Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses.

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:Introduction: Hepatocellular carcinoma (HCC) is one of the most aggressive solid tumors and oncogenic pathways (e.g Akt, IGF signaling) are often activated in high proliferating HCC. Among several genetic alterations, epigenetic changes seem to be involved in the development and progression of HCC. DNA hypermethylation of promoter regions is almost always associated with transcriptional silencing and can lead to inactivation of tumor suppressor genes (TSG) in cancer cells. Aim: (1) To identify genes differently methylated in a subclass of HCC associated with proliferation and, (2) To correlate methylation changes with activation of molecular pathways. Methods: gDNA of 20 HCC, 8 cirrhotic and 8 normal liver samples was extracted and the methylation status was detected by the Illumina HumanMethylation27 BeadChip and immunohistochemistry of p-AKT, pIGF IR, p-S6 was analyzed. Results: Unsupervised clustering clearly classified normal livers, cirrhosis and HCC in 3 different groups. 961 genes were significantly hypermethylated in HCC compared to cirrhotic and 3942 genes showed hypermethylation in cirrhotic compared to normal liver tissue. 163 genes showed stepwise significant hypermethylation from normal to cirrhotic to HCC, including well described (p16, SOCS2, SFRP5, RBP1) and potential (SRD5A2, PCDH8, IGF-1R, UCHL1) TSGs, and the miR-10a. 133 genes were specifically hypermethylated in HCC. Among them the transcription factors GATA2, DLX1, and KLF14, all significantly inversely correlated to gene expression (p=0.003, p=0.03, and p=0.007, respectively). The methylation status of SOCS2 (p=0.025) and DLX1 (p=0.025) was significantly correlated to phosphorylation of IGFR1. Samples with RBP1 hypermethylation showed significantly higher AFP serum levels (p=0.018). Conclusion: Whole genome methylation analysis markedly classifies normal, cirrhotic and HCC samples. 8 TSGs play a key role in this stepwise progression of hypermethylation in the development of HCC and could be a promising point of action in anticancer therapy. Genomic DNA extracted from fresh frozen tissue specimens and cell lines was hybridized to genome-wide mthylation beadarray after bisulphite treatment. Keywords: DNA methylation, hepatocellular carcinoma, tissue, cell line

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.

Dataset Information

Heterogeneity of gene-expression profiles of hepatocellular carcinoma tumors

Publications

Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure