Project description:The aim of this study is to identify by whole genome microarray expression profiling a molecular signature of HCC samples that correlates with growth rate of the tumor and survival. This signature could eventually be used as prognostic marker. The samples were prospectively derived from hepatocellular carcinoma tissue as well as non-tumor tissue from the livers of the same patients. Expression of five genes (ANGPT2, NETO2,NR4A1,DLL4,ESM1) from this signature was re-evaluated in a validation cohort by real-time PCR, confirming its correlation with growth rate and survival.
Project description:The aim of this study is to identify by whole genome microarray expression profiling a molecular signature of HCC samples that correlates with growth rate of the tumor and survival. This signature could eventually be used as prognostic marker. The samples were prospectively derived from hepatocellular carcinoma tissue as well as non-tumor tissue from the livers of the same patients. Expression of five genes (ANGPT2, NETO2,NR4A1,DLL4,ESM1) from this signature was re-evaluated in a validation cohort by real-time PCR, confirming its correlation with growth rate and survival. The bioinformatical analysis of 161 microarray datasets were obtained from single color hybridization of human RNAs on Agilent Whole Human Genome Oligo Microarrays after T7 RNA amplification. For the purpose of this study, two discriminatory gene sets analysis were performed: up-regulated and down regulated in fast-growing tumors. For the discrimination between fast- and slow-growing tumors, the fastest quartile of the growth rate spectrum was compared with the three other quartiles. For a gene to be included, a significant discrimination (uncorrected p-value <0.01) and a 2-fold expression difference was required.
Project description:Genome-wide expression analysis of 228 hepatocellular carcinoma and 168 cirrhotic samples as part of a integrated study of gene expression and DNA-methylation de-regulation in patients with hepatocellular carcinoma Analysis of whole-genome transcriptome changes in human samples from hepatocellular carcinoma patients
Project description:This project completed the transcriptome analysis of 6 samples and obtained 12142010 reads Clean Data (after quality control sequencing data). The average clean data volume of each sample was 1833443535 bp , the Q30 base percentage was over 80%, and the GC content was 68.15. % To 46.53%. In this study, we used RNA sequencing and integrated bioinformatics approach to explore hub miRNA-mRNA interactions that are highly associated with hepatocellular carcinoma development. Our data indicated that miR-139-5p is closely related to the overall survival rate of hepatocellular carcinoma patients and directly combines with ITGB8 to regulate its expression.
Project description:The aim of this study is to identify by Next Generation Sequencing - RNA-seq profiling a molecular signature of Hepatocellular Carcinoma samples that correlates with survival. The samples were retrospectively derived from hepatocellular carcinoma tissue as well as non-tumor tissue from the livers of the same patients. The bioinformatical analysis of 32 pairs RNA-seq datasets were obtained from human RNAs on Illumina Hiseq-PE150. Due to the lack of biological sample duplication, this datasets were used hisat2 2.1.0 and gfold v1.1.4 for expression analysis to identify differences in gene expression between tumors and adjacent tissues. (including up- and down-regulation).
Project description:The prognosis of hepatocellular carcinoma (HCC) after surgery is poor due to its high recurrence rate. Oligonucleotide microarrays were used to analyze the gene expression of HCC patients with differing recurrent-free survival times following resection to see if gene expression can predict recurrence of HCC. Keywords: Disease states analysis
Project description:Background: PTEN loss contributes to the development of many cancers and is associated with both hepatocellular carcinoma and cholangiocarcinoma. The pathogenesis of these malignancies is unclear, but they are speculated to arise from common cellular origins. We explored the influence of secondary effects, like hypoxia signaling, through co-deletion of Pten and Vhl in a murine model.Methods: We used a CreER-linked keratin 18 mouse model to conditionally delete Pten, Vhl or both, evaluating the resultant tumors by histology and gene expression microarray. A cohort of human cholangiocarcinoma samples was evaluated for relationships between HIF-1a expression and clinical outcomes.Results: Both Pten deletion genotypes developed liver tumors, but with differing phenotypes. Pten deletion alone led to large, invasive tumors with widespread hepatosteatosis. Co-deletion of Pten and Vhl resulted in low tumor burden and reduced steatosis. Microarray analysis divided mouse tumors’ respective genotypes by gene expression. This gene expression profile grouped a human tumor cohort according to histologic type with the Pten deletion signature aligning with hepatocellular carcinoma, whereas the Pten; Vhl deletion signature associated with cholangiocarcinomas. In a human cholangiocarcinoma cohort, we observed correlation between HIF-1a expression and overall survival.Conclusions: Pten deletion leads to tumor formation and steatosis in mouse livers. Co-deletion of Vhl and Pten resulted in lower tumor burden with gene expression profiling suggesting a switch from hepatocellular expression features to an expression profile more consistent with cholangiocarinoma. A possible relation between HIF-1a expression and increased overall survival in human cholangiocarcinoma suggests that hypoxia signaling influences tumor phenotype. reference x sample
Project description:Galectin-9 suppresses growth of Li-7 cells, a cell line of human hepatocellular carcinoma, in xenograft model analysis. Micro RNA expression in xenografts of Li-7 cells, a cell line of hepatocellular carcinoma, with or without administration of galectin-9 were assessed.
