ArticleFrontiers in oncology2021
Bioinformatics Analysis Using ATAC-seq and RNA-seq for the Identification of 15 Gene Signatures Associated With the Prediction of Prognosis in Hepatocellular Carcinoma.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- PETScan: score-based genome-wide association analysis of RNA-Seq and ATAC-Seq data.Bioinformatics (Oxford, England) · 2026Article
- [ERI3 expression is elevated in hepatocellular carcinoma and correlates with poor patient prognosis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- GDI2 protein: research progress and its mechanisms in diseases.Frontiers in cell and developmental biology · 2026Review
- SAC3 domain containing 1 intervention in energy metabolism reprogramming assists in the progression of hepatocellular carcinoma.World journal of gastrointestinal oncology · 2025Article
- Peroxiredoxin 6 in Stress Orchestration and Disease Interplay.Antioxidants (Basel, Switzerland) · 2025Review
- Application of a risk score model based on tyrosine-related genes in the prognosis and treatment of patients with lung adenocarcinoma.Frontiers in immunology · 2025Article
- Review
- LncRNA HOTAIR as a ceRNA is related to breast cancer risk and prognosis.Breast cancer research and treatment · 2023Article
- Advances in SEMA3F regulation of clinically high-incidence cancers.Cancer biomarkers : section A of Disease markers · 2023Article
- Chemical modulation ofWellcome open research · 2023Article
- Integration of RNA-seq and ATAC-seq identifies muscle-regulated hub genes in cattle.Frontiers in veterinary science · 2022Article
- Single-Cell Sequencing and Its Applications in Liver Cancer.Frontiers in oncology · 2022Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression (RNA-seq) and overall survival (OS) in TCGA were combined using chromosome accessibility (ATAC-seq) to search for key molecules affecting liver cancer prognosis.
methodsWe used the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) to analyse chromatin accessibility in the promoter regions of whole genes in liver hepatocellular carcinoma (LIHC) and then screened differentially expressed genes (DEGs) at the mRNA level by transcriptome sequencing technology (RNA-seq). We obtained genes significantly associated with overall survival (OS) by a one-way Cox analysis. The three were screened by taking intersection and further using a Kaplan-Meier (KM) for validation. A prognostic model was constructed using the obtained genes by LASSO regression analysis.The expression of these genes in hepatocellular carcinomas was then analysed. The protein expression of these genes was verified using the Human Protein Atlas(HPA) online datasets and immunohistochemistry.
resultsATAC-seq, RNA-seq and survival analysis, combined with a LASSO prediction model, identified signatures of 15 genes (
conclusionsPRDX6, GCLM, HTATIP2, SEMA3F, UCK2, NOL10, KIF18A, RAP2A, BOD1, GDI2, ZIC2, GTF3C6, SLC1A5, ERI3 and SAC3D1 may affect the prognosis of LIHC.
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