Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review. Br J Cancer. 2015;112:1141-1156. [PMID: 25826224 PMCID: PMC4385954 DOI: 10.1038/bjc.2015.38]

Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.

The Current Status of the Liver Liquid Biopsy in MASH Related HCC: Overview and Future Directions

Metabolic dysfunction-associated steatohepatitis (MASH) is one of the major risk factors for chronic liver disease and hepatocellular carcinoma (HCC). The incidence of MASH in Western countries continues to rise, driving HCC as the third cause of cancer-related death worldwide. HCC has become a major global health challenge, partly from the obesity epidemic promoting metabolic cellular disturbances but also from the paucity of biomarkers for its early detection. Over 50% of HCC cases are clinically present at a late stage, where curative measures are no longer beneficial. Currently, there is a paucity of both specific and sensitive biological markers for the early-stage detection of HCC. The search for biological markers in the diagnosis of early HCC in high-risk populations is intense. We described the potential role of surrogates for a liver biopsy in the screening and monitoring of patients at risk for nesting HCC.

Sugar-Sweetened and Artificially Sweetened Beverages and Risk of Liver Cancer and Chronic Liver Disease Mortality

Importance

Approximately 65% of adults in the US consume sugar-sweetened beverages daily.

Objective

To study the associations between intake of sugar-sweetened beverages, artificially sweetened beverages, and incidence of liver cancer and chronic liver disease mortality.

Design, Setting, and Participants

A prospective cohort with 98 786 postmenopausal women aged 50 to 79 years enrolled in the Women's Health Initiative from 1993 to 1998 at 40 clinical centers in the US and were followed up to March 1, 2020.

Exposures

Sugar-sweetened beverage intake was assessed based on a food frequency questionnaire administered at baseline and defined as the sum of regular soft drinks and fruit drinks (not including fruit juice); artificially sweetened beverage intake was measured at 3-year follow-up.

Main Outcomes and Measures

The primary outcomes were (1) liver cancer incidence, and (2) mortality due to chronic liver disease, defined as death from nonalcoholic fatty liver disease, liver fibrosis, cirrhosis, alcoholic liver diseases, and chronic hepatitis. Cox proportional hazards regression models were used to estimate multivariable hazard ratios (HRs) and 95% CIs for liver cancer incidence and for chronic liver disease mortality, adjusting for potential confounders including demographics and lifestyle factors.

Results

During a median follow-up of 20.9 years, 207 women developed liver cancer and 148 died from chronic liver disease. At baseline, 6.8% of women consumed 1 or more sugar-sweetened beverage servings per day, and 13.1% consumed 1 or more artificially sweetened beverage servings per day at 3-year follow-up. Compared with intake of 3 or fewer servings of sugar-sweetened beverages per month, those who consumed 1 or more servings per day had a significantly higher risk of liver cancer (18.0 vs 10.3 per 100 000 person-years [P value for trend = .02]; adjusted HR, 1.85 [95% CI, 1.16-2.96]; P = .01) and chronic liver disease mortality (17.7 vs 7.1 per 100 000 person-years [P value for trend <.001]; adjusted HR, 1.68 [95% CI, 1.03-2.75]; P = .04). Compared with intake of 3 or fewer artificially sweetened beverages per month, individuals who consumed 1 or more artificially sweetened beverages per day did not have significantly increased incidence of liver cancer (11.8 vs 10.2 per 100 000 person-years [P value for trend = .70]; adjusted HR, 1.17 [95% CI, 0.70-1.94]; P = .55) or chronic liver disease mortality (7.1 vs 5.3 per 100 000 person-years [P value for trend = .32]; adjusted HR, 0.95 [95% CI, 0.49-1.84]; P = .88).

Conclusions and Relevance

In postmenopausal women, compared with consuming 3 or fewer servings of sugar-sweetened beverages per month, those who consumed 1 or more sugar-sweetened beverages per day had a higher incidence of liver cancer and death from chronic liver disease. Future studies should confirm these findings and identify the biological pathways of these associations.

Revisiting artificial intelligence diagnosis of hepatocellular carcinoma with DIKWH framework

Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high morbidity and fatality rate. Traditional diagnostic methods for HCC are primarily based on clinical presentation, imaging features, and histopathology. With the rapid development of artificial intelligence (AI), which is increasingly used in the diagnosis, treatment, and prognosis prediction of HCC, an automated approach to HCC status classification is promising. AI integrates labeled clinical data, trains on new data of the same type, and performs interpretation tasks. Several studies have shown that AI techniques can help clinicians and radiologists be more efficient and reduce the misdiagnosis rate. However, the coverage of AI technologies leads to difficulty in which the type of AI technology is preferred to choose for a given problem and situation. Solving this concern, it can significantly reduce the time required to determine the required healthcare approach and provide more precise and personalized solutions for different problems. In our review of research work, we summarize existing research works, compare and classify the main results of these according to the specified data, information, knowledge, wisdom (DIKW) framework.

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.

Essential amino acids as diagnostic biomarkers of hepatocellular carcinoma based on metabolic analysis

Metabolomics, defined as the comprehensive identification of all small metabolites in a biological sample, has the power to shed light on phenotypic changes associated with various diseases, including cancer. To discover potential metabolomic biomarkers of hepatocellular carcinoma (HCC), we investigated the metabolomes of tumor and non-tumor tissue in 20 patients with primary HCC using capillary electrophoresis-time-of-flight mass spectrometry. We also analyzed blood samples taken immediately before and 14 days after hepatectomy to identify associated changes in the serum metabolome. Marked changes were detected in the different quantity of 61 metabolites that could discriminate between HCC tumor and paired non-tumor tissue and additionally between HCC primary tumors and colorectal liver metastases. Among the 30 metabolites significantly upregulated in HCC tumors compared with non-tumor tissues, 10 were amino acids, and 7 were essential amino acids (leucine, valine, tryptophan, isoleucine, methionine, lysine, and phenylalanine). Similarly, the serum metabolomes of HCC patients before hepatectomy revealed a significant increase in 16 metabolites, including leucine, valine, and tryptophan. Our results reveal striking differences in the metabolomes of HCC tumor tissue compared with non-tumor tissue, and identify the essential amino acids leucine, valine, and tryptophan as potential metabolic biomarkers for HCC.

Colorimetric biosensor for visual determination of Golgi protein 73 based on reduced graphene oxide-carboxymethyl chitosan-Hemin/platinum@palladium nanozyme with peroxidase-like activity

A Golgi protein 73 (GP73) colorimetric biosensor based on the reduced graphene oxide-carboxymethyl chitosan-hemin/platinum@palladium nanoparticles (RGO-CMCS-Hemin/Pt@Pd NPs) with peroxidase-like activity was constructed. The RGO-CMCS-Hemin/Pt@Pd NPs with high peroxidase-like activity were successfully synthesized under mild conditions. Then, the aminylated GP73 aptamer (Apt) was bound to the RGO-CMCS-Hemin/Pt@Pd NPs to form the recognition probe. Another unmodified GP73 aptamer (AptI) was served as the capture probe. In the presence of target GP73, the capture probe and the recognition probe specifically bind to GP73 and form a RGO-CMCS-Hemin/Pt@Pd NP-Apt/GP73/AptI sandwich-type structure, which can oxidase the colorless 3,3',5,5'-tetramethylbenzidine (TMB) into blue oxTMB in the presence of H₂O₂. GP73 detection was achieved by measuring the peak UV absorption at 652 nm. Under the optimum conditions, the GP73 concentration was linearly related to the absorbance intensity in the range 10.0-110.0 ng/mL, and the limit of detection (LOD) was 4.7 ng/mL. The proposed colorimetric biosensor was successfully applied to detect GP73 in spiked human serum samples with recoveries of 98.2-107.0% and RSDs of 1.90-5.44%, demonstrating the excellent potential for highly sensitive GP73 detection in clinical detection. A colorimetric biosensor for visual determination of GP73 based on RGO-CMCS-Hemin/Pt@Pd NPs nanozyme with peroxidase-like activity was designed. The GP73 biosensor responses linearly from 10.0-110.0 ng/mL with LOD of 4.7 ng/mL, and shows acceptable specificity and good recovery.

Antitumor effect and metabonomics of niclosamide micelles

Polymer micelles now have promising applications in the treatment of cancer, increasing the water solubility and bioavailability of drugs. Previous studies have found that micelles of niclosamide have good anti‐liver cancer effect. In view of the poor water solubility of niclosamide (NIC), we decided to prepare niclosamide micelles. However, its therapeutic mechanism is not clear, so this paper conducted a preliminary study on its vitro anti‐tumour mechanism and metabonomics to find out its impact. It was found that the drug‐loaded micelles (PEG_2K‐FIbu/NIC) had an inhibitory effect on HepG2 cells. Moreover, it can promote apoptosis of HepG2 cells and block S and G2/M phase of cell cycle. The plasma and liver metabolomics of mice in normal group, model group and administration group were studied by UPLC‐MS and ¹H‐NMR. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS‐DA) were used to process the data and find the relevant metabolites. metaboanalyst 5.0 was used to integrate the relevant metabolites to find the main related metabolic pathways. Thus, the anti‐tumour mechanism of PEG_2K‐FIbu/NIC was analysed. Fifty‐one biomarkers were detected in plasma, and 43 biomarkers were detected in liver. After comprehensive biomarker and metabolic pathway analysis, it was found that PEG_2K‐FIbu/NIC micelles could affect the changes of many metabolites, mainly affecting amino acid metabolism. This article is an in‐depth study based on the published Preparation and pharmacodynamics of niclosamide micelles (DOI: 10.1016/j.jddst.2021.103088).

Discovery of potential active ingredients of Er-Zhi-Wan, a famous traditional Chinese formulation, in model rat serum for treating osteoporosis with kidney-yin deficiency by UPLC-Q/TOF-MS and molecular docking

Er-Zhi-Wan (EZW), a classical traditional Chinese formulation, has attracted more and more attention. This study was carried out to analyze the constituents of EZW absorbed into blood and find out the potential active ingredients for treating osteoporosis (OP) with kidney-yin deficiency (KYD). The rat model of OP with KYD was achieved by ovariectomies and using the mixture of thyroxine and reserpine. Then ultra-high performance liquid chromatography coupled with a quadrupole time-of-flight mass spectrometer (UPLC-Q/TOF-MS) combined with statistical analysis was used to analyze the constituents of EZW absorbed into blood and differential components between the normal and OP with KYD rats. Finally, the components identified in OP with KYD rats were docked with targets of OP with KYD found in online databases. The results of molecular docking were adopted to find the potential active ingredients and further verified in vitro experiment. A total of 21 prototype compounds and 69 metabolites were identified in serum. Among them, 63 components in model rats and 50 components in normal rats were summarized, respectively. Most of the identified metabolites in serum of model rats were produced by hydrolysis, oxidation or glucuronidation, while in serum of normal rats were produced by hydrolysis, oxidation and methylation. According to the results of molecular docking, specnuezhenide, salidroside, tyrosol, echinacoside and verbascoside could be classified as potential active ingredients. The activity of salidroside and a metabolite was verified by pharmacodynamics analysis. In summary, UPLC-Q/TOF-MS system was combined with molecular docking to search the potential active ingredients from model rats of OP with KYD, which provided a new idea for the research on the pharmacodynamic material basis of other traditional medicine. Moreover, the result of this study lays the foundation for further study regarding the mechanism of EZW in treating OP with KYD.

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.

1H-NMR-based metabolomics reveals the biomarker panel and molecular mechanism of hepatocellular carcinoma progression

Hepatocellular carcinoma (HCC) is one of the most extensive and most deadly cancers in the world. Biomarkers for early diagnosis of HCC are still lacking, and noninvasive and effective biomarkers are urgently needed. Metabolomics is committed to studying the changes of metabolites under stimulation, and provides a new approach for discovery of potential biomarkers. In the current work, 1H nuclear magnetic resonance (NMR) metabolomics approach was utilized to explore the potential biomarkers in HCC progression, and the biomarker panel was evaluated by receiver operating characteristic (ROC) curve analyses. Our results revealed that a biomarker panel consisting of hippurate, creatinine, putrescine, choline, and taurine might be involved in HCC progression. Functional pathway analysis showed that taurine and hypotaurine metabolism is markedly involved in the occurrence and development of HCC. Furthermore, our results indicated that the TPA activity and the level and expression of PKM2 were gradually increased in HCC progression. This research provides a scientific basis for screening potential biomarkers 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.

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.

Discovery of novel serum metabolic biomarkers in patients with polycystic ovarian syndrome and premature ovarian failure

Several widely recognized metabolites play a role in regulating the pathophysiological processes of various disorders. Nonetheless, the lack of effective biomarkers for the early diagnosis of polycystic ovarian syndrome (PCOS) and premature ovarian failure (POF) has led to the discovery of serum-based metabolic biomarkers for these disorders. We aimed to identify various differentially expressed metabolites (DEMs) through serum-based metabolic profiling in patients with PCOS and POF and in healthy individuals by using liquid chromatography–mass spectrometry analysis. Furthermore, heatmap clustering, correlation, and Z-score analyses were performed to identify the top DEMs. Kyoto Encyclopedia of Genes and Genomes enriched pathways of DEMs were determined using metabolite-based databases. Moreover, the clinical significance of these DEMs was evaluated on the basis of area under the receiver operating characteristic curve. Significantly dysregulated expressions of several metabolites were observed in the intergroup comparisons of the PCOS, POF, and healthy control groups. Furthermore, 6 DEMs were most frequently observed among the three groups. The expressions of these DEMs were not only directly correlated but also exhibited potential significance in patients with PCOS and POF. Novel metabolites with up/downregulated expressions can be discovered in patients with PCOS and POF using serum-based metabolomics; these metabolites show good diagnostic performance and can act as effective biomarkers for the early detection of PCOS and POF. Furthermore, these metabolites might be involved in the pathophysiological mechanisms of PCOS and POF via interplay with corresponding genes.

Characterization of metabolic landscape in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, accounting for approximately 75%-85% of primary liver cancers. Metabolic alterations have been labeled as an emerging hallmark of tumors. Specially, the last decades have registered a significant improvement in our understanding of the role of metabolism in driving the carcinogenesis and progression of HCC. In this paper, we provide a review of recent studies that investigated the metabolic traits of HCC with a specific focus on three common metabolic alterations involving glycolysis, lipid metabolism, and glutamine addiction which have been gaining much attention in the field of HCC. Next, we describe some representative diagnostic markers or tools, and promising treatment agents that are proposed on the basis of the aforementioned metabolic alterations for HCC. Finally, we present some challenges and directions that may promisingly speed up the process of developing objective diagnostic markers and therapeutic options underlying HCC. Specifically, we recommend future investigations to carefully take into account the influence of heterogeneity, control for study-specific confounds, and invite the validation of existing biomarkers.

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.

Bis-indole alkaloid caulerpin from a new source Sargassum platycarpum: isolation, characterization, in vitro anticancer activity, binding with nucleobases by DFT calculations and MD simulation

Caulerpin, a bis-indole alkaloid is isolated from a new source Sargassum platycarpum, brown alga (family Sargassaceae) for the first time. The structure of caulerpin was characterized by IR, H1NMR, C13 NMR, HSQC, HMBC, EI-MS spectroscopy. Antifungal results suggest that caulerpin has been inhibited Cryptococcus neoformas (12 mm) and Candida albicans (7 mm) than other microbes. In vitro anticancer activity of caulerpin has been explored by cell viability assay against new human cancer cell line (liver-HepG2). The results show that caulerpin has low IC50 value (24.6 ± 2.1 µg/mL) against HepG-2. Based on the least toxic activity of caulerpin, these results encourage for future in vivo anticancer study. The binding of caulerpin molecule with the two nucleobases (T/U) bases has been studied by DFT methods. According to the AIM analysis, there are two types of interactions between caulerpin and T/U bases partially covalent partially electrostatic and electrostatic in gas and water phases. Based on NBO analysis, the charges were transferred from the lone-pair (n) in orbitals of O atoms of caulerpin to the σ* orbitals of T/U bases atoms. ΔEbin in the state of caulerpin-T bases complexes are lower than those in the caulerpin-U bases complexes in both gas and water phase. MD simulation supported that caulerpin-T/U bases complexes are stable in presence of explicit water phase. Thus, the findings of our study will be useful for giving an insight into the caulerpin/bases complexes that could be helpful in future experimental studies to develop the performance of caulerpin molecules as natural candidate drug. Communicated by Ramaswamy H. Sarma.

The role of farnesoid X receptor in metabolic diseases, and gastrointestinal and liver cancer

Farnesoid X receptor (FXR) is a ligand-activated transcription factor involved in the control of bile acid (BA) synthesis and enterohepatic circulation. FXR can influence glucose and lipid homeostasis. Hepatic FXR activation by obeticholic acid is currently used to treat primary biliary cholangitis. Late-stage clinical trials investigating the use of obeticholic acid in the treatment of nonalcoholic steatohepatitis are underway. Mouse models of metabolic disease have demonstrated that inhibition of intestinal FXR signalling reduces obesity, insulin resistance and fatty liver disease by modulation of hepatic and gut bacteria-mediated BA metabolism, and intestinal ceramide synthesis. FXR also has a role in the pathogenesis of gastrointestinal and liver cancers. Studies using tissue-specific and global Fxr-null mice have revealed that FXR acts as a suppressor of hepatocellular carcinoma, mainly through regulating BA homeostasis. Loss of whole-body FXR potentiates progression of spontaneous colorectal cancer, and obesity-induced BA imbalance promotes intestinal stem cell proliferation by suppressing intestinal FXR in Apc^min/+ mice. Owing to altered gut microbiota and FXR signalling, changes in overall BA levels and specific BA metabolites probably contribute to enterohepatic tumorigenesis. Modulating intestinal FXR signalling and altering BA metabolites are potential strategies for gastrointestinal and liver cancer prevention and treatment. In this Review, studies on the role of FXR in metabolic diseases and gastrointestinal and liver cancer are discussed, and the potential for development of targeted drugs are summarized.

Six Metabolism Related mRNAs Predict the Prognosis of Patients With Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common aggressive solid malignant tumors and current research regards HCC as a type of metabolic disease. This study aims to establish a metabolism-related mRNA signature model for risk assessment and prognosis prediction in HCC patients. Methods: HCC data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Enrichment Analysis (GSEA) website. Least absolute shrinkage and selection operator (LASSO) was used to screen out the candidate mRNAs and calculate the risk coefficient to establish the prognosis model. A high-risk group and low-risk group were separated for further study depending on their median risk score. The reliability of the prediction was evaluated in the validation cohort and the whole cohort. Results: A total of 548 differential mRNAs were identified from HCC samples (n = 374) and normal controls (n = 50), 45 of which were correlated with prognosis. A total of 373 samples met the screening criteria and there were randomly divided into the training cohort (n = 186) and the validation cohort (n = 187). In the training cohort, six metabolism-related mRNAs were used to construct a prognostic model with a LASSO regression model. Based on the risk model, the overall survival rate of the high-risk cohort was significantly lower than that of the low-risk cohort. The results of a time-ROC curve proved that the risk score (AUC = 0.849) had a higher prognostic value than the pathological grade, clinical stage, age or gender. Conclusion: The model constructed by the six metabolism-related mRNAs has a significant value for survival prediction and can be applied to guide the evaluation of HCC and the designation of clinical therapy.

Serum Golgi protein 73 as a sensitive biomarker for early detection of hepatocellular carcinoma among Egyptian patients with hepatitis C virus-related cirrhosis

Background

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. Early detection of HCC is always a challenging task for physicians. Serum Golgi protein 73 (GP73) is considered a potential tumor marker for the detection of HCC. However, the diagnostic value of GP73 for the HCC diagnosis is still controversial. This research was designed to assess the diagnostic efficacy of GP73 as a diagnostic tool for HCC in cases with hepatitis C virus-related cirrhosis.

Methods

Eighty-seven subjects were allocated into four different groups in this prospective research (HCC, liver cirrhosis, chronic hepatitis C, and healthy control group). Serum alpha-fetoprotein (AFP) and GP73 were tested for all subjects in the study. Detection of focal hepatic lesions was based on imaging by abdominal ultrasonography and triphasic computed tomography.

Results

The cut-off values for GP73 and AFP were 534.5 ng/L and 32 ng/mL, respectively. The specificity of GP73 was 87%, and the sensitivity was 88%, while the specificity and sensitivity of AFP levels were 80% and 72%, respectively. The negative predictive value of GP73 was 87.5%, and the positive predictive value of GP73 was 84.6%, while the same parameters of AFP were 73.1% and 75%, respectively.

Conclusion

Serum Golgi protein 73 could be a valuable biomarker and a useful diagnostic tool for the early diagnosis of HCC in cases of hepatitis C virus-related cirrhosis.

Piezo1 impairs hepatocellular tumor growth via deregulation of the MAPK-mediated YAP signaling pathway

Accumulating evidence has revealed the mechanosensitive ion channel protein Piezo1 is contributing to tumorigenesis. However, its role in hepatocellular carcinoma (HCC) remains unexplored. In this study, we demonstrated that Piezo1 was expressed in the HepG2 cell line and depletion of Piezo1 impaired proliferation and migration, as well as increased apoptosis in these cells. Using a Piezo1-specific activator, Yoda1, we identified that calcium entry induced by Yoda1 resulted in phosphorylation of JNK, p38, and ERK, thereby activating the mitogen-activated protein kinase (MAPK) pathway, in a dose- and time-dependent manner. More strikingly, Piezo1 activation integrated with YAP signaling to control the nuclear translocation of YAP and regulation of its target genes. JNK, p38, and ERK (MAPK signaling) regulated Yoda1-induced YAP activation. Consistent with the association of calpain with Piezo1, we also found that calpain activity was decreased by siRNA-mediated knockdown of Piezo1. In addition, the growth of HCC tumors was inhibited in Piezo1 haploinsufficient mice. Together, our findings establish that the Piezo1/MAPK/YAP signaling cascade is essential for HepG2 cell function. These results highlight the importance of Piezo1 in HCC and the potential utility of Piezo1 as a biomarker and therapeutic target.

Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

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.

Remodeling Lipids in the Transition from Chronic Liver Disease to Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma (HCC) has poor prognosis. We studied blood lipids by comparing healthy volunteers to patients with chronic liver disease (CLD), and to patients with HCC caused by viral infections. We contrasted our findings in blood to lipid alterations in liver tumor and nontumor tissue samples from HCC patients. In blood, most lipid species were found at increased levels in CLD patients compared to healthy volunteers. This trend was mostly reversed in HCC versus CLD patients. In liver tumor tissues, levels of many lipids were decreased compared to paired nontumor liver tissues. Differences in lipid levels were further defined by alterations in the degree of saturation in the fatty acyl chains. Some lipids, including free fatty acids, saturated lysophosphatidylcholines and saturated triacylglycerides, showed a continuous trend in the transition from the blood of healthy controls to CLD and HCC patients. For HCC patients, phosphatidylglycerides showed similar alterations in both blood and tissues.

Abstract

Hepatocellular carcinoma (HCC) is a worldwide health problem. HCC patients show a 50% mortality within two years of diagnosis. To better understand the molecular pathogenesis at the level of lipid metabolism, untargeted UPLC MS—QTOF lipidomics data were acquired from resected human HCC tissues and their paired nontumor hepatic tissues (n = 46). Blood samples of the same HCC subjects (n = 23) were compared to chronic liver disease (CLD) (n = 15) and healthy control (n = 15) blood samples. The participants were recruited from the National Liver Institute in Egypt. The lipidomics data yielded 604 identified lipids that were divided into six super classes. Five-hundred and twenty-four blood lipids were found as significantly differentiated (p < 0.05 and qFDR p < 0.1) between the three study groups. In the blood of CLD patients compared to healthy control subjects, almost all lipid classes were significantly upregulated. In CLD patients, triacylglycerides were found as the most significantly upregulated lipid class at qFDR p = 1.3 × 10⁻⁵⁶, followed by phosphatidylcholines at qFDR p = 3.3 × 10⁻⁵¹ and plasmalogens at qFDR p = 1.8 × 10^-46. In contrast, almost all blood lipids were significantly downregulated in HCC patients compared to CLD patients, and in HCC tissues compared to nontumor hepatic tissues. Ceramides were found as the most significant lipid class (qFDR p = 1 × 10⁻¹⁴) followed by phosphatidylglycerols (qFDR p = 3 × 10⁻⁹), phosphatidylcholines and plasmalogens. Despite these major differences, there were also common trends in the transitions between healthy controls, CLD and HCC patients. In blood, several mostly saturated triacylglycerides showed a continued increase in the trajectory towards HCC, accompanied by reduced levels of saturated free fatty acids and saturated lysophospatidylcholines. In contrast, the largest overlaps of lipid alterations that were found in both HCC tissue and blood comparisons were decreased levels of phosphatidylglycerols and sphingolipids. This study highlights the specific impact of HCC tumors on the circulating lipids. Such data may be used to target lipid metabolism for prevention, early detection and treatment of HCC in the background of viral-related CLD etiology.

A Lipidomic Signature Complements Stemness Features Acquisition in Liver Cancer Cells

Lipid catabolism and anabolism changes play a role in stemness acquisition by cancer cells, and cancer stem cells (CSCs) are particularly dependent on the activity of the enzymes involved in these processes. Lipidomic changes could play a role in CSCs’ ability to cause disease relapse and chemoresistance. The exploration of lipid composition and metabolism changes in CSCs in the context of hepatocellular cancer (HCC) is still incomplete and their lipidomic scenario continues to be elusive. We aimed to evaluate through high-throughput mass spectrometry (MS)-based lipidomics the levels of the members of the six major classes of sphingolipids and phospholipids in two HCC cell lines (HepG2 and Huh-7) silenced for the expression of histone variant macroH2A1 (favoring stemness acquisition), or silenced for the expression of focal adhesion tyrosine kinase (FAK) (hindering aggressiveness and stemness). Transcriptomic changes were evaluated by RNA sequencing as well. We found definite lipidomic and transcriptomic changes in the HCC lines upon knockdown (KD) of macroH2A1 or FAK, in line with the acquisition or loss of stemness features. In particular, macroH2A1 KD increased total sphingomyelin (SM) levels and decreased total lysophosphatidylcholine (LPC) levels, while FAK KD decreased total phosphatidylcholine (PC) levels. In conclusion, in HCC cell lines knocked down for specific signaling/epigenetic processes driving opposite stemness potential, we defined a lipidomic signature that hallmarks hepatic CSCs to be exploited for therapeutic strategies.

The use of minimally invasive biomarkers for the diagnosis and prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common cause of cancer-related deaths worldwide. Despite advances in systemic therapies, patient survival remains low due to late diagnosis and frequent underlying liver diseases. HCC diagnosis generally relies on imaging and liver tissue biopsy. Liver biopsy presents limitations because it is invasive, potentially risky for patients and it frequently misrepresents tumour heterogeneity. Recently, liquid biopsy has emerged as a way to monitor cancer progression in a non-invasive manner. Tumours shed content into the bloodstream, such as circulating tumour cells (CTCs), circulating nucleic acids, extracellular vesicles and proteins, that can be isolated from biological fluids of patients with HCC. These biomarkers provide knowledge regarding the genetic landscape of tumours and might be used for diagnostic or prognostic purposes. In this review, we summarize recent literature on circulating biomarkers for HCC, namely CTCs, circulating tumour DNA (ctDNA), RNA, extracellular vesicles and proteins, and their clinical relevance in HCC.

Longitudinal change of metabolite profile and its relation to multiple risk factors for the risk of developing hepatitis B-related hepatocellular carcinoma

Despite considerable knowledge of viral pathogenesis, the pathophysiological changes related to the multifactorial, multistep process of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) development remains unclear. Longitudinal metabolomics study can reveal biological process for disease progression. We performed metabolite profiling with longitudinal prediagnostic plasma samples from two nested case-control studies of hepatitis B surface antigen carriers participating in ultrasound screening for HCC, one within a government employee cohort (870 samples from 109 HCC cases and 107 controls) and the other within a hospital-based cohort (266 samples from 63 HCC cases and 114 controls). Of the 34 measured metabolites, tyrosine, isoleucine, and glutamine were consistently associated with HCC. In analyses combining longitudinal data, a high metabolic risk score based on the three amino acids was robustly associated with increased risk of HCC (OR = 3.71, 95% confidence interval: 2.53-5.42), even after adjustment for clinical factors, or when assessed for different times up to ≥8 years before diagnosis. Similar association was observed in an independent, prospective analysis comprising 633 randomly selected individuals of the government employee cohort. More importantly, this metabolite signature was longitudinally influenced by HBV-infection phase and involved in gradual progression to liver fibrosis and cirrhosis. Furthermore, mediation analysis showed that the score mediated substantial proportions of the associations of key viral factors, insulin resistance, and diabetes status with HCC risk. Our results suggest that an amino-acid dysregulation metabotype may play a role in HBV-related HCC development, and may also be linked to common pathways that mediate increased HCC risks.

Plasma proteome atlas for differentiating tumor stage and post-surgical prognosis of hepatocellular carcinoma and cholangiocarcinoma

Although mass spectrometry-based plasma proteomics enables sensitive and large-scale discovery and validation of biomarkers for various diseases, its integrative application to hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) is not well investigated. Therefore, we analyzed albumin- and immunoglobulin G-depleted plasma samples from 148 and 60 patients with HCC and CCA, respectively, using liquid chromatography-tandem mass spectrometry. The algorithm used to measure the content of each protein was the percentage of exponentially modified protein abundance index. From 5320 proteins assayed in plasma, 53 and 25 biomarker candidates were identified for HCC and CCA, respectively. The abundance of six and two HCC markers particularly protruded in stage II and III, respectively, whereas plasma serine protease inhibitor was the sole marker the level of which steadily decreased with CCA progression. From a prognostic facet, we showed candidate markers and their cutoff levels for evaluating probability of tumor recurrence and patient survival period. Combination Kaplan-Meier models showed that HCC stage III or IV and both the content of alpha-2-HS-glycoprotein and apolipoprotein CIII <0.2% exhibited the poorest post-surgical recurrence-free and overall survivals. Furthermore, the content of afamin ≥0.2% played a significant role on the poor prognosis in patients with CCA. Our findings, taken together, characterized novel plasma biomarker signatures in dissecting tumor stages and post-surgical outcomes of HCC and CCA.

Omics-derived hepatocellular carcinoma risk biomarkers for precision care of chronic liver diseases

Precise hepatocellular carcinoma (HCC) risk prediction will play increasingly important roles with the contemporary HCC etiologies, that is, non-alcoholic fatty liver disease and resolved hepatitis C virus infection. Because the HCC incidence rate in this emerging patient population is relatively low (~1% per year), identification of a subset of patients at the highest risk is critical to concentrate the effort and resources of regular HCC screening to those who most need it. Omics profiling has been derived using several candidate HCC risk biomarkers, which could refine HCC screening by enabling individual risk-based personalized or risk-stratified patient management. Various types of biomolecules have been explored as sources of information to predict HCC risk at various time horizons. Germline DNA polymorphisms likely reflect race/ethnicity- and/or etiology-specific susceptibility to HCC development or chronic liver disease progression toward carcinogenesis. Transcriptomic dysregulations in the diseased liver capture functional molecular status supporting oncogenesis such as inflammatory pathway and myofibroblast activation. Circulating nucleic acids, proteins, and metabolites could serve as less-invasive measures of molecular HCC risk. Characterization of gut microbiota could also inform HCC risk estimation. Each biomarker could have its niche of clinical application depending on logistics of use, performance, and costs with a goal to eventually improve patient prognosis as a part of the whole algorithm of chronic liver disease management.

1H NMR-based metabolomics analyses in children with Helicobacter pylori infection and the alteration of serum metabolites after treatment

BACKGROUND AND AIMS

Helicobacter pylori (H. pylori) infection can occur in early childhood, without eradication therapies such infection can persist throughout life and cause many different diseases. This study investigated the metabolic characteristics and explored the underlying mechanism of children with H. pylori infection, and identified potential biomarkers for evaluating the efficacy of H. pylori eradication therapies.

METHODS

We performed ¹H NMR-based metabonomics coupled with multivariate analysis to investigate the metabolic profiling of serum samples between Children with and without H. pylori infection. In the same manner, we compared the alternations of metabolites in H. pylori-infected children before and after H. pylori eradication therapies.

RESULTS

21 metabolites from serum in H. pylori-infected and H. pylori-uninfected children were identified, which were mainly involved in energy, amino acid, lipid and microbial metabolism. We found that the serum levels of trimethylamine N-oxide and alanine were significantly higher in H. pylori-infected children compared to uninfected sera, whereas lactate was significantly lower. We also found that the levels of trimethylamine N-oxide and creatine in H. pylori-infected children was significantly decreased after H. pylori eradication therapies, whereas lactate and low-density lipoprotein/very low-density lipoprotein was significantly increased.

CONCLUSIONS

This is the first study using ¹H NMR-based metabolomics approach to explore the effects of H. pylori infection in children. Our results demonstrated that the disturbances of metabolism in energy, amino acids, lipids and microbiota could play an important role in the pathogenesis of gastrointestinal and extragastric diseases caused by H. pylori infection. Trimethylamine N-oxide and lactate might serve as potential serum biomarkers for evaluating the efficacy of H. pylori eradication therapies.

Liquid Biopsies in Hepatocellular Carcinoma: Are We Winning?

Hepatocellular carcinoma (HCC) represents the sixth most common cancer worldwide and the third most common cause of cancer-related death. One of the major problems faced by researchers and clinicians in this area is the lack of reliable disease biomarkers, which would allow for an earlier diagnosis, follow-up or prediction of treatment response, among others. In this regard, the “HCC circulome”, defined as the pool of circulating molecules in the bloodstream derived from the primary tumor, represents an appealing target, the so called liquid biopsy. Such molecules encompass circulating tumor proteins, circulating tumor cells (CTCs), extracellular vesicles (EVs), tumor-educated platelets (TEPs), and circulating tumor nucleic acids, namely circulating tumor DNA (ctDNA) and circulating tumor RNA (ctRNA). In this article, we summarize recent findings highlighting the promising role of liquid biopsies as novel potential biomarkers in HCC, emphasizing on its clinical performance.

Severe metabolic alterations in liver cancer lead to ERK pathway activation and drug resistance

BACKGROUND

The extracellular signal-regulated kinase (ERK) pathway regulates cell growth, and is hyper-activated and associated with drug resistance in hepatocellular carcinoma (HCC). Metabolic pathways are profoundly dysregulated in HCC. Whether an altered metabolic state is linked to activated ERK pathway and drug response in HCC is unaddressed.

METHODS

We deprived HCC cells of glutamine to induce metabolic alterations and performed various assays, including metabolomics (with 13C-glucose isotope tracing), microarray analysis, and cell proliferation assays. Glutamine-deprived cells were also treated with kinase inhibitors (e.g. Sorafenib, Erlotinib, U0126 amongst other MEK inhibitors). We performed bioinformatics analysis and stratification of HCC tumour microarrays to determine upregulated ERK gene signatures in patients.

FINDINGS

In a subset of HCC cells, the withdrawal of glutamine triggers a severe metabolic alteration and ERK phosphorylation (pERK). This is accompanied by resistance to the anti-proliferative effect of kinase inhibitors, despite pERK inhibition. High intracellular serine is a consistent feature of an altered metabolic state and contributes to pERK induction and the kinase inhibitor resistance. Blocking the ERK pathway facilitates cell proliferation by reprogramming metabolism, notably enhancing aerobic glycolysis. We have identified 24 highly expressed ERK gene signatures that their combined expression strongly indicates a dysregulated metabolic gene network in human HCC tissues.

INTERPRETATION

A severely compromised metabolism lead to ERK pathway induction, and primes some HCC cells to pro-survival phenotypes upon ERK pathway blockade. Our findings offer novel insights for understanding, predicting and overcoming drug resistance in liver cancer patients. FUND: DFG, BMBF and Sino-German Cooperation Project.

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.

Dickkopf-1 contributes to hepatocellular carcinoma tumorigenesis by activating the Wnt/β-catenin signaling pathway

Dysregulation of dickkopf-related protein 1 (DKK1) expression has been reported in a variety of human cancers. We previously reported that DKK1 was upregulated in hepatocellular carcinoma (HCC). However, the role of DKK1 in HCC remains unclear. This study aimed to investigate the clinical significance and biological functions of DKK1 in HCC. The expression of DKK1 was examined in cirrhotic and HCC tissues by immunohistochemistry and quantitative real-time polymerase chain reaction (qRT-PCR). DKK1 was silenced or overexpressed in HCC cell lines, and in vitro and in vivo studies were performed. Immunohistochemistry revealed that DKK1 was weakly expressed in cirrhotic tissues (8/22, 36.4%) but upregulated in HCC tissues (48/53, 90.6%, cohort 1). Significant upregulation of DKK1 was observed in 57.6% (19/33, cohort 2) of HCC tissues by qRT-PCR, and the expression of DKK1 was associated with tumor size (P = 0.024) and tumor number (P = 0.019). Genetic depletion of DKK1 impaired the proliferation, colony-forming ability, invasion, and tumor formation of HCC cells (HepG2 and HUH-7). Conversely, forced expression of DKK1 increased the proliferation, colony-forming ability, and invasion of HepG2 and HUH-7 cells in vitro and enhanced tumor formation in vivo. Subsequent investigation revealed that the DKK1-mediated proliferation and tumorigenicity of HepG2 and HUH-7 cells is dependent on the Wnt/β-catenin signaling pathway. These findings indicate that DKK1 plays an oncogenic role in HCC by activating the Wnt/β-catenin signaling pathway.

The positive correlation of TIPRL with LC3 and CD133 contributes to cancer aggressiveness: potential biomarkers for early liver cancer

Studies have reported dysregulation of TIPRL, LC3 and CD133 in liver cancer tissues. However, their respective relationships to liver cancer and roles as biomarkers for prognosis and diagnosis of liver cancer have never been studied. Here we report that the level of TIPRL is significantly correlated with levels of LC3 (Spearman r = 0.9) and CD133 (r = 0.7) in liver cancer tissues. We observed significant upregulations of TIPRL, LC3 and CD133 in hepatocellular carcinomas (HCCs) compared with adjacent normal tissues. Importantly, TIPRL, tested among additional variables, showed a significant impact on the prognosis of HCC patients. TIPRL knockdown significantly reduced expressions of LC3, CD133, stemness-related genes, as well as viability and stemness of liver cancer cell-lines, which were promoted by ectopic TIPRL expression. Either alone or as a combination, TIPRL, LC3 and CD133 showed significant values of area under the curve (AUC) and sensitivity/specificity in early liver cancer tissues. Furthermore, the statistical association and the diagnostic efficacies of TIPRL, LC3 and CD133 in HCC tissues were confirmed in a different IHC cohort. This data demonstrates that the complex involvement of TIPRL/LC3/CD133 in liver cancer aggressiveness can together or individually serve as potential biomarkers for the early detection of liver cancer.

Characterisation of the Urinary Metabolic Profile of Liver Fluke-Associated Cholangiocarcinoma

BACKGROUND

Human infection with Opisthorchis viverrini, a carcinogenic liver fluke inhabiting the biliary tree, is endemic in Southeast Asia. Chronic infection is associated with a fatal complication, cholangiocarcinoma (CCA), a late-presenting and aggressive malignancy. Currently, annual mortality rates from CCA mirror trends in incidence, due in part to limited availability of efficient prognostic and early diagnostic biomarkers. With ability to detect thousands of urinary metabolites using metabonomics, the urine metabolome holds great potential in providing an insight into system-level alterations in carcinogenesis and in identifying metabolic markers altered in response to disturbed homoeostasis.

METHODS

Global molecular profiling using reversed-phase ultraperformance liquid chromatography mass spectrometry was utilised to acquire the urinary spectral profile of 137 Thai subjects (48 at high risk of infection, 41 with O. viverrini infection, 34 periportal fibrosis and 14 CCA) from Khon Kaen, Thailand.

RESULTS

Multivariate statistical analysis identified perturbation in several molecular classes related to purine metabolism and lipid metabolism in the CCA urine metabolome. These markers mainly reflect changes in energy metabolism to support proliferation (increased fatty acid oxidation and purine recycling), DNA methylation and hepatic injury.

CONCLUSIONS

Several metabolites of biological interest were discovered from this proof-of-principle dataset. Augmenting these findings is essential to accelerate the development of urinary metabolic markers in CCA.

Classification of early and late stage liver hepatocellular carcinoma patients from their genomics and epigenomics profiles

Background

Liver Hepatocellular Carcinoma (LIHC) is one of the major cancers worldwide, responsible for millions of premature deaths every year. Prediction of clinical staging is vital to implement optimal therapeutic strategy and prognostic prediction in cancer patients. However, to date, no method has been developed for predicting the stage of LIHC from the genomic profile of samples.

Methods

The Cancer Genome Atlas (TCGA) dataset of 173 early stage (stage-I), 177 late stage (stage-II, Stage-III and stage-IV) and 50 adjacent normal tissue samples for 60,483 RNA transcripts and 485,577 methylation CpG sites, was extensively analyzed to identify the key transcriptomic expression and methylation-based features using different feature selection techniques. Further, different classification models were developed based on selected key features to categorize different classes of samples implementing different machine learning algorithms.

Results

In the current study, in silico models have been developed for classifying LIHC patients in the early vs. late stage and cancerous vs. normal samples using RNA expression and DNA methylation data. TCGA datasets were extensively analyzed to identify differentially expressed RNA transcripts and methylated CpG sites that can discriminate early vs. late stages and cancer vs. normal samples of LIHC with high precision. Naive Bayes model developed using 51 features that combine 21 CpG methylation sites and 30 RNA transcripts achieved maximum MCC (Matthew’s correlation coefficient) 0.58 with an accuracy of 78.87% on the validation dataset in discrimination of early and late stage. Additionally, the prediction models developed based on 5 RNA transcripts and 5 CpG sites classify LIHC and normal samples with an accuracy of 96–98% and AUC (Area Under the Receiver Operating Characteristic curve) 0.99. Besides, multiclass models also developed for classifying samples in the normal, early and late stage of cancer and achieved an accuracy of 76.54% and AUC of 0.86.

Conclusion

Our study reveals stage prediction of LIHC samples with high accuracy based on the genomics and epigenomics profiling is a challenging task in comparison to the classification of cancerous and normal samples. Comprehensive analysis, differentially expressed RNA transcripts, methylated CpG sites in LIHC samples and prediction models are available from CancerLSP (http://webs.iiitd.edu.in/raghava/cancerlsp/).

Mass Spectrometry as a Clinical Integrative Tool to Evaluate Hepatocellular Carcinoma: Moving to the Mainstream

Introduction: Since the pioneering work of J. J. Thomson on magnetic deflection of charged particles, mass spectrometry (MS) has become the most progressive clinical tool by continuously providing new applications in medical research. In hepatocellular carcinoma (HCC), MS can be used from surveillance in early stages of the disease to constant evaluation of effective treatments. Areas covered: This Special Report highlights the groundbreaking possibilities of mass spectrometry clinical application in the mainstream to evaluate HCC development and progression. Expert opinon: MS has been employed to understand a myriad of liver diseases, such as the identification of early biomarkers in cirrhosis and HVB and HVC, as well as metabolic alterations of lipidic imbalance in HCC due to fatty liver disease. In an integrative point-of-view, researchers worldwide are looking for molecular signatures that may represent more faithfully the complex scenario of the onset and progression of HCC. Following the steps of MELD score (Model of End-stage Liver Disease), which evaluates biochemical dysfunction of end-stage liver diseases, the necessity to use innovative attempts to pursue a molecular-MEaLD (mMEaLD - molecular Model for Early Liver Disease), shifting MS to the upstream and from the lab facilities into the mainstream, inside the surgery room.

Tissue and serum metabolomic phenotyping for diagnosis and prognosis of hepatocellular carcinoma

More than two-thirds of patients with hepatocellular carcinoma (HCC) cannot receive curative therapy and have poor survival due to late diagnosis and few prognostic directions. In our study, nontargeted and targeted metabolomics analyses were conducted by liquid chromatography-mass spectrometry to characterize metabolic features of HCC and identify diagnostic and prognostic biomarker candidate incorporating liver tissue and serum metabolites. A total of 552 subjects, including 432 with liver tissue and 120 with serum specimens, were recruited in China. In the discovery cohort, a series of 138 metabolites were identified to discriminate HCC tissues from matched nontumor tissues. Retinol presented with the highest area under the curve (AUC) of 0.991 and associated with Edmondson grade. In the validation cohort, all metabolites in retinol metabolism pathway were examined and the levels of retinol and retinal in tumor tissue and serum decreased in the order of normal to cirrhosis to HCC of Edmondson Grades I to IV. Retinol and retinal levels could also differentiate between HCC and cirrhosis, with AUCs of 0.996 and 0.994, respectively, in tissue and 0.812 and 0.744, respectively, in serum. The AUC of the combined retinol and retinal panel in serum was 0.852. Univariate and multivariate Cox regression identified this panel as an independent predictor for HCC and showed that low expression of retinol and retinal correlated with decreased survival time. In conclusion, the retinol metabolic signature had considerable diagnostic and prognostic value for identifying HCC patients who would benefit from prompt therapy and optimal prognostic direction.

Biomarkers vs imaging in the early detection of hepatocellular carcinoma and prognosis

Hepatocellular carcinoma (HCC) is the 5^th most frequently diagnosed cancer in the world, according to the World Health Organization. The incidence of HCC is between 3/100000 and 78.1/100000, with a high incidence reported in areas with viral hepatitis B and hepatitis C, thus affecting Asia and Africa predominantly. Several international clinical guidelines address HCC diagnosis and are structured according to the geographical area involved. All of these clinical guidelines, however, share a foundation of diagnosis by ultrasound surveillance and contrast imaging techniques, particularly computed tomography, magnetic resonance imaging, and sometimes contrast-enhanced ultrasound. The primary objective of this review was to systematically summarize the recent published studies on the clinical utility of serum biomarkers in the early diagnosis of HCC and for the prognosis of this disease.

Function, Detection and Alteration of Acylcarnitine Metabolism in Hepatocellular Carcinoma

Acylcarnitines play an essential role in regulating the balance of intracellular sugar and lipid metabolism. They serve as carriers to transport activated long-chain fatty acids into mitochondria for β-oxidation as a major source of energy for cell activities. The liver is the most important organ for endogenous carnitine synthesis and metabolism. Hepatocellular carcinoma (HCC), a primary malignancy of the live with poor prognosis, may strongly influence the level of acylcarnitines. In this paper, the function, detection and alteration of acylcarnitine metabolism in HCC were briefly reviewed. An overview was provided to introduce the metabolic roles of acylcarnitines involved in fatty acid β-oxidation. Then different analytical platforms and methodologies were also briefly summarised. The relationship between HCC and acylcarnitine metabolism was described. Many of the studies reported that short, medium and long-chain acylcarnitines were altered in HCC patients. These findings presented current evidence in support of acylcarnitines as new candidate biomarkers for studies on the pathogenesis and development of HCC. Finally we discussed the challenges and perspectives of exploiting acylcarnitine metabolism and its related metabolic pathways as a target for HCC diagnosis and prognosis.

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.

Analysis of bodily fluids using vibrational spectroscopy: a direct comparison of Raman scattering and infrared absorption techniques for the case of glucose in blood serum

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies.

Differentially expressed serum host proteins in hepatitis B and C viral infections

Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infection often lead to hepatocellular carcinoma (HCC), which is mostly detected in advanced stage. Hence, its early detection is of paramount importance using a biomarker having sensitivity and specificity both. The present study highlights differentially expressed host proteins in response to HBV/HCV infection at different stages. Comparative proteomic study was done by two-dimensional gel electrophoresis followed by mass spectrometry. Sera from each of chronically infected, liver cirrhosis and HCC in HBV or HCV infection along with controls were selected. Analysis of functional association between differentially expressed proteins with viral hepatitis was extensively carried out. Forty-three differentially expressed spots (≥ 1.5 fold; P < 0.05) on two-dimensional gel electrophoresis were corresponded to 28 proteins by mass spectrometry in variable liver diseases. Haptoglobin protein levels were decreased upon disease progression to HCC due to HBV infection. The other proteins expressed differentially are ceruloplasmin, serum paraoxonase 1, retinol binding protein and leucine rich alpha 2 proteins in plasma maybe associated to HBV HCC. Whereas, upregulation of C4a/C4b showed it as a reliable marker in patients with end stage liver disease related to HCV infection. ApolipoproteinA1 levels in liver diseases in both HBV and HCV infection corresponding to healthy controls may be a common marker for early diagnosis and disease monitoring. Protein interaction studies by extensive pathway analysis using bioinformatics tools such as EnrichNet application and STRING revealed significant associations with specific infections.

Identification of Protein Abundance Changes in Hepatocellular Carcinoma Tissues Using PCT-SWATH

PURPOSE

To rapidly identify protein abundance changes in biopsy-level fresh-frozen hepatocellular carcinoma (HCC).

EXPERIMENTAL DESIGN

The pressure-cycling technology (PCT) is applied and sequential window acquisition of all theoretical mass spectra (SWATH-MS) workflow is optimized to analyze 38 biopsy-level tissue samples from 19 HCC patients. Each proteome is analyzed with 45 min LC gradient. MCM7 is validated using immunohistochemistry (IHC).

RESULTS

A total of 11 787 proteotypic peptides from 2579 SwissProt proteins are quantified with high confidence. The coefficient of variation (CV) of peptide yield using PCT is 32.9%, and the R² of peptide quantification is 0.9729. Five hundred forty-one proteins showed significant abundance change between the tumor area and its adjacent benign area. From 24 upregulated pathways and 13 suppressed ones, enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues are observed. Protein changes based on α-fetoprotein expression and hepatitis B virus infection are further analyzed. The data altogether highlight 16 promising tumor marker candidates. The upregulation of minichromosome maintenance complex component 7 (MCM7) is further observed in multiple HCC tumor tissues by IHC.

CONCLUSIONS AND CLINICAL RELEVANCE

The practicality of rapid proteomic analysis of biopsy-level fresh-frozen HCC tissue samples with PCT-SWATH has been demonstrated and promising tumor marker candidates including MCM7 are identified.

Silencing of Xeroderma Pigmentosum Group D Gene Promotes Hepatoma Cell Growth by Reducing P53 Expression

BACKGROUND This study investigated the effect of xeroderma pigmentosum group D (XPD) silencing on the growth of hepatoma cells and assessed the mechanisms. MATERIAL AND METHODS XPD gene was silenced by siRNA in hepatoma cells. The experiments were randomly divided into a control group, a liposome control group, a negative control (NC) group, an XPD siRNA group, and an XPD siRNA + P53 inhibitor group. 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) was used to detect cell viability 24 h after gene silencing and treatments. Terminal deoxynucleotidyl transferases (TdT)-mediated dUTP nick-end labeling (TUNEL) and flow cytometry were used to detect apoptosis. Invasive ability was detected by Transwell assay. Additionally, the expression of mouse double-minute 2 homolog (Mdm2), mouse double-minute 4 homolog (Mdm4), CyclinD1, P21, Bax, P53, C-sis, and Bcl-2 was detected by real-time polymerase chain reaction and Western blotting. RESULTS Compared with the NC group, XPD siRNA significantly reduced XPD expression at both mRNA and protein levels. XPD siRNA significantly promoted cell proliferation, reduced apoptosis, and promoted cell invasive ability. Expression of CyclinD1, Bcl-2, and C-sis increased significantly after XPD silencing, while the expression of P21, Mdm2, Mdm4, Bax, and P53 significantly decreased (vs. NC, P<0.05). Importantly, P53 inhibitor (1 μM bpV) further enhanced the effect of XPD silencing (vs. XPD silencing, P<0.05). CONCLUSIONS Our data revealed that XPD silencing promoted growth of hepatoma cells by reducing P53 expression.

Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases

In the past decade, advances in liquid chromatography-mass spectrometry (LC-MS) have revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply, researchers are now primed to uncover key metabolites and their associations with diseases. The employment of untargeted metabolomics has led to new biomarker discoveries and a better mechanistic understanding of diseases with applications in precision medicine. However, many major pertinent challenges remain. First, compound identification has been poor, and left an overwhelming number of unidentified peaks. Second, partial, incomplete metabolomes persist due to factors such as limitations in mass spectrometry data acquisition speeds, wide-range of metabolites concentrations, and cellular/tissue/temporal-specific expression changes that confound our understanding of metabolite perturbations. Third, to contextualize metabolites in pathways and biology is difficult because many metabolites partake in multiple pathways, have yet to be described species specificity, or possess unannotated or more-complex functions that are not easily characterized through metabolomics analyses. From a translational perspective, information related to novel metabolite biomarkers, metabolic pathways, and drug targets might be sparser than they should be. Thankfully, significant progress has been made and novel solutions are emerging, achieved through sustained academic and industrial community efforts in terms of hardware, computational, and experimental approaches. Given the rapidly growing utility of metabolomics, this review will offer new perspectives, increase awareness of the major challenges in LC-MS metabolomics that will significantly benefit the metabolomics community and also the broader the biomedical community metabolomics aspire to serve.

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

BACKGROUND AND AIMS

Metabolomics serves as an important tool in distinguishing changes in metabolic pathways and the diagnosis of human disease. Hepatocellular carcinoma (HCC) is a malignance present of heterogeneous metabolic disorder and lack of effective biomarker for surveillance and diagnosis. In this study, we searched for potential metabolite biomarkers of HCC using tissue and serum metabolomics approach.

METHODS

A total of 30 pairs of matched liver tissue samples from HCC patients and 90 serum samples (30 HCC patients, 30 liver cirrhosis patients, and 30 healthy individuals) were assessed. Metabolomics was performed through ultra performance liquid chromatography-mass spectrometry in conjunction with multivariate and univariate statistical analyses.

RESULTS

A total of six differential metabolites including chenodeoxycholic acid (CDCA), glycocholic acid (GCA), LPC20:5, LPE18:0, succinyladenosine and uridine were present in HCC tissue and serum samples. CDCA, LPC20:5, succinyladenosine and uridine were used to construct a diagnostic model based on logistic regression. The four-metabolite panel discriminated HCC from liver cirrhosis with an AUC score of 0.938, sensitivity of 93.3% and specificity of 86.7%. For all HCC and cirrhosis patients, the diagnostic accuracy increased to 96.7% and 90.0%, respectively.

CONCLUSION

The combination of CDCA, LPC20:5, succinyladenosine and uridine can be used as a biomarker panel to improve HCC sensitivity and specificity. This panel significantly benefits HCC diagnostics and reveals new insight into HCC pathogenesis.