Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Liver
DISEASE(S): Cancer
PROVIDER: ST001152 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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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.
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Project description:The interactive pathway of the gut-liver axis underscores the significance of microbiome modulation in the pathogenesis and progression of various liver diseases, including hepatocellular carcinoma (HCC). This study aims to investigate the disparities in the composition and functionality of the hepatic microbiota between tumor tissues and adjacent normal liver tissues, and their implications in the etiology of HCC. We conducted a comparative analysis of the hepatic microbiome between adjacent normal liver tissues and tumor tissues from HCC patients. Samples were categorized according to the modified Union for International Cancer Control (mUICC) staging system into Non-tumor, mUICC stage I, mUICC stage II, and mUICC stage III groups. Microbial richness and community composition were analyzed, and phylogenetic profiles were examined to identify significantly altered microbial taxa among the groups. Predicted metabolic pathways were analyzed using PICRUSt2. Our analysis did not reveal significant differences in microbial richness and community composition with the development of HCC. However, phylogenetic profiling identified significantly altered microbial taxa among the groups. Sphingobium, known for degrading polychlorinated biphenyls (PCBs), exhibited a significantly negative correlation with clinical indices in HCC patients. Conversely, Sphingomonas, a gut bacterium associated with various liver diseases, showed a positive correlation. Predicted metabolic pathways suggested a correlation between atrazine degradation and valine, leucine, and isoleucine biosynthesis with mUICC stage and tumor size. Our results underscore the critical link between hepatic microbial composition and function and the HCC tumor stage, suggesting a potentially pivotal role in the development of HCC. These findings highlight the importance of targeting the hepatic microbiome for therapeutic strategies in HCC.
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Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most serious malignant tumors threatening human life with a high mortality rate. The liver regenerative capacity after hepatectomy in early-stage HCC patients is influenced by various factors, including surgical methods and energy metabolism. This study aims to provide a prognostic model based on genes related to liver regeneration that can predict the prognosis of non-tumor tissues in HCC patients.Patients and methodsA total of 584 non-tumor tissues from HCC patients were collected from three independent databases. Kaplan-Meier survival curves were used to identify prognostic liver-regeneration genes. Subsequently, a prognostic indicator, designated as the Liver Regeneration score (LR score), was determined using single-sample gene set enrichment analysis (ssGSEA). Independent cohorts were used to verify the relationship between LR score and prognosis in non-tumor tissues of HCC patients. Furthermore, a liver regeneration-related model was established to validate key genes identified through LASSO Cox regression analysis.ResultsWe constructed a gene set comprising 24 liver regeneration-related genes, and the LR score was utilized to predict the prognosis of HCC patients based on its levels in non-tumor tissues. In non-tumor tissues of HCC patients, higher LR scores were associated with improved prognosis. Higher LR scores in non-tumor tissues indicate improved liver metabolism in HCC patients, revealed by Enrichment analysis. LASSO Cox regression analysis identified two key genes, DHTKD1 (dehydrogenase E1 and transketolase domain containing 1) and PHYH (phytanoyl-CoA 2-hydroxylase), and higher expression levels of these genes in non-tumor tissues were correlated with better prognosis. The expression levels of these two genes also changed corresponding to the progression of liver regeneration.ConclusionIn summary, our study has introduced a novel LR gene signature for HCC patients, providing a predictive model for estimating clinical prognosis from non-tumor tissues. The LR score demonstrates promise as a reliable indicator for predicting overall survival in HCC.
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Project description:BackgroundDuring the last decade, investigations have focused on revealing genes or proteins that are involved in HCC carcinogenesis using either genetic or proteomic techniques. However, these studies are overshadowed by a lack of good internal reference standards. The need to identify "housekeeping" markers, whose expression is stable in various experimental and clinical conditions, is therefore of the utmost clinical relevance in quantitative studies. This is the first study employed 2-DE analysis to screen for potential reference markers and aims to correlate the abundance of these proteins with their level of transcript expression.MethodsA Chinese cohort of 224 liver tissues samples (105 cancerous, 103 non-tumourous cirrhotic, and 16 normal) was profiled using 2-DE analysis. Expression of the potential reference markers was confirmed by western blot, immunohistochemistry and real-time quantitative PCR. geNorm algorithm was employed for gene stability measure of the identified reference markers.ResultsThe expression levels of three protein markers beta-actin (ACTB), heat shock protein 60 (HSP60), and protein disulphide isomerase (PDI) were found to be stable using p-values (p > 0.99) as a ranking tool in all 224 human liver tissues examined by 2-DE analysis. Of high importance, ACTB and HSP 60 were successfully validated at both protein and mRNA levels in human hepatic tissues by western blot, immunohistochemistry and real-time quantitative PCR. In addition, no significant correlation of these markers with any clinicopathological features of HCC and cirrhosis was found. Gene stability measure of these two markers with other conventionally applied housekeeping genes was assessed by the geNorm algorithm, which ranked ACTB and HSP60 as the most stable genes among this cohort of clinical samples.ConclusionOur findings identified 2 reference markers that exhibited stable expression across human liver tissues with different conditions thus should be regarded as reliable reference moieties for normalisation of gene and protein expression in clinical research employing human hepatic tissues.
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