A new NMR-based metabolomics approach for the diagnosis of biliary tract cancer.
OBJECTIVE
Biliary tract cancer is highly lethal at presentation, with increasing mortality worldwide. Current diagnostic measures employing multiple criteria such as imaging, cytology, and serum tumor markers are not satisfactory, and a new diagnostic tool is needed. Because bile is a cognate metabolite-rich bio-fluid in the biliary ductal system, we tested a new metabolomic approach to develop an effective diagnostic tool.


METHODS
Biles were collected prospectively from patients with cancer (n=17) or benign biliary tract diseases (n=21) with percutaneous or endoscopic methods. Nuclear magnetic resonance spectra (NMR) of these biles were analyzed using orthogonal partial least square discriminant analysis (OPLS-DA).


RESULTS
The metabolomic 2-D score plot showed good separation between cancer and benign groups. The contributing NMR signals were analyzed using a statistical TOCSY approach. The diagnostic performance assessed by leave-one-out analysis exhibited 88% sensitivity and 81% specificity, better than the conventional markers (CEA, CA19-9, and bile cytology).


CONCLUSIONS
The NMR-based metabolomics approach provides good performance in discriminating cancer and benign biliary duct diseases. The excellent predictability of the method suggests that it can, at least, augment the currently available diagnostic approaches.
Wen
He
H
Department of Biochemistry, Inha University Hospital and Center for Advanced Medical Education by BK21 Project, College of Medicine, Inha University, Incheon, Republic of Korea.
Yoo
Sung Soo
SS
Kang
Jinho
J
Kim
Hee Goo
HG
Park
Jin-Seok
JS
Jeong
Seok
S
Lee
Jung Il
JI
Kwon
Hyuk Nam
HN
Kang
Sunmi
S
Lee
Don-Haeng
DH
Park
Sunghyouk
S
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001646:Bile / Q000378:metabolism*; D001660:Biliary Tract Diseases / Q000175:diagnosis / Q000378:metabolism; D001661:Biliary Tract Neoplasms / Q000175:diagnosis* / Q000378:metabolism*; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D055432:Metabolomics / Q000379:methods* / Q000706:statistics & numerical data; D008875:Middle Aged; D015999:Multivariate Analysis; D011446:Prospective Studies