Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Total RNA Sequencing in HCC Patients

ABSTRACT: Total RNA Sequencing in HCC Patients

PROVIDER: PRJNA1161405 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Total RNA Sequencing in HCC Patients

Project description:Total RNA Sequencing in HCC Patients

2025-09-12 | GSE277232 | GEO

RNA sequencing (RNA-SEQ) of 21 HBV-HCC patients with non-neoplastic liver and tumor tissues

Project description:Purpose: 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 patient’s 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.

2018-03-01 | GSE94660 | GEO

RNA-seq of human hepatocellular carcinoma (HCC) patients

Project description:Tumor samples and matching healthy tissue from 23 human hepatocellular carcinoma (HCC) patients and one hepatocellular adenoma patient were collected after surgical resection. Total RNA was harvested and sequenced with a strand-specific single-end RNA-seq protocol.

2021-12-23 | E-MTAB-8915 | biostudies-arrayexpress

RNA-seq of human hepatocellular carcinoma (HCC) patients

Project description:RNA-seq of human hepatocellular carcinoma (HCC) patients

| PRJEB37650 | ENA

Total poly(A)+ RNA sequencing

Project description:Total poly(A)+ RNA sequencing

| PRJNA627618 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of tumor samples from HCC patients receiving Nivolumab.

Project description:To identify critical tumor-secreting factors that may contribute to immunotherapy efficacy against HCC, we subjected tumor samples from 10 HCC patients to whole-transcriptome sequencing, and categorized the patients into two groups according to clinical response to nivolumab. We then performed gene expression profiling analysis using data obtained from RNA-seq of Nivolumab reponders and non-reponsers.

2023-12-06 | GSE215011 | GEO

Total RNA-seq in patients with hematological malignancy

Project description:Total RNA-seq in patients with hematological malignancy

| PRJNA486089 | ENA

Small RNA sequencing data of tumors and paired adjacent tissues from HCC patients

Project description:Small RNA sequencing data of tumors and paired adjacent tissues from HCC patients

| PRJNA716180 | ENA

SMARTer single cell total RNA sequencing

Project description:SMARTer single cell total RNA sequencing

| PRJNA490894 | ENA

Transcriptome analysis in hepatocellular carcinoma (HCC) tissues

Project description:We report the application of RNA sequencing technology for high-throughput profiling in HCC tissues. In the present study, to explore novel biomarkers of HCC, we firstly explored the expression profiles of mRNAs and miRNAs in three pairs of HCC patients (tumor tissues and non-tumorous tissues) by high-throughput RNA sequencing. A total of 1024 mRNAs were found to be significantly dysregulated (636 up-regulated and 388 down-regulated), 50 miRNAs were found to be significantly dysregulated (27 up-regulated and 23 down-regulated) in the HCC tissues compared with the non-tumorous tissues.Then validae the differentially expressed miRNAs by qRT-PCR in HCC tissues and serum. This study provides a framework for the application of miRNAs to be ideal biomarkers for HCC.

2023-02-28 | GSE146719 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data