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

Altered Metabolites in Hepatocellular Carcinoma (HCC) Paving the Road for Metabolomics Signature and Biomarkers for Early Diagnosis of HCC

Globally, hepatocellular carcinoma (HCC) is one of the most commonly encountered cancers. Because the current early diagnostic tests for HCC are not very sensitive, most cases of the disease are discovered late when it is in its terminal stage. Cellular metabolism changes during carcinogenesis to enable cancer cells to adapt to the hypoxic milieu, boost anabolic synthesis, promote survival, and evade apoptotic death signals. Omic techniques represent a breakthrough in the field of diagnostic technology. For example, Metabolomics analysis could be used to identify these metabolite alterations. Understanding the metabolic alterations linked to HCC is crucial for improving high-risk patients' surveillance and understanding the illness's biology. This review highlights the metabolic alterations linked to energy production in cancer cells, as well as the significantly altered metabolites and pathways associated with hepatocarcinogenesis, including acylcarnitines (ACs), amino acids, proteins, lipids, carbohydrates, glucose, and lactate, which reflect the anabolic and catabolic changes occurring in these cells. Additionally, it discusses the clinical implications of recent metabolomics that may serve as potential biomarkers for early diagnosis and monitoring of the progression of HCC.

Imaging Investigation of Hepatocellular Carcinoma Progress via Monitoring γ-Glutamyltranspeptidase Level with a Near-Infrared Fluorescence/Photoacoustic Bimodal Probe

Hepatocellular carcinoma (HCC) is one of the main principal causes of cancer death, and the late definite diagnosis limits therapeutic approaches in time. The early diagnosis of HCC is essential, and the previous investigations on the biomarkers inferred that the γ-glutamyltranspeptidase (GGT) level could indicate the HCC process. Herein, a near-infrared fluorescence/photoacoustic (NIRF/PA) bimodal probe, CySO3-GGT, was developed for monitoring the GGT level and thus to image the HCC process. After the in-solution tests, the bimodal response was convinced. The various HCC processes were imaged by CySO3-GGT at the cellular level. Then, the CCl4-induced HCC (both induction and treatment) and the subcutaneous and orthotopic xenograft mice models were selected. All throughout the tests, CySO3-GGT achieved NIRF and PA bimodal imaging of the HCC process. In particular, CySO3-GGT could effectively realize 3D imaging of the HCC nodule by visualizing the boundary between the tumor and the normal tissue. The information here might offer significant guidance for the dynamic monitoring of HCC in the near future.

Comparative analysis of bile metabolic profile in patients with biliary obstruction complicated by Clonorchis sinensis infection

Background

Clonorchiasis is an important foodborne parasitic disease. However, eggs of Clonorchis sinensis (C. sinensis) cannot be detected in feces during biliary obstruction. Moreover, many diseases can cause biliary obstruction, such as gallstones, adenocarcinoma, cholangiocarcinoma and Ascaris lumbricoides infection. Therefore, it is of great significance to distinguish between patients of biliary obstruction and biliary obstruction with C. sinensis infection.

Methods

A total of 48 biliary obstruction patients were enrolled, including 23 infected with C. sinensis (C. sinensis) (OB+C.s) and 25 non-infected subjects (OB). The bile samples were collected by endoscopic retrograde cholangiopancreatography and analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, bile amino acid levels were determined by targeted metabolomics analysis.

Result

A total of 146 and 132 significant metabolites were identified in electrospray ionization (ESI)+ and ESI- modes, respectively. The levels of amino acids (asparagine, glutamate, ornithine) and polyamines (spermidine and spermine) were significantly changed. Targeted analysis showed that the levels of amino acids (such as L-arginine, L-glutamine, L-lysine, L-propionic, and L-tyrosine) were lower in OB+C.s patients compared to those in OB patients. Marked metabolic pathways were involved in "Glutathione metabolism", "Caffeine metabolism", "Alanine, aspartate and glutamate metabolism", "Arginine and proline metabolism", "Purine metabolism", "Beta-Alanine metabolism", and "D-glutamine and D-glutamate metabolism".

Conclusion

These results show that there were significant differences between OB+C.s and OB patients, especially in amino acids. The metabolic signature and perturbations in metabolic pathways may help to better distinguish OB+C.s and OB patients.

Metabolomics-Guided Identification of a Distinctive Hepatocellular Carcinoma Signature

BACKGROUND

Hepatocellular carcinoma (HCC) is a major contributor to cancer-related morbidity and mortality burdens globally. Given the fundamental metabolic activity of hepatocytes within the liver, hepatocarcinogenesis is bound to be characterized by alterations in metabolite profiles as a manifestation of metabolic reprogramming.

METHODS

HCC and adjacent non-tumoral liver specimens were obtained from patients after HCC resection. Global patterns in tissue metabolites were identified using non-targeted ¹H Nuclear Magnetic Resonance (¹H-NMR) spectroscopy whereas specific metabolites were quantified using targeted liquid chromatography-mass spectrometry (LC/MS).

RESULTS

Principal component analysis (PCA) within our ¹H-NMR dataset identified a principal component (PC) one of 53.3%, along which the two sample groups were distinctively clustered. Univariate analysis of tissue specimens identified more than 150 metabolites significantly altered in HCC compared to non-tumoral liver. For LC/MS, PCA identified a PC1 of 45.2%, along which samples from HCC tissues and non-tumoral tissues were clearly separated. Supervised analysis (PLS-DA) identified decreases in tissue glutathione, succinate, glycerol-3-phosphate, alanine, malate, and AMP as the most important contributors to the metabolomic signature of HCC by LC/MS.

CONCLUSIONS

Together, ¹H-NMR and LC/MS metabolomics have the capacity to distinguish HCC from non-tumoral liver. The characterization of such distinct profiles of metabolite abundances underscores the major metabolic alterations that result from hepatocarcinogenesis.

Curcumin induces apoptosis in human hepatocellular carcinoma cells by decreasing the expression of STAT3/VEGF/HIF-1α signaling

Curcumin is the most abundant derivative of turmeric rhizome. Although studies have proved that curcumin could inhibit the growth of tumors, its specific molecular mechanism has not yet been fully elucidated. This study aims to systematically elaborate the mechanisms of curcumin against hepatocellular carcinoma. The anti-tumor effect of curcumin was determined by the cell viability test. Flow cytometry was applied to examine the cell cycle and the apoptosis of cancer cells, and the cancer cell migration was detected by wound healing experiments. The expressions of signal transducers and activators of transcription 3 (STAT3), vascular endothelial growth factor (VEGF), and hypoxia-inducible factor-1α (HIF-1α) in cancer cells were examined by immunostaining and analyzed by the Image J analysis system. After treatment with curcumin, the apoptosis ratio of HepG2 cells increased significantly (P < 0.05). The proliferation of cancer cells was arrested at the S-phase cell cycle, and the migration of cancer cells was inhibited by the increasing concentration of curcumin, together with the decreasing expressions of STAT3, VEGF, and HIF-1α signaling pathways. The results indicate that curcumin could effectively inhibit the growth and migration of hepatocarcinoma cells by inducing cancer cell apoptosis, blocking the cancer cell cycle in the S phase, and reducing the expression of STAT3, VEGF, and HIF-1α signaling pathways.

An exploratory human study of superstable homogeneous lipiodol-indocyanine green formulation for precise surgical navigation in liver cancer

The clinical applications of transcatheter arterial embolization (TAE) conversion therapy combined with hepatectomy have been severely restricted by ill-defined tumoral boundaries and miniscule hidden lesions. Fluorescent surgical navigation is a promising method for overcoming these barriers. However, sufficient delivery of the fluorescent probe into the tumor region after long-term TAE is challenging due to blockade of the tumor-supplying artery. Here, a super-stable homogeneous intermix formulating technology (SHIFT) to physically mix lipiodol and indocyanine green (ICG) formulation (SHIFT and ICG) for fluorescent surgical navigation after long-term TAE conversion therapy is provided. Through the retrospective study of 45 clinical liver cancer patients, it is found that SHIFT and ICG formulation have excellent tumor deposition effect and safety. During surgical resection after long-term TAE conversion therapy, SHIFT and ICG could clearly identify in real time the full tumor regions and boundaries and had a high signal-to-normal tissues ratio-even the indistinguishable satellite lesions could be identified with a strong fluorescence intensity. Meanwhile, SHIFT and ICG could improve operative, anesthetic, and postoperative variables associated with postoperative complications. This simple and effective SHIFT could provide precise fluorescent navigation for surgical resection following long-term embolization therapy in clinical practice and has great potential for a translational pipeline.

Biomarker discovery and application-An opportunity to resolve the challenge of liver cancer diagnosis and treatment

Liver cancer is one of the most common malignancies, with severe morbidity and mortality. While considerable progress has been made in liver cancer treatment, the 5-year overall survival (OS) of patients has not improved significantly. Reasons include the inadequate capability of early screening and diagnosis, a high incidence of recurrence and metastasis, a high degree of tumor heterogeneity, and an immunosuppressive tumor microenvironment. Therefore, the identification and validation of specific and robust liver cancer biomarkers are of major importance for early screening, timely diagnosis, accurate prognosis, and the prevention of tumor progression. In this review, we highlight some of the latest research progress and potential applications of liver cancer biomarkers, describing hotspots and prospective directions in biomarker discovery.

Multi-Omics Analysis Revealed a Significant Alteration of Critical Metabolic Pathways Due to Sorafenib-Resistance in Hep3B Cell Lines

Hepatocellular carcinoma (HCC) is the second prominent cause of cancer-associated death worldwide. Usually, HCC is diagnosed in advanced stages, wherein sorafenib, a multiple target tyrosine kinase inhibitor, is used as the first line of treatment. Unfortunately, resistance to sorafenib is usually encountered within six months of treatment. Therefore, there is a critical need to identify the underlying reasons for drug resistance. In the present study, we investigated the proteomic and metabolomics alterations accompanying sorafenib resistance in hepatocellular carcinoma Hep3B cells by employing ultra-high-performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). The Bruker Human Metabolome Database (HMDB) library was used to identify the differentially abundant metabolites through MetaboScape 4.0 software (Bruker). For protein annotation and identification, the Uniprot proteome for Homo sapiens (Human) database was utilized through MaxQuant. The results revealed that 27 metabolites and 18 proteins were significantly dysregulated due to sorafenib resistance in Hep3B cells compared to the parental phenotype. D-alanine, L-proline, o-tyrosine, succinic acid and phosphatidylcholine (PC, 16:0/16:0) were among the significantly altered metabolites. Ubiquitin carboxyl-terminal hydrolase isozyme L1, mitochondrial superoxide dismutase, UDP-glucose-6-dehydrogenase, sorbitol dehydrogenase and calpain small subunit 1 were among the significantly altered proteins. The findings revealed that resistant Hep3B cells demonstrated significant alterations in amino acid and nucleotide metabolic pathways, energy production pathways and other pathways related to cancer aggressiveness, such as migration, proliferation and drug-resistance. Joint pathway enrichment analysis unveiled unique pathways, including the antifolate resistance pathway and other important pathways that maintain cancer cells' survival, growth, and proliferation. Collectively, the results identified potential biomarkers for sorafenib-resistant HCC and gave insights into their role in chemotherapeutic drug resistance, cancer initiation, progression and aggressiveness, which may contribute to better prognosis and chemotherapeutic outcomes.

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

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

Medicinal Plants for the Treatment of Gastrointestinal Cancers From the Metabolomics Perspective

Gastrointestinal cancer (GIC), primarily including colorectal cancer, gastric cancer, liver cancer, pancreatic cancer, and esophageal cancer, is one of the most common causes of cancer-related deaths with increasing prevalence and poor prognosis. Medicinal plants have been shown to be a great resource for the treatment of GIC. Due to their complex manifestations of multi-component and multi-target, the underlying mechanisms how they function against GIC remain to be completely deciphered. Cell metabolism is of primary importance in the initialization and development of GIC, which is reported to be a potential target. As an essential supplement to the newest “omics” sciences, metabolomics focuses on the systematic study of the small exogenous and endogenous metabolites involved in extensive biochemical metabolic pathways of living system. In good agreement with the systemic perspective of medicinal plants, metabolomics offers a new insight into the efficacy assessment and action mechanism investigation of medicinal plants as adjuvant therapeutics for GIC therapy. In this review, the metabolomics investigations on metabolism-targeting therapies for GIC in the recent 10 years were systematically reviewed from five aspects of carbohydrate, lipid, amino acid, and nucleotide metabolisms, as well as other altered metabolisms (microbial metabolism, inflammation, and oxidation), with particular attention to the potential of active compounds, extracts, and formulae from medicinal plants. Meanwhile, the current perspectives and future challenges of metabolism-targeting therapies of medicinal plants for GIC were also discussed. In conclusion, the understanding of the action mechanisms of medicinal plants in GIC from the metabolomics perspective will contribute to the clinical application of potential candidates from the resourceful medicinal plants as novel and efficient adjuvant therapeutics for GIC therapy.

The Role of Chronic Liver Diseases in the Emergence and Recurrence of Hepatocellular Carcinoma: An Omics Perspective

Hepatocellular carcinoma (HCC) typically develops from a background of cirrhosis resulting from chronic inflammation. This inflammation is frequently associated with chronic liver diseases (CLD). The advent of next generation sequencing has enabled extensive analyses of molecular aberrations in HCC. However, less attention has been directed to the chronically inflamed background of the liver, prior to HCC emergence and during recurrence following surgery. Hepatocytes within chronically inflamed liver tissues present highly activated inflammatory signaling pathways and accumulation of a complex mutational landscape. In this altered environment, cells may transform in a stepwise manner toward tumorigenesis. Similarly, the chronically inflamed environment which persists after resection may impact the timing of HCC recurrence. Advances in research are allowing an extensive epigenomic, transcriptomic and proteomic characterization of CLD which define the emergence of HCC or its recurrence. The amount of data generated will enable the understanding of oncogenic mechanisms in HCC from the CLD perspective and provide the possibility to identify robust biomarkers or novel therapeutic targets for the treatment of primary and recurrent HCC. Importantly, biomarkers defined by the analysis of CLD tissue may permit the early detection or prevention of HCC emergence and recurrence. In this review, we compile the current omics based evidence of the contribution of CLD tissues to the emergence and recurrence of HCC.

Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms

PURPOSE

Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and distinguish between differing metastatic disease burdens. Here, we hypothesized that biomarkers within the blood metabolome could identify cancers within a mixed population of patients referred from primary care with nonspecific symptoms, the so-called "low-risk, but not no-risk" patient group, as well as distinguishing between those with and without metastatic disease.

EXPERIMENTAL DESIGN

Patients (n = 304 comprising modeling, n = 192, and test, n = 92) were recruited from 2017 to 2018 from the Oxfordshire Suspected CANcer (SCAN) pathway, a multidisciplinary diagnostic center (MDC) referral pathway for patients with nonspecific signs and symptoms. Blood was collected and analyzed by NMR metabolomics. Orthogonal partial least squares discriminatory analysis (OPLS-DA) models separated patients, based upon diagnoses received from the MDC assessment, within 62 days of initial appointment.

RESULTS

Area under the ROC curve for identifying patients with solid tumors in the independent test set was 0.83 [95% confidence interval (CI): 0.72-0.95]. Maximum sensitivity and specificity were 94% (95% CI: 73-99) and 82% (95% CI: 75-87), respectively. We could also identify patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% (95% CI: 72-99) and 88% (95% CI: 53-98), respectively.

CONCLUSIONS

For a mixed group of patients referred from primary care with nonspecific signs and symptoms, NMR-based metabolomics can assist their diagnosis, and may differentiate both those with malignancies and those with and without metastatic disease. See related commentary by Van Tine and Lyssiotis, p. 1477.

Limitations and Possibilities of Transarterial Chemotherapeutic Treatment of Hepatocellular Carcinoma

Because diagnostic tools for discriminating between hepatocellular carcinoma (HCC) and advanced cirrhosis are poor, HCC is often detected in a stage where transarterial chemoembolization (TACE) is the best treatment option, even though it provides a poor survival gain. Despite having been used worldwide for several decades, TACE still has many limitations. First, there is a vast heterogeneity in the cellular composition and metabolism of HCCs as well as in the patient population, which renders it difficult to identify patients who would benefit from TACE. Often the delivered drug does not penetrate sufficiently selectively and deeply into the tumour and the drug delivery system is not releasing the drug at an optimal clinical rate. In addition, therapeutic effectiveness is limited by the crosstalk between the tumour cells and components of the cirrhotic tumour microenvironment. To improve this widely used treatment of one of our most common and deadly cancers, we need to better understand the complex interactions between drug delivery, local pharmacology, tumour targeting mechanisms, liver pathophysiology, patient and tumour heterogeneity, and resistance mechanisms. This review provides a novel and important overview of clinical data and discusses the role of the tumour microenvironment and lymphatic system in the cirrhotic liver, its potential response to TACE, and current and possible novel DDSs for locoregional treatment.

Characteristics of serum metabolites in sporadic amyotrophic lateral sclerosis patients based on gas chromatography-mass spectrometry

To identify differential metabolites and metabolic pathways and provide guidance for the novel biomarkers for diagnosis and prognosis of amyotrophic lateral sclerosis (ALS). ALS patients and people without nervous diseases were recruited. Metabolomic analysis was performed using gas chromatography-mass spectrometry (GC/MS). The orthogonal projections to latent structures discriminant analysis (OPLS-DA) were used to identify differential metabolites. Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst were used to identify metabolic pathways. 75 metabolites were detected and aligned. The OPLS-DA showed the metabolomic profile of ALS patients and those in the fast-progression and slow-progression ALS groups differed from that of CTRL (p < 0.05). The levels of maltose, glyceric acid, lactic acid, beta-alanine, phosphoric acid, glutamic acid, ethanolamine and glycine in ALS were significantly higher, while 2,4,6-tri-tert-butylbenzenethiol was lower. Glycine, serine and threonine metabolism, D-glutamine and D-glutamate metabolism, alanine, aspartate, and glutamate metabolism, beta-alanine metabolism, and pyruvate metabolism were significantly altered metabolic pathways in ALS. ROC was used to discriminate ALS from CTRL with an AUC of 0.898 (p < 0.001) using 2,4,6-tri-tert-butylbenzenethiol, beta-alanine, glycine, and ethanolamine. The serum metabolites and metabolic pathways in ALS patients are significantly altered compared with CTRL. These findings may contribute to the early diagnosis of ALS.

Liver and urine metabolomics reveal the protective effect of Gandou decoction in copper-laden Hepatolenticular degeneration model rats

Hepatolenticular degeneration (HLD) is an inherited disorder associated with human copper metabolism. Gandou decoction (GDD), a traditional Chinese medicinal formula, has been used as a therapeutic agent for the treatment of HLD in China for decades. Recent pharmacological evaluation in our laboratory has demonstrated that GDD exerts positive and beneficial effects on HLD model rats. However, its underlying therapeutic mechanisms are not yet well understood. To explore the potential therapeutic effects of GDD against HLD, liver and urine metabolomics approach combined with histopathological examination were performed to reveal the underlying mechanisms. Changes in metabolic profiles were estimated by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) coupled with multivariate statistical analyses. The results indicated that GDD could significantly improve liver pathological variations. Moreover, 19 and 11 significantly altered metabolites were found in the liver and urine between the normal and model groups, respectively. After GDD treatment, the levels of all these disordered metabolites showed different degrees of improvement compared with the model group, including lysoPC(18:2), lysoPE(20:2/0:0), PC(18:1/14:1), alpha-linolenic acid, sphinganine, taurochenodesoxycholic acid, tetracosahexaenoic acid, 13-OxoODE, and 13-L-hydroperoxyl inoleic acid. Metabolic pathway enrichment suggested that lipid and oxidative stress metabolism were the two main pathways that participated in copper-laden rat models with GDD administration. This work indicates that GDD could achieve a therapeutic effect on HLD by ameliorating the associated metabolic disturbances.

HMGCS2 in metabolic pathways was associated with overall survival in hepatocellular carcinoma: A LASSO-derived study

This integrated bioinformatic study aimed to investigate potential prognostic candidates in hepatocellular carcinoma (HCC). In the GSE14520, GSE101685, and The Cancer Genome Atlas (TCGA) datasets, differentially expressed genes (DEGs) were identified and functional pathways of common DEGs were enriched. The least absolute shrinkage and selection operator (LASSO) model was used to screen the potential parameters associated with overall survival (OS) in HCC patients. Metabolic pathways were the most significantly enriched functional pathways of common DEGs in these three datasets. After LASSO model analysis, HMGCS2, UGP2, BCLC staging and TNM staging were screened as potential prognostic candidates for OS in HCC patients in GSE14520. HMGCS2 in the metabolic pathway was significantly downregulated in tumor tissues and peripheral blood mononuclear cells in HCC patients (all p < 0.05). Cox regression model indicated that HMGCS2 might be associate with OS in HCC patients in GSE14520 and in the TCGA (p = 0.029 and p = 0.05, respectively). Kaplan-Meier analysis demonstrated that HMGCS2 downregulation in tumors contributed to an unfavorable OS in HCC patients, both in GSE14520 and in the TCGA (p = 0.0001 and p = 0.0002, respectively). Additionally, HMGCS2 was significantly downregulated in HCC patients with high alpha-fetoprotein (AFP), main tumor size >5 cm, multinodular, advanced tumor staging including BCLC, TNM and CLIP (all p < 0.05). HMGCS2 was involved in metabolic pathways, and downregulated HMGCS2 in tumors was associated with unfavorable OS in HCC patients.

NMR-Based Lipid Metabolite Profiles to Predict Outcomes in Patients Undergoing Interventional Therapy for a Hepatocellular Carcinoma (HCC): A Substudy of the SORAMIC Trial

Simple Summary

A hepatocellular carcinoma (HCC) is the most common cause of death in patients suffering from chronic liver diseases. In order to improve the prediction of outcomes in HCC patients, there is a need for new biomarkers. This pilot study aimed at identifying serum metabolites for the prediction of outcomes of HCC patients using nuclear magnetic resonance (NMR) spectroscopy. This analysis revealed that high serum concentrations of myo-inositol or dimethylamine were associated with an improved overall survival. In contrast, high concentrations of total cholesterol, LDL-cholesterol and LDL particles (LDL-P) were associated with a decreased overall survival. The identification of novel biomarkers using this NMR-based technology holds promise for opening new directions in the conduction of interventional trials in HCCs.

Abstract

Background: This exploratory study aimed to evaluate lipidomic and metabolomic profiles in patients with early and advanced HCCs and to investigate whether certain metabolic parameters may predict the overall survival in these patients. Methods: A total of 60 patients from the prospective, randomized-controlled, multicenter phase II SORAMIC trial were included in this substudy; among them were 30 patients with an early HCC who underwent radiofrequency ablation combined with sorafenib or a placebo and 30 patients with an advanced HCC who were treated with a selective internal radiation therapy (SIRT) plus sorafenib vs. sorafenib alone. The blood serum of these patients was analyzed using a standardized nuclear magnetic resonance (NMR) platform. All tested metabolites were correlated with the overall survival. Results: The overall survival (OS) was significantly higher in patients with an early HCC (median OS: 34.0 months) compared with patients with an advanced HCC (median OS: 12.0 months) (p < 0.0001). Patients with high serum concentrations of myo-inositol (MI) had a higher overall survival compared with patients with low concentrations (21.6 vs. 13.8 months) with a Pearson correlation coefficient of 0.331 (p = 0.011). Patients with high serum concentrations of dimethylamine had a higher overall survival compared with patients with low concentrations (25.1 vs. 19.7 months) with a Pearson correlation coefficient of 0.279 (p = 0.034). High concentrations of total cholesterol, LDL-cholesterol and LDL particles (LDL-P) were associated with a decreased overall survival. Conclusions: NMR-based lipidomic and metabolomic profiling has the potential to identify individual metabolite biomarkers that predict the outcome of patients with an HCC exposed to non-invasive therapeutic management.

The role of metabolomics in hepatocellular carcinoma

Background

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

Main body

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

Conclusions

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

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.

High Squalene Epoxidase in Tumors Predicts Worse Survival in Patients With Hepatocellular Carcinoma: Integrated Bioinformatic Analysis on NAFLD and HCC

This study aimed to identify candidate biomarkers for predicting outcomes in nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC). Using Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) databases, we identified common upregulated differential expressed genes (DEGs) in patients with NAFLD/nonalcoholic steatohepatitis (NASH) and HCC and conducted survival analysis of these upregulated DEGs with HCC outcomes. Two common upregulated DEGs including squalene epoxidase (SQLE) and EPPK1 messenger RNA (mRNA) were significantly upregulated in NAFLD, NASH, and HCC tissues, both in GSE45436 (P < .001) and TCGA profile (P < .001). Both SQLE and EPPK1 mRNA were upregulated in 15.56% and 8.06% patients with HCC in TCGA profile. Overexpression of SQLE in tumors was significantly associated with worse overall survival (OS) and disease-free survival (DFS) in patients with HCC (log-rank P = .027 and log-rank P = .048, respectively), while no statistical significances of OS and DFS were found in EPPK1 groups (both log-rank P > .05). For validation, SQLE upregulation contributed to significantly worse OS in patients wih HCC using Kaplan-Meier plotter analysis (hazard ratio = 1.43, 95% confidence interval: 1.01-2.02, log-rank P = .043). In addition, high level of SQLE significantly associated with advanced neoplasm histologic grade, advanced AJCC stage, and α-fetoprotein elevation (P = .036, .045, and .029, respectively). Squalene epoxidase is associated with OS and DFS and serves as a novel prognostic biomarker for patients with HCC.

Gut microbiota alterations are distinct for primary colorectal cancer and hepatocellular carcinoma

Colorectal cancer (CRC) and hepatocellular carcinoma (HCC) are the second and third most common causes of death by cancer, respectively. The etiologies of the two cancers are either infectious insult or due to chronic use of alcohol, smoking, diet, obesity and diabetes. Pathological changes in the composition of the gut microbiota that lead to intestinal inflammation are a common factor for both HCC and CRC. However, the gut microbiota of the cancer patient evolves with disease pathogenesis in unique ways that are affected by etiologies and environmental factors. In this review, we examine the changes that occur in the composition of the gut microbiota across the stages of the HCC and CRC. Based on the idea that the gut microbiota are an additional "lifeline" and contribute to the tumor microenvironment, we can observe from previously published literature how the microbiota can cause a shift in the balance from normal → inflammation → diminished inflammation from early to later disease stages. This pattern leads to the hypothesis that tumor survival depends on a less pro-inflammatory tumor microenvironment. The differences observed in the gut microbiota composition between different disease etiologies as well as between HCC and CRC suggest that the tumor microenvironment is unique for each case.

Metabolomic Analysis Identifies Glycometabolism Pathways as Potential Targets of Qianggan Extract in Hyperglycemia Rats

Qianggan formula, a designed prescription according to the Traditional Chinese Medicine (TCM) theory, is widely used in treating chronic liver diseases, and indicated to prevent blood glucose increase in patients via unknown mechanisms. To unravel the effects and underlying mechanisms of Qianggan formula on hyperglycemia, we administrated Qianggan extract to high fat and high sucrose (HFHS) diet rats. Results showed that four-week Qianggan extract intervention significantly decreased serum fasting blood glucose, hemoglobin A1c, and liver glycogen levels. Gas chromatography-mass spectrometry (GC-MS) approach was employed to explore metabolomic profiles in liver and fecal samples. By multivariate and univariate statistical analysis (variable importance of projection value > 1 and p value < 0.05), 44 metabolites (18 in liver and 30 in feces) were identified as significantly different. Hierarchical cluster analysis revealed that most differential metabolites had opposite patterns between pair-wise groups. Qianggan extract restored the diet induced metabolite perturbations. Metabolite sets enrichment and pathway enrichment analysis revealed that the affected metabolites were mainly enriched in glycometabolism pathways such as glycolysis/gluconeogenesis, pentose phosphate pathway, fructose, and mannose metabolism. By compound-reaction-enzyme-gene network analysis, batches of genes (e.g. Hk1, Gck, Rpia, etc) or enzymes (e.g. hexokinase and glucokinase) related to metabolites in enriched pathways were obtained. Our findings demonstrated that Qianggan extract alleviated hyperglycemia, and the effects might be partially due to the regulation of glycometabolism related pathways.

1H-NMR based metabolomic profiling of cord blood in gestational hypothyroidism

Background

Gestational hypothyroidism (GHT) is a common pregnancy-related thyroid disfunction. The adverse outcomes by GHT has been increasingly recognized, leading to more public awareness of the disease. However, comprehensive understanding of the prognosis of GHT has not yet achieved. Metabolomics is a powerful tool in evaluation of disease outcomes, and cord blood represents an excellent candidate for the investigation of gestational outcomes.

Methods

In the present study, we performed 1H-NMR based metabolomics on cord blood of 18 pregnant women with GHT and 18 non hypothyroidism (NHT) control.

Results

The metabolomic profile of GHT was separated with the NHT control. A total of 8 metabolites with altered abundances were observed, among which Creatinine and O-Phosphocholine were elevated and the others were downregulated in GHT. Spearman rank correlation suggested that the eight differential metabolites were correlated with the GHT related thyroid hormones. Pathway analysis of the differential metabolites indicated that two metabolic pathways were significantly altered in GHT (adjusted P<0.05), including tyrosine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis. Enrichment analysis of the differential metabolites against disease-associated metabolite sets suggested that GHT was associated with disease risks of non-insulin dependent diabetes mellitus, isovaleric acidemia, and methylmalonic aciduria.

Conclusions

The results of this study revealed GHT associated metabolic changes in cord blood, providing insights into the metabolic intermediates between GHT and its related disease risks.

Effects of canagliflozin on growth and metabolic reprograming in hepatocellular carcinoma cells: Multi-omics analysis of metabolomics and absolute quantification proteomics (iMPAQT)

Aim

Metabolic reprograming is crucial in the proliferation of hepatocellular carcinoma (HCC). Canagliflozin (CANA), a sodium-glucose cotransporter 2 (SGLT2) inhibitor, affects various metabolisms. We investigated the effects of CANA on proliferation and metabolic reprograming of HCC cell lines using multi-omics analysis of metabolomics and absolute quantification proteomics (iMPAQT).

Methods

The cells were counted 72 hours after treatment with CANA (10 μM; n = 5) or dimethyl sulfoxide (control [CON]; n = 5) in Hep3B and Huh7 cells. In Hep3B cells, metabolomics and iMPAQT were used to evaluate the levels of metabolites and metabolic enzymes in the CANA and CON groups (each n = 5) 48 hours after treatment.

Results

Seventy-two hours after treatment, the number of cells in the CANA group was significantly decreased compared to that in the CON group in Hep3B and Huh7 cells. On multi-omics analysis, there was a significant difference in the levels of 85 metabolites and 68 metabolic enzymes between the CANA and CON groups. For instance, CANA significantly downregulated ATP synthase F1 subunit alpha, a mitochondrial electron transport system protein (CON 297.28±20.63 vs. CANA 251.83±22.83 fmol/10 μg protein; P = 0.0183). CANA also significantly upregulated 3-hydroxybutyrate, a beta-oxidation metabolite (CON 530±14 vs. CANA 854±68 arbitrary units; P<0.001). Moreover, CANA significantly downregulated nucleoside diphosphate kinase 1 (CON 110.30±11.37 vs. CANA 89.14±8.39 fmol/10 μg protein; P = 0.0172).

Conclusions

We found that CANA suppressed the proliferation of HCC cells through alterations in mitochondrial oxidative phosphorylation metabolism, fatty acid metabolism, and purine and pyrimidine metabolism. Thus, CANA may suppress the proliferation of HCC by regulating metabolic reprograming.

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

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

Comprehensive evaluation of SPATS2 expression and its prognostic potential in liver cancer

Spermatogenesis associated serine rich 2 (SPATS2) has been reported to be dysregulated in few types of cancer; however, no reports have investigated SPATS2 in liver cancer. The aim of the present study was to investigate SPATS2 expression in liver cancer and to analyze its association with the prognosis of liver cancer patients.We examined the differential expression of SPATS2 in liver cancer by exploring The Cancer Genome Atlas (TCGA) database. The diagnostic efficiency of SPATS2 was obtained by Receiver Operating Characteristic (ROC) curve. The Chi-Squared test was used to assess clinical relevance. Survival analysis and Cox regression model were used to detect the effect of SPATS2 on the survival of liver cancer patients. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to SPATS2 expression.SPATS2 is highly expressed in liver cancer (P < 2.2e-16) and has the high diagnostic ability (AUC = 0.964). Survival analysis showed that patients with high SPATS2 expression have an apparently shorter overall survival (OS, P < .0001) and relapse-free survival (RFS, P < .0001). Cox regression analysis showed that high SPATS2 expression might be an independent risk factor for liver cancer (OS, HR = 2.41, P = .000; RFS, HR = 1.90, P < .001). GSEA analysis identified 3 signaling pathways (Mitotic spindle, G2 M checkpoint, E2F targets) that were enriched in the presence of high SPATS2 expression.SPATS2 expression could be a novel diagnostic and prognostic biomarker in liver cancer.

Overexpression of MiR-452-5p in hepatocellular carcinoma tissues and its prospective signaling pathways

BACKGROUND

The implication of miR-452-5p and its prospective machinery in hepatocellular carcinoma (HCC) remains largely unknown. For this reason, this study aimed to inspect the clinical implication of miR-452-5p expression in HCC tissues with multiple detection approaches, to analyze its potential function via in silico methods, and to validate this using a dual-luciferase reporter assay.

METHODS

The assessment of the expression level of miR-452-5p in HCC was conducted via four methods: 1) in-house real-time quantitative PCR (RT-qPCR), 2) miRNA-sequencing (miRNA-seq) from The Cancer Genome Atlas (TCGA), 3) miRNA microarrays from the Gene Expression Omnibus (GEO), and 4) comprehensive meta-analyses calculating the standard mean difference (SMD) and summary of receiver operator characteristic (sROC). Following the target prediction, one of the potential targets of miR-452-5p was validated through a dual-luciferase reporter assay.

RESULTS

MiR-452-5p was consistently elevated in HCC tissues via various detection methods, including in-house RT-qPCR, miRNA-seq, and miRNA microarrays. The final SMD was 0.842 for 820 cases of HCC samples. Simultaneously, the area under curve (AUC) of the sROC was 0.80 (0.76-0.83). The 1,135 predicted targets of miR-452-5p were enriched in the pathways of cytokine-cytokine receptor interaction, carbon metabolism, and complement and coagulation cascades. Among these predicted targets, CDKN1B was verified to be a real target of miR-452-5p.

CONCLUSION

The overexpression of miR-452-5p may play a pivotal role in the carcinogenesis of HCC via targeting multiple signaling pathways and genes. The function and molecular machinery of miR-452-5p in HCC requires further in-depth exploration.

Phospholipids are A Potentially Important Source of Tissue Biomarkers for Hepatocellular Carcinoma: Results of a Pilot Study Involving Targeted Metabolomics

Background: Hepatocellular carcinoma (HCC) pathogenesis involves the alteration of multiple liver-specific metabolic pathways. We systematically profiled cancer- and liver-related classes of metabolites in HCC and adjacent liver tissues and applied supervised machine learning to compare their potential yield for HCC biomarkers. Methods: Tumor and corresponding liver tissue samples were profiled as follows: Bile acids by ultra-performance liquid chromatography (LC) coupled to tandem mass spectrometry (MS), phospholipids by LC-MS/MS, and other small molecules including free fatty acids by gas chromatography—time of flight MS. The overall classification performance of metabolomic signatures derived by support vector machine (SVM) and random forests machine learning algorithms was then compared across classes of metabolite. Results: For each metabolite class, there was a plateau in classification performance with signatures of 10 metabolites. Phospholipid signatures consistently showed the highest discrimination for HCC followed by signatures derived from small molecules, free fatty acids, and bile acids with area under the receiver operating characteristic curve (AUC) values of 0.963, 0.934, 0.895, 0.695, respectively, for SVM-generated signatures comprised of 10 metabolites. Similar classification performance patterns were observed with signatures derived by random forests. Conclusion: Membrane phospholipids are a promising source of tissue biomarkers for discriminating between HCC tumor and liver tissue.

Multiple “Omics” data-based biomarker screening for hepatocellular carcinoma diagnosis

The huge prognostic difference between early and late stage hepatocellular carcinoma (HCC) is a challenging diagnostic problem. Alpha-fetoprotein is the mostly widely used biomarker for HCC used in the clinic, however it’s sensitivity and specificity of is not optimal. The development and application of multiple biotechnologies, including next generation sequencing, multiple “omics” data, that include genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics has been used for HCC diagnostic biomarker screening. Effective biomarkers/panels/models have been identified and validated at different clinical levels. A large proportion of these have a good diagnostic performance for HCC, especially for early HCC. In this article, we reviewed the various HCC biomarkers derived from “omics” data and discussed the advantages and disadvantages for diagnosis HCC.

Field cancerization therapy with ingenol mebutate contributes to restoring skin-metabolism to normal-state in patients with actinic keratosis: a metabolomic analysis

Actinic keratosis (AK) is a skin premalignant lesion, which progresses into squamous cell carcinoma (SCC) if left untreated. Ingenol mebutate gel is approved for local treatment of non-hyperkeratotic, non-hypertrophic AK; it also has the potential to act as a field cancerization therapy to prevent the progression of AK to SCC. To gain better insights into the mechanisms of ingenol mebutate beyond the mere clinical assessment, we investigated, for the first time, the metabolome of skin tissues from patients with AK, before and after ingenol mebutate treatment, with high-resolution magic angle spinning nuclear magnetic resonance spectroscopy. The metabolomic profiles were compared with those of tissues from healthy volunteers. Overall, we identified a number of metabolites, the homeostasis of which became altered during the process of tumorigenesis from healthy skin to AK, and was restored, at least partially, by ingenol mebutate therapy. These metabolites may help to attain a better understanding of keratinocyte metabolism and to unmask the metabolic pathways related to cell proliferation. These results provide helpful information to identify biomarkers with prognostic and therapeutic significance in AK, and suggest that field cancerization therapy with ingenol mebutate may contribute to restore skin metabolism to a normal state in patients with AK.

Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma

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

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.

FAM83D is associated with gender, AJCC stage, overall survival and disease-free survival in hepatocellular carcinoma

Prognostic significance of family with sequence similarity 83, member D (FAM83D) in hepatocellular carcinoma (HCC) patients has not been well-investigated using Gene Expression Omnibus (GEO) series and TCGA database, we compared FAM83D expression levels between tumor and adjacent tissues, and correlated FAM83D in tumors with outcomes and clinico-pathological features in HCC patients. Validated in GSE33006, GSE45436, GSE84402 and TCGA, FAM83D was significantly overexpressed in tumor tissues than that in adjacent tissues (all P<0.01). FAM83D up-regulation was significantly associated with worse overall survival (OS) and disease-free survival (DFS) in HCC patients (Log rank P=0.00583 and P=4.178E-04, respectively). Cox analysis revealed that FAM83D high expression was significantly associated with OS in HCC patients [hazard ratio (HR) = 1.44, 95% confidence interval (CI) = 1.005-2.063, P=0.047]. Additionally, patients deceased or recurred/progressed had significantly higher FAM83D mRNA levels than those living or disease-free (P=0.0011 and P=0.0238, respectively). FAM83D high expression group had significantly more male patients and advanced American Joint Committee on Cancer (AJCC) stage cases (P=0.048 and P=0.047, respectively). FAM83D mRNA were significantly overexpressed in male (P=0.0193). Compared with patients with AJCC stage I, those with AJCC stage II and stage III-IV had significantly higher FAM83D mRNA levels (P = 0.0346 and P=0.0045, respectively). In conclusion, overexpressed in tumors, FAM83D is associated with gender, AJCC stage, tumor recurrence and survival in HCC.

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

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

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.

Aldo-Keto Reductase Family 1 Member B10 (AKR1B10) overexpression in tumors predicts worse overall survival in hepatocellular carcinoma

Overexpression of AKR1B10 correlated with tumorigenesis of many human malignancies; however, the prognostic value of AKR1B10 expression in patients with hepatocellular carcinoma (HCC) still remains controversial. In this analysis, AKR1B10 expression in HCC tumors were evaluated in GEO, TCGA and Oncomine databases, and a survival analysis of AKR1B10 based on TCGA profile was performed. We found that AKR1B10 was significantly overexpressed in tumors compared with nontumors in 7 GEO series (GSE14520, GSE25097, GSE33006, GSE45436, GSE55092, GSE60502, GSE77314) and TCGA profile (all P < 0.05). Meta-analysis in Oncomine database revealed that AKR1B10 was significantly upregulated in cirrhosis, liver cell dysplasia and HCC compared with normal tissues (all P < 0.05). Kaplan-Meier analysis demonstrated that high AKR1B10 in tumors were significantly associated with worse overall survival (OS) in HCC patients (P < 0.05). Subgroup analysis showed that AKR1B10 overexpression were associated with poor 1-year, 3-year and 5-year OS (all P < 0.05). In addition, prognostic values of AKR1B10 upregulation for OS were more significant in HCC with hepatitis-virus-free (P = 0.00055), White race (P = 0.0029) and alcohol-free (P = 0.013), and both in male and female (P = 0.014 and P = 0.034, respectively). In conclusion: AKR1B10 was upregulated in tumors and correlated with worse OS in HCC patients.

Enolase-1 serves as a biomarker of diagnosis and prognosis in hepatocellular carcinoma patients

Background

Hepatocellular carcinoma (HCC) is an aggressive malignancy with high incidence rate and poor prognosis. Enolase-1 (ENO1), a key glycolytic enzyme, has been implicated in the tumorigenesis of various cancers. However, its diagnostic value and clinical significance in HCC are unclear.

Methods

Data of 374 HCC tissues and 50 nontumor tissues were retrieved from The Cancer Genome Atlas database, and the expression level of ENO1 mRNA in HCC was evaluated. In addition, a meta-analysis of 12 HCC cohorts deposited in the Gene Expression Omnibus database was conducted to determine ENO1 expression levels. The diagnostic power of ENO1 in distinguishing HCC tissues from non-HCC tissues was confirmed by receiver operating characteristic (ROC) curve analysis. A tissue microarray comprising 93 HCC specimens and 87 adjacent normal specimens was used to validate ENO1 expression, and its prognostic value in HCC was ascertained by Kaplan–Meier analysis and Cox regression models. In addition, the gene set enrichment analysis was performed to predict the molecular mechanism of ENO1 action in HCC.

Results

ENO1 was overexpressed in HCC tissues and associated with worse outcomes in terms of overall survival (OS) (P<0.01) and disease-free survival (P<0.01). ENO1 expression (P<0.01) was an independent prognostic variable for the OS of HCC patients. Moreover, as per the ROC curve analysis, it had good diagnostic power as well. In addition, elevated expression of ENO1 was significantly correlated with the cell cycle and DNA replication pathway, consistent with its association with pro-proliferative genes such as MKI67, PCNA, CDK4, CDK2, and MELK.

Conclusion

ENO1 was markedly upregulated and was an oncogene-associated protein in HCC. It is a promising prognostic and diagnostic biomarker for HCC.

Metabolic profiling of copper-laden hepatolenticular degeneration model rats and the interventional effects of Gandou decoction using UPLC-Q-TOF/MS

The direct cause of hepatolenticular degeneration (HLD) is copper metabolic disorder caused by autosomal recessive inheritance. Gandou decoction (GDD), a classical traditional Chinese medicine formula, exhibits unambiguous therapeutic effect on HLD in China for decades. However, the mechanism of effect on HLD is not clear. With this purpose, the effects of copper content and histopathology inspection on the HLD rat model were investigated. Then, metabolomics study based on ultra-performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS^E) analysis and multivariate statistical analysis was adopted to further reveal the mechanism of action of GDD against HLD. The results showed that the characteristics of liver tissues after GDD treatment were significantly reversed, close to the control group, suggesting that GDD has a therapeutic effect on HLD. Furthermore, HLD interferes with 2 metabolites of the metabolic pathway in rats. Among them, up-regulation of Lactic acid, Tryptophan, Phenylalanine, Triacylglycerol and down-regulation of Linoleic acid, Alpha Linolenic acid, Phosphatidylcholine, Taurine is particularly significant. Analysis of metabolic pathways by a unique pathway analysis revealed significant changes in several pathways including lipid metabolism, amino metabolism and glucose metabolism in HLD. This study showed that GDD could provide satisfactory therapeutic effects on HLD and metabolomics study can be utilized to further understand the molecular mechanisms.