» Articles » PMID: 35541871

Metabolomic Estimation of the Diagnosis of Hepatocellular Carcinoma Based on Ultrahigh Performance Liquid Chromatography Coupled with Time-of-flight Mass Spectrometry

Overview
Journal RSC Adv
Specialty Chemistry
Date 2022 May 11
PMID 35541871
Authors
Affiliations
Soon will be listed here.
Abstract

Metabolomics has been shown to be an effective tool for biomarker screening and pathway characterization and disease diagnosis. Metabolic characteristics of hepatocellular carcinoma (HCC) may enable the discovery of novel biomarkers for its diagnosis. In this work, metabolomics was used to investigate metabolic alterations of HCC patients. Plasma samples from HCC patients and age-matched healthy controls were investigated using high resolution ultrahigh performance liquid chromatography-mass spectrometry and metabolic differences were analyzed using pattern recognition methods. 23 distinguishable metabolites were identified. The altered metabolic pathways were associated with arginine and proline metabolism, glycine, serine and threonine metabolism, steroid hormone biosynthesis, starch and sucrose metabolism, . To demonstrate the utility of plasma biomarkers for the diagnosis of HCC, five metabolites comprising deoxycholic acid 3-glucuronide, 6-hydroxymelatonin glucuronide, 4-methoxycinnamic acid, 11b-hydroxyprogesterone and 4-hydroxyretinoic acid were selected as candidate biomarkers. These metabolites that contributed to the combined model could significantly increase the diagnostic performance of HCC. It has proved to be a powerful tool in the discovery of new biomarkers for disease detection and suggest that panels of metabolites may be valuable to translate our findings to clinically useful diagnostic tests.

Citing Articles

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Liu B, Shi J, Su R, Zheng R, Xing F, Zhang Y Front Immunol. 2024; 15:1370771.

PMID: 38707906 PMC: 11067499. DOI: 10.3389/fimmu.2024.1370771.


Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis.

Anh N, Long N, Min Y, Ki Y, Kim S, Jung C Metabolites. 2023; 13(11).

PMID: 37999208 PMC: 10672761. DOI: 10.3390/metabo13111112.


Mass spectrometry-based metabolomics for discovering active ingredients and exploring action mechanism of herbal medicine.

Guo S, Qiu S, Cai Y, Wang Z, Yang Q, Tang S Front Chem. 2023; 11:1142287.

PMID: 37065828 PMC: 10102349. DOI: 10.3389/fchem.2023.1142287.


Small molecule metabolites: discovery of biomarkers and therapeutic targets.

Qiu S, Cai Y, Yao H, Lin C, Xie Y, Tang S Signal Transduct Target Ther. 2023; 8(1):132.

PMID: 36941259 PMC: 10026263. DOI: 10.1038/s41392-023-01399-3.


Applications and potential mechanisms of herbal medicines for rheumatoid arthritis treatment: a systematic review.

Li T, Zhang A, Miao J, Sun H, Yan G, Wu F RSC Adv. 2022; 9(45):26381-26392.

PMID: 35685403 PMC: 9127666. DOI: 10.1039/c9ra04737a.


References
1.
Bowers J, Hughes E, Skill N, Maluccio M, Raftery D . Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS. J Chromatogr B Analyt Technol Biomed Life Sci. 2014; 966:154-62. PMC: 4304798. DOI: 10.1016/j.jchromb.2014.02.043. View

2.
Wang L, Ko E, Gilchrist J, Pittman K, Rautanen A, Pirinen M . Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis. Sci Adv. 2017; 3(3):e1602096. PMC: 5342653. DOI: 10.1126/sciadv.1602096. View

3.
Ranjbar M, Luo Y, Di Poto C, Varghese R, Ferrarini A, Zhang C . GC-MS Based Plasma Metabolomics for Identification of Candidate Biomarkers for Hepatocellular Carcinoma in Egyptian Cohort. PLoS One. 2015; 10(6):e0127299. PMC: 4452085. DOI: 10.1371/journal.pone.0127299. View

4.
Liang Q, Wang C, Li B, Zhang A . Metabolic fingerprinting to understand therapeutic effects and mechanisms of silybin on acute liver damage in rat. Pharmacogn Mag. 2015; 11(43):586-93. PMC: 4522847. DOI: 10.4103/0973-1296.160469. View

5.
Zhang F, Zhang Y, Zhao W, Deng K, Wang Z, Yang C . Metabolomics for biomarker discovery in the diagnosis, prognosis, survival and recurrence of colorectal cancer: a systematic review. Oncotarget. 2017; 8(21):35460-35472. PMC: 5471069. DOI: 10.18632/oncotarget.16727. View