Metabolomics in hepatocellular carcinoma: From biomarker discovery to precision medicine

Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabo...

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Published inFrontiers in medical technology Vol. 4; p. 1065506
Main Authors Wu, Xingyun, Wang, Zihao, Luo, Li, Shu, Dan, Wang, Kui
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 04.01.2023
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Summary:Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabolic patterns during HCC initiation and progression has been obstructing the precision medicine in clinical practice. As a noninvasive and global screening approach, metabolomics serves as a powerful tool to dynamically monitor metabolic patterns and identify promising metabolite biomarkers, therefore holds a great potential for the development of tailored therapy for HCC patients. In this review, we summarize the recent advances in HCC metabolomics studies, including metabolic alterations associated with HCC progression, as well as novel metabolite biomarkers for HCC diagnosis, monitor, and prognostic evaluation. Moreover, we highlight the application of multi-omics strategies containing metabolomics in biomarker discovery for HCC. Notably, we also discuss the opportunities and challenges of metabolomics in nowadays HCC precision medicine. As technologies improving and metabolite biomarkers discovering, metabolomics has made a major step toward more timely and effective precision medicine for HCC patients.
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Abbreviations HCC, hepatocellular carcinoma; HBV, hepatitis B virus; HCV, hepatitis C virus; NAFLD, non-alcoholic fatty liver disease; AFP, α-fetoprotein; NMR, nuclear magnetic resonance; MS, mass spectrometry; DEN, diethyl-nitrosamine; GC, gas chromatography; LC, liquid chromatography; CE, capillary electrophoresis; FFA, free fatty acid; ESI, electrospray ionization; FT-ICR, Fourier transform ion cyclotron resonance; TOF, time of flight; Q, quadrupole; SRM, selected reaction monitoring; MRM, multiple reaction monitoring; PCA, principal component analysis; PLS-DA, partial least squares regression discriminant analysis; OPLS, orthogonal partial last squares; ROC, receiver operating characteristic; NFSM, network-based feature selection method; UPLC, ultra-performance liquid chromatographic; LASSO, least absolute shrinkage and selection operator; TACE, transcatheter arterial chemoembolization; RFA, radiofrequency ablation; UGPase 2, uridine diphosphate glucose pyrophosphorylase 2; TP53, tumor protein p53; TCF1, transcription factor 1; SCD, stearoyl-CoA-desaturase; HBc, hepatitis B virus core protein; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes pathway.
Edited by: Chon Lok Lei, University of Macau, China
Specialty Section: This article was submitted to Medtech Data Analytics, a section of the journal Frontiers in Medical Technology
These authors have contributed equally to this work and share first authorship
Reviewed by: Xuefeng Li, University of Texas MD Anderson Cancer Center, United States Xiaonan Zheng, University of Oxford, United Kingdom
ISSN:2673-3129
2673-3129
DOI:10.3389/fmedt.2022.1065506