MicroRNA Profile Predicts Recurrence of Hepatocellular Carcinoma in Milan Criteria Cases with Mild Liver Cirrhosis.
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ABSTRACT:
ORGANISM(S): Homo sapiens
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PROVIDER: S-DIXA-D-1060 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:In this study, we utilized microRNA expression profiling to assess risk of HCC recurrence after liver resection.
2011-02-08 | GSE21362 | GEO
Project description:In this study, we utilized microRNA expression profiling to assess risk of HCC recurrence after liver resection. We examined microRNA expression profiling in paired tumor and non-tumor liver tissues of 73 HCC patients with mild cirrhosis (Child-Pugh A/B) who satisfy Milan Criteria. We constructed prediction models of recurrence-free survival using Cox proportional hazard model and principal component analysis.
2011-02-08 | E-GEOD-21362 | biostudies-arrayexpress
Project description:OBJECTIVE: Hepatocellular carcinoma (HCC) is difficult to manage due to the high frequency of post-surgical recurrence. Early detection of the HCC recurrence after liver resection is important in making further therapeutic options, such as salvage liver transplantation. In this study, we utilized microRNA expression profiling to assess the risk of HCC recurrence after liver resection. METHODS: We examined microRNA expression profiling in paired tumor and non-tumor liver tissues from 73 HCC patients who satisfied the Milan Criteria. We constructed prediction models of recurrence-free survival using the Cox proportional hazard model and principal component analysis. The prediction efficiency was assessed by the leave-one-out cross-validation method, and the time-averaged area under the ROC curve (ta-AUROC). RESULTS: The univariate Cox analysis identified 13 and 56 recurrence-related microRNAs in the tumor and non-tumor tissues, such as miR-96. The number of recurrence-related microRNAs was significantly larger in the non-tumor-derived microRNAs (N-miRs) than in the tumor-derived microRNAs (T-miRs, P<0.0001). The best ta-AUROC using the whole dataset, T-miRs, N-miRs, and clinicopathological dataset were 0.8281, 0.7530, 0.7152, and 0.6835, respectively. The recurrence-free survival curve of the low-risk group stratified by the best model was significantly better than that of the high-risk group (Log-rank: P?=?0.00029). The T-miRs tend to predict early recurrence better than late recurrence, whereas N-miRs tend to predict late recurrence better (P<0.0001). This finding supports the concept of early recurrence by the dissemination of primary tumor cells and multicentric late recurrence by the 'field effect'. CONCLUSION: MicroRNA profiling can predict HCC recurrence in Milan criteria cases.
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Project description:BackgroundThe antitumor immune response may play a major role in the clinical outcome of hepatocellular carcinoma (HCC). We characterized the liver immune microenvironment by direct hybridization of RNA extracted from HCC and nontumorous tissues.MethodsRNA was extracted from frozen liver tissue samples of HCC (T; n = 30) and nontumorous tissues (NT; n = 33) obtained from 38 patients. Matched samples were available for 25 patients. The immune gene expression profile was analyzed with the nCounter GX Human Immunology v2 system (NanoString Technologies), which detects the expression levels of 579 immune response-related genes simultaneously.ResultsSince the immune gene expression profile of T and NT tissues was significantly different, the prognostic relevance of the liver immune microenvironment was evaluated in the T and NT samples separately. Unsupervised clustering detected two main clusters of immune gene expression both in T and in NT liver samples. In both cases, the expression clusters identified groups of patients with a significantly different median time to HCC recurrence (TTR) but similar overall survival. Based on T tissue, two groups with median TTR of 19 and 127 months, respectively, were detected (p < 0.005). Expression of genes related to T-cell activation was associated with longer TTR. The analysis of NT tissue discriminated subsets of patients with median TTR of 22 and 68 months (p < 0.05). In contrast to T tissue, a predominant inflammatory immune environment was associated with shorter TTR.ConclusionsImmune gene expression profiles predictive of TTR could be identified both in HCC and in adjacent cirrhotic tissues. Longer TTR was associated with overexpression in T tissue and downregulation in NT tissue of the immune response and of inflammation-related genes.
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Project description:Most hepatocellular carcinoma (HCC) patients occur on a background of liver cirrhosis, the molecular mechanisms of liver cirrhosis and its progression to HCC remain to be fully elucidated. Single cell differentiation trajectory analysis has been used in cell classification and tumor molecular typing, which correlated with disease progression and patient prognosis. Here we use cell differentiation trajectory analysis to investigate the relevance of liver cirrhosis and HCC. Single-cell RNA sequencing (scRNA-seq) data of liver cirrhosis and bulk RNA-seq and clinical data of HCC were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) for analysis. HCC samples were divided into three subtypes, based on differentiation-related genes (DRGs) of liver cirrhosis, each with a different expression profile and overall survival (OS). A two- DRGs (CD34 and RAMP3) based prognostic risk scoring (RS) signature was established which could differentiate OS between high-risk and low-risk groups. And expression levels of CD34 and RAMP3 were predominantly high in endothelial cells. By integrating the RS and clinicopathological features, a nomogram was constructed and can accurately predicted the 1-year, 3-years, and 5-years OS. In conclusion, cell differentiation trajectory of liver cirrhosis can predict the prognosis of HCC, and provides new perspectives on the mechanisms of progression of liver cirrhosis to HCC.
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Project description:BackgroundPredictive biomarkers for the recurrence of hepatocellular carcinoma (HCC) have great benefit in the selection of treatment options, including liver transplantation (LT), for HCC. The purpose of this study was to identify specific microRNAs (miRs) in exosomes from the serum of patients with recurrent HCC and to validate these molecules as novel biomarkers for HCC recurrence.MethodsWe employed microarray-based expression profiling of miRs derived from exosomes in the serum of HCC patients to identify a biomarker that distinguishes between patients with and without HCC recurrence after LT. This was followed by the validation in a separate cohort of 59 HCC patients who underwent living related LT. The functions and potential gene targets of the recurrence-specific miRs were analysed using a database, clinical samples and HCC cell lines.ResultsWe found that miR-718 showed significantly different expression in the serum exosomes of HCC cases with recurrence after LT compared with those without recurrence. Decreased expression of miR-718 was associated with HCC tumour aggressiveness in the validated cohort series. We identified HOXB8 as a potential target gene of miR-718, and its upregulation was associated with poor prognosis.ConclusionCirculating miRs in serum exosomes have potential as novel biomarkers for predicting HCC recurrence.
| S-EPMC4453648 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) has been associated with diabetes and obesity, but a possible connection with the metabolic syndrome (MetS) and its potential interaction with hepatitis and cirrhosis are open to discussion. Our previous investigations have shown that GGPPS1 plays a critical role during hyperinsulinism. In this report, the expression and distribution of GGPPS1 in liver cancer, and its clinical significance were investigated.Methods70 patients with hepatocellular carcinoma (HCC) were included in this study. Three different types of tissues from each HCC patient were assembled immediately after surgical resection: tumor-free tissue >5 cm far from tumor edge (TF), adjacent nonmalignant tissue within 2 cm (AT), and tissue from the tumor (TT). Normal liver tissues from 10 liver transplant donors served as healthy control (HC) while 10 patients with liver cirrhosis as cirrhosis control (CC). The expression and distribution of GGPPS1 were detected by immunohistochemistry, western blots, or real-time PCR. The relationship between the expression of GGPPS1 and clinic pathologic index were analyzed.ResultsWe found that GGPPS1 was intensified mainly in the cytoplasm of liver tumor cells. Both the expression of GGPPS1 mRNA and protein were upregulated in TT comparing to AT or TF. Meanwhile, HCC patients with cirrhosis had relative higher expression of GGPPS1. In addition, many pathologic characters show close correlation with GGPPS1, such as tumor stage, vessel invasion, and early recurrence.ConclusionGGPPS1 may play a critical role during the development of HCC from cirrhosis and is of clinical significance for predicting biological character of HCC.
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Project description:While we and others have uncovered and validated several genomic predictors for metastatic recurrences, a molecular or genomic predictor that can reliably identify high-risk patients for late de novo recurrence has not been firmly established. We analyzed previously reported gene expression data from human livers that underwent partial hepatectomy or transplantation, which were representative physiological conditions that trigger liver regeneration signals. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 hepatocellular carcinoma (HCC) patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for recurrence of HCC after surgery.
2014-11-03 | GSE39791 | GEO
Project description:While we and others have uncovered and validated several genomic predictors for metastatic recurrences, a molecular or genomic predictor that can reliably identify high-risk patients for late de novo recurrence has not been firmly established. We analyzed previously reported gene expression data from human livers that underwent partial hepatectomy or transplantation, which were representative physiological conditions that trigger liver regeneration signals. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 hepatocellular carcinoma (HCC) patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for recurrence of HCC after surgery. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 HCC patients who underwent surgical resection as the primary treatment.
2014-11-03 | E-GEOD-39791 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) exhibit essential regulatory functions related to cell growth, apoptosis, development and differentiation. Dysregulated expression of miRNAs is associated with a wide variety of human diseases. As such miRNA signatures are valuable as biomarkers for disease and for making treatment decisions. Hepatitis B virus (HBV) is a major risk factor for hepatocellular carcinoma (HCC). Here we screened for miRNAs in chronic HBV associated HCC.To determine the miRNAs in HCC occurrence associated with HBV infection, we analyzed global miRNA expression profiles in 12 pairs of HCC and adjacent matched non-HCC tissues from HBV-positive and HBV-negative patients using microarray analyses. The microarray result was validated by real-time PCR in 32 HBV-positive and 24 HBV-negative patient HCC samples. The potential candidate target genes of the miRNAs were predicted by miRWalk software. Genes simultaneously predicted as targets by two or more miRNAs were subjected to GO and KEGG pathway analysis. The miRNA regulatory network analysis was performed using the Ingenuity Pathway Analysis (IPA) software.Eight miRNAs (miR-223, miR-98, miR-15b, miR-199a-5p, miR-19b, miR-22, miR-451, and miR-101) were involved in HBV-unrelated HCC, 5 miRNAs (miR-98, miR-375, miR-335, miR-199a-5p, and miR-22) were involved in HBV infection, and 7 miRNAs (miR-150, miR-342-3p, miR-663, miR-20b, miR-92a-3p, miR-376c-3p and miR-92b) were specifically altered in HBV-related HCC. Gene Ontology and KEGG analyses predict that these HBV-related HCC miRNAs are involved in the regulation of: transcription, RNA polymerase II promoter, phosphorylation of proteins through MAPK signaling pathway, focal adhesion, and actin cytoskeleton. IPA analysis also suggest that these miRNAs act on AGO2, TP53, CCND1, and 11 other genes that significantly influence HCC occurrence and HBV infection.Our data indicates that the unique 7 miRNAs expression signature could be involved in the development HBV- related HCC.
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