Project description:The lack of biomarkers for patient stratification, taking into consideration tumor heterogeneity and innate drug resistance, represents a major issue for the management of hepatocellular carcinoma (HCC) patients, leading to treatment failure in a high percentage of cases. Moreover, the discovery of biomarkers is a clinical challenge for monitoring disease progression in patients undergoing targeted therapies. This study aimed to investigate the microRNA profile in rat HCC specimens compared to normal rat liver.
Project description:Background: Several studies have investigated the association of miRNAs with hepatocellular carcinoma (HCC) but the data are not univocal. Methods: We performed a microarray study of miRNAs in hepatitis C virus (HCV)-associated HCC and other liver diseases and healthy conditions. Results and Conclusions: The simultaneous comparison of different liver diseases and normal livers allowed the identification of 18 miRNAs exclusively expressed in HCV-associated HCC, with sensitivity and specificity values of diagnostic-grade. A total number of 76 liver specimens obtained from 43 patients were analyzed: 26 liver specimens obtained from 10 patients with HCV-associated HCC, including 9 specimens from the tumor area (HCC) and 17 specimens from the surrounding non-tumorous tissue affected by cirrhosis (HCC-CIR); 18 specimens from 10 patients with HCV-associated cirrhosis without HCC (CIR); 13 specimens from 4 patients with HBV-associated acute liver failure (ALF); 12 specimens from 12 liver donors (LD); and 7 from normal liver of 7 subjects who underwent hepatic resection for liver angioma (NL).
Project description:We attempted to development prediction methods for hepatocellular carcinoma (HCC) in chronic hepatitis C patients who have been successfully treated by anti-viral therapy. 2565 miRNAs in 43 liver tissues specimens were analyzed.
Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. This SuperSeries is composed of the following subset Series: GSE10140: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Training Set, Liver) GSE10141: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Training Set, HCC) GSE10142: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Validation Set) Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.
Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.
Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.
Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.
Project description:Liver transplantation (LT) is an optimal treatment for a selected group of hepatocellular carcinoma (HCC) patients. However, about 10%-25% of LT cases develop post-transplant HCC recurrence, which drastically reduces the long-term survival of HCC patients. This study gives an analysis of the recurrent HCC after LT and the corresponding primary tumor. Results provide insight into the molecular mechanisms underlying post-LT HCC recurrence.
Project description:<p>Hepatocellular carcinoma (HCC) accounts for 85-90% of primary liver cancers. We have focused on three major HCC etiologies:hepatitis C virus (HCV), hepatitis B virus (HBV), and nonviral causes. The onset and progression of cancer is driven by extensive rearrangement and mutation of the genome. We combined our capability to capture and enrich exome DNA with the next generation sequencing capacity to allow us to detect and characterize the somatic mutation profile of patients with HCC. Patient samples were collected by the Liver Center, Division of Abdominal Transplantation in the Baylor College of Medicine Department of Surgery. Sequencing of HCC is one of the NHGRI Center Initiated Projects in progress in the Human Genome Sequencing Center at Baylor College of Medicine.</p>
Project description:The role of chronic hepatitis C virus (HCV) in the pathogenesis of HCV-associated hepatocellular carcinoma (HCC) is not completely understood, particularly at the molecular level. We studied gene expression in normal, pre-malignant (cirrhosis), and tumor (HCC) liver tissues using Affymetrix GeneChips. Experiment Overall Design: Liver tissue samples were obtained from patients waiting for liver transplantation at one of the GR2HCC Centers. Additionally, normal liver and tumor samples were also obtained from the Liver Tissue Cell Distribution System. For each sample, RNA was extracted and hybridized to an Affymetrix GeneChip.