Key Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MorePurpose: Chronic Hepatitis B virus (HBV) infection leads to liver fibrosis which is a major risk factor in Hepatocellular carcinoma (HCC) and an independent risk factor of recurrence after HCC tumor resection. HBV genome can be inserted into human genome, and chronic inflammation may trigger somatic mutations. Several studies characterized HBV integration sites in HCC patients with regard to frequently occurring hotspots. However, how HBV integration and other genomic changes contribute to the risk of tumor recurrence with regard to different degree of liver fibrosis is not clearly understood. In this study, we aim to find potential molecular mechanisms underlying tumor recurrence of HBV-associated HCC (HBV-HCC) with different degree of liver fibrosis.; Methods: We performed RNA sequencing of 21 pairs of tumor and non-neoplastic liver tissues of HBV-HCC patients and performed comprehensive genomic analysis of our RNAseq data and public available sequencing data related to HBV-HCC. We developed a robust pipeline for sensitively identifying HBV integration sites based on sequencing data. Simulations with sequencing data showed that our method outperformed existing methods. We also compared SNPs of each sample with SNPs in cancer census database and inferred patients pathogenic SNP loads in tumor and non-neoplastic liver tissues.; Conclusions: The HBV-integration and pathogenic SNP load patterns for HCC recurrence risk vary depending on liver fibrosis stage, suggesting potentially different tumorigenesis mechanisms for low and high liver fibrosis patients. SOURCE: Jun Zhu (jun.zhu@mssm.edu) - Integrative Network Biology Group Ichan School of Medicine at Mount Sinai
View on GEOView in PlutoEnhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreUse Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView quality control data and experiment metadata for this experiment.
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team