Utilization of metabolomics to identify serum biomarkers for hepatocellular carcinoma in patients with liver cirrhosis

Taurocholic acid represents an earlier and more sensitive biomarker and promotes cholestatic hepatotoxicity in ANIT-treated rats

Bile acid homeostasis is crucial for the normal physiological functioning of the liver. Disruptions in bile acid profiles are closely linked to the occurrence of cholestatic liver injury. As part of our diagnostic and therapeutic approach, we aimed to investigate the disturbance in bile acid profiles during cholestasis and its correlation with cholestatic liver injury. Before the occurrence of liver injury, alterations in bile acid profiles were detected in both plasma and liver between 8 and 16 h, persisting up to 96 h. TCA, TCDCA, and TUDCA in the plasma, as well as TCA, TUDCA, TCDCA, TDCA, TLCA, and THDCA in the liver, emerged as early sensitive and potential markers for diagnosing ANIT-induced cholestasis at 8-16 h. The distinguishing features of ANIT-induced liver injury were as follows: T-BAs exceeding G-BAs and serum biochemical indicators surpassing free bile acids. Notably, plasma T-BAs, particularly TCA, exhibited higher sensitivity to cholestatic hepatotoxicity compared with serum enzyme activity and liver histopathology. Further investigation revealed that TCA exacerbated ANIT-induced liver injury by elevating liver function enzyme activity, inflammation, and bile duct proliferation and promoting the migration of bile duct epithelial cell. Nevertheless, no morphological changes or alterations in transaminase activity indicative of liver damage were observed in the rats treated with TCA alone. Additionally, there were no changes in bile acid profiles or inflammatory responses under physiological conditions with maintained bile acid homeostasis. In summary, our findings suggest that taurine-conjugated bile acids in both plasma and liver, particularly TCA, can serve as early and sensitive markers for predicting intrahepatic cholestatic drugs and can act as potent exacerbators of cholestatic liver injury progression. However, exogenous TCA does not induce liver injury under physiological conditions where bile acid homeostasis is maintained.

Liquid Chromatography/Tandem Mass Spectrometry-Based Simultaneous Analysis of 32 Bile Acids in Plasma and Conventional Biomarker-Integrated Diagnostic Screening Model Development for Hepatocellular Carcinoma

Imaging tests, tumor marker (TM) screening, and biochemical tests provide a definitive diagnosis of hepatocellular carcinoma (HCC). However, some patients with HCC may present TM-negative results, warranting a need for developing more sensitive and accurate screening biomarkers. Various diseases exhibit increased blood levels of bile acids, biosynthesized from cholesterol in the liver, and they have been associated with HCC. Herein, we analyzed plasma bile acids using liquid chromatography/tandem mass spectrometry and integrated them with conventional biomarkers to develop a diagnostic screening model for HCC. Plasma samples were obtained from patients diagnosed with chronic hepatitis, hepatic cirrhosis (HC), and HCC. A QTRAP 6500 mass spectrometer and a Nexera liquid chromatograph with a YMC-Triart C18 analytical column were used. The mobile phase A was a 20 mmol/L ammonium formate solution, and mobile phase B was a methanol/acetonitrile mixture (1:1, v/v) with 20 mmol/L ammonium formate. After determining the concentrations of 32 bile acids, statistical analysis and diagnostic screening model development were performed. Plasma concentrations of bile acids differed between sample groups, with significant differences observed between patients with HC and HCC. By integrating bile acid results with conventional biochemical tests, a potential diagnostic screening model for HCC was successfully developed. Future studies should increase the sample size and analyze the data in detail to verify the diagnostic efficacy of the model.

Differences in Prediagnostic Serum Metabolomic and Lipidomic Profiles Between Cirrhosis Patients with and without Incident Hepatocellular Carcinoma

Background

Early detection of hepatocellular carcinoma (HCC) is crucial for improving patient outcomes, but we lack robust clinical biomarkers. This study aimed to identify a metabolite and/or lipid panel for early HCC detection.

Methods

We developed a high-resolution liquid chromatography mass spectrometry (LC-MS)-based profiling platform and evaluated differences in the global metabolome and lipidome between 28 pre-diagnostic serum samples from patients with cirrhosis who subsequently developed HCC (cases) and 30 samples from patients with cirrhosis and no HCC (controls). We linked differentially expressed metabolites and lipids to their associated genes, proteins, and transcriptomic signatures in publicly available datasets. We used machine learning models to identify a minimal panel to distinguish between cases and controls.

Results

Among cases compared with controls, 124 metabolites and 246 lipids were upregulated, while 208 metabolites and 73 lipids were downregulated. The top upregulated metabolites were glycoursodeoxycholic acid, 5-methyltetrahydrofolic acid, octanoyl-coenzyme A, and glycocholic acid. Elevated lipids comprised glycerol lipids, cardiolipin, and phosphatidylethanolamine, whereas suppressed lipids included oxidized phosphatidylcholine and lysophospholipids. There was an overlap between differentially expressed metabolites and lipids and previously published transcriptomic signatures, illustrating an association with liver disease severity. A panel of 12 metabolites that distinguished between cases and controls with an area under the receiver operating curve of 0.98 for the support vector machine (interquartile range, 0.9-1).

Conclusion

Using prediagnostic serum samples, we identified a promising metabolites panel that accurately identifies patients with cirrhosis who progressed to HCC. Further validation of this panel is required.

Untargeted metabolomics reveals potential health risks associated with chronic exposure to environmentally relevant concentrations of 2-Phenylphenol

Chronic exposure to endocrine-disrupting chemicals through foods of aquatic origin, at levels that are commonly found in the environment, can affect metabolic health and lead to metabolic diseases. One such chemical is 2-phenylphenol (2-PP), a suspected endocrine disruptor that is used extensively in agriculture and industry, and has become a widespread pollutant in aquatic environments. This study evaluated the risk of exposure to 2-PP through foods of aquatic origin from Vembanad Lake, using a Target Hazard Quotient (THQ) and an untargeted metabolomics approach. The study found that 2-PP content was higher in samples from areas with intense industrial, tourism, and agricultural activities. The average concentration of 2-PP in fish, crustaceans, and mollusks from the Vembanad estuary ranged from 0.012 to 0.017 mg/kg. The mean concentration of 2-PP was used to assess the THQ of exposure to the coastal population. The results showed that the THQ value was <1, indicating a low to moderate health risk for both adults and children. Furthermore, an untargeted metabolomics approach using HPLC-Q-Orbitrap MS was used to study the metabolome changes associated with chronic exposure to 2-PP (at the environmentally relevant concentration) over 60 days in the Wistar albino rat model. The findings indicated significant alterations in the phospholipid, fatty acid, sterol lipid, and amino acid profiles, suggesting that chronic exposure to 2-PP at environmentally relevant concentrations could affect purine, phenylalanine, tyrosine, and cholesterol metabolism.

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

Identifying and translating hepatocellular carcinoma (HCC) biomarkers from bench to bedside using mass spectrometry-based metabolomics and lipidomics is hampered by inconsistent findings. Here, we investigated HCC at systemic and metabolism-centric multiomics levels by conducting a meta-analysis of quantitative evidence from 68 cohorts. Blood transcript biomarkers linked to the HCC metabolic phenotype were externally validated and prioritized. In the studies under investigation, about 600 metabolites were reported as putative HCC-associated biomarkers; 39, 20, and 10 metabolites and 52, 12, and 12 lipids were reported in three or more studies in HCC vs. Control, HCC vs. liver cirrhosis (LC), and LC vs. Control groups, respectively. Amino acids, fatty acids (increased 18:1), bile acids, and lysophosphatidylcholine were the most frequently reported biomarkers in HCC. BAX and RAC1 showed a good correlation and were associated with poor prognosis. Our study proposes robust HCC biomarkers across diverse cohorts using a data-driven knowledge-based approach that is versatile and affordable for studying other diseases.

The Role of Mass Spectrometry in Hepatocellular Carcinoma Biomarker Discovery

Hepatocellular carcinoma (HCC) is the main liver malignancy and has a high mortality rate. The discovery of novel biomarkers for early diagnosis, prognosis, and stratification purposes has the potential to alleviate its disease burden. Mass spectrometry (MS) is one of the principal technologies used in metabolomics, with different experimental methods and machine types for different phases of the biomarker discovery process. Here, we review why MS applications are useful for liver cancer, explain the MS technique, and briefly summarise recent findings from metabolomic MS studies on HCC. We also discuss the current challenges and the direction for future research.

Biomarker Discovery for Hepatocellular Carcinoma in Patients with Liver Cirrhosis Using Untargeted Metabolomics and Lipidomics Studies

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is the third leading cause of mortality globally. Patients with HCC have a poor prognosis due to the fact that the emergence of symptoms typically occurs at a late stage of the disease. In addition, conventional biomarkers perform suboptimally when identifying HCC in its early stages, heightening the need for the identification of new and more effective biomarkers. Using metabolomics and lipidomics approaches, this study aims to identify serum biomarkers for identification of HCC in patients with liver cirrhosis (LC). Serum samples from 20 HCC cases and 20 patients with LC were analyzed using ultra-high-performance liquid chromatography-Q Exactive mass spectrometry (UHPLC-Q-Exactive-MS). Metabolites and lipids that are significantly altered between HCC cases and patients with LC were identified. These include organic acids, amino acids, TCA cycle intermediates, fatty acids, bile acids, glycerophospholipids, sphingolipids, and glycerolipids. The most significant variability was observed in the concentrations of bile acids, fatty acids, and glycerophospholipids. In the context of HCC cases, there was a notable increase in the levels of phosphatidylethanolamine and triglycerides, but the levels of fatty acids and phosphatidylcholine exhibited a substantial decrease. In addition, it was observed that all of the identified metabolites exhibited a superior area under the receiver operating characteristic (ROC) curve in comparison to alpha-fetoprotein (AFP). The pathway analysis of these metabolites revealed fatty acid, lipid, and energy metabolism as the most impacted pathways. Putative biomarkers identified in this study will be validated in future studies via targeted quantification.

Metabolomics and network analysis uncovered profound inflammation-associated alterations in hepatitis B virus-related cirrhosis patients with early hepatocellular carcinoma

Patients with hepatitis B virus (HBV)-related liver cirrhosis (LC) are at high risk for hepatocellular carcinoma (HCC). Limitations in the early detection of HCC give rise to poor survival in this high-risk population. Here, we performed comprehensive metabolomics on health individuals and HBV-related LC patients with and without early HCC. Compared to non-HCC patients (N = 108) and health controls (N = 80), we found that patients with early HCC (N = 224) exhibited a specific plasma metabolome map dominated by lipid alterations, including lysophosphatidylcholines, lysophosphatidic acids and bile acids. Pathway and function network analyses indicated that these metabolite alterations were closely associated with inflammation responses. Using multivariate regression and machine learning approaches, we identified a five-metabolite combination that showed significant performances in differentiating early-HCC from non-HCC than α-fetoprotein (area under the curve values, 0.981 versus 0.613). At metabolomic levels, this work provides additional insights of metabolic dysfunction related to HCC progressions and demonstrates the plasma metabolites might be measured to identify early HCC in patients with HBV-related LC.

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 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.

Evaluation of Amino Acids Profile as Non-Invasive Biomarkers of Hepatocellular Carcinoma in Egyptians

BACKGROUND

Hepatocellular carcinoma (HCC) is the most dangerous complication of chronic liver disease. It is a multifactorial complicated disease. Hepatitis C and hepatitis B viruses (HCV and HBV, respectively) represent the main causes of HCC in Egypt. Early diagnosis is very important to aid in early intervention.

OBJECTIVES

The goal of this research is to evaluate the metabolic role of different amino acids as non-invasive biomarkers over the course of HCC.

METHODS

This study included 302 participants with 97 diagnosed, untreated HCC patients, 81 chronic HCV patients, 56 chronic HBV patients, 18 co-infected patients, and a control group of 50 normal age and gender-matched individuals. All participants provided complete medical histories and underwent complete clinical examinations, abdominal ultrasonography and/or computed tomography, routine laboratory investigations, estimation of serum α-fetoprotein, and determination of amino acid levels using ultra-performance liquid chromatography (UPLC MS/MS).

RESULTS

This work revealed a decline in branched chain amino acids (BCAA) and increase in aromatic amino acids (AAA) among infected groups (HCC, HBV, HCV, and co-infected patients) compared to control subjects and a marked change in Fisher's and the BCAAs/tyrosine molar concentration ratios (BTR) between controls and infected groups.

CONCLUSION

Different amino acids could be used as non-invasive markers to discriminate and follow chronic hepatitis patients to predict the course of HCC.

LargeMetabo: an out-of-the-box tool for processing and analyzing large-scale metabolomic data

Large-scale metabolomics is a powerful technique that has attracted widespread attention in biomedical studies focused on identifying biomarkers and interpreting the mechanisms of complex diseases. Despite a rapid increase in the number of large-scale metabolomic studies, the analysis of metabolomic data remains a key challenge. Specifically, diverse unwanted variations and batch effects in processing many samples have a substantial impact on identifying true biological markers, and it is a daunting challenge to annotate a plethora of peaks as metabolites in untargeted mass spectrometry-based metabolomics. Therefore, the development of an out-of-the-box tool is urgently needed to realize data integration and to accurately annotate metabolites with enhanced functions. In this study, the LargeMetabo package based on R code was developed for processing and analyzing large-scale metabolomic data. This package is unique because it is capable of (1) integrating multiple analytical experiments to effectively boost the power of statistical analysis; (2) selecting the appropriate biomarker identification method by intelligent assessment for large-scale metabolic data and (3) providing metabolite annotation and enrichment analysis based on an enhanced metabolite database. The LargeMetabo package can facilitate flexibility and reproducibility in large-scale metabolomics. The package is freely available from https://github.com/LargeMetabo/LargeMetabo.

Hepatocellular carcinoma: Novel understandings and therapeutic strategies based on bile acids (Review)

Bile acids (BAs) are the major components of bile and products of cholesterol metabolism. Cholesterol is catalyzed by a variety of enzymes in the liver to form primary BAs, which are excreted into the intestine with bile, and secondary BAs are formed under the modification of the gut microbiota. Most of the BAs return to the liver via the portal vein, completing the process of enterohepatic circulation. BAs have an important role in the development of hepatocellular carcinoma (HCC), which may participate in the progression of HCC by recognizing receptors such as farnesoid X receptor (FXR) and mediating multiple downstream pathways. Certain BAs, such as ursodeoxycholic acid and obeticholic acid, were indicated to be able to delay liver injury and HCC progression. In the present review, the structure and function of BAs were introduced and the metabolism of BAs and the process of enterohepatic circulation were outlined. Furthermore, the mechanisms by which BAs participate in the development of HCC were summarized and possible strategies for targeting BAs and key sites of their metabolic processes to treat HCC were suggested.

Bile acids as drivers and biomarkers of hepatocellular carcinoma

The prevalence of hepatocellular carcinoma (HCC) is rapidly increasing, driven not least in part by the escalating prevalence of non-alcoholic fatty liver disease. Bile acid (BA) profiles are altered in patients with HCC and there is a developing body of evidence from in vitro human cellular models as well as rodent data suggesting that BA are able to modulate fundamental processes that impact on cellular phenotype predisposing to the development of HCC including senescence, proliferation and epithelial-mesenchymal transition. Changes in BA profiles associated with HCC have the potential to be exploited clinically. Whilst excellent diagnostic and imaging tools are available, their use to screen populations with advanced liver disease at risk of HCC is limited by high cost and low availability. The mainstay for HCC screening among subjects with cirrhosis remains frequent interval ultrasound scanning. Importantly, currently available serum biomarkers add little to diagnostic accuracy. Here, we review the current literature on the use of BA measurements as predictors of HCC incidence in addition to their use as a potential screening method for the early detection of HCC. Whilst these approaches do show early promise, there are limitations including the relatively small cohort sizes, the lack of a standardized approach to BA measurement, and the use of inappropriate control comparator samples.

Gut microbiota combined with metabolomics reveal the mechanism of curcumol on liver fibrosis in mice

OBJECTIVE

Liver fibrosis is a reversible pathological process, and its prevention and treatment hold great significance for patients with chronic liver disease. This study combined 16S rRNA analysis of gut microbiota and serum metabolomics to explore the mechanism of curcumol's effect on liver fibrosis in mice. The results clarified the relationship between the gut microbiota and metabolites in the process of liver fibrosis.

MATERIALS AND METHODS

In this study, we randomly divided mice into a control group, a model group, and a curcumol treatment group to analyze the pathological changes in the liver tissue as well as the activities of the toll-like receptor 4 (TLR4)/nuclear factory kappa B (NF-κB) signaling pathway and inflammatory factors, such as tumor necrosis factor (TNF), interleukin 6 (IL-6), and IL-8. The gut microbiota were analyzed by 16 S rRNA sequencing, and serum metabolites were examined by liquid chromatography-mass spectrometry (LC-MS) metabolomic analysis.

RESULTS

Molecular biological testing found that curcumol could significantly improve the pathological changes of the liver tissue and inhibit the occurrence of liver inflammation. Intestinal flora testing found that curcumol could significantly change the abundances of Veillonellaceae, Prerotella_oulorum, and Alistipes_finegoldii. Metabolomics analysis found that curcumol's antihepatic fibrosis effect may be related to its regulation of arachidonic acid metabolism. Correlation analysis suggested that curcumol regulated the abundances of Bacteroidota and Bacteroides and participated in the metabolism of Prostaglandin B2.

CONCLUSIONS

When liver fibrosis occurs, the intestinal flora and metabolic network are altered. The effect of curcumol on liver fibrosis may be related to its regulation of intestinal flora and the resulting interference with metabolic pathways, thereby reducing liver inflammation.

Optimized Systematic Review Tool: Application to Candidate Biomarkers for the Diagnosis of Hepatocellular Carcinoma

This review aims to develop an appropriate review tool for systematically collating metabolites that are dysregulated in disease and applies the method to identify novel diagnostic biomarkers for hepatocellular carcinoma (HCC). Studies that analyzed metabolites in blood or urine samples where HCC was compared with comparison groups (healthy, precirrhotic liver disease, cirrhosis) were eligible. Tumor tissue was included to help differentiate primary and secondary biomarkers. Searches were conducted on Medline and EMBASE. A bespoke "risk of bias" tool for metabolomic studies was developed adjusting for analytic quality. Discriminant metabolites for each sample type were ranked using a weighted score accounting for the direction and extent of change and the risk of bias of the reporting publication. A total of 84 eligible studies were included in the review (54 blood, 9 urine, and 15 tissue), with six studying multiple sample types. High-ranking metabolites, based on their weighted score, comprised energy metabolites, bile acids, acylcarnitines, and lysophosphocholines. This new review tool addresses an unmet need for incorporating quality of study design and analysis to overcome the gaps in standardization of reporting of metabolomic data. Validation studies, standardized study designs, and publications meeting minimal reporting standards are crucial for advancing the field beyond exploratory studies.

A prospective investigation of serum bile acids with risk of liver cancer, fatal liver disease, and biliary tract cancer

Bile acids (BAs), major regulators of the gut microbiota, may play an important role in hepatobiliary cancer etiology. However, few epidemiologic studies have comprehensively examined associations between BAs and liver or biliary tract cancer. In the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) study, we designed 1:1 matched, nested, case-control studies of primary liver cancer (n = 201 cases), fatal liver disease (n = 261 cases), and primary biliary tract cancer (n = 138 cases). Using baseline serum collected ≤30 years before diagnosis or death, we measured concentrations of 15 BAs with liquid chromatography-tandem mass spectrometry. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) using multivariable conditional logistic regression models, adjusted for age, education, diabetes status, smoking, alcohol intake, and body mass index. We accounted for multiple comparisons using a false discovery rate (FDR) correction. Comparing the highest to the lowest quartile, seven BAs were positively associated with liver cancer risk, including taurocholic acid (TCA) (OR, 5.62; 95% CI, 2.74-11.52; Q trend < 0.0001), taurochenodeoxycholic acid (TCDCA) (OR, 4.77; 95% CI, 2.26-10.08; Q trend < 0.0001), and glycocholic acid (GCA) OR, 5.30; 95% CI, 2.41-11.66; Q trend < 0.0001), and 11 were positively associated with fatal liver disease risk, including TCDCA (OR, 9.65; 95% CI, 4.41-21.14; Q trend < 0.0001), TCA (OR, 7.45; 95% CI, 3.70-14.97; Q trend < 0.0001), and GCA (OR, 6.98; 95% CI, 3.32-14.68; Q trend < 0.0001). For biliary tract cancer, associations were generally >1 but not significant after FDR correction. Conjugated BAs were strongly associated with increased risk of liver cancer and fatal liver disease, suggesting mechanistic links between BA metabolism and liver cancer or death from liver disease.

Lipid alterations in chronic liver disease and liver cancer

Lipids are a complex and diverse group of molecules with crucial roles in many physiological processes, as well as in the onset, progression, and maintenance of cancers. Fatty acids and cholesterol are the building blocks of lipids, orchestrating these crucial metabolic processes. In the liver, lipid alterations are prevalent as a cause and consequence of chronic hepatitis B and C virus infections, alcoholic hepatitis, and non-alcoholic fatty liver disease and steatohepatitis. Recent developments in lipidomics have also revealed that dynamic changes in triacylglycerols, phospholipids, sphingolipids, ceramides, fatty acids, and cholesterol are involved in the development and progression of primary liver cancer. Accordingly, the transcriptional landscape of lipid metabolism suggests a carcinogenic role of increasing fatty acids and sterol synthesis. However, limited mechanistic insights into the complex nature of the hepatic lipidome have so far hindered the development of effective therapies.

Changing Metabolic Patterns along the Colorectal Adenoma–Carcinoma Sequence

Colorectal cancer (CRC) is a major public health burden and one of the leading causes of cancer-related deaths worldwide. Screening programs facilitate early diagnosis and can help to reduce poor outcomes. Serum metabolomics can extract vital molecular information that may increase the sensitivity and specificity of colonoscopy in combination with histopathological examination. The present study identifies serum metabolite patterns of treatment-naïve patients, diagnosed with either advanced adenoma (AA) or CRC in colonoscopy screenings, in the framework of the SAKKOPI (Salzburg Colon Cancer Prevention Initiative) program. We used a targeted flow injection analysis and liquid chromatography-tandem mass spectrometry metabolomics approach (FIA- and LC-MS/MS) to characterise the serum metabolomes of an initial screening cohort and two validation cohorts (in total 66 CRC, 76 AA and 93 controls). The lipidome was significantly perturbed, with a proportion of lipid species being downregulated in CRC patients, as compared to AA and controls. The predominant alterations observed were in the levels of lyso-lipids, glycerophosphocholines and acylcarnitines, but additionally, variations in the quantity of hydroxylated sphingolipids could be detected. Changed amino acid metabolism was restricted mainly to metabolites of the arginine/dimethylarginine/NO synthase pathway. The identified metabolic divergences observed in CRC set the foundation for mechanistic studies to characterise biochemical pathways that become deregulated during progression through the adenoma to carcinoma sequence and highlight the key importance of lipid metabolites. Biomarkers related to these pathways could improve the sensitivity and specificity of diagnosis, as well as the monitoring of therapies.

Metabolomic biomarkers for hepatocellular carcinoma: A systematic review

Hepatocellular carcinoma (HCC) is a highly malignant cancer which lack of effective diagnosis and prognosis biomarkers, therefore surging studies focused on the metabolite candidates for HCC. The current study was designed to systematically review the metabolic studies for HCC, summarize the current available evidence and provide implication for further studies within this area. By systematically screening Pubmed and Embase, and eligibility assessment, we eventually included 55 pieces of studies. After summarized their characteristics, we reviewed them by 3 parts, regarding to the different biofluid they carried out the experiments. By collecting the candidates from all the included studies, we carried out pathway enrichment to see the representative of the reported candidates, as expected the pathway consistent with the current knowledge of HCC. Next, we conduct quality assessment on the included studies. Only 36% of the current evidence grouped as high quality, indicating the quality of metabolic studies needs further improvement.

M, El-Said H. Value of Bile Acids in Diagnosing Hepatitis C Virus-Induced Liver Cirrhosis and Hepatocellular Carcinoma

Background: Metabonomic studies have related bile acids to hepatic impairment, but their role in predicting hepatocellular carcinoma still unclear. The study aimed to examine the feasibility of bile acids in distinguishing hepatocellular carcinoma from post hepatitis C virus-induced liver cirrhosis.

Methods: An ultra-performance liquid chromatography coupled with mass spectrometry measured 14 bile acids in patients with noncirrhotic post hepatitis C virus disease (n = 50), cirrhotic post hepatitis C virus disease (n = 50), hepatocellular carcinoma (n = 50), and control group (n = 50).

Results: The spectrum of liver disease was associated with a significant increase in many conjugated bile acids. The fold changes in many bile acid concentrations showed a linear trend with hepatocellular carcinoma &gt; cirrhotic disease &gt; noncirrhotic disease &gt; healthy controls (p &lt; 0.05). Receiver operating characteristic curve analysis revealed five conjugated acids TCA, GCA, GUDCA, TCDCA, GCDCA, that discriminated hepatocellular carcinoma from noncirrhotic liver patients (AUC = 0.85–0.96) with a weaker potential to distinguish it from chronic liver cirrhosis (AUC = 0.41–0.64).

Conclusion: Serum bile acids are associated primarily with liver cirrhosis with little value in predicting the progress of cirrhotic disease to hepatocellular carcinoma.

A Time-Resolved-Fluorescence Lateral Flow Assay for Rapid Detection of Cholyglycine Acid for the Diagnosis of Liver Diseases

Liver disease is a great danger to human health. The determination of blood level of Cholyglycine acid (CG) is a vital biomarker for the assessment of liver function in clinic, which is contribute to the diagnosis of liver diseases. Thus, establishing accuracy, rapid and convenient method for the detection of glycolic acid is of great significance. In this study, a time-resolved-fluorescence (TRF) lateral flow assay for rapid detection of CG was development. The analytical detection limit (mean of zero-2 SD) was 0.06 μg/mL The method showed good linearity in the range of 0.2–40 g/mL and was not affected by biomolecules with similar structure to CG. The analytical mean recovery of control was between 90–110% and the imprecision of intra- and inter-assay of CVs was less than 10%. No significant matrix effect was observed in saline, serum, plasma or whole blood. A good correlation was found with the homogeneous enzyme immunoassay (HEIA) assay (slopes 1.0463, y-intercepts 0.2721 μg/mL, R = 0.989, n = 50, P < 0.001). The CG TRF analysis could provide reproducible and quantitative information about the state of liver in a few minutes, which is suitable for the detection of liver diseases in point-of-care-testing (POCT) conditions.

Role of bile acids in the prediction of hepatocellular carcinoma in HCV-induced liver cirrhosis

Background

Bile acids are essential organic molecules synthesized from cholesterol in the liver and regarded as indicators of hepatobiliary impairment; however, their role in the pathogenesis of hepatocellular carcinoma (HCC) is still unclear. The study aimed to examine the feasibility of bile acids in distinguishing HCC from post hepatitis C virus liver cirrhosis. A UPLC/MS was used to measure 14 bile acids in patients with noncirrhotic HCV disease (n = 50), cirrhotic HCV disease (n = 50), hepatocellular carcinoma (n = 50), and control group (n = 50).

Results

The progression of liver cirrhosis to HCC was associated with a significant increase in serum bile acids compared to the normal or the noncirrhotic HCV disease (p < 0.05). The fold changes in bile acids concentrations showed a trend that HCC > cirrhotic HCV disease > noncirrhotic HCV disease. Four conjugated acids GCA, GCDCA, GUDCA, and TCDCA steadily increased across the different groups. ROC curves analysis revealed that these bile acids discriminated noncirrhotic liver patients from HCC (AUC 0.850–0.963), with a weaker potential to distinguish chronic liver cirrhosis from HCC (AUC 0.414–0.638).

Conclusion

The level of serum bile acid was associated primarily with liver cirrhosis, with little value in predicting the progress of chronic liver cirrhotic disease into hepatocellular carcinoma.

Taurochenodeoxycholic acid inhibits the proliferation and invasion of gastric cancer and induces its apoptosis

Taurochenodeoxycholic acid (TCDCA) is the principal ingredient of Compound Shougong Powder. Despite traditional Chinese medicine (TCM) research demonstrates that Compound Shougong Powder can restrict tumor growth, whether TCDCA exerts a role in suppressing cancer as the major ingredient of Compound Shougong Powder remains unknown. This study aims to clarify the regulatory mechanism of TCDCA on gastric cancer. Gastric cancer cells SGC-7901 were cultured to investigate the effects of TCDCA on proliferation and apoptosis. Furthermore, a subcutaneously implanted tumor model was established using SGC-7901 cells in BALB/C nude mice and tumor volume was measured under low and high dose treatment of TCDCA. Cell proliferation, apoptosis, and invasion were subjected to 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) assay, flow cytometry, and transwell assay. Differentially expressed genes were screened by transcriptome sequencing. Nude mouse tumorigenicity assay was initiated to identify the effect of TCDCA on both tumor volume and weight, and the expression of candidate genes screened by transcriptome sequencing was determined by real-time fluorescence quantification (qPCR) and Western blot. The experiments revealed that TCDCA could significantly inhibit the proliferation and invasion of gastric cancer cells and induce apoptosis of these cells. Meanwhile, test findings via in vivo indicated that TCDCA severely diminished the volume and weight of tumors. This study first demonstrated that TCDCA inhibited the proliferation and invasion of gastric cancer and induced apoptosis, which is expected to serve as an experimental basis for the application of TCM in tumor therapeutic options. PRACTICAL APPLICATIONS: Through this study, the inhibitory effect of Taurochenodeoxycholic acid on gastric cancer can be clarified, which provides a new research basis for the application of traditional Chinese medicine (TCM) and TCM monomer in cancer. In addition, this study can further promote the research and application of Chinese traditional medicine, which has important application value and economic benefits.

Clinical significance of small molecule metabolites in the blood of patients with different types of liver injury

To understand the characteristic of changes of serum metabolites between healthy people and patients with hepatitis B virus (HBV) infection at different stages of disease, and to provide reference metabolomics information for clinical diagnosis of liver disease patients. 255 patients with different stages of HBV infection were selected. 3 mL blood was collected from each patient in the morning to detect differences in serum lysophosphatidylcholine, acetyl-l-carnitine, oleic acid amide, and glycocholic acid concentrations by UFLC-IT-TOF/MS. The diagnostic values of four metabolic substances were evaluated by receiver operating characteristic (ROC) curve. The results showed that the optimal cut-off value of oleic acid amide concentration of the liver cirrhosis and HCC groups was 23.6 mg/L, with a diagnostic sensitivity of 88.9% and specificity of 70.6%. The diagnostic efficacies of the three substances were similar in the hepatitis and HCC groups, with an optimal cut-off value of 2.04 mg/L, and a diagnostic sensitivity and specificity of 100% and 47.2%, respectively. The optimal cut-off value of lecithin of the HBV-carrier and HCC groups was 132.85 mg/L, with a diagnostic sensitivity and specificity of 88.9% and 66.7%, respectively. The optimal cut-off value of oleic acid amide of the healthy and HCC groups was 129.03 mg/L, with a diagnostic sensitivity and specificity of 88.4% and 83.3%, respectively. Lysophosphatidylcholine, acetyl-l-carnitine, and oleic acid amide were potential metabolic markers of HCC. Among them, lysophosphatidylcholine was low in the blood of HCC patients, and its diagnostic efficacy was better than that of acetyl-l-carnitine and oleic acid amide, providing reference metabolomics information in clinical diagnosis and future research.

Association between Pre-Diagnostic Serum Bile Acids and Hepatocellular Carcinoma: The Singapore Chinese Health Study

Hepatocellular carcinoma (HCC) is a commonly diagnosed malignancy with poor prognosis. Rising incidence of HCC may be due to rising prevalence of metabolic dysfunction-associated fatty liver disease, where altered bile acid metabolism may be implicated in HCC development. Thirty-five bile acids were quantified using ultra-performance liquid chromatography triple-quadrupole mass spectrometry assays in pre-diagnostic serum of 100 HCC cases and 100 matched controls from the Singapore Chinese Health Study. Conditional logistic regression was used to assess associations for bile acid levels with risk of HCC. Conjugated primary bile acids were significantly elevated whereas the ratios of secondary bile acids over primary bile acids were significantly lower in HCC cases than controls. The respective odds ratios and 95% confidence intervals of HCC were 6.09 (1.75-21.21) for highest vs. lowest tertile of cholic acid species and 30.11 (5.88-154.31) for chenodeoxycholic acid species. Doubling ratio of taurine-over glycine-conjugated chenodeoxycholic acid was associated significantly with 40% increased risk of HCC whereas doubling ratio of secondary over primary bile acid species was associated with 30-40% reduced risk of HCC. In conclusion, elevated primary bile acids and taurine over glycine-conjugated ratios were strongly associated with HCC risk whereas the ratios of secondary bile acids over primary bile acids were inversely associated with HCC risk.

The role of metabolomics in hepatocellular carcinoma

Background

Hepatocellular carcinoma is the most common primary liver malignancy, with the highest incidence in the developing world, including Egypt. Hepatocellular carcinoma is usually diagnosed in the terminal stage of the disease because of the low sensitivity of the available screening tests. During the process of carcinogenesis, the cellular metabolism is altered to allow cancer cells to adapt to the hypoxic environment and therefore increase anabolic synthesis and survival and avoid the apoptotic death signals. These changes in metabolic status can be tracked by metabolomics analysis.

Main body

Metabolomics is a comprehensive approach for identifying metabolic signatures towards the screening, prediction, and earlier diagnosis of hepatocellular carcinoma with greater efficiency than the conventional diagnostic biomarker. The identification of metabolic changes associated with hepatocellular carcinoma is essential to the understanding of disease pathophysiology and enables better monitoring of high-risk individuals. However, due to the complexity of the metabolic pathways associated with hepatocellular carcinoma, the details of these perturbations are still not adequately characterized. The current status of biomarkers for hepatocellular carcinoma and their insufficiencies and metabolic pathways linked to hepatocellular carcinogenesis are briefly addressed in this mini-review. The review focused on the significantly changed metabolites and pathways associated with hepatocellular carcinoma such as phospholipids, bile acids, amino acids, reactive oxygen species metabolism, and the metabolic changes related to energy production in a cancer cell. The review briefly discusses the sensitivity of metabolomics in the prediction and prognosis of hepatocellular carcinoma and the effect of coexisting multiple etiologies of the disease.

Conclusions

Metabolomics profiling is a potentially promising tool for better predicting, diagnosis, and prognosis of hepatocellular carcinoma.

Blood-Based Targeted Metabolomics Discriminate Patients with Alcoholic Liver Cirrhosis from Those with Non-Cirrhotic Liver Damage: An Explorative Study

BACKGROUND

Early detection of liver cirrhosis is crucial for secondary prevention of complications. However, noninvasive blood-based patient monitoring tools are lacking. In this explorative study, we conducted a targeted metabolomic analysis in order to identify possible serum markers indicating alcoholic liver cirrhosis (aLiC) with or without hepatocellular carcinoma (HCC).

METHODS

Venous blood of 30 individuals was collected: healthy controls ("Con", n = 12), patients with aLiC without and with HCC ("aLiC": n = 6 and "aLiC + HCC": n = 6), and patients with other liver diseases ("oLiD": n = 6). A targeted metabolomic analysis was conducted using the AbsoluteIDQ® p180 Kit (Biocrates Life Sciences®, Innsbruck, Austria). Statistical analysis was performed by applying a one-way ANOVA on all subgroups followed by a t test for pairwise comparison of subgroups and logistic regression analysis.

RESULTS

ANOVA revealed 29 metabolites that significantly discriminate between the different cohorts. Among these analytes, 25 were significantly altered in Con versus aLiC, as indicated by t test, most importantly SM C18:1 (p < 0.001), SM C20:2 (p = 0.001), SM (OH) C22:2 (p < 0.001), lysoPC a C20:4 (p < 0.001), and PC aa C36:5 (p < 0.001). To a similar extent, the metabolites discriminated also between the oLiD and aLiC but less between the Con or oLiD and aLiC + HCC cohorts. Most of these analytes were either lyso- and phosphatidylcholines or sphingomyelins. Results were not significant for comparison of Con versus oLiD and aLiC versus aLiC + HCC.

CONCLUSION

Decreased lyso- and phosphatidylcholine as well as sphingomyelin species in venous blood could help to detect liver cirrhosis in patients with non-cirrhotic liver disease.

Efficacy of Analytical Technologies in Metabolomics Studies of the Gastrointestinal Cancers

According to the reports of the World Health Organization and the International Agency for Research on Cancer, cancer is the second leading cause of human death worldwide. However, early-stage detection of cancers can efficiently enhance the chance of therapy and saving lives. Metabolomics strategies apply a variety of approaches to discover new potential diagnoses, prognoses, and/or therapeutic biomarkers of various diseases. Metabolomics aims to identify and measure different low-molecular-weight biomolecules in physiological environments. In these studies, special metabolites are extracted from biological samples and identified using analytical techniques. Afterward, using data processing programs discovering significantly associated biomarkers is pursued. In the present review, we aimed to discuss recently reported analytical approaches on the metabolomics studies of gastrointestinal cancers including gastric, colorectal, and esophageal cancers. The gas- and liquid-chromatography with different detectors have been shown that are the main analytical techniques and for metabolites quantification, nuclear magnetic resonance has been utilized as a master method.

A novel bioinformatics approach to identify the consistently well-performing normalization strategy for current metabolomic studies

Unwanted experimental/biological variation and technical error are frequently encountered in current metabolomics, which requires the employment of normalization methods for removing undesired data fluctuations. To ensure the 'thorough' removal of unwanted variations, the collective consideration of multiple criteria ('intragroup variation', 'marker stability' and 'classification capability') was essential. However, due to the limited number of available normalization methods, it is extremely challenging to discover the appropriate one that can meet all these criteria. Herein, a novel approach was proposed to discover the normalization strategies that are consistently well performing (CWP) under all criteria. Based on various benchmarks, all normalization methods popular in current metabolomics were 'first' discovered to be non-CWP. 'Then', 21 new strategies that combined the 'sample'-based method with the 'metabolite'-based one were found to be CWP. 'Finally', a variety of currently available methods (such as cubic splines, range scaling, level scaling, EigenMS, cyclic loess and mean) were identified to be CWP when combining with other normalization. In conclusion, this study not only discovered several strategies that performed consistently well under all criteria, but also proposed a novel approach that could ensure the identification of CWP strategies for future biological problems.

MMEASE: Online meta-analysis of metabolomic data by enhanced metabolite annotation, marker selection and enrichment analysis

Large-scale and long-term metabolomic studies have attracted widespread attention in the biomedical studies yet remain challenging despite recent technique progresses. In particular, the ineffective way of experiment integration and limited capacity in metabolite annotation are known issues. Herein, we constructed an online tool MMEASE enabling the integration of multiple analytical experiments with an enhanced metabolite annotation and enrichment analysis (https://idrblab.org/mmease/). MMEASE was unique in capable of (1) integrating multiple analytical blocks; (2) providing enriched annotation for >330 thousands of metabolites; (3) conducting enrichment analysis using various categories/sub-categories. All in all, MMEASE aimed at supplying a comprehensive service for large-scale and long-term metabolomics, which might provide valuable guidance to current biomedical studies. SIGNIFICANCE: To facilitate the studies of large-scale and long-term metabolomic analysis, MMEASE was developed to (1) achieve the online integration of multiple datasets from different analytical experiments, (2) provide the most diverse strategies for marker discovery, enabling performance assessment and (3) significantly amplify metabolite annotation and subsequent enrichment analysis. MMEASE aimed at supplying a comprehensive service for long-term and large-scale metabolomics, which might provide valuable guidance to current biomedical studies.

Novel Biomarkers to Distinguish between Type 3c and Type 2 Diabetes Mellitus by Untargeted Metabolomics

Pancreatogenic diabetes mellitus (T3cDM) is a highly frequent complication of pancreatic disease, especially chronic pancreatitis, and it is often misdiagnosed as type 2 diabetes mellitus (T2DM). A correct diagnosis allows the appropriate treatment of these patients, improving their quality of life, and various technologies have been employed over recent years to search for specific biomarkers of each disease. The main aim of this metabolomic project was to find differential metabolites between T3cDM and T2DM. Reverse-phase liquid chromatography coupled to high-resolution mass spectrometry was performed in serum samples from patients with T3cDM and T2DM. Multivariate Principal Component and Partial Least Squares-Discriminant analyses were employed to evaluate between-group variations. Univariate and multivariate analyses were used to identify potential candidates and the area under the receiver-operating characteristic (ROC) curve was calculated to evaluate their diagnostic value. A panel of five differential metabolites obtained an area under the ROC curve of 0.946. In this study, we demonstrate the usefulness of untargeted metabolomics for the differential diagnosis between T3cDM and T2DM and propose a panel of five metabolites that appear altered in the comparison between patients with these diseases.

Predicting human health from biofluid-based metabolomics using machine learning

Biofluid-based metabolomics has the potential to provide highly accurate, minimally invasive diagnostics. Metabolomics studies using mass spectrometry typically reduce the high-dimensional data to only a small number of statistically significant features, that are often chemically identified—where each feature corresponds to a mass-to-charge ratio, retention time, and intensity. This practice may remove a substantial amount of predictive signal. To test the utility of the complete feature set, we train machine learning models for health state-prediction in 35 human metabolomics studies, representing 148 individual data sets. Models trained with all features outperform those using only significant features and frequently provide high predictive performance across nine health state categories, despite disparate experimental and disease contexts. Using only non-significant features it is still often possible to train models and achieve high predictive performance, suggesting useful predictive signal. This work highlights the potential for health state diagnostics using all metabolomics features with data-driven analysis.

Quantification of common and planar bile acids in tissues and cultured cells

Bile acids (BAs) have been established as ubiquitous regulatory molecules implicated in a large variety of healthy and pathological processes. However, the scope of BA heterogeneity is often underrepresented in current literature. This is due in part to inadequate detection methods, which fail to distinguish the individual constituents of the BA pool. Thus, the primary aim of this study was to develop a method that would allow the simultaneous analysis of specific C24 BA species, and to apply that method to biological systems of interest. Herein, we describe the generation and validation of an LC-MS/MS assay for quantification of numerous BAs in a variety of cell systems and relevant biofluids and tissue. These studies included the first baseline level assessment for planar BAs, including allocholic acid, in cell lines, biofluids, and tissue in a nonhuman primate (NHP) laboratory animal, Macaca mulatta, in healthy conditions. These results indicate that immortalized cell lines make poor models for the study of BA synthesis and metabolism, whereas human primary hepatocytes represent a promising alternative model system. We also characterized the BA pool of M. mulatta in detail. Our results support the use of NHP models for the study of BA metabolism and pathology in lieu of murine models. Moreover, the method developed here can be applied to the study of common and planar C24 BA species in other systems.

Sugar Alcohols Have a Key Role in Pathogenesis of Chronic Liver Disease and Hepatocellular Carcinoma in Whole Blood and Liver Tissues

The major risk factors for hepatocellular carcinoma (HCC) are hepatitis C and B viral infections that proceed to Chronic Liver Disease (CLD). Yet, the early diagnosis and treatment of HCC are challenging because the pathogenesis of HCC is not fully defined. To better understand the onset and development of HCC, untargeted GC-TOF MS metabolomics data were acquired from resected human HCC tissues and their paired non-tumor hepatic tissues (n = 46). Blood samples of the same HCC subjects (n = 23) were compared to CLD (n = 15) and healthy control (n = 15) blood samples. The participants were recruited from the National Liver Institute in Egypt. The GC-TOF MS data yielded 194 structurally annotated compounds. The most strikingly significant alteration was found for the class of sugar alcohols that were up-regulated in blood of HCC patients compared to CLD subjects (p < 2.4 × 10⁻¹²) and CLD compared to healthy controls (p = 4.1 × 10⁻⁷). In HCC tissues, sugar alcohols were the most significant (p < 1 × 10⁻⁶) class differentiating resected HCC tissues from non-malignant hepatic tissues for all HCC patients. Alteration of sugar alcohol levels in liver tissues also defined early-stage HCC from their paired non-malignant hepatic tissues (p = 2.7 × 10⁻⁶). In blood, sugar alcohols differentiated HCC from CLD subjects with an ROC-curve of 0.875 compared to 0.685 for the classic HCC biomarker alpha-fetoprotein. Blood sugar alcohol levels steadily increased from healthy controls to CLD to early stages of HCC and finally, to late-stage HCC patients. The increase in sugar alcohol levels indicates a role of aldo-keto reductases in the pathogenesis of HCC, possibly opening novel diagnostic and therapeutic options after in-depth validation.

Role of lipids in pathophysiology, diagnosis and therapy of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is an aggressive and widespread cancer. Patients with liver cirrhosis of different aetiologies are at a risk to develop HCC. It is important to know that in approximately 20% of cases primary liver tumors arise in a non-cirrhotic liver. Lipid metabolism is variable in patients with chronic liver diseases, and lipid metabolites involved therein do play a role in the development of HCC. Of note, lipid composition of carcinogenic tissues differs from non-affected liver tissues. High cholesterol and low ceramide levels in the tumors protect the cells from oxidative stress and apoptosis, and do also promote cell proliferation. So far, detailed characterization of the mechanisms by which lipids enable the development of HCC has received little attention. Evaluation of the complex roles of lipids in HCC is needed to better understand the pathophysiology of HCC, the later being of paramount importance for the development of urgently needed therapeutic interventions. Disturbed hepatic lipid homeostasis has systemic consequences and lipid species may emerge as promising biomarkers for early diagnosis of HCC. The challenge is to distinguish lipids specifically related to HCC from changes simply related to the underlying liver disease. This review article discusses aberrant lipid metabolism in patients with HCC.

Integrated Plasma and Bile Metabolomics Based on an UHPLC-Q/TOF-MS and Network Pharmacology Approach to Explore the Potential Mechanism of Schisandra chinensis-Protection From Acute Alcoholic Liver Injury

Schisandra chinensis (SC) is a well-known important traditional Chinese medicine (TCM) that has been used to treat liver disease in China for a long time. However, its overall effects and mechanism of action are unclear. The present study aimed to explore the potential mechanism of SC in protection against alcoholic liver injury (ALI). In this research, to enable a full assessment of metabolic changes in ALI in Sprague-Dawley rats and to increase our understanding of physiological changes in normal and pathological states, ultra-high performance liquid chromatography combined with quadrupole time of flight mass spectrometry (UHPLC-Q/TOF-MS) was used to probe potential biomarkers to learn more about ALI and to evaluate the overall effect of SC for ALI in rats. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate global metabolomic alterations and to evaluate the therapeutic effects of SC in rats. The component–target–pathway network of SC was then constructed on the basis of the network pharmacology, and the liver injury-relevant signaling pathways were thus dissected and validated. The results showed that SC has conspicuous therapeutic efficacy for ALI, as suggested by the results of the pathological section and biochemical index assays, such as those for Alanine aminotransferase (ALT), Aspartate transaminase (AST), Alkaline phosphatase (AKP), γ-glutamyl transferase (γ-GT/GGT), Reactive oxygen species (ROS), and Malondialdehyde (MDA). Furthermore, 21 kinds of potential biomarkers were identified in plasma samples of ALI rats, and 20 kinds of potential biomarkers were identified in their bile samples. The biomarkers were mainly related to inflammation and dysfunctions of amino acids and energy metabolism. The recovery of these dysfunctions partly led to the curative effect of SC on ALI.

Metabolic rearrangements in primary liver cancers: cause and consequences

Primary liver cancer (PLC) is the fourth most frequent cause of cancer-related death. The high mortality rates arise from late diagnosis and the limited accuracy of diagnostic and prognostic biomarkers. The liver is a major regulator, orchestrating the clearance of toxins, balancing glucose, lipid and amino acid uptake, managing whole-body metabolism and maintaining metabolic homeostasis. Tumour onset and progression is frequently accompanied by rearrangements of metabolic pathways, leading to dysregulation of metabolism. The limitation of current therapies targeting PLCs, such as hepatocellular carcinoma and cholangiocarcinoma, points towards the importance of deciphering this metabolic complexity. In this Review, we discuss the role of metabolic liver disruptions and the implications of these processes in PLCs, emphasizing their clinical relevance and value in early diagnosis and prognosis and as putative therapeutic targets. We also describe system biology approaches able to reconstruct the metabolic complexity of liver diseases. We also discuss whether metabolic rearrangements are a cause or consequence of PLCs, emphasizing the opportunity to clinically exploit the rewired metabolism. In line with this idea, we discuss circulating metabolites as promising biomarkers for PLCs.

Profiling of plasma metabolomics in patients with hepatitis C-related liver cirrhosis and hepatocellular carcinoma

Aim of the study

The diagnosis of hepatocellular carcinoma (HCC) is usually late, due to the lack of early detection of biomarkers for HCC. Metabolomics analysis has emerged as a useful tool for studying human diseases. The objective of the study was to investigate the differences in plasma metabolites between hepatitis C virus (HCV)-induced cirrhosis and HCC.

Material and methods

22 subjects with HCV-related liver cirrhosis and 22 subjects with HCC were enrolled. Clinical, routine laboratory and imaging studies were done. Gas chromatography/mass spectrometry (GC/MS) was used for metabolomics analysis of patients' plasma samples.

Results

34 known metabolites were detected, of which five metabolites were identified to have the strongest discriminatory power for separation between HCC and cirrhosis groups: octanoic acid (caprylic acid), decanoic (capric acid), oleic acid, oxalic acid and glycine. These are 3 fatty acids (FA), a dicarboxylic acid and a glucogenic amino acid, respectively. No significant correlation was found between the relative intensities of the five metabolites and any of the patient or tumor characteristics (Child-Turcotte-Pugh (CTP) score, Barcelona Clinic Liver Cancer (BCLC) stage, number of focal lesions and size of largest focal lesion). ROC curve analysis was performed and area under the curve (AUC) was calculated, revealing that oleic acid, octanoic (caprylic) acid and glycine had higher positive predictive value than α-fetoprotein.

Conclusions

The study of metabolomics (particularly involving FA) may help define distinct metabolic patterns to distinguish HCV-induced liver cirrhosis from HCC patients. Future research in this field is still needed, particularly concerning HCC treatment strategies which target fatty acid-related metabolic pathways.

Metabolomic Profiles for HBV Related Hepatocellular Carcinoma Including Alpha-Fetoproteins Positive and Negative Subtypes

Background: Hepatocellular carcinoma (HCC) is very common globally prevalent cancer. Due to its poor clinical prognosis, increasing the diagnostic rate of HCC is urgently needed. Herein, we validate discovered metabolomic biomarkers to distinguish Hepatitis B virus (HBV)-related HCC, including alpha-fetoprotein (AFP) negative (AFP–) and positive (AFP+) individuals.

Methods: We recruited 130 HCC subjects (independent case-control, randomized clinical cohorts) to our study. We separated the subjects randomly into two panels: (1) 58 individuals for the discovery panel; and (2) 72 individuals for the validation panel. For each panel, gender and age-matched hepatitis B group (HBG) and healthy group were included as controls. Plasma samples were collected for metabolic profiling by liquid chromatography—mass spectrometry—based metabolomics assays. We applied both non-targeted metabolomics analyses and targeted metabolomics analyses. Significantly changed metabolites (SCMs) were identified. The power of SCMs to discriminate HCC and HBG or healthy group was determined by receiver operating characteristic curve (ROC) analysis.

Results: Ten SCMs were selected form the discovery panel, and further verified in the validation panel. ROC analyses indicated that 1 SCMs (LysoPC (24:0)) could discriminate HCC from HBG (AUC = 0.765). Further, 8 SCMs including (LysoPC (17:0), LysoPC (20:4(8Z,11Z,14Z,17Z)), LysoPC (22:0), LysoPC (24:0), PE (P-16:0/22:4(7Z,10Z,13Z,16Z)), SM (d18:1/22:1(13Z)), Creatinine, and L-Isoleucine) displayed a heightened ability to discriminate between HCC and healthy controls (AUC were more than 0.800). Most of these SCMs were important in lipid metabolism.

Conclusions: LysoPC (24:0) could distinguished HCC from HBG, and 8 SCMs distinguished HCC from healthy controls. LysoPC and other metabolites have the potential to serve as non-invasive biomarkers for HBV related AFP– and AFP+ HCC.

Diagnosis of hepatocellular carcinoma using a novel anti-glycocholic acid monoclonal antibody-based method

Glycocholic acid (GCA) is a novel identified biomarker for hepatocellular carcinoma (HCC). However, clinical pathological study of GCA has not been extensive due to the limited availability of anti-GCA monoclonal antibodies (mAbs) and restricted detection methods. In the present study, using human GCA conjugated with bovine serum albumin as the immunogen to immunize BALB/c mice, a novel anti-GCA mAb was generated and characterized. The isotypes of heavy chain and light chain of anti-GCA mAb were examined to be IgG2a and κ, respectively, with a high affinity constant (2.6×10⁸ mol/l). The anti-GCA mAb binds GCA with high specificity and sensitivity, and the 50% inhibitory rate was 77.09 ng/ml. The present study also established a rapid, sensitive and efficient indirect competitive ELISA analysis using this anti-GCA mAb to detect the level of GCA produced by different HCC cell lines. Therefore, the present study may successfully develop a novel method for early HCC diagnosis, and also provide insights for further research and treatment of HCC.

Assessing the Effectiveness of Direct Data Merging Strategy in Long-Term and Large-Scale Pharmacometabonomics

Because of the extended period of clinic data collection and huge size of analyzed samples, the long-term and large-scale pharmacometabonomics profiling is frequently encountered in the discovery of drug/target and the guidance of personalized medicine. So far, integration of the results (ReIn) from multiple experiments in a large-scale metabolomic profiling has become a widely used strategy for enhancing the reliability and robustness of analytical results, and the strategy of direct data merging (DiMe) among experiments is also proposed to increase statistical power, reduce experimental bias, enhance reproducibility and improve overall biological understanding. However, compared with the ReIn, the DiMe has not yet been widely adopted in current metabolomics studies, due to the difficulty in removing unwanted variations and the inexistence of prior knowledges on the performance of the available merging methods. It is therefore urgently needed to clarify whether DiMe can enhance the performance of metabolic profiling or not. Herein, the performance of DiMe on 4 pairs of benchmark datasets was comprehensively assessed by multiple criteria (classification capacity, robustness and false discovery rate). As a result, integration/merging-based strategies (ReIn and DiMe) were found to perform better under all criteria than those strategies based on single experiment. Moreover, DiMe was discovered to outperform ReIn in classification capacity and robustness, while the ReIn showed superior capacity in controlling false discovery rate. In conclusion, these findings provided valuable guidance to the selection of suitable analytical strategy for current metabolomics.

[High-performance liquid chromatography-mass spectrometry-based serum metabolic profiling in patients with HBV-related hepatocellular carcinoma]

OBJECTIVE

To explore the diagnostic value of the serum metabolites identified by high-performance liquid chromatography-mass spectrometry (HPLC/MS) for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).

METHODS

A total of 126 patients admitted to Tianjin Third Central Hospital were enrolled, including 27 patients with HBV-related hepatitis with negative viral DNA (DNA-N), 24 with HBV-related hepatitis with positive viral DNA, 24 with HBV-related liver cirrhosis, 27 with HBV-related HCC undergoing surgeries or radiofrequency ablation, and 24 with HBV-related HCC receiving interventional therapy, with 25 healthy volunteers as the normal control group. Serum samples were collected from all the subjects for HPLC/MS analysis, and the data were pretreated to establish an orthogonal partial least- squares discriminant analysis (OPLS-DA) model. The differential serum metabolites were preliminarily screened by comparisons between the HBV groups and the control group, and the characteristic metabolites were identified according to the results of non-parametric test. The potential clinical values of these characteristic metabolites were evaluated using receiver operator characteristic curve (ROC) analysis.

RESULTS

A total of 25 characteristic metabolites were identified in the HBV- infected patients, including 9 lysophosphatidylcholines, 2 fatty acids, 17α-estradiol, sphinganine, 5-methylcytidine, vitamin K2, lysophosphatidic acid, glycocholic acid and 8 metabolites with few reports. The patients with HBV- related HCC showed 22 differential serum metabolites compared with the control group, 4 differential metabolites compared with patients with HBV-related liver cirrhosis; 10 differential metabolites were identified in patients with HBV-related HCC receiving interventional therapy compared with those receiving surgical resection or radiofrequency ablation. From the normal control group to HBV-related HCC treated by interventional therapy, many metabolites underwent variations following a similar pattern.

CONCLUSIONS

We identified 25 characteristic metabolites in patients with HBV-related HCC, and these metabolites may have potential clinical values in the diagnosis of HBV-related HCC. The continuous change of some of these metabolites may indicate the possibility of tumorigenesis, and some may also have indications for the choice of surgical approach.

Role of Sphingosine Kinase 1 and Sphingosine-1-Phosphate Axis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is primarily diagnosed in the latter stages of disease progression and is the third leading cause of cancer deaths worldwide. Thus, there is a need to find biomarkers of early HCC as well as the development of more effective treatments for the disease. Sphingosine-1-phosphate (S1P) is a pleiotropic lipid signaling molecule produced by two isoforms of sphingosine kinase (SphK1 and SphK2) that is involved in regulation of many aspects of mammalian physiology and pathophysiology, including inflammation, epithelial and endothelial barrier function, cancer, and metastasis, among many others. Abundant evidence indicates that SphK1 and S1P promote cancer progression and metastasis in multiple types of cancers. However, the role of SphK/S1P in HCC is less well studied. Here, we review the current state of knowledge of SphKs and S1P in HCC, including evidence for the correlation of SphK1 expression and S1P levels with progression of HCC and negative outcomes, and discuss how this information could lead to the design of more effective diagnostic and treatment modalities for HCC.

Lipids as Biomarkers of Cancer and Bacterial Infections

Lipids are ubiquitous molecules, known to play important roles in various cellular processes. Alterations to the lipidome can therefore be used as a read-out of the signs of disease, highlighting the importance to consider lipids as biomarkers in addition of nucleic acid and proteins. Lipids are among the primary structural and functional constituents of biological tissues, especially cell membranes. Along with membrane formation, lipids play also a crucial role in cell signalling, inflammation and energy storage. It was shown recently that lipid metabolism disorders play an important role in carcinogenesis and development. As well, the role of lipids in disease is particularly relevant for bacterial infections, during which several lipid bacterial virulence factors are recognized by the human innate immune response, such as lipopolysaccharide in Gram-negative bacteria, lipoteichoic acid in Gram-positive bacteria, and lipoglycans in mycobacteria. Compared to nucleic acids and proteins, a complete analysis of the lipidome, which is the comprehensive characterization of different lipid families, is usually very challenging due to the heterogeneity of lipid classes and their intrinsic physicoproperties caused by variations in the constituents of each class. Understanding the chemical diversity of lipids is therefore crucial to understanding their biological relevance and, as a consequence, their use as potential biomarkers for non-infectious and infectious diseases. This mini-review exposes the current knowledge and limitations of the use of lipids as biomarkers of the top global killers which are cancer and bacterial infections.

Discovery and Validation of Clinical Biomarkers of Cancer: A Review Combining Metabolomics and Proteomics

Early detection and diagnosis of cancer can allow timely medical intervention, which greatly improves chances of survival and enhances quality of life. Biomarkers play an important role in assisting clinicians and health care providers in cancer diagnosis and treatment follow-up. In spite of years of research and the discovery of thousands of candidate cancer biomarkers, only a few have transitioned to routine usage in the clinic. This review highlights advances in proteomics technologies that have enabled high rates of discovery of candidate cancer biomarkers and evaluates integration with other omics technologies to improve their progress through to validation and clinical translation. Furthermore, it gauges the role of metabolomics technology in cancer biomarker research and assesses it as a complementary tool in aiding cancer biomarker discovery and validation.

HST-MRM-MS: A Novel High-Sample-Throughput Multiple Reaction Monitoring Mass Spectrometric Method for Multiplex Absolute Quantitation of Hepatocellular Carcinoma Serum Biomarker

Absolute quantification of clinical biomarkers by mass spectrometry (MS) has been challenged due to low sample-throughput of current multiple reaction monitoring (MRM) methods. For this problem to be overcome, in this work, a novel high-sample-throughput multiple reaction monitoring mass spectrometric (HST-MRM-MS) quantification approach is developed to achieve simultaneous quantification of 24 samples. Briefly, triplex dimethyl reagents (L, M, and H) and eight-plex iTRAQ reagents were used to label the N- and C-termini of the Lys C-digested peptides, respectively. The triplex dimethyl labeling produces three coelute peaks in MRM traces, and the iTRAQ labeling produces eight peaks in MS2, resulting in 24 (3×8) channels in a single experiment. HST-MRM-MS has shown good accuracy ( R² > 0.98 for absolute quantification), reproducibility (RSD < 15%), and linearity (2-3 orders of magnitude). Moreover, the novel method has been successfully applied in quantifying serum biomarkers in hepatocellular carcinoma (HCC)-related serum samples. In conclusion, HST-MRM-MS is an accurate, high-sample-throughput, and broadly applicable MS-based absolute quantification method.

Sphingolipids at the Crossroads of NAFLD and Senescence

Nonalcoholic fatty liver disease (NAFLD) is a group of liver disorders encompassing simple hepatic steatosis and its more aggressive forms of nonalcoholic steatohepatitis and cirrhosis. It is a rapidly growing health concern and the major cause for the increasing incidence of primary liver tumors. Unequivocal evidence shows that sphingolipid metabolism is altered in the course of the disease and these changes might contribute to NAFLD progression. Recent data provide solid support to the notion that deregulated ceramide and sphingosine-1-phosphate metabolism are present at all stages of NAFLD, i.e., steatosis, nonalcoholic steatohepatitis, advanced fibrosis, and hepatocellular carcinoma (HCC). Insulin sensitivity, de novo lipogenesis, and the resulting lipotoxicity, fibrosis, and angiogenesis are all seemingly regulated in a manner that involves either ceramide and/or sphingosine-1-phosphate. Sphingolipids might also participate in the onset of hepatocellular senescence. The latter has been shown to contribute to the advancement of cirrhosis to HCC in the classical cases of end-stage liver disease, i.e., viral- or alcohol-induced; however, emerging evidence suggests that senescence is also involved in the pathogenicity of NAFLD possibly via changes in ceramide metabolism.

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

Hepatocellular carcinoma (HCC) is the third most common cause of death from cancer, with increasing prevalence worldwide. The mortality rate of HCC is similar to its incidence rate, which reflects its poor prognosis. At present, the diagnosis of HCC is still mostly dependent on invasive biopsy, imaging methods, and serum α-fetoprotein (AFP) testing. Because of the asymptomatic nature of early HCC, biopsy and imaging methods usually detect HCC at the middle–late stages. AFP has limited sensitivity and specificity, as many other nonmalignant liver diseases can also result in a very high serum level of AFP. Therefore, better biomarkers with higher sensitivity and specificity at earlier stages are greatly needed. Since metabolic reprogramming is an essential hallmark of cancer and the liver is the metabolic hub of living systems, it is useful to investigate HCC from a metabolic perspective. As a noninvasive and nondestructive approach, metabolomics provides holistic information on dynamically metabolic responses of living systems to both endogenous and exogenous factors. Therefore, it would be conducive to apply metabolomics in investigating HCC. In this review, we summarize recent metabolomic studies on HCC cellular, animal, and clinicopathologic models with attention to metabolomics as a biomarker in cancer diagnosis. Recent applications of metabolomics with respect to therapeutic and prognostic evaluation of HCC are also covered, with emphasis on the potential of treatment by drugs from natural products. In the last section, the current challenges and trends of future development of metabolomics on HCC are discussed. Overall, metabolomics provides us with novel insight into the diagnosis, prognosis, and therapeutic evaluation of HCC.

Metabolomics: From liver chiromancy to personalized precision medicine in advanced chronic liver disease

Currently there is a lack of accurate biomarkers for diagnosis and prognosis in advanced liver diseases. Either the occurrence of first decompensation, or diagnosis of acute on chronic liver failure, severe alcoholic hepatitis, or hepatocellular carcinoma (HCC), none of the available biomarkers are satisfactory. Metabolomics is the newest of omics, being much closer than the others to the actual phenotype and pathologic changes that characterizes a certain condition. It deals with a much wider spectrum of low molecular weight bio-compounds providing a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication and therapy. Until now metabolomics was applied in a wide spectrum of liver conditions, but the findings were contradictory. This review proposes a synthesis of the existing evidences of metabolomics use in advanced chronic liver diseases, decompensated liver cirrhosis, severe alcoholic hepatitis and HCC.