LC/MS-Based Global Metabolomic Identification of Serum Biomarkers Differentiating Hepatocellular Carcinoma from Chronic Hepatitis B and Liver Cirrhosis

Alterations in serum metabolic profiles of early-stage hepatocellular carcinoma patients after radiofrequency ablation therapy

OBJECTIVE

To investigate the alterations in serum metabolic profiles and early-stage hepatocellular carcinoma (HCC) patient characteristics after radiofrequency ablation (RFA) therapy. This evaluation aimed to assess treatment effectiveness and identify potential novel approaches and targets for HCC treatment and prognosis monitoring.

METHODS

Untargeted metabolomics technology was employed to analyze serum metabolic profiles in healthy volunteer controls (NCs) and early stage HCC patients before and after RFA therapy. Additionally, Human Metabolome Database and Kyoto Encyclopedia of Genes and Genomes database were used to identify the differential metabolites (DMs) and metabolic pathways. Cystoscape was utilized to construct DM gene networks. Amino acid analyses were performed to validate our findings.

RESULTS

We identified 11, 14, and six DMs between the NC and HCC groups, HCC patients before and after RFA therapy, and post-RFA HCC and NC groups, respectively. The expression levels of these DMs, particularly those of amino acids and lipids, significantly changed. Compared with the NC group, higher levels of L-tyrosine, aspartate, and 18-oxo-oleate were observed in HCC patients, which were significantly reduced in patients after RFA therapy. Meanwhile, HCC patients after RFA therapy had increased levels of L-arginine, phosphatidic acid (20:3), and lysophosphatidyl choline (LPC) (20:4) compared to those before therapy, while their levels before therapy were lower than those of NC. Moreover, most metabolites in the post-RFA and NC groups showed no significant changes in expression, except for L-tyrosine and LPC (16:0). These metabolites could potentially serve as characteristic factors of early-stage HCC patients after RFA therapy. Joint pathway analysis revealed striking changes, mainly in phenylalanine, tyrosine, and tryptophan biosynthesis; alanine, aspartate, and glutamate metabolism; and arginine and aminoacyl-tRNA biosynthesis. Bioinformatics analysis of publicly available data preliminarily identified 187 DM-related metabolic enzymes.

CONCLUSION

Our study proposed novel targets for early-stage HCC treatment, laying the groundwork for improving treatment efficacy and prognosis of early-stage HCC patients.

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.

Metabolomics in cirrhosis: Recent advances and opportunities

Liver cirrhosis (LC) represents a significant hepatic disorder that persistently commands the attention of the scientific community, especially concerning its pathogenesis and therapeutic approaches. Metabolomics, the comprehensive profiling of an organism's metabolome, has been increasingly applied in the research of cirrhosis over the past decade. This review summarizes the recent advancements and applications of metabolomics within the context of LC research, in recent five years. It highlights the role of metabolomics in the diagnosis of LC, the assessment of prognostic markers, and the evaluation of therapeutic outcomes. The discussion focuses on the potential and challenges of metabolomics in LC research, including the evolution of analytical technologies, advancements in bioinformatics, and the challenges impeding clinical implementation. Additionally, the review anticipates the forthcoming developments in metabolomics related to LC research, with the objective of facilitating innovative approaches for early detection and intervention in LC.

Characteristics of microbiome-derived metabolomics according to the progression of alcoholic liver disease

BACKGROUND AND AIM

The prevalence and severity of alcoholic liver disease (ALD) are increasing. The incidence of alcohol-related cirrhosis has risen up to 2.5%. This study aimed to identify novel metabolite mechanisms involved in the development of ALD in patients. The use of gut microbiome-derived metabolites is increasing in targeted therapies. Identifying metabolic compounds is challenging due to the complex patterns that have long-term effects on ALD. We investigated the specific metabolite signatures in ALD patients.

METHODS

This study included 247 patients (heathy control, HC: n = 62, alcoholic fatty liver, AFL; n = 25, alcoholic hepatitis, AH; n = 80, and alcoholic cirrhosis, AC, n = 80) identified, and stool samples were collected. 16S rRNA sequencing and metabolomics were performed with MiSeq sequencer and liquid chromatography coupled to time-of-flight-mass spectrometry (LC-TOF-MS), respectively. The untargeted metabolites in AFL, AH, and AC samples were evaluated by multivariate statistical analysis and metabolic pathotypic expression. Metabolic network classifiers were used to predict the pathway expression of the AFL, AH, and AC stages.

RESULTS

The relative abundance of Proteobacteria was increased and the abundance of Bacteroides was decreased in ALD samples (p = 0.001) compared with that in HC samples. Fusobacteria levels were higher in AH samples (p = 0.0001) than in HC samples. Untargeted metabolomics was applied to quantitatively screen 103 metabolites from each stool sample. Indole-3-propionic acid levels are significantly lower in AH and AC (vs. HC, p = 0.001). Indole-3-lactic acid (ILA: p = 0.04) levels were increased in AC samples. AC group showed an increase in indole-3-lactic acid (vs. HC, p = 0.040) level. Compared with that in HC samples, the levels of short-chain fatty acids (SCFAs: acetic acid, butyric acid, propionic acid, iso-butyric acid, and iso-valeric acid) and bile acids (lithocholic acids) were significantly decreased in AC. The pathways of linoleic acid metabolism, indole compounds, histidine metabolism, fatty acid degradation, and glutamate metabolism were closely associated with ALD metabolism.

CONCLUSIONS

This study identified that microbial metabolic dysbiosis is associated with ALD-related metabolic dysfunction. The SCFAs, bile acids, and indole compounds were depleted during ALD progression.

CLINICAL TRIAL

Clinicaltrials.gov, number NCT04339725.

MS3 Imaging Enables the Simultaneous Analysis of Phospholipid C═C and sn-Position Isomers in Tissues

Mass spectrometry (MS) imaging of lipids in tissues with high structure specificity is challenging in the effective fragmentation of position-selective structures and the sensitive detection of multiple lipid isomers. Herein, we develop an MS3 imaging method for the simultaneous analysis of phospholipid C═C and sn-position isomers by on-tissue photochemical derivatization, nanospray desorption electrospray ionization (nano-DESI), and a dual-linear ion trap MS system. A novel laser-based sensing probe is developed for the real-time adjustment of the probe-to-surface distance for nano-DESI. This method is validated in mouse brain and kidney sections, showing its capability of sensitive resolving and imaging of the fatty acyl chain composition, the sn-position, and the C═C location of phospholipids in an MS3 scan. MS3 imaging of phospholipids has shown the capability of differentiation of cancerous, fibrosis, and adjacent normal regions in liver cancer tissues.

Metabolomic analysis identifies dysregulation of lipid metabolism in the immune clearance phase of chronic hepatitis B patients

There is an accelerated progression of liver necroinflammation and fibrosis in the liver during the immune clearance (IC) phase of Chronic hepatitis B virus (HBV) infection, which are critical indicators of antiviral treatment for chronic hepatitis B (CHB) infection. This study applied serum metabolomics to identify the potential metabolite biomarkers for differential diagnosis between the CHB immune tolerance (IT) and Immune clearance (IC) phases. A liquid chromatography-mass spectrometry (LC-MS)-based approach was applied to evaluate and compared the serum metabolic profiles of 28 patients in IT phase and 33 patients in IC phase and appropriate statistical methods with MetaboAnalystR 2.0 R package to analyze those metabolites. The differential metabolites between IT and TC groups were classified and the top altered classification were lipids and lipid-like molecules and fatty acyls, clearly indicating that there were differences in the lipid metabolomic profile of HBV-infected patients with IT vs. IR phase. We identified the top 10 potential metabolite biomarkers for differential diagnosis between IT and IR. There were four lipid metabolites among them and the AUC of two of them, octadecadienoyl-sn-glycero-3-phosphocholine and 3-Cycloheptene-l-acetic acid, were 0.983 and 0.933. octadecadienoyl-sn-glycero-3-phosphocholine is Diacylglycerol (18:2n6/18:0) and 3-Cycloheptene-l-acetic acid is hydroxy fatty acids, both of which were associated with lipid metabolism. This study not only provides the potential metabolic biomarkers but also insight into the mechanism of CHB progression during IT clearance phase.

Targeting metabolic reprogramming in hepatocellular carcinoma to overcome therapeutic resistance: A comprehensive review

Hepatocellular carcinoma (HCC) poses a heavy burden on human health with high morbidity and mortality rates. Systematic therapy is crucial for advanced and mid-term HCC, but faces a significant challenge from therapeutic resistance, weakening drug effectiveness. Metabolic reprogramming has gained attention as a key contributor to therapeutic resistance. Cells change their metabolism to meet energy demands, adapt to growth needs, or resist environmental pressures. Understanding key enzyme expression patterns and metabolic pathway interactions is vital to comprehend HCC occurrence, development, and treatment resistance. Exploring metabolic enzyme reprogramming and pathways is essential to identify breakthrough points for HCC treatment. Targeting metabolic enzymes with inhibitors is key to addressing these points. Inhibitors, combined with systemic therapeutic drugs, can alleviate resistance, prolong overall survival for advanced HCC, and offer mid-term HCC patients a chance for radical resection. Advances in metabolic research methods, from genomics to metabolomics and cells to organoids, help build the HCC metabolic reprogramming network. Recent progress in biomaterials and nanotechnology impacts drug targeting and effectiveness, providing new solutions for systemic therapeutic drug resistance. This review focuses on metabolic enzyme changes, pathway interactions, enzyme inhibitors, research methods, and drug delivery targeting metabolic reprogramming, offering valuable references for metabolic approaches to HCC treatment.

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.

CYP2E1 triggered GRP78/ATF6/CHOP signaling axis inhibit apoptosis and promotes progression of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death worldwide. Cytochrome P450 2E1 (CYP2E1) is an enzyme, primarily involved in the metabolism of xenobiotics and procarcinogens. The present study was designed to investigate the potential role of CYP2E1 triggered endoplasmic reticulum stress in the progression of HCC through inhibition of apoptosis. In vitro CYP2E1 promotes HepG2 cell migration, reduced chromatin condensation, enhanced intracellular ROS accumulation and induce cell cycle progression. Conversely this effect was averted by CYP2E1 siRNA, selective inhibitor Diallyl sulphide (DAS) and antioxidants (vitamin C and E). In vivo Diethylnitrosamine (DEN) induced HCC rats showed decreased body weight and increased relative liver weight. Moreover, macro trabecular-massive HCC (MTM-HCC) histological subtyping showed pathological features like well-differentiated tumors, micro-trabecular and pseudo glandular patterns, megakaryocytes and cholestasis. Masson's trichrome staining revealed an intensive accumulation of collagen fibers in the extracellular matrix (ECM). Increased CYP2E1, VEGF and PCNA enhance the carcinogenicity as revealed in immunohistochemistry results. Immunoblot analysis showed reduced expression of copper-zinc superoxide dismutase (CuZnSOD) and manganese superoxide dismutase (MnSOD) in cytosolic as well as mitochondrial fraction of rat liver tissue respectively. Also, increased level of CYP2E1 stimulated the upregulation of unfolded proteins response (UPR) and ER stress-related proteins such as Glucose regulatory protein 78 (GRP78), activating transcription factor 6 (ATF6) and CCAAT enhancer-binding protein (C/EBP) homologous protein (CHOP). Meanwhile, CYP2E1 stimulated ER-stress reduces BCL2 and downregulates the cleaved caspase 3 thus suppresses apoptosis. in. Furthermore, immunofluorescence revealed increased expression level of α-SMA in the HCC rat liver tissue. The level of CYP2E1 mRNA was significantly increased. Altogether, these findings indicate that CYP2E1 has a dynamic role in the pathogenesis of HCC and might be a budding agent in liver carcinogenesis therapy.

Hollow multishelled heterostructures with enhanced performance for laser desorption/ionization mass spectrometry based metabolic diagnosis

High-performance metabolic diagnosis-based laser desorption/ionization mass spectrometry (LDI-MS) improves the precision diagnosis of diseases and subsequent treatment. Inorganic matrices are promising for the detection of metabolites by LDI-MS, while the structure and component impacts of the matrices on the LDI process are still under investigation. Here, we designed a multiple-shelled ZnMn2O4/(Co, Mn)(Co, Mn)2O4 (ZMO/CMO) as the matrix from calcined MOF-on-MOF for detecting metabolites in LDI-MS and clarified the synergistic impacts of multiple-shells and the heterostructure on LDI efficiency. The ZMO/CMO heterostructure allowed 3-5 fold signal enhancement compared with ZMO and CMO with the same morphology. Furthermore, the ZMO/CMO heterostructure with a triple-shelled hollow structure displayed a 3-fold signal enhancement compared to its nanoparticle counterpart. Taken together, the triple-shelled hollow ZMO/CMO exhibits 102-fold signal enhancement compared to the commercial matrix products (e.g., DHB and DHAP), allowing for sensitive metabolic profiling in bio-detection. We directly extracted metabolic patterns by the optimized triple-shelled hollow ZMO/CMO particle-assisted LDI-MS within 1 s using 100 nL of serum and used machine learning as the readout to distinguish hepatocellular carcinoma from healthy controls with the area under the curve value of 0.984. Our approach guides us in matrix design for LDI-MS metabolic analysis and drives the development of a nanomaterial-based LDI-MS platform toward precision diagnosis.

Metabolomics Approaches for the Diagnosis, Treatment, and Better Disease Management of Viral Infections

Metabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.

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.

Metabolite profiling analysis of hepatitis B virus-induced liver cirrhosis patients with minimal hepatic encephalopathy using gas chromatography-time-of-flight mass spectrometry and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry

This study used gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) and ultra-performance liquid chromatography-quadrupole TOFMS (UPLC-QTOFMS) metabonomic analytical techniques in combination with bioinformatics and pattern recognition analysis methods to analyze the serum metabolite profiling of hepatitis B virus (HBV)-induced liver cirrhosis patients with minimal hepatic encephalopathy (MHE), to find the specific biomarkers of MHE, to reveal the pathogenesis of MHE, and to determine a promising approach for early diagnosis of MHE. Serum samples of 100 normal controls (NC group), 29 HBV-induced liver cirrhosis patients with MHE (MHE group), and 24 HBV-induced liver cirrhosis patients without MHE [comprising 12 cases of compensated cirrhosis (CS group) and 12 cases of decompensated cirrhosis (DS group)] were collected and employed into GC-TOFMS and UPLC-QTOFMS platforms for serum metabolite detection; the outcome data were then analyzed using principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA). There were no significant differential metabolites between the NC group and the CS group. A series of key differential metabolites were detected. According to the variable influence in projection values and P-values, 60 small-molecule metabolites were considered to be dysregulated in the MHE group (compared to the NC group); 27 of these 60 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 4, marked in bold); 66 small-molecule metabolites were considered to be dysregulated in the DS group (compared to the NC group); 34 of these 66 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 5, marked in bold). According to the fold-change values, 9 of these 27 metabolites, namely valine, oxalic acid, erythro-sphingosine, 4,7,10,13,16,19-docosahexaenoic acid, isoleucine, allo-isoleucine, thyroxine, rac-octanoyl carnitine, and tocopherol (vitamin E), were downregulated in the MHE group (compared to the NC group); the other 18, namely adenine, glycochenodeoxycholic acid, fucose, allothreonine, glycohyocholic acid, glycoursodeoxycholic acid, tyrosine, taurocheno-deoxycholate, phenylalanine, 2-hydroxy-3-methyl-butanoic acid, hydroxyacetic acid, taurocholate, sorbitol, rhamnose, tauroursodeoxycholate, tolbutamide, pyroglutamic acid, and malic acid, were upregulated; 6 of these 34 metabolites were downregulated in the DS group (compared to the NC group), and the other 28 were upregulated, as shown in Table 5. (a) GC-TOFMS and UPLC-QTOFMS metabonomic analytical platforms can detect a range of metabolites in the serum; this might be of great help to study the pathogenesis of MHE and may provide a new approach for the early diagnosis of MHE. (b) Metabonomics analysis in combination with pattern recognition analysis might have great potential to distinguish the HBV-induced liver cirrhosis patients who have MHE from the normal healthy population and HBV-induced liver cirrhosis patients without MHE.

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.

Hepatocellular Carcinoma in 2021: An Exhaustive Update

Primary liver cancer is a challenging global health concern with an estimated more than a million persons to be affected annually by the year 2025. The commonest type is hepatocellular carcinoma (HCC), which has been increasing in incidence the world over, mostly due to chronic viral hepatitis B infection. In the last decade, paradigm changes in the etiology, understanding of molecular biology, and pathogenesis, including the role of gut microbiota; medical and surgical treatments, and outcome trends are notable. The application of omics-based technology has helped us unlock the molecular and immune landscape of HCC, through which novel targets for drug treatment such as immune-checkpoint inhibitors have been identified. Novel tools for the surveillance and diagnosis of HCC include protein-, genomics-, and composite algorithm-based clinical/biomarker panels. Magnetic resonance imaging-based novel techniques have improved HCC diagnosis through ancillary features that enhance classical criteria while positron emission tomography has shown value in prognostication. Identification of the role of gut microbiota in the causation and progression of HCC has opened areas for novel therapeutic research. A select group of patients still benefit from modified surgical and early interventional radiology treatments. Improvements in radiotherapy protocols, identification of parameters of futility among radiological interventions, and the emergence of novel first-line systemic therapies that include a combination of antiangiogenic and immune-checkpoint inhibitors have seen a paradigm change in progression-free and overall survival. The current review is aimed at providing exhaustive updates on the etiology, molecular biology, biomarker diagnosis, imaging, and recommended treatment options in patients with HCC.