Literature DB >> 27913395

Metabolomic Characterization of Hepatocellular Carcinoma in Patients with Liver Cirrhosis for Biomarker Discovery.

Cristina Di Poto1, Alessia Ferrarini1, Yi Zhao2, Rency S Varghese1, Chao Tu1, Yiming Zuo1, Minkun Wang1, Mohammad R Nezami Ranjbar1, Yue Luo1, Chi Zhang1, Chirag S Desai3, Kirti Shetty4, Mahlet G Tadesse5, Habtom W Ressom6.   

Abstract

Background: Metabolomics plays an important role in providing insight into the etiology and mechanisms of hepatocellular carcinoma (HCC). This is accomplished by a comprehensive analysis of patterns involved in metabolic alterations in human specimens. This study compares the levels of plasma metabolites in HCC cases versus cirrhotic patients and evaluates the ability of candidate metabolites in distinguishing the two groups. Also, it investigates the combined use of metabolites and clinical covariates for detection of HCC in patients with liver cirrhosis.
Methods: Untargeted analysis of metabolites in plasma from 128 subjects (63 HCC cases and 65 cirrhotic controls) was conducted using gas chromatography coupled to mass spectrometry (GC-MS). This was followed by targeted evaluation of selected metabolites. LASSO regression was used to select a set of metabolites and clinical covariates that are associated with HCC. The performance of candidate biomarkers in distinguishing HCC from cirrhosis was evaluated through a leave-one-out cross-validation based on area under the receiver operating characteristics (ROC) curve.
Results: We identified 11 metabolites and three clinical covariates that differentiated HCC cases from cirrhotic controls. Combining these features in a panel for disease classification using support vector machines (SVM) yielded better area under the ROC curve compared with alpha-fetoprotein (AFP).Conclusions: This study demonstrates the combination of metabolites and clinical covariates as an effective approach for early detection of HCC in patients with liver cirrhosis.Impact: Further investigation of these findings may improve understanding of HCC pathophysiology and possible implication of the metabolites in HCC prevention and diagnosis. Cancer Epidemiol Biomarkers Prev; 26(5); 675-83. ©2016 AACR. ©2016 American Association for Cancer Research.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27913395      PMCID: PMC5413442          DOI: 10.1158/1055-9965.EPI-16-0366

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


  20 in total

Review 1.  Review of mass spectrometry-based metabolomics in cancer research.

Authors:  David B Liesenfeld; Nina Habermann; Robert W Owen; Augustin Scalbert; Cornelia M Ulrich
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-10-04       Impact factor: 4.254

Review 2.  Assessment of branched-chain amino Acid status and potential for biomarkers.

Authors:  Andrea Tom; K Sreekumaran Nair
Journal:  J Nutr       Date:  2006-01       Impact factor: 4.798

Review 3.  Hepatocellular carcinoma.

Authors:  Alejandro Forner; Josep M Llovet; Jordi Bruix
Journal:  Lancet       Date:  2012-02-20       Impact factor: 79.321

Review 4.  The metabolomic window into hepatobiliary disease.

Authors:  Diren Beyoğlu; Jeffrey R Idle
Journal:  J Hepatol       Date:  2013-05-25       Impact factor: 25.083

5.  Muscle metabolism and whole blood amino acid profile in patients with liver disease.

Authors:  Gitte Dam; Michael Sørensen; Mads Buhl; Thomas D Sandahl; Niels Møller; Peter Ott; Hendrik Vilstrup
Journal:  Scand J Clin Lab Invest       Date:  2015-08-04       Impact factor: 1.713

Review 6.  Hepatocellular carcinoma: Review of disease and tumor biomarkers.

Authors:  Jin Un Kim; Mohamed I F Shariff; Mary M E Crossey; Maria Gomez-Romero; Elaine Holmes; I Jane Cox; Haddy K S Fye; Ramou Njie; Simon D Taylor-Robinson
Journal:  World J Hepatol       Date:  2016-04-08

7.  Management of hepatocellular carcinoma: an update.

Authors:  Jordi Bruix; Morris Sherman
Journal:  Hepatology       Date:  2011-03       Impact factor: 17.425

8.  MetaboAnalyst 3.0--making metabolomics more meaningful.

Authors:  Jianguo Xia; Igor V Sinelnikov; Beomsoo Han; David S Wishart
Journal:  Nucleic Acids Res       Date:  2015-04-20       Impact factor: 16.971

9.  MetaboNetworks, an interactive Matlab-based toolbox for creating, customizing and exploring sub-networks from KEGG.

Authors:  Joram M Posma; Steven L Robinette; Elaine Holmes; Jeremy K Nicholson
Journal:  Bioinformatics       Date:  2013-10-30       Impact factor: 6.937

10.  The complex role of branched chain amino acids in diabetes and cancer.

Authors:  Thomas M O'Connell
Journal:  Metabolites       Date:  2013-10-14
View more
  15 in total

1.  INDEED: R package for network based differential expression analysis.

Authors:  Zhenzhi Li; Yiming Zuo; Chaohui Xu; Rency S Varghese; Habtom W Ressom
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2019-01-24

2.  Metabolic signatures of hepatolithiasis using ultra-high performance liquid chromatography-tandem mass spectrometry.

Authors:  Cong Wang; Jun Yang; Enliang Li; Shuaiwu Luo; Chi Sun; Yuting Liao; Min Li; Jin Ge; Jun Lei; Fan Zhou; Linquan Wu; Wenjun Liao
Journal:  Metabolomics       Date:  2022-08-17       Impact factor: 4.747

3.  Prognostic gene biomarker identification in liver cancer by data mining.

Authors:  Gang Liu; Haitao Tang; Chen Li; Haiyan Zhen; Zhigang Zhang; Yongzhong Sha
Journal:  Am J Transl Res       Date:  2021-05-15       Impact factor: 4.060

4.  Multi-omic Pathway and Network Analysis to Identify Biomarkers for Hepatocellular Carcinoma.

Authors:  Megan E Barefoot; Rency S Varghese; Yuan Zhou; Cristina Di Poto; Alessia Ferrarini; Habtom W Ressom
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2019-07

5.  Abdominal ultrasound and alpha-foetoprotein for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease.

Authors:  Agostino Colli; Tin Nadarevic; Damir Miletic; Vanja Giljaca; Mirella Fraquelli; Davor Štimac; Giovanni Casazza
Journal:  Cochrane Database Syst Rev       Date:  2021-04-15

6.  Identification of race-associated metabolite biomarkers for hepatocellular carcinoma in patients with liver cirrhosis and hepatitis C virus infection.

Authors:  Cristina Di Poto; Shisi He; Rency S Varghese; Yi Zhao; Alessia Ferrarini; Shan Su; Abdullah Karabala; Mesfin Redi; Hassen Mamo; Amol S Rangnekar; Thomas M Fishbein; Alexander H Kroemer; Mahlet G Tadesse; Rabindra Roy; Zaki A Sherif; Deepak Kumar; Habtom W Ressom
Journal:  PLoS One       Date:  2018-03-14       Impact factor: 3.240

Review 7.  Multiple "Omics" data-based biomarker screening for hepatocellular carcinoma diagnosis.

Authors:  Xiao-Na Liu; Dan-Ni Cui; Yu-Fang Li; Yun-He Liu; Gang Liu; Lei Liu
Journal:  World J Gastroenterol       Date:  2019-08-14       Impact factor: 5.742

Review 8.  Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma.

Authors:  Bin Chen; Lana Garmire; Diego F Calvisi; Mei-Sze Chua; Robin K Kelley; Xin Chen
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2020-01-03       Impact factor: 46.802

Review 9.  Deciphering hepatocellular carcinoma through metabolomics: from biomarker discovery to therapy evaluation.

Authors:  Wei Guo; Hor Yue Tan; Ning Wang; Xuanbin Wang; Yibin Feng
Journal:  Cancer Manag Res       Date:  2018-04-11       Impact factor: 3.989

10.  The Effects of Graded Levels of Calorie Restriction: XIII. Global Metabolomics Screen Reveals Graded Changes in Circulating Amino Acids, Vitamins, and Bile Acids in the Plasma of C57BL/6 Mice.

Authors:  Cara L Green; Quinlyn A Soltow; Sharon E Mitchell; Davina Derous; Yingchun Wang; Luonan Chen; Jing-Dong J Han; Daniel E L Promislow; David Lusseau; Alex Douglas; Dean P Jones; John R Speakman
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2019-01-01       Impact factor: 6.053

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.