ABSTRACT: Infection with Hepatitis C Virus Depends on TACSTD2, a Regulator of Claudin-1 and Occludin Highly Downregulated in Hepatocellular Carcinoma [patient]
Project description:Infection with Hepatitis C Virus Depends on TACSTD2, a Regulator of Claudin-1 and Occludin Highly Downregulated in Hepatocellular Carcinoma
Project description:Infection with Hepatitis C Virus Depends on TACSTD2, a Regulator of Claudin-1 and Occludin Highly Downregulated in Hepatocellular Carcinoma [cell line]
Project description:Study goal is to disclose features of gene expressio profile of non-cancerous liver-infiltrating lymphocytes of type C hepatitis patients with hepatocellular carcinomas and tumor-infiltrating lymphocytes of type C hepatitis patients with hepatocellular carcinomas. Keywords: gene expression profile, non-cancerous liver-infiltrating lymphocytes, tumor-infiltrating lymphocytes, type C hepatitis, hepatocellular carcinoma Non-cancerous liver-infiltrating lymphocytes were obtained by laser capture microdissection from surgically resected liver tissues of 12 type C hepatitis patients with hepatocellular carcinoma. The mRNA was amplified and expression profile was comprehensively analyzed with reference RNA using oligo-DNA chip. Tumor-infiltrating lymphocytes were obtained by laser capture microdissection from surgically resected cancer tissues of 12 type C hepatitis patients with hepatocellular carcinoma. The mRNA was amplified and expression profile was comprehensively analyzed with reference RNA using oligo-DNA chip.
Project description:Study goal is to disclose features of gene expressio profile of non-cancerous liver-infiltrating lymphocytes of type C hepatitis patients with hepatocellular carcinomas and tumor-infiltrating lymphocytes of type C hepatitis patients with hepatocellular carcinomas. Keywords: gene expression profile, non-cancerous liver-infiltrating lymphocytes, tumor-infiltrating lymphocytes, type C hepatitis, hepatocellular carcinoma
Project description:HCV+ cells were detected by smiFISH on liver section of a patient with hepatocellular carcinoma. Clusters of HCV+ and HCV- cells were captured by laser microdissection and transriptomes analysed by RNA sequening. Highly sensitive single molecule fluorescent in situ hybridization applied to frozen tissue sections of a hepatitis C patient allowed the delineation of clusters of infected hepatocytes. Laser micro-dissection followed by RNAseq analysis of HCV-positive and -negative regions from the tumoral and non-tumoral tissues from the same patient revealed HCV-related deregulation of expression of genes in the tumor and in the non-tumoral tissue.
Project description:A quantitative label-free proteome analysis was performed using plasma samples from 22 hepatitis-C virus (HCV)-induced liver cirrhosis patients, 16 HCV-positive hepatocellular carcinoma patients with underlying cirrhosis and 18 healthy controls. Plasma microparticles (PMPS) were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS. A quantitative label-free proteome analysis was performed using plasma samples from 22 hepatitis-C virus (HCV)-induced liver cirrhosis patients, 16 HCV-positive hepatocellular carcinoma patients with underlying cirrhosis and 18 healthy controls. Plasma microparticles (PMPS) were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS.
Project description:A quantitative label-free proteome analysis was performed using plasma samples from 22 hepatitis-C virus (HCV)-induced liver cirrhosis patients, 16 HCV-positive hepatocellular carcinoma patients with underlying cirrhosis and 18 healthy controls. Plasma microparticles (PMPS) were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS. A quantitative label-free proteome analysis was performed using plasma samples from 22 hepatitis-C virus (HCV)-induced liver cirrhosis patients, 16 HCV-positive hepatocellular carcinoma patients with underlying cirrhosis and 18 healthy controls. Plasma microparticles (PMPS) were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS.
Project description:The potential significance of plasma extracellular vesicle-derived miRNAs in non-hepatitis B-, non-hepatitis C-related hepatocellular carcinoma as biomarker for the diseases was explored.
Project description:Using CapitalBio Technology Human CircRNA Array v2 (4x180K) microarray, we compared the expression of circular RNAs in the plasma from five hepatitis B virus-related hepatocellular carcinoma patients and five chronic hepatitis B patients.
Project description:Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight independent patient cohorts across the world. In addition, aiming to establish the real world applicability of a classification system, we profiled 118 formalin-fixed, paraffin-embedded tissues from an additional patient cohort. A total of 603 patients were analyzed, representing the major etiologies of HCC (hepatitis B and C) collected from Western and Eastern countries. We observed three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum alpha-fetoprotein levels. An analysis of the components of the signatures indicated that S1 reflected aberrant activation of the WNT signaling pathway, S2 was characterized by proliferation as well as MYC and AKT activation, and S3 was associated with hepatocyte differentiation. Functional studies indicated that the WNT pathway activation signature characteristic of S1 tumors was not simply the result of beta-catenin mutation but rather was the result of transforming growth factor-beta activation, thus representing a new mechanism of WNT pathway activation in HCC. These experiments establish the first consensus classification framework for HCC based on gene expression profiles and highlight the power of integrating multiple data sets to define a robust molecular taxonomy of the disease. Surgically resected 118 tumor tissues from patients with hepatocellular carcinoma (HCC)