Tissue and serum metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma

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

Introduction

Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy.

Methods

Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS.

Results

A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy.

Discussion

This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

UHPLC-MS-Based Metabolomics Reveal the Potential Mechanism of Armillaria mellea Acid Polysaccharide in and Its Effects on Cyclophosphamide-Induced Immunosuppressed Mice

Armillaria mellea (Vahl) P. Kumm is commonly used for food and pharmaceutical supplements due to its immune regulatory function, and polysaccharides are one of its main components. The aim of this research is to study the immunological activity of the purified acidic polysaccharide fraction, namely, AMPA, isolated from Armillaria mellea crude polysaccharide (AMP). In this study, a combination of the immune activity of mouse macrophages in vitro and serum metabonomics in vivo was used to comprehensively explore the cell viability and metabolic changes in immune-deficient mice in the AMPA intervention, with the aim of elucidating the potential mechanisms of AMPA in the treatment of immunodeficiency. The in vitro experiments revealed that, compared with LPS-induced RAW264.7, the AMPA treatment elevated the levels of the cellular immune factors IL-2, IL-6, IgM, IgA, TNF-α, and IFN-γ; promoted the expression of immune proteins; and activated the TLR4/MyD88/NF-κB signaling pathway to produce immunological responses. The protein expression was also demonstrated in the spleen of the cyclophosphamide immunosuppressive model in vivo. The UHPLC-MS-based metabolomic analysis revealed that AMPA significantly modulated six endogenous metabolites in mice, with the associated metabolic pathways of AMPA for treating immunodeficiency selected as potential therapeutic biomarkers. The results demonstrate that phosphorylated acetyl CoA, glycolysis, and the TCA cycle were mainly activated to enhance immune factor expression and provide immune protection to the body. These experimental results are important for the development and application of AMPA as a valuable health food or drug that enhances immunity.

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.

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.

The Potential of Bile Acids as Biomarkers for Metabolic Disorders

Bile acids (BAs) are well known to facilitate the absorption of dietary fat and fat-soluble molecules. These unique steroids also function by binding to the ubiquitous cell membranes and nuclear receptors. As chemical signals in gut-liver axis, the presence of metabolic disorders such as nonalcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), and even tumors have been reported to be closely related to abnormal levels of BAs in the blood and fecal metabolites of patients. Thus, the gut microbiota interacting with BAs and altering BA metabolism are critical in the pathogenesis of numerous chronic diseases. This review intends to summarize the mechanistic links between metabolic disorders and BAs in gut-liver axis, and such stage-specific BA perturbation patterns may provide clues for developing new auxiliary diagnostic means.

Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling

Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (n = 31), HC (healthy controls) group (n = 57) and non-OA group (n = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (18:0/22:6), p-cresol sulfate and so on, were identified as critical metabolites for the diagnosis of OA and HC and yielded an area under the curve (AUC) of 0.978. The other panel of unknown m/z 239.091, phosphatidylcholine (18:0/18:0) and phenylalanine were found to distinguish OA from non-OA and achieved an AUC of 0.888. These potential biomarkers are mainly involved in lipid metabolism, glucose metabolism and amino acid metabolism. It is expected to reveal new insight into OA pathogenesis from changed metabolic pathways.

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.

Circulating Metabolic Markers Related to the Diagnosis of Hepatocellular Carcinoma

Primary liver carcinoma is the sixth most common cancer worldwide, while hepatocellular carcinoma (HCC) is the most dominant cancer type. Chronic hepatitis B and C virus infections and aflatoxin exposure are the main risk factors, while nonalcoholic fatty liver disease caused by obesity, diabetes, and metabolic syndrome are the more common risk factors for HCC. Metabolic disorders caused by these high-risk factors are closely related to the tumor microenvironment of HCC, revealing a possible cause-and-effect relationship between the two. These metabolic disorders involve many complex metabolic pathways, such as carbohydrate, lipid, lipid derivative, amino acid, and amino acid derivative metabolic processes. The resulting metabolites with significant abnormal changes in the concentration level in circulating blood may be used as biomarkers to guide the diagnosis, treatment, or prognosis of HCC. At present, there are high-throughput technologies that can quickly detect small molecular metabolites in many samples. Compared to tissue biopsy, blood samples are easier to obtain, and patients’ willingness to participate is higher, which makes it possible to study blood HCC biomarkers. Over the past few years, a substantial body of research has been performed worldwide, and other potential biomarkers have been identified. Unfortunately, due to the limitations of each study, only a few markers have been widely verified and are suitable for clinical use. This review briefly summarizes the potential blood metabolic markers related to the diagnosis of HCC, mainly focusing on amino acids and their derivative metabolism, lipids and their derivative metabolism, and other possible related metabolisms.

The gut microbiota metabolite glycochenodeoxycholate activates TFR-ACSL4-mediated ferroptosis to promote the development of environmental toxin-linked MAFLD

Metabolic dysfunction-associated fatty liver disease (MAFLD) has become the most common chronic liver disorders in the world, and yet has no approved pharmacotherapy due to the etiology is complex. In the last ten years, increasing evidence have identified the environmental pollutants as risk factors for MAFLD. However, the underlying mechanism remains unclear. Our study found that bromoacetic acid (BAA, a typical kind of environmental toxin) increased triglycerides and total cholesterol levels as well as induced obvious hepatic steatosis and inflammation. The lipidomics showed that ferroptosis was implicated in the environmental toxin-linked MAFLD. Besides, the analysis of microbial metabolomics showed significant change of gut microbiome in BAA groups and the content of gut microbiota metabolite (glycochenodeoxycholate, GCDCA) increased sharply. In vitro study, we observed features of ferroptotic cells by transmission electron microscopy after BAA/GCDCA treatment. Besides, we demonstrated that BAA/GCDCA significantly increased iron contents, with upregulating transferrin receptor (TFR) and acyl-CoA synthetase long-chain family 4 (ACSL4) expression levels. By contrast, iron chelator or silencing TFR relieved BAA/GCDCA-induced lipid metabolism disorder and inflammation. What's more, the interaction between TFR and ACSL4 was also identified. Taken together, we found that, in response to environmental toxin, gut microbiota metabolite GCDCA activates TFR-ACSL4-mediated ferroptosis, which triggered subsequent lipid metabolism disorder and inflammation. Moreover, these findings firstly highlighted the functional relevance among ferroptosis, lipid metabolism and gut microbiota metabolite during environmental pollutant exposure, which shed light on the deep mechanism of environmental toxin-related MAFLD, providing potential targets for the prevention of MAFLD.

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.

A Serum Metabolite Classifier for the Early Detection of Type 2 Diabetes Mellitus-Positive Hepatocellular Cancer

Type 2 diabetes mellitus (T2DM) has been identified as an independent risk factor for hepatocellular cancer (HCC). However, there are no ideal biomarkers for the surveillance and early detection of HCC in the T2DM population at present. In this study, we aimed to explore novel metabolite biomarkers for T2DM-positive [T2DM(+)] HCC by metabolomic analysis. At first, many serum metabolites were found dysregulated in T2DM(+) HCC patients in untargeted metabolomic analyses. Targeted metabolite analyses confirmed that serum benzoic acid and citrulline were increased, and creatine was decreased in T2DM(+) HCC compared to the T2DM group. A metabolite classifier including benzoic acid, creatine, and citrulline was identified as a novel biomarker for the diagnosis of T2DM(+) HCC, with an area under the ROC curve (AUC) of 0.93 for discriminating T2DM(+) HCC patients from T2DM patients. In addition, the metabolite classifier detected small-size (AUC = 0.94), early-stage (AUC = 0.94), and AFP-negative (AUC = 0.96) tumors with high sensitivity and specificity. The combination of this metabolite classifier and AFP might be useful in the surveillance and early detection of HCC in the T2DM population. In conclusion, this study establishes a novel diagnostic tool for T2DM(+) HCC.

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.

Predictive value of serum bile acids as metabolite biomarkers for liver cirrhosis: a systematic review and meta-analysis

INTRODUCTION

A large number of studies have explored the potential biomarkers for detecting liver cirrhosis in an early stage, yet consistent conclusions are still warranted.

OBJECTIVES

To conduct a review and a meta-analysis of the existing studies that test the serum level of bile acids in cirrhosis as the potential biomarkers to predict cirrhosis.

METHODS

Six databases had been searched from inception date to April 12, 2021. Screening and selection of the records were based on the inclusion criteria. The risk of bias was assessed with the Newcastle-Ottawa quality assessment scale (NOS). Mean difference (MD) and confidence intervals 95% (95% CI) were calculated by using the random effect model for the concentrations of bile acids in the meta-analysis, and I² statistic was used to measure studies heterogeneity. This study was registered on PROSPERO.

RESULTS

A total of 1583 records were identified and 31 studies with 2679 participants (1263 in the cirrhosis group, 1416 in the healthy control group) were included. The quality of included studies was generally high, with 25 studies (80.6%) rated over 7 stars. A total of 45 bile acids or their ratios in included studies were extracted. 36 increased in the cirrhosis group compared with those of the healthy controls by a qualitative summary, 5 decreased and 4 presented with mixing results. The result of meta-analysis among 12 studies showed that 13 bile acids increased, among which four primary conjugated bile acids showed the most significant elevation in the cirrhosis group: GCDCA (MD = 11.38 μmol/L, 95% CI 8.21-14.55, P < 0.0001), GCA (MD = 5.72 μmol/L, 95% CI 3.47-7.97, P < 0.0001), TCDCA (MD = 3.57 μmol/L, 95% CI 2.64-4.49, P < 0.0001) and TCA (MD = 2.14 μmol/L, 95% CI 1.56-2.72, P < 0.0001). No significant differences were found between the two groups in terms of DCA (MD = - 0.1 μmol/L, 95% CI - 0.18 to - 0.01, P < 0.0001) and LCA (MD = - 0.01 μmol/L, 95% CI - 0.01 to - 0.02, P < 0.0001), UDCA (MD = - 0.14 μmol/L, 95% CI - 0.04 to - 0.32, P < 0.0001), and TLCA (MD = 0 μmol/L, 95% CI 0-0.01, P < 0.0001). Subgroup analysis in patients with hepatitis B cirrhosis showed similar results.

CONCLUSION

Altered serum bile acids profile seems to be associated with cirrhosis. Some specific bile acids (GCA, GCDCA, TCA, and TCDCA) may increase with the development of cirrhosis, which possibly underlay their potential role as predictive biomarkers for cirrhosis. Yet this predictive value still needs further investigation and validation in larger prospective cohort studies.

Chenodeoxycholic Acid Enhances the Effect of Sorafenib in Inhibiting HepG2 Cell Growth Through EGFR/Stat3 Pathway

Background

Hepatocellular carcinoma (HCC) is a highly invasive disease with a high mortality rate. Our previous study found that Chenodeoxycholic acid (CDCA) as an endogenous metabolite can enhance the anti-tumor effect. Sorafenib has limited overall efficacy as a first-line agent in HCC, and combined with CDCA may improve its efficacy.

Methods

HepG2 cells and Balb/c nude mice were used respectively for in vitro and in vivo experiments. Flow cytometry, Western blotting, HE and immunohistochemical staining and immunofluorescence were used to study the effects of CDCA combined with sorafenib on HepG2 cell growth and apoptosis-related proteins. Magnetic bead coupling, protein profiling and magnetic bead immunoprecipitation were used to find the targets of CDCA action. The effect of CDCA on EGFR/Stat3 signaling pathway was further verified by knocking down Stat3 and EGFR. Finally, fluorescence confocal, and molecular docking were used to study the binding site of CDCA to EGFR.

Results

In this study, we found that CDCA enhanced the effect of sorafenib in inhibiting the proliferation, migration and invasion of HepG2 cells. Magnetic bead immunoprecipitation and protein profiling revealed that CDCA may enhance the effect of sorafenib by affecting the EGFR/Stat3 signaling pathway. Further results from in vitro and in vivo gene knockdown experiments, confocal experiments and molecular docking showed that CDCA enhances the efficacy of sorafenib by binding to the extracellular structural domain of EGFR.

Conclusion

This study reveals the mechanism that CDCA enhances the inhibitory effect of sorafenib on HepG2 cell growth in vitro and in vivo, providing a potential new combination strategy for the treatment of HCC.

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.

Knockout of Putative Tumor Suppressor Aldh1l1 in Mice Reprograms Metabolism to Accelerate Growth of Tumors in a Diethylnitrosamine (DEN) Model of Liver Carcinogenesis

Simple Summary

Cancers often loose the enzyme of folate metabolism ALDH1L1. We proposed that such loss is advantageous for the malignant tumor growth and tested this hypothesis in mice proficient or deficient (gene knockout) in ALDH1L1 expression. Liver cancer in both groups was induced by injection of chemical carcinogen diethylnitrosamine. While the number of tumors observed in ALDH1L1 proficient and deficient mice was similar, tumors grew faster and to a larger size in the knockout mice. We conclude that the ALDH1L1 loss promotes liver tumor growth without affecting tumor initiation or multiplicity. Accelerated growth of tumors lacking the enzyme was linked to several metabolic pathways, which are beneficial for rapid proliferation.

Abstract

Cytosolic 10-formyltetrahydrofolate dehydrogenase (ALDH1L1) is commonly downregulated in human cancers through promoter methylation. We proposed that ALDH1L1 loss promotes malignant tumor growth. Here, we investigated the effect of the Aldh1l1 mouse knockout (Aldh1l1^−/−) on hepatocellular carcinoma using a chemical carcinogenesis model. Fifteen-day-old male Aldh1l1 knockout mice and their wild-type littermate controls (Aldh1l1^+/+) were injected intraperitoneally with 20 μg/g body weight of DEN (diethylnitrosamine). Mice were sacrificed 10, 20, 28, and 36 weeks post-DEN injection, and livers were examined for tumor multiplicity and size. We observed that while tumor multiplicity did not differ between Aldh1l1^−/− and Aldh1l1^+/+ animals, larger tumors grew in Aldh1l1^−/− compared to Aldh1l1^+/+ mice at 28 and 36 weeks. Profound differences between Aldh1l1^−/− and Aldh1l1^+/+ mice in the expression of inflammation-related genes were seen at 10 and 20 weeks. Of note, large tumors from wild-type mice showed a strong decrease of ALDH1L1 protein at 36 weeks. Metabolomic analysis of liver tissues at 20 weeks showed stronger differences in Aldh1l1^+/+ versus Aldh1l1^−/− metabotypes than at 10 weeks, which underscores metabolic pathways that respond to DEN in an ALDH1L1-dependent manner. Our study indicates that Aldh1l1 knockout promoted liver tumor growth without affecting tumor initiation or multiplicity.

Clinical Aspects of Gut Microbiota in Hepatocellular Carcinoma Management

Liver cancer, predominantly hepatocellular carcinoma (HCC), is the third leading cause of cancer-related deaths worldwide. Emerging data highlight the importance of gut homeostasis in the pathogenesis of HCC. Clinical and translational studies revealed the patterns of dysbiosis in HCC patients and their potential role for HCC diagnosis. Research on underlying mechanisms of dysbiosis in HCC development pointed out the direction for improving the treatment and prevention. Despite missing clinical studies, animal models showed that modulation of the gut microbiota by probiotics may become a new way to treat or prevent HCC development.

Enhanced performance of a surface plasmon resonance-based immunosensor for the detection of glycocholic acid

The concentration of glycocholic acid (GCA) in urine and blood is an important biomarker for liver cancer. Monitoring of GCA depends to a large extent on the availability of appropriate analytical techniques. In this work, based on the immobilization of GCA-OVA onto the sensor chip surface, a label-free competitive inhibition immunoassay for the determination of GCA with the surface plasmon resonance (SPR) technique was developed. The proposed SPR immunosensor is simple to prepare, recyclable and exhibits excellent sensitivity to GCA (a linear range of 13.3-119.4 ng mL^-1 and a limit of detection (LOD) of 2.5 ng mL^-1), which was 14 times lower than that of the traditional immunoassay. Excellent recoveries and correlation between these two methods were observed (R² = 0.995). Hence, it can be proved that the SPR immunosensor could be used to achieve rapid and sensitive quantitative detection of GCA in real urine samples and meet clinical needs.

Identification of Key Genes in Purine Metabolism as Prognostic Biomarker for Hepatocellular Carcinoma

Background

Deregulated purine metabolism is critical for fast-growing tumor cells by providing nucleotide building blocks and cofactors. Importantly, purine antimetabolites belong to the earliest developed anticancer drugs and are still prescribed in clinics today. However, these antimetabolites can inhibit non-tumor cells and cause undesired side effects. As liver has the highest concentration of purines, it makes liver cancer a good model to study important nodes of dysregulated purine metabolism for better patient selection and precisive cancer treatment.

Methods

By using a training dataset from TCGA, we investigated the differentially expressed genes (DEG) of purine metabolism pathway (hsa00230) in hepatocellular carcinoma (HCC) and determined their clinical correlations to patient survival. A prognosis model was established by Lasso-penalized Cox regression analysis, and then validated through multiple examinations including Cox regression analysis, stratified analysis, and nomogram using another ICGC test dataset. We next treated HCC cells using chemical drugs of the key enzymes in vitro to determine targetable candidates in HCC.

Results

The DEG analysis found 43 up-regulated and 2 down-regulated genes in the purine metabolism pathway. Among them, 10 were markedly associated with HCC patient survival. A prognostic correlation model including five genes (PPAT, DCK, ATIC, IMPDH1, RRM2) was established and then validated using the ICGC test dataset. Multivariate Cox regression analysis found that both prognostic risk model (HR = 4.703 or 3.977) and TNM stage (HR = 2.303 or 2.957) independently predicted HCC patient survival in the two datasets respectively. The up-regulations of the five genes were further validated by comparing between 10 pairs of HCC tissues and neighboring non-tumor tissues. In vitro cellular experiments further confirmed that inhibition of IMPDH1 significantly repressed HCC cell proliferation.

Conclusion

In summary, this study suggests that purine metabolism is deregulated in HCC. The prognostic gene correlation model based on the five purine metabolic genes may be useful in predicting HCC prognosis and patient selection. Moreover, the deregulated genes are targetable by specific inhibitors.

Metabolic Profiling Identified a Novel Biomarker Panel for Metabolic Syndrome-Positive Hepatocellular Cancer

Metabolic syndrome (MetS) is an independent risk factor for hepatocellular cancer (HCC). Currently, there is no highly sensitive and specific biomarkers for HCC surveillance in MetS population. Metabolomics has been reported as a powerful technology for biomarker discovery. In the present study, we aimed to explore novel biomarkers with high sensitivity and specificity for MetS-positive [MetS(+)] HCC by metabolomic analysis. At first, many serum metabolites were found dysregulated in MetS(+) HCC individuals. Validation of the dysregulated metabolites by targeted metabolite analyses revealed that serum L-glutamic acid (L-glu), pipecolic acid (PA) and 7-methylguanine (7-mG) were increased in MetS(+) HCC compared to MetS group. Then a biomarker panel including L-glu, PA and alpha-fetoprotein (AFP) was identified as a novel biomarker for the diagnosis of MetS(+) HCC. Receiver operating characteristic (ROC) curve was drawn and the area under the ROC curve (AUC) was 0.87 for discriminating MetS(+) HCC from MetS group. The biomarker panel was capable of detecting small (AUC = 0.82) and early-stage (AUC = 0.78) tumors as well. Moreover, it exhibited great diagnostic performance (AUC = 0.93) for discriminating MetS(+) HCC from other MetS-associated cancers, including colorectal cancer and gastric cancer. Collectively, our study establishes a novel diagnostic tool for MetS(+) HCC.

Targeting the alternative bile acid synthetic pathway for metabolic diseases

The gut microbiota is profoundly involved in glucose and lipid metabolism, in part by regulating bile acid (BA) metabolism and affecting multiple BA-receptor signaling pathways. BAs are synthesized in the liver by multi-step reactions catalyzed via two distinct routes, the classical pathway (producing the 12α-hydroxylated primary BA, cholic acid), and the alternative pathway (producing the non-12α-hydroxylated primary BA, chenodeoxycholic acid). BA synthesis and excretion is a major pathway of cholesterol and lipid catabolism, and thus, is implicated in a variety of metabolic diseases including obesity, insulin resistance, and nonalcoholic fatty liver disease. Additionally, both oxysterols and BAs function as signaling molecules that activate multiple nuclear and membrane receptor-mediated signaling pathways in various tissues, regulating glucose, lipid homeostasis, inflammation, and energy expenditure. Modulating BA synthesis and composition to regulate BA signaling is an interesting and novel direction for developing therapies for metabolic disease. In this review, we summarize the most recent findings on the role of BA synthetic pathways, with a focus on the role of the alternative pathway, which has been under-investigated, in treating hyperglycemia and fatty liver disease. We also discuss future perspectives to develop promising pharmacological strategies targeting the alternative BA synthetic pathway for the treatment of metabolic diseases.

Comprehensive Dipeptide Analysis Revealed Cancer-Specific Profile in the Liver of Patients with Hepatocellular Carcinoma and Hepatitis

As the physical properties and functionality of dipeptides differ from those of amino acids, they have attracted attention in metabolomics; however, their functions in vivo have not been clarified in detail. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and its major cause is chronic hepatitis. This study was conducted to explore tumor-specific dipeptide characteristics by performing comprehensive dipeptide analysis in the tumor and surrounding nontumor tissue of patients with HCC. Dipeptides were analyzed by liquid chromatography tandem mass spectrometry and capillary electrophoresis tandem mass spectrometry. Principal component analysis using 236 detected dipeptides showed differences in the dipeptide profiles between nontumor and tumor tissues; however, no clear difference was observed in etiological comparison. In addition, the N- and C-terminal amino acid compositions of the detected dipeptides significantly differed, suggesting the substrate specificity of enzyme proteins, such as peptidase. Furthermore, hepatitis-derived HCC may show a characteristic dipeptide profile even before tumor formation. These results provide insight into HCC pathogenesis and may help identify novel biomarkers for diagnosis.

Plasma metabolomic profiles in liver cancer patients following stereotactic body radiotherapy

Background

Stereotactic body radiotherapy (SBRT) is an effective treatment for hepatocellular carcinoma (HCC). This study sought to identify differentially expressed plasma metabolites in HCC patients at baseline and early during SBRT, and to explore if changes in these metabolites early during SBRT may serve as biomarkers for radiation-induced liver injury and/or tumour response.

Methods

Forty-seven HCC patients were treated with SBRT on previously published prospective trials. Plasma samples were collected at baseline and after one to two fractions of SBRT, and analysed by GC/MS and LC/MS for untargeted and targeted metabolomics profiling, respectively.

Findings

Sixty-nine metabolites at baseline and 62 metabolites after one to two fractions of SBRT were differentially expressed, and strongly separated the Child Pugh (CP) B from the CP A HCC patients. These metabolites are associated with oxidative stress and alterations in hepatic cellular metabolism. Differential upregulation of serine, alanine, taurine, and lipid metabolites early during SBRT from baseline was noted in the HCC patients who demonstrated the greatest increase in CP scores at three months post SBRT, suggesting that high protein and lipid turnover early during SBRT may portend increased clinical liver toxicity. Twenty annotated metabolites including fatty acids, glycerophospholipids, and acylcarnitines were differentially upregulated early during SBRT from baseline and separated patients with complete/partial response from those with stable disease at three months post SBRT.

Interpretation

Dysregulation of amino acid and lipid metabolism detected early during SBRT are associated with subsequent clinical liver injury and tumour response in HCC.

UPLC-MS-based serum metabolomics reveals protective effect of Ganoderma lucidum polysaccharide on ionizing radiation injury

ETHNOPHARMACOLOGICAL RELEVANCE

Ganoderma lucidum Polysaccharide (GLP),traditional Chinese medicine (TCM) active ingredient, has a long history and has good curative effects on radiation injury. However, the mechanism of GLP treating radiation injury has not been clearly elucidated.

THE AIM OF THE STUDY

This study was aimed to investigate the preventive effects of GLP on mice with radiation injury and to explore its mechanisms by serum metabolomics.

MATERIALS AND METHODS

Thirty mice were randomly divided into three groups,and namely 10 per group. The normal control group and the radiation model with normal saline and GLP group with GLP treatment (96 mg·kg-1) for 14 days. 2 h after 7th day after the intragastric administration, the model group and GLP group were subjected to whole body irradiation by X-rays except the normal control group. The peripheral blood WBC, RBC, HGB, PLT indicators.UPLC-Q-TOF-MS technique was used to analyze the serum of normal group, model group and GLP group, and to explore its potential key biomarkers and corresponding related metabolic pathways.

RESULTS

The number of peripheral blood leukocytes (WBC) in the radiation model group was lower than that in the GLP group and the number of platelets (PLT) in the GLP group was significantly higher than that in the model group.Combined with the methods of principal component analysis (PCA), projection to latent structure-discrimination analysis (PLS-DA), three group were clearly distinguished from each other and 18 metabolites were identified as the potential biomarkers in the GLP treated mice. The identified biomarkers indicated that there were perturbations of the taurine and hypotaurine metabolism and glycerophospholipid metabolism.

CONCLUSION

GLP can play a role in radiation protection by improving the expression of related potential biomarkers and related metabolic pathways in serum of radiation-induced mice.

Development and validation of bile acid profile-based scoring system for identification of biliary atresia: a prospective study

BACKGROUND

Early distinguishing biliary atresia from other causes of infantile cholestasis remains a major challenge. We aimed to develop and validate a scoring system based on bile acid for identification of biliary atresia.

METHODS

In a prospective study, a total of 141 infants with cholestasis were enrolled in two sets (derivation cohort, n = 66; validation cohort, n = 75) from 2014 to 2018. Variables with significant difference between biliary atresia and non-biliary atresia infants were selected in the derivation cohort. Then, a scoring system including those variables was designed and validated.

RESULTS

Among 66 patients in the derivation cohort, 34 (51.5%) had biliary atresia. A scoring system was proposed with the following variables: glycochenodeoxycholic acid/chenodeoxycholic acid, clay stool, and gamma-glutamyl transferase. The total score ranged from 0 to 41, and a cutoff value of 15 identified biliary atresia with an area under receiver operating characteristic curve of 0.87 (95% confidence interval, 0.77-0.94), sensitivity of 85.3%, and specificity of 81.3% in the derivation cohort; these values were also confirmed in a validation cohort with a sensitivity of 90.0% and specificity of 80.0%.

CONCLUSIONS

The proposed simple scoring system had good diagnostic accuracy for estimating the risk of biliary atresia in infants with cholestasis.

Zhibaidihuang Decoction Ameliorates Cell Oxidative Stress by Regulating the Keap1-Nrf2-ARE Signalling Pathway

Zhibaidihuang decoction (ZBDHD) is a Chinese herbal formula, which is used in Chinese traditional medicine to treat symptoms of Yinxuhuowang (Yin deficiency and high fire) syndrome. This study elucidates the mechanism of ZBDHD on oral ulcers, one Yinxuhuowang syndrome. Simultaneously, some ingredients in ZBDHD were found and identified by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A Ganjiangfuzirougui decoction- (GJD-) induced Yinxuhuowang syndrome SD rat model was used to demonstrate the efficiency of ZBDHD treatment. The oral mucosa of rat in the GJD group, stained with hematoxylin and eosin (H&E), showed epidermal shedding and inflammatory cell infiltration. And an alleviation efficiency of ZBDHD in GJD-induced pathological changes in the oral mucosa could be obtained. ZBDHD treatment restored the GJD-induced imbalance of metabolites, which were choline, glycocholic acid, and palmitoyl-L-carnitine (PALC). GJD stimulated the expression of NF-κB. And the overexpressed of NF-κB in mucosa of rat in the GJD group could be inhibited by ZBDHD treatment. Simultaneously, the optimal efficiency of ZBDHD treatment on the cellular ATP content, oxygen consumption rate (OCR), and superoxide dismutase (SOD) concentration was evaluated, in vitro assay. Compared to the control cells, the ATP content, OCR, and SOD activity in the ZBDHD-treated cells were significantly higher. For the mechanisms study, seven cytokines were screened with a Dual-Luciferase Reporter gene assay. In the ARE assay, the luciferase signal was stimulated significantly by ZBDHD. In cells, the transcription of nrf2, maf, and keap1, which were related to the ARE pathway, was elevated by ZBDHD treatment. Our study demonstrated that high-dose GJD could lead to Yinxuhuowang syndrome, such as oral ulcers, and the imbalance in serum metabolites. And ZBDHD can improve oral cell inflammation and the imbalance of metabolism by inhibiting NF-κB and enhancing the activity of the ARE signalling pathway to ameliorate oxidative stress in the cell. This study provides a theoretical basis for the clinical application of ZBDHD.

Mass Spectrometry-Based Non-targeted Metabolic Profiling for Disease Detection: Recent Developments

Mass spectrometry (MS) plays an important role in seeking biomarkers for disease detection. High-quality quantitative data is needed for accurate analysis of metabolic perturbations in patients. This article describes recent developments in MS-based non-targeted metabolomics research with applications to the detection of several major common human diseases, focusing on study cohorts, MS platforms utilized, statistical analyses and discriminant metabolite identification. Potential disease biomarkers recently discovered for type 2 diabetes, cardiovascular disease, hepatocellular carcinoma, breast cancer and prostate cancer through metabolomics are summarized, and limitations are discussed.

Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) causes more than half a million annual deaths worldwide. Understanding the mechanisms contributing to HCC development is highly desirable for improved surveillance, diagnosis, and treatment. Liver tissue metabolomics has the potential to reflect the physiological changes behind HCC development. Also, it allows identification of biomarker candidates for future evaluation in biofluids and investigation of racial disparities in HCC. Tumor and nontumor tissues from 40 patients were analyzed by both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) platforms to increase the metabolome coverage. The levels of the metabolites extracted from solid liver tissue of the HCC area and adjacent non-HCC area were compared. Among the analytes detected by GC-MS and LC-MS with significant alterations, 18 were selected based on biological relevance and confirmed metabolite identification. These metabolites belong to TCA cycle, glycolysis, purines, and lipid metabolism and have been previously reported in liver metabolomic studies where high correlation with HCC progression is implied. We demonstrated that metabolites related to HCC pathogenesis can be identified through liver tissue metabolomic analysis. Additionally, this study has enabled us to identify race-specific metabolites associated with 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.