UPLC-MS-based metabonomic analysis of intervention effects of Da-Huang-Xiao-Shi decoction on ANIT-induced cholestasis

In recent years, there has been a plethora of attempts to discover biomarkers that are more reliable than α-fetoprotein for the early prediction and prognosis of hepatocellular carcinoma (HCC). Efforts have involved such fields as genomics, transcriptomics, epigenetics, microRNA, exosomes, proteomics, glycoproteomics, and metabolomics. HCC arises against a background of inflammation, steatosis, and cirrhosis, due mainly to hepatic insults caused by alcohol abuse, hepatitis B and C virus infection, adiposity, and diabetes. Metabolomics offers an opportunity, without recourse to liver biopsy, to discover biomarkers for premalignant liver disease, thereby alerting the potential of impending HCC. We have reviewed metabolomic studies in alcoholic liver disease (ALD), cholestasis, fibrosis, cirrhosis, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH). Specificity was our major criterion in proposing clinical evaluation of indole-3-lactic acid, phenyllactic acid, N-lauroylglycine, decatrienoate, N-acetyltaurine for ALD, urinary sulfated bile acids for cholestasis, cervonoyl ethanolamide for fibrosis, 16α-hydroxyestrone for cirrhosis, and the pattern of acyl carnitines for NAFL and NASH. These examples derive from a large body of published metabolomic observations in various liver diseases in adults, adolescents, and children, together with animal models. Many other options have been tabulated. Metabolomic biomarkers for premalignant liver disease may help reduce the incidence of HCC.

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“…ex Hemsl.) [89], and Da-Huang-Xiao-Shi decoction [90]. In addition to TCMs, melatonin (100 mg/kg p.o.)…”

Section: Cholestasismentioning

confidence: 99%

Metabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy

Beyoğlu

Idle

2020

Metabolites

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“…There is thus an urgent need to discriminate accurate and non-invasive biomarkers to assist the early diagnosis and clinical management of CRC ( 15 , 16 ). However, metabolomics is usually utilized to discriminate the potential biomarkers and, for the purpose of the study, the complexity and hugeness of metabolic networks based on a limited number of single pathways to characterize pathological states in animals and human ( 17 ).…”

Section: Discussionmentioning

confidence: 99%

Untargeted GC-MS-Based Metabolomics for Early Detection of Colorectal Cancer

Zhu

Wang

et al. 2021

Front. Oncol.

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BackgroundColorectal cancer (CRC) is one of the most common malignant gastrointestinal cancers in the world with a 5-year survival rate of approximately 68%. Although researchers accumulated many scientific studies, its pathogenesis remains unclear yet. Detecting and removing these malignant polyps promptly is the most effective method in CRC prevention. Therefore, the analysis and disposal of malignant polyps is conducive to preventing CRC.MethodsIn the study, metabolic profiling as well as diagnostic biomarkers for CRC was investigated using untargeted GC-MS-based metabolomics methods to explore the intervention approaches. In order to better characterize the variations of tissue and serum metabolic profiles, orthogonal partial least-square discriminant analysis was carried out to further identify significant features. The key differences in tR–m/z pairs were screened by the S-plot and VIP value from OPLS-DA. Identified potential biomarkers were leading in the KEGG in finding interactions, which show the relationships among these signal pathways.ResultsFinally, 17 tissue and 13 serum candidate ions were selected based on their corresponding retention time, p-value, m/z, and VIP value. Simultaneously, the most influential pathways contributing to CRC were inositol phosphate metabolism, primary bile acid biosynthesis, phosphatidylinositol signaling system, and linoleic acid metabolism.ConclusionsThe preliminary results suggest that the GC-MS-based method coupled with the pattern recognition method and understanding these cancer-specific alterations could make it possible to detect CRC early and aid in the development of additional treatments for the disease, leading to improvements in CRC patients’ quality of life.

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“…The liver specimen was fixed in 10% formalin solution, embedded in paraffin wax and sliced into 5 μm sections. Deparaffinized sections were stained with hematoxylin-eosin (HE staining) and examined by light microscopy as described previously (Zhu and Feng, 2019).…”

Section: Histological Examinationmentioning

confidence: 99%

Mechanism of Paeoniflorin on ANIT-Induced Cholestatic Liver Injury Using Integrated Metabolomics and Network Pharmacology

et al. 2021

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Background: Paeoniflorin (PF), the major active compound isolated from the roots of Paeonia lactiflora Pall., has been used in the treatment of severe hepatic diseases for several decades and displays bright prospects in liver protective effect. However, its biological mechanism that regulates bile acid metabolism and cholestatic liver injury has not been fully elucidated. Our study aims to investigate the mechanism by which PF in the treatment of cholestatic liver injury using a comprehensive approach combining metabolomics and network pharmacological analysis.Methods: The hepatoprotective effect of PF against cholestasis liver injury, induced by α-naphthylisothiocyanate (ANIT), was evaluated in rats. The serum biochemical indices including ALT, AST, TBA, TBIL, ALP, ALB, and the pathological characteristics of the liver were analyzed. Moreover, UHPLC-Q-TOF was performed to explore the feces of rats with ANIT-induced cholestatic liver injury treated with PF and the potential biomarkers were screened by metabolomics. The targets for the regulation of potential biomarkers by PF were screened by network pharmacology, and then the relevant key targets were verified by immunohistochemical and western blotting methods.Results: PF significantly improved serum indexes and alleviated liver histological damage. Metabolomics analyses showed that the therapeutic effect of PF is mainly associated with the regulation of 13 metabolites involved in 16 metabolic pathways. The “PF-targets-metabolites” interaction network was constructed, and then five key targets including CDC25B, CYP2C9, MAOB, mTOR, and ABCB1 that regulated the potential biomarkers were obtained. The above five targets were further verified by immunohistochemistry and western blotting, and the results showed that PF significantly improved the expression of key proteins regulating these biomarkers.Conclusion: Our study provides direct evidence for the modulatory properties of PF treatment on ANIT-induced cholestatic liver injury using metabolomics and network pharmacology analyses. PF exhibits favorable pharmacological effect by regulating related signal pathways and key targets for biomarkers. Therefore, these findings may help better understand the complex mechanisms and provide a new and effective approach to the treatment of cholestatic liver injury.

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UPLC-MS-based metabonomic analysis of intervention effects of Da-Huang-Xiao-Shi decoction on ANIT-induced cholestasis

Cited by 21 publications

References 38 publications

Metabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy

Metabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy

Untargeted GC-MS-Based Metabolomics for Early Detection of Colorectal Cancer

Mechanism of Paeoniflorin on ANIT-Induced Cholestatic Liver Injury Using Integrated Metabolomics and Network Pharmacology

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