Gas chromatography/time-of-flight mass spectrometry-based metabonomics of hepatocarcinoma in rats with lung metastasis: elucidation of the metabolic characteristics of hepatocarcinoma at formation and metastasis

Urinary biomarkers for hepatocellular carcinoma: current knowledge for clinicians

Hepatocellular carcinoma (HCC) is the most predominant primary liver cancer, causing many illnesses and deaths worldwide. The insidious clinical presentation, difficulty in early diagnosis, and the highly malignant nature make the prognosis of HCC extremely poor. The complex and heterogeneous pathogenesis of HCC poses significant challenges to developing therapies. Urine-based biomarkers for HCC, including diagnostic, prognostic, and monitoring markers, may be valuable supplements to current tools such as serum α-fetoprotein (AFP) and seem promising for progress in precision medicine. Herein, we reviewed the major urinary biomarkers for HCC and assessed their potential for clinical application. Molecular types, testing platforms, and methods for building multimolecule models in the included studies have shown great diversity, thus providing abundant novel tools for future clinical transformation and applications.

Metabolomics and integrated network pharmacology analysis reveal SNKAF decoction suppresses cell proliferation and induced cell apoptisis in hepatocellular carcinoma via PI3K/Akt/P53/FoxO signaling axis

BACKGROUND

There is no comprehensive treatment method for hepatocellular carcinoma (HCC); hence, research and development are still focused on systemic therapies, including drugs. Sinikangai fang (SNKAF) decoction, a classic Chinese herbal prescription, has been widely used to treat liver cancer. However, there is no research on its core active component and target.

METHODS

Mouse models were established to measure the anticancer effect of SNKAF decoction on HCC. Further, we investigated the effect of SNKAF decoction on inhibition of hepatoma cells proliferation using cell viability, cloning and invasion assays in vitro. The components of SNKAF were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and TCM@Taiwan database. Metabolomic analysis was used to identify the potential genes and pathways in HCC treated with SNKAF decoction. Then, the expression of phosphoinositide 3-kinase (PI3K), Akt, P53, FoxO proteins of the potential signal pathways were detected using Western blot.

RESULTS

The animal experiments showed that SNKAF decoction inhibited tumor growth (P < 0.05) and induced no weight loss in the mice. In vitro data showed that HCCLM3 and MHCC97H cell proliferation was inhibited by SNKAF serum in a time- and concentration dependent manner. Further combined analysis network pharmacology with metabonomics showed that 217 target genes overlapped. The core target genes included BCL2, MCL1, Myc, PTEN, gsk3b, CASP9, CREB1, MDM2, pt53 and CCND1. Cancer-associated pathways were largely involved in SNKAF mechanisms, including P53, FoxO, and PI3K/Akt signaling pathways, which are closely related to induced-tumor cell apoptosis. In addition, Western bolt verified that 10% SNKAF serum significantly affected the main proteins of PI3K/Akt/P53/FoxO signaling pathway in both cell lines.

CONCLUSION

SNKAF decoction-containing serum inhibited HCCLM3 and MHCC97H cell proliferation, migration, invasion, and induced-tumor cell apoptosis in-vivo. We confirmed that SNKAF decoction is a promising alternative treatments for HCC patients.

Gas chromatography/mass spectrometry analysis of organic acid profiles in human serum: A protocol of direct ultrasound-assisted derivatization

RATIONALE

Low-molecular-weight organic acids that generally contain one to three carboxyl groups are involved in many important biological processes; therefore, it is important to develop a quantitative method for analyzing organic acids in serum in order to allow an evaluation of metabolic changes. In this study, we evaluated a protocol for detecting 26 organic acids in serum based on ultrasound-assisted derivatization by gas chromatography/mass spectrometry (GC/MS).

METHODS

Serum samples were prepared using ultrasound-assisted silane derivatization before GC/MS analysis to quantify concentrations of organic acids. Additionally, we investigated the variables affecting derivatization yields, including the extraction solvent, derivatization reagents, and derivatization conditions (reaction temperature, duration, and sonication parameters). The protocol was ultimately applied to detect organic acid profiles related to obesity.

RESULTS

We used acetone as the extraction solvent and determined suitable derivatization conditions, as follows: BSTFA + 1% TMCS, 50°C, 10 min, and 100% ultrasound power. The protocol showed satisfactory linearity (r = 0.9958-0.9996), a low limit of detection (0.04-0.42 μmol/L), good reproducibility (coefficient of variation (CV) %: 0.32-13.76%), acceptable accuracy (recovery: 82.97-114.96%), and good stability within 5 days (CV%: 1.35-12.01% at room temperature, 1.24-14.09% at 4°C, and 1.01-11.67% at -20°C). Moreover, the protocol was successfully applied to obtain the organic acid profiles from obese and healthy control subjects.

CONCLUSIONS

We identified and validated a protocol for ultrasound-assisted derivatization prior to GC/MS analysis for detecting 26 kinds of organic acids in serum. The results suggest the efficacy of this protocol for clinical applications to determine metabolic changes related to fluctuations in organic acid profiles.

Animal Models: A Useful Tool to Unveil Metabolic Changes in Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma (HCC) represents an important health problem. At the moment, systemic therapies offered only modest clinical benefits. Thus, HCC represents a cancer extremely difficult to treat, and therapeutic breakthroughs are urgently needed. Metabolic reprogramming of neoplastic cells has been recognized as one of the core hallmarks of cancer. Experimental animal models represent an important tool that allows to investigate metabolic changes underlying HCC development and progression. In the present review, we characterize available rodent models of hepatocarcinogenesis. Moreover, we discuss the possibility that pharmacological targeting of Warburg metabolism may represent an additional tool to improve already available therapeutic approaches for HCC.

Abstract

Hepatocellular carcinoma (HCC) is one the most frequent and lethal human cancers. At present, no effective treatment for advanced HCC exist; therefore, the overall prognosis for HCC patients remains dismal. In recent years, a better knowledge of the signaling pathways involved in the regulation of HCC development and progression, has led to the identification of novel potential targets for therapeutic strategies. However, the obtained benefits from current therapeutic options are disappointing. Altered cancer metabolism has become a topic of renewed interest in the last decades, and it has been included among the core hallmarks of cancer. In the light of growing evidence for metabolic reprogramming in cancer, a wide number of experimental animal models have been exploited to study metabolic changes characterizing HCC development and progression and to further expand our knowledge of this tumor. In the present review, we discuss several rodent models of hepatocarcinogenesis, that contributed to elucidate the metabolic profile of HCC and the implications of these changes in modulating the aggressiveness of neoplastic cells. We also highlight the apparently contrasting results stemming from different animal models. Finally, we analyze whether these observations could be exploited to improve current therapeutic strategies for HCC.

A New Role for the Spleen: Aggravation of the Systemic Inflammatory Response in Rats with Severe Acute Pancreatitis

Little is known about the role of the spleen in mediating systemic inflammatory responses in severe acute pancreatitis (SAP). We investigated the role played by the spleen in rats after SAP induction. Splenectomy was performed at designated time points after SAP induction. Pancreatic tissue and serum samples were collected and subjected to histologic, immunohistochemical, and immunologic analyses. After SAP induction, the splenic immune response was enhanced during SAP progression, as shown by the increased diameter of the splenic periarterial lymphatic sheath and the thickness of the splenic marginal zone. Rats with splenectomy developed acute pancreatitis more slowly than rats without splenectomy. In addition, pancreatic tissues of rats with splenectomy contained lower levels of serum amylase, tumor necrosis factor-α, and IL-6 and exhibited less acinar cell death, leukocyte infiltration, and interstitial edema than those of rats without splenectomy. Compared with splenectomy alone, cotreatment with splenectomy and the administration of splenic cells originating from a rat with SAP 12 hours after induction increased systemic inflammation in SAP rats. Splenic factors exacerbated SAP-associated liver and lung injury and accentuated intestinal mucosal barrier dysfunction. Splenectomy altered the serum cytokine profile in rats with SAP. In a rat model of SAP, the spleen exacerbated the systematic inflammatory responses and injury to multiple organs, indicating a new role for the spleen in SAP.

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

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

Utilization of metabonomics to identify serum biomarkers in murine H22 hepatocarcinoma and deduce antitumor mechanism of Rhizoma Paridis saponins

Murine H22 hepatocarcinoma model is so popular to be used for the preclinical anticancer candidate's evaluation. However, the metabolic biomarkers of this model were not identified. Meanwhile, Rhizoma Paridis saponins (RPS) as natural products have been found to show strong antitumor activity, while its anti-cancer mechanism is not clear. To search for potential metabolite biomarkers of this model, serum metabonomics approach was applied to detect the variation of metabolite biomarkers and the related metabolism genes and signaling pathway were used to deduce the antitumor mechanisms of RPS. As a result, ten serum metabolites were identified in twenty-four mice including healthy mice, non-treated cancer mice, RPS-treated cancer mice and RPS-treated healthy mice. RPS significantly decreased tumor weight correlates to down-regulating lactate, acetate, N-acetyl amino acid and glutamine signals (p < 0.05), which were marked metabolites screened according to the very important person (VIP), loading plot and receiver operating characteristic curve (ROC) tests. For the analysis of metabolic enzyme related genes, RPS reversed the aerobic glycolysis through activating tumor suppressor p53 and PTEN, and suppressed FASN to inhibit lipogenesis. What's more, RPS repressed Myc and GLS expression and decreased glutamine level. The regulating PI3K/Akt/mTOR and HIF-1α/Myc/Ras networks also participated in these metabolic changes. Taken together, RPS suppressed ATP product made the tumor growth slow, which indicated a good anti-cancer effect and new angle for understanding the mechanism of RPS. In conclusion, this study demonstrated that the utility of (1)H NMR metabolic profiles taken together with tumor weight and viscera index was a promising screening tool for evaluating the antitumor effect of candidates. In addition, RPS was a potent anticancer agent through inhibiting cancer cellular metabolism to suppress proliferation in hepatoma H22 tumor murine, which promoted the application of RPS in the future.

Metabolic changes in rat urine after acute paraquat poisoning and discriminated by support vector machine

Paraquat is quick-acting and non-selective, killing green plant tissue on contact; it is also toxic to human beings and animals. In this study, we developed a urine metabonomic method by gas chromatography-mass spectrometry to evaluate the effect of acute paraquat poisoning on rats. Pattern recognition analysis, including both partial least squares discriminate analysis and principal component analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the levels of benzeneacetic acid and hexadecanoic acid of the acute paraquat poisoning group (intragastric administration 36 mg/kg) increased, while the levels of butanedioic acid, pentanedioic acid, altronic acid decreased. Based on these urinary metabolomics data, support vector machine was applied to discriminate the metabolomic change of paraquat groups from the control group, which achieved 100% classification accuracy. In conclusion, metabonomic method combined with support vector machine can be used as a useful diagnostic tool in paraquat-poisoned rats.

Low-dose splenic radiation inhibits liver tumor development of rats through functional changes in CD4+CD25+Treg cells

The increased number of CD4(+)CD25(+)Treg cells in tumor local and peripheral splenic tissues is related to the low immune function as well as to tumor recurrence and metastasis. Our pre-clinical studies showed that low-dose radiation (LDR) of the spleen in liver cancer patients significantly improves immune functions. However, the molecular mechanisms of such radiation remained ill defined. This study explores the role of CD4(+)CD25(+)Treg cells in radiation-induced immunomodulatory effects. Using the diethylnitrosamine (DEN)-induced rat liver tumor model and in vitro cell experiments, the percentage of CD4(+)CD25(+)Treg/CD4(+) cells in the blood and the expressions of Foxp3(+), IL-10, TGF-β, and cytotoxic T lymphocyte-associated antigen-4(CTLA-4) in spleen and liver tumors significantly decreased after LDR of the spleen in rats with liver cancer. The tumors became smaller than those in the non-radiated group, with both showing a parallel relation. Flow cytometry and MTT results revealed that LDR failed to inhibit CD4(+)CD25(+)Treg cell proliferation. Conversely, apoptosis was reduced and proliferation was stimulated. This process also changed CTLA-4 molecule expression on the surfaces of CD4(+)CD25(+)Treg cells and reduced their inhibitory function against CD4(+)CD25(-)T cell proliferation, and the suppression function of CD4(+)CD25(+)Treg cells was further weakened with the introduction of the CTLA-4 inhibitor. Findings demonstrate that the reduction of CTLA-4 expression on the CD4(+)CD25(+)Treg cell surface and the further inhibition of cell function may be considered as important regulators of LDR-induced immunomodulatory effects. This study provides experimental evidence to elucidate the immune enhancement induced by this process and presents a novel method for liver cancer immunotherapy.

Metabolomic Analysis of Liver Tissue from the VX2 Rabbit Model of Secondary Liver Tumors

Purpose. The incidence of liver neoplasms is rising in USA. The purpose of this study was to determine metabolic profiles of liver tissue during early cancer development. Methods. We used the rabbit VX2 model of liver tumors (LT) and a control group consisting of sham animals implanted with Gelfoam into their livers (LG). After two weeks from implantation, liver tissue from lobes with and without tumor was obtained from experimental animals (LT+/LT−) as well as liver tissue from controls (LG+/LG−). Peaks obtained by Gas Chromatography-Mass Spectrometry were subjected to identification. 56 metabolites were identified and their profiles compared between groups using principal component analysis (PCA) and a mixed-effect two-way ANOVA model. Results. Animals recovered from surgery uneventfully. Analyses identified a metabolite profile that significantly differs in experimental conditions after controlling the False Discovery Rate (FDR). 16 metabolites concentrations differed significantly when comparing samples from (LT+/LT−) to samples from (LG+/LG−) livers. A significant difference was also shown in 20 metabolites when comparing samples from (LT+) liver lobes to samples from (LT−) liver lobes. Conclusion. Normal liver tissue harboring malignancy had a distinct metabolic signature. The role of metabolic profiles on liver biopsies for the detection of early liver cancer remains to be determined.

The metabolomic window into hepatobiliary disease

The emergent discipline of metabolomics has attracted considerable research effort in hepatology. Here we review the metabolomic data for non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), cirrhosis, hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), alcoholic liver disease (ALD), hepatitis B and C, cholecystitis, cholestasis, liver transplantation, and acute hepatotoxicity in animal models. A metabolomic window has permitted a view into the changing biochemistry occurring in the transitional phases between a healthy liver and hepatocellular carcinoma or cholangiocarcinoma. Whether provoked by obesity and diabetes, alcohol use or oncogenic viruses, the liver develops a core metabolomic phenotype (CMP) that involves dysregulation of bile acid and phospholipid homeostasis. The CMP commences at the transition between the healthy liver (Phase 0) and NAFLD/NASH, ALD or viral hepatitis (Phase 1). This CMP is maintained in the presence or absence of cirrhosis (Phase 2) and whether or not either HCC or CCA (Phase 3) develops. Inflammatory signalling in the liver triggers the appearance of the CMP. Many other metabolomic markers distinguish between Phases 0, 1, 2 and 3. A metabolic remodelling in HCC has been described but metabolomic data from all four Phases demonstrate that the Warburg shift from mitochondrial respiration to cytosolic glycolysis foreshadows HCC and may occur as early as Phase 1. The metabolic remodelling also involves an upregulation of fatty acid β-oxidation, also beginning in Phase 1. The storage of triglycerides in fatty liver provides high energy-yielding substrates for Phases 2 and 3 of liver pathology. The metabolomic window into hepatobiliary disease sheds new light on the systems pathology of the liver.

Tissue metabolomics of hepatocellular carcinoma: tumor energy metabolism and the role of transcriptomic classification

Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up- and down-regulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding nontumor liver tissues from the same patients was investigated by gas chromatography-mass spectrometry (GCMS)-based metabolomics. HCC was characterized by ∼2-fold depletion of glucose, glycerol 3- and 2-phosphate, malate, alanine, myo-inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a 4-fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3-phosphate, malate, myo-inositol, or stearic acid tissue concentrations were found, suggesting that the Wnt/β-catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid, suggesting that the high serum α-fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism.

CONCLUSION

Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process.

Estimation of psychological stress in humans: a combination of theory and practice

Stress has long been known to increase susceptibility to health disorders. In 2009, American Psychological Association further established association of stress to serious health problems. However, a quantitative and accurate way to evaluate and estimate stress status of individuals is still a big challenge. It has been shown, in large animal models using cattle, that psychological stress can be quantified as well as disease susceptibility could be predicted through biomarker discovery. Taking cue from those studies, we have evaluated and estimated psychological stress level of individuals theoretically and validated experimentally. Various biomarkers have also been identified which can be associated to psychological stress to predict stress status of unknown individuals.

Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the commonest primary hepatic malignancy and the third most common cause of cancer-related death worldwide. Incidence remains highest in the developing world and is steadily increasing across the developed world. Current diagnostic modalities, of ultrasound and α-fetoprotein, are expensive and lack sensitivity in tumor detection. Because of its asymptomatic nature, HCC is usually diagnosed at late and advanced stages, for which there are no effective therapies. Thus, biomarkers for early detection and molecular targets for treating HCC are urgently needed. Emerging high-throughput metabolomics technologies have been widely applied, aiming at the discovery of candidate biomarkers for cancer staging, prediction of recurrence and prognosis, and treatment selection. Metabolic profiles, which are affected by many physiological and pathological processes, may provide further insight into the metabolic consequences of this severe liver disease. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand HCC phenotypes. The power of metabolomics allows an unparalleled opportunity to query the molecular mechanisms of HCC. This technique-driven review aims to demystify the metabolomics pathway, while also illustrating the potential of this technique, with recent examples of its application in HCC.

Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry

Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry, and matrix assisted laser desorption ionization-mass spectrometry. Then, the findings of studies about GC-MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.