakawa, Yuichi; Abe, Yuta; Takano, Kimihiro; Kawachi, Shigeyuki; Shimazu, Motohide; Soga, Tomoyoshi; Tomita, Masaru; Sunamura, Makoto. 2017. "Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination" Int. J. Mol. Sci. 18, no. 4: 767. https://doi.org/10.3390/ijms18040767

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