Comprehensive Metabolomic Search for Biomarkers to Differentiate Early Stage Hepatocellular Carcinoma from Cirrhosis.
Ontology highlight
ABSTRACT:
SUBMITTER: Kim DJ
PROVIDER: S-EPMC6826937 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundHepatocellular 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.
| S-EPMC8772637 | biostudies-literature
Project description:BackgroundMolecular changes in HCC development are largely unknown. As the liver plays a fundamental role in the body's metabolism, metabolic changes are to be expected.AimsWe aimed to identify metabolomic changes in HCC in comparison to liver cirrhosis (LC) patients, which could potentially serve as novel biomarkers for HCC diagnosis and prognosis.MethodsMetabolite expression from 38 HCC from the SORAMIC trial and 32 LC patients were analyzed by mass spectrometry. Metabolites with significant differences between LC and HCC at baseline were analyzed regarding expression over follow-up. In addition, association with overall survival was tested using univariate Cox proportional-hazard analysis.Results41 metabolites showed differential expression between LC and HCC patients. 14 metabolites demonstrated significant changes in HCC patients during follow-up. Campesterol, lysophosphatidylcholine, octadecenoic and octadecadienoic acid, and furoylglycine showed a differential expression in the local ablation vs. palliative care group. High expression of eight metabolites (octadecenoic acid, 2-hydroxybutyrate, myo-inositol, isocitrate, erythronic acid, creatinine, pseudouridine, and erythrol) were associated with poor overall survival. The association between poor OS and octadecenoic acid and creatinine remained statistically significant even after adjusting for tumor burden and LC severity.ConclusionOur findings give promising insides into the metabolic changes during HCC carcinogenesis and provide candidate biomarkers for future studies. Campesterol and furoylglycine in particular were identified as possible biomarkers for HCC progression. Moreover, eight metabolites were detected as predictors for poor overall survival.
| S-EPMC11258188 | biostudies-literature
Project description:BackgroundLiver cirrhosis is one of the major drivers of hepatocellular carcinoma (HCC). In the present study, we aimed to identify and validate new biomarker for early prediction of HCC development in early-stage cirrhosis patients.MethodsmRNA expression and clinical parameters of GSE63898, GSE89377, GSE15654, GSE14520, and TCGA-HCC cohort and ICGC-HCC cohort were downloaded for analysis. Wilcoxon test was performed to identify DEGs. Univariate and multivariate Cox regression analysis were used to develop the risk signature, and ROC analysis was performed to analyze the predictive accuracy and sensitivity of the risk signature.ResultsThere were 42 DEGs (including 28 upregulated genes and 14 downregulated genes) found in early-stage liver cirrhosis patients before developing HCC from GSE1565442. Then, a risk signature consisting of 8 DEGs could effectively classify early-stage cirrhosis patients into high-risk group with shorter HCC development time and low-risk group with longer HCC development time from GSE15654. Multivariate Cox analysis indicated that the risk signature was an independent prognostic factor for the prediction of HCC development and ROC analysis showed that the signature exhibited good predictive efficiency in predicting 2-, 5-, and 10-year HCC development. Mechanistically, significantly higher proportions of CD8 T cells were found to be enriched in cirrhosis patients with low risk score, and higher CD8 T cells were associated with longer HCC development time. Besides, the signature was an independent prognostic factor for poorer prognosis of early-stage liver cirrhosis patients of GSE15654. Moreover, the signature could also separate HCC patients from healthy controls and was also associated with the poorer prognosis of HCC patients from three HCC cohorts. Finally, we also identified HDAC inhibitors, such as trichostatin A, to be a potential chemopreventive treatment for the prevention of HCC development by targeting risk signature based on CMap analysis.ConclusionA risk signature was developed and validated for early prediction of HCC development, which may be a useful tool to set up individualized follow-up interval schedules.
| S-EPMC8318773 | biostudies-literature
Project description:Chronic hepatitis B virus (CHB) infection is one of the primary risk factors associated with the development of hepatocellular carcinoma (HCC). Despite having been extensively studied, diagnosing early-stage HCC remains challenging, and diagnosed patients have a poor (3-5%) survival rate. Identifying new approaches to detect changes in the serum metabolic profiles of patients with CHB and liver cirrhosis (LC) may provide a valuable approach to better detect HCC at an early stage when it is still amenable to treatment, thereby improving patient prognosis and survival. In the present study, we, therefore, employed a liquid chromatography-mass spectrometry (LC-MS)-based approach to evaluate the serum metabolic profiles of 30 CHB patients, 29 LC patients, and 30 HCC patients. We then employed appropriate statistical methods to identify those metabolites that were best able to distinguish HCC cases from LC and CHB controls. A mass-based database was then used to putatively identify these metabolites. We then confirmed the identities of a subset of these metabolites through comparisons with the MS/MS fragmentation patterns and retention times of reference standards. The serum samples were then reanalyzed to quantify the levels of these selected metabolites and of other metabolites that have previously been identified as potential HCC biomarkers. Through this approach, we observed clear differences in the metabolite profiles of the CHB, LC, and HCC patient groups in both positive- and negative-ion modes. We found that the levels of taurodeoxy cholic acid (TCA) and 1,2-diacyl-3-β-d-galactosyl-sn-glycerol rose with the progression from CHB to LC to HCC, whereas levels of 5-hydroxy-6E,8Z,11Z,14Z,17Z-eicosapentaenoic acid, and glycyrrhizic acid were gradually reduced with liver disease progression in these groups. The ROC analysis showed that taurodeoxy cholic acid (TCA), 1,2-diacyl-3-β-d-galactosyl-sn-glycerol, 5-hydroxy-6E,8Z,11Z,14Z,17Z-eicosapentaenoic acid, and glycyrrhizic acid had a diagnosis performance with liver disease progression. These four metabolites have a significant correlation with alpha fetal protein (AFP) level and age. Our results highlight novel metabolic biomarkers that have the potential to be used for differentiating between CHB, LC, and HCC patients, thereby facilitating the identification and treatment of patients with early-stage HCC.
| S-EPMC7818305 | biostudies-literature
Project description:Background: Metabolomics plays an important role in providing insight into the etiology and mechanisms of hepatocellular carcinoma (HCC). This is accomplished by a comprehensive analysis of patterns involved in metabolic alterations in human specimens. This study compares the levels of plasma metabolites in HCC cases versus cirrhotic patients and evaluates the ability of candidate metabolites in distinguishing the two groups. Also, it investigates the combined use of metabolites and clinical covariates for detection of HCC in patients with liver cirrhosis.Methods: Untargeted analysis of metabolites in plasma from 128 subjects (63 HCC cases and 65 cirrhotic controls) was conducted using gas chromatography coupled to mass spectrometry (GC-MS). This was followed by targeted evaluation of selected metabolites. LASSO regression was used to select a set of metabolites and clinical covariates that are associated with HCC. The performance of candidate biomarkers in distinguishing HCC from cirrhosis was evaluated through a leave-one-out cross-validation based on area under the receiver operating characteristics (ROC) curve.Results: We identified 11 metabolites and three clinical covariates that differentiated HCC cases from cirrhotic controls. Combining these features in a panel for disease classification using support vector machines (SVM) yielded better area under the ROC curve compared with alpha-fetoprotein (AFP).Conclusions: This study demonstrates the combination of metabolites and clinical covariates as an effective approach for early detection of HCC in patients with liver cirrhosis.Impact: Further investigation of these findings may improve understanding of HCC pathophysiology and possible implication of the metabolites in HCC prevention and diagnosis. Cancer Epidemiol Biomarkers Prev; 26(5); 675-83. ©2016 AACR.
| S-EPMC5413442 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is a global health problem associated with chronic liver disease. Its pathogenesis varies according to the underlying etiological factors, although in most cases it develops from liver cirrhosis. The disease progression is accompanied by pathological angiogenesis, which is a prerequisite that favors the development of HCC. This study aims at contributing to our understanding of the role of angiogenic factors in the progression of liver disease. For this purpose, we evaluate the clinical significance of serum angiogenic markers (VEGF, Ang-1, Ang-2, the angiopoietin receptor Tie1/2, HGF, and PECAM-1) first in cirrhotic and HCC patients separately, and then comparing cirrhotic patients with and without HCC. We enrolled 62 patients, out of whom 33 were diagnosed with HCC and 29 with liver cirrhosis without signs of neoplasia. Patients underwent venous blood sampling before and after receiving treatments for the diagnosed disease. Serum markers were evaluated using ELISA assays for Tie1 and the Bio-Plex Multiplex system for the remaining ones. Biomarker levels were investigated as a function of clinical scores for disease staging (MELD and Fibrosis Index, FI). In cirrhotic patients, Ang-1 and Ang-2 correlate with MELD (ρAng-1 = -0.73, p = 2E-5) and FI (ρAng-1 = -0.52, p = 7E-3, ρAng-2 = 0.53, p = 3E-3). A reduction of Ang-2 levels (p = 0.047) and of the Ang-2/Ang-1 ratio (p = 0.031) is observed in cirrhotic patients diagnosed with viral hepatitis after antiviral treatments. In HCC patients, Ang-1 negatively correlates with FI (ρ = -0.63, p = 1E-4), and PECAM-1 positively correlates with MELD (ρ = 0.44, p = 0.01). A significant Ang-1 reduction was observed in deceased patients during the study compared to ones who survived (p = 0.01). In HCC patients, VEGF levels were increased after tumor treatment (p = 0.037). Notably, HGF levels in cirrhotic patients with HCC are significantly raised (p = 0.017) compared to that in those without HCC. Our results suggest that serum angiogenic markers, with emphasis on Ang-1/2, can contribute to the development of quantitative tools for liver disease staging and therapy monitoring. The comparison between cirrhotic patients with and without HCC suggests that HGF levels are potentially useful for monitoring the insurgence of HCC after a cirrhosis diagnosis. High Ang-1 levels in HCC patients appear to have a protective role as well as prognostic significance.
| S-EPMC8750498 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) ranks third in overall global cancer-related mortality. Symptomatic presentation often means advanced disease where potentially curative treatment options become very limited. Numerous international guidelines propose the routine monitoring of those with the highest risk factors for the condition in order to diagnose potential tumourigenesis early. To aid this, the fields of metabonomic- and proteomic-based biomarker discovery have applied advanced tools to identify early changes in protein and metabolite expression in HCC patients vs controls. With robust validation, it is anticipated that from these candidates will rise a high-performance non-invasive test able to diagnose early HCC and related conditions. This review gathers the numerous markers proposed by studies using mass spectrometry and proton nuclear magnetic resonance spectroscopy and evaluates areas of consistency as well as discordance.
| S-EPMC4385954 | biostudies-literature
Project description:Coronary atherosclerosis (CAS) is the pathogenesis of coronary heart disease, which is a prevalent and chronic life-threatening disease. Initially, this disease is not always detected until a patient presents with seriously vascular occlusion. Therefore, new biomarkers for appropriate and timely diagnosis of early CAS is needed for screening to initiate therapy on time. In this study, we used an untargeted metabolomics approach to identify potential biomarkers that could enable highly sensitive and specific CAS detection. Score plots from partial least-squares discriminant analysis clearly separated early-stage CAS patients from controls. Meanwhile, the levels of 24 metabolites increased greatly and those of 18 metabolites decreased markedly in early CAS patients compared with the controls, which suggested significant metabolic dysfunction in phospholipid, sphingolipid, and fatty acid metabolism in the patients. Furthermore, binary logistic regression showed that nine metabolites could be used as a combinatorial biomarker to distinguish early-stage CAS patients from controls. The panel of nine metabolites was then tested with an independent cohort of samples, which also yielded satisfactory diagnostic accuracy (AUC?=?0.890). In conclusion, our findings provide insight into the pathological mechanism of early-stage CAS and also supply a combinatorial biomarker to aid clinical diagnosis of early-stage CAS.
| S-EPMC5603568 | biostudies-literature
Project description:Background & aimsThe effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of current screening modalities.MethodsWe developed a multicenter prospective cohort of patients with cirrhosis undergoing surveillance with MRI and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up.ResultsWe identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who did not develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, and PNPLA3 and TMS6SF2 single nucleotide polymorphisms, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top six variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC 0.88, 95% CI 0.83-0.93). Finally, 23 metabolites distinguished Cases with LI-RADS-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases.ConclusionsThis study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as biomarkers of HCC risk, and microbiota-derived metabolites as contributors to HCC development.Impact and implicationsThe effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited. There is an urgent need for improvement in risk stratification and new screening modalities, particularly blood biomarkers. Longitudinal collection of paired blood samples and MRI images from patients with cirrhosis is particularly valuable in assessing how early blood and imaging markers become positive during the period when lesions are observed to obtain a diagnosis of HCC. We generated a multicenter prospective cohort of patients with cirrhosis under surveillance with contrast MRI, applied untargeted metabolomics on 612 serum samples from 203 patients and identified metabolites associated with risk of HCC development. Such biomarkers may significantly improve early-stage HCC detection for patients with cirrhosis undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality.
| S-EPMC11321296 | biostudies-literature
Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential serum biomarkers in patients with early stage ESCC.MethodsSixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using 1H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers.ResultsUsing OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence.Conclusions1H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.
| S-EPMC6886491 | biostudies-literature