Literature DB >> 31358519

Urinary Metabolites Diagnostic and Prognostic of Intrahepatic Cholangiocarcinoma.

Christopher M Diehl1, Amelia L Parker1, Majda Haznadar1, Kristopher W Krausz2, Elise D Bowman1, Siritida Rabibhadana3, Marshonna Forgues1, Vajarabhongsa Bhudhisawasdi3, Frank J Gonzalez2, Chulabhorn Mahidol3,4, Anuradha Budhu1, Xin W Wang1, Mathuros Ruchirawat4,5, Curtis C Harris6.   

Abstract

BACKGROUND: Liver cancer is the second leading cause of cancer-related deaths worldwide. With a predicted 2.4-fold rise in liver cancer incidence by 2020, there is an urgent need for early, inexpensive diagnostic biomarkers to deploy in the clinic.
METHODS: We employed ultraperformance liquid chromatography tandem mass-spectrometry (UPLC/MS-MS) for the quantitation of four metabolites, creatine riboside (CR), N-acetylneuraminic acid (NANA), cortisol sulfate, and a lipid molecule designated as 561+, in urine samples from the NCI-MD cohort comprising 98 hepatocellular carcinoma (HCC) cases, 101 high-risk subjects, and 95 controls. Validation was carried out in the TIGER-LC cohort [n = 370 HCC and intrahepatic cholangiocarcinoma (ICC) cases, 471 high-risk subjects, 251 controls], where ICC, the second most common primary hepatic malignancy, is highly prevalent. Metabolite quantitation was also conducted in TIGER-LC tissue samples (n = 48 ICC; n = 51 HCC).
RESULTS: All profiled metabolites were significantly increased in liver cancer when compared with high-risk subjects and controls in the NCI-MD study. In the TIGER-LC cohort, the four-metabolite profile was superior at classifying ICC than a clinically utilized marker, CA19-9, and their combination led to a significantly improved model (AUC = 0.88, P = 4E-8). Metabolites CR and NANA were significantly elevated in ICC when compared with HCC cases in both urine and tissue samples. High levels of CR were associated with poorer prognosis in ICC.
CONCLUSIONS: Four metabolites are significantly increased in HCC and ICC and are robust at classifying ICC in combination with the clinically utilized marker CA19-9. IMPACT: Noninvasive urinary metabolite biomarkers hold promise for diagnostic and prognostic evaluation of ICC. ©2019 American Association for Cancer Research.

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Year:  2019        PMID: 31358519      PMCID: PMC6774833          DOI: 10.1158/1055-9965.EPI-19-0453

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  38 in total

1.  The utility of CA 19-9 in the diagnoses of cholangiocarcinoma in patients without primary sclerosing cholangitis.

Authors:  A H Patel; D M Harnois; G G Klee; N F LaRusso; G J Gores
Journal:  Am J Gastroenterol       Date:  2000-01       Impact factor: 10.864

2.  Guidelines for the diagnosis and management of intrahepatic cholangiocarcinoma.

Authors:  John Bridgewater; Peter R Galle; Shahid A Khan; Josep M Llovet; Joong-Won Park; Tushar Patel; Timothy M Pawlik; Gregory J Gores
Journal:  J Hepatol       Date:  2014-03-27       Impact factor: 25.083

3.  Transcriptomic profiling reveals hepatic stem-like gene signatures and interplay of miR-200c and epithelial-mesenchymal transition in intrahepatic cholangiocarcinoma.

Authors:  Naoki Oishi; Mia R Kumar; Stephanie Roessler; Junfang Ji; Marshonna Forgues; Anuradha Budhu; Xuelian Zhao; Jesper B Andersen; Qing-Hai Ye; Hu-Liang Jia; Lun-Xiu Qin; Taro Yamashita; Hyun Goo Woo; Yoon Jun Kim; Shuichi Kaneko; Zhao-You Tang; Snorri S Thorgeirsson; Xin Wei Wang
Journal:  Hepatology       Date:  2012-08-22       Impact factor: 17.425

4.  Urinary Metabolite Risk Biomarkers of Lung Cancer: A Prospective Cohort Study.

Authors:  Majda Haznadar; Qiuyin Cai; Kristopher W Krausz; Elise D Bowman; Ezra Margono; Rintaro Noro; Matthew D Thompson; Ewy A Mathé; Heather M Munro; Mark D Steinwandel; Frank J Gonzalez; William J Blot; Curtis C Harris
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-03-24       Impact factor: 4.254

Review 5.  After the feature presentation: technologies bridging untargeted metabolomics and biology.

Authors:  Kevin Cho; Nathaniel G Mahieu; Stephen L Johnson; Gary J Patti
Journal:  Curr Opin Biotechnol       Date:  2014-05-06       Impact factor: 9.740

6.  Trends in survival after surgery for cholangiocarcinoma: a 30-year population-based SEER database analysis.

Authors:  Hari Nathan; Timothy M Pawlik; Christopher L Wolfgang; Michael A Choti; John L Cameron; Richard D Schulick
Journal:  J Gastrointest Surg       Date:  2007-09-05       Impact factor: 3.452

7.  Expert consensus document: Cholangiocarcinoma: current knowledge and future perspectives consensus statement from the European Network for the Study of Cholangiocarcinoma (ENS-CCA).

Authors:  Jesus M Banales; Vincenzo Cardinale; Guido Carpino; Marco Marzioni; Jesper B Andersen; Pietro Invernizzi; Guro E Lind; Trine Folseraas; Stuart J Forbes; Laura Fouassier; Andreas Geier; Diego F Calvisi; Joachim C Mertens; Michael Trauner; Antonio Benedetti; Luca Maroni; Javier Vaquero; Rocio I R Macias; Chiara Raggi; Maria J Perugorria; Eugenio Gaudio; Kirsten M Boberg; Jose J G Marin; Domenico Alvaro
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2016-04-20       Impact factor: 46.802

8.  Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012.

Authors:  Jacques Ferlay; Isabelle Soerjomataram; Rajesh Dikshit; Sultan Eser; Colin Mathers; Marise Rebelo; Donald Maxwell Parkin; David Forman; Freddie Bray
Journal:  Int J Cancer       Date:  2014-10-09       Impact factor: 7.396

9.  Dysregulated signaling hubs of liver lipid metabolism reveal hepatocellular carcinoma pathogenesis.

Authors:  Sunjae Lee; Adil Mardinoglu; Cheng Zhang; Doheon Lee; Jens Nielsen
Journal:  Nucleic Acids Res       Date:  2016-05-23       Impact factor: 16.971

10.  Metabolomic biomarkers of pancreatic cancer: a meta-analysis study.

Authors:  Khyati Y Mehta; Hung-Jen Wu; Smrithi S Menon; Yassi Fallah; Xiaogang Zhong; Nasser Rizk; Keith Unger; Mark Mapstone; Massimo S Fiandaca; Howard J Federoff; Amrita K Cheema
Journal:  Oncotarget       Date:  2017-08-18
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  3 in total

1.  Improved detection and precise relative quantification of the urinary cancer metabolite biomarkers - Creatine riboside, creatinine riboside, creatine and creatinine by UPLC-ESI-MS/MS: Application to the NCI-Maryland cohort population controls and lung cancer cases.

Authors:  Daxesh P Patel; Gary T Pauly; Takeshi Tada; Amelia L Parker; Leila Toulabi; Yasuyuki Kanke; Takahiro Oike; Kristopher W Krausz; Frank J Gonzalez; Curtis C Harris
Journal:  J Pharm Biomed Anal       Date:  2020-09-01       Impact factor: 3.935

2.  Pre- and Post-Resection Urine Metabolic Profiles of Bladder Cancer Patients: Results of Preliminary Studies on Time Series Metabolomics Analysis.

Authors:  Julia Jacyna; Marta Kordalewska; Małgorzata Artymowicz; Marcin Markuszewski; Marcin Matuszewski; Michał J Markuszewski
Journal:  Cancers (Basel)       Date:  2022-02-25       Impact factor: 6.639

3.  Creatine riboside is a cancer cell-derived metabolite associated with arginine auxotrophy.

Authors:  Amelia L Parker; Leila Toulabi; Takahiro Oike; Yasuyuki Kanke; Daxeshkumar Patel; Takeshi Tada; Sheryse Taylor; Jessica A Beck; Elise Bowman; Michelle L Reyzer; Donna Butcher; Skyler Kuhn; Gary T Pauly; Kristopher W Krausz; Frank J Gonzalez; S Perwez Hussain; Stefan Ambs; Bríd M Ryan; Xin Wei Wang; Curtis C Harris
Journal:  J Clin Invest       Date:  2022-07-15       Impact factor: 19.456

  3 in total

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