ArticleCancer management and research2019
Integrated analysis of lncRNA-associated ceRNA network reveals potential biomarkers for the prognosis of hepatitis B virus-related hepatocellular carcinoma.
Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 27 citations in OpenAlex.
- MiR-4725-3p acts as an oncogene and prognostic biomarker in hepatocellular carcinoma.World journal of surgical oncology · 2026Article
- Mechanistic role of long non-coding RNAs in the pathogenesis of metabolic dysfunction-associated steatotic liver disease and fibrosis.eGastroenterology · 2024Article
- A systematic study on the treatment of hepatitis B-related hepatocellular carcinoma with drugs based on bioinformatics and key target reverse network pharmacology and experimental verification.Infectious agents and cancer · 2023Article
- Advances in targeting of miR‑10‑associated lncRNAs/circRNAs for the management of cancer (Review).Oncology letters · 2023Review
- Article
- Long noncoding RNAs in hepatitis B virus replication and oncogenesis.World journal of gastroenterology · 2022Review
- Diversity of Dysregulated Long Non-Coding RNAs in HBV-Related Hepatocellular Carcinoma.Frontiers in immunology · 2022Review
- The prognostic values of serum markers in hepatocellular carcinoma after invasive therapies based on real-world data.Journal of clinical laboratory analysis · 2021Article
- Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis.Frontiers in genetics · 2021Article
- Long Non-coding RNA SENP3-EIF4A1 Functions as a Sponge of miR-195-5p to Drive Triple-Negative Breast Cancer Progress by Overexpressing CCNE1.Frontiers in cell and developmental biology · 2021Article
- Elevated CELSR3 expression is associated with hepatocarcinogenesis and poor prognosis.Oncology letters · 2020Article
- Identification of potential key genes and pathways in hepatitis B virus-associated hepatocellular carcinoma by bioinformatics analyses.Oncology letters · 2020Article
- A positive feedback loop involving the LINC00346/β-catenin/MYC axis promotes hepatocellular carcinoma development.Cellular oncology (Dordrecht, Netherlands) · 2020Article
- Article
- LINC00346 Acts as a Competing Endogenous RNA Regulating Development of Hepatocellular Carcinoma via Modulating CDK1/CCNB1 Axis.Frontiers in bioengineering and biotechnology · 2020Article
- Article
- Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma.Journal of Cancer · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is evidence that abnormal expression of lncRNAs is associated with hepatitis B virus (HBV) infection-induced hepatocellular carcinoma (HCC). However, the mechanisms remain not fully elucidated. The study aimed to identify novel lncRNAs and explore their underlying mechanisms based on the ceRNA hypothesis.
methodsThe RNA and miRNA expression profiling in 20 tumor and matched adjacent tissues from HBV-HCC patients were retrieved from the Gene Expression Omnibus database under accession numbers GSE77509 and GSE76903, respectively. Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) were identified using the EdgeR package. Protein-protein interaction (PPI) network was constructed for DEGs followed by module analysis. The ceRNA network was constructed based on interaction relationships between miRNAs and mRNAs/lncRNAs. The functions of DEGs were predicted using DAVID and BinGO databases. The prognosis values (overall survival [OS] and recurrence-free survival [RFS]) of ceRNA network genes were determined using The Cancer Genome Atlas (TCGA) data with Cox regression analysis and Kaplan-Meier method.
resultsThe present study screened 643 DELs, 83 DEMs, and 1,187 DEGs. PPI network analysis demonstrated that CDK1 and CCNE1 were hub genes and extracted in functionally related modules. E2F2, CDK1, and CCNE1 were significantly enriched into cell cycle pathway. FAM182B-miR-125b-5p-E2F2 and LINC00346-miR-10a-5p-CDK1/CCNE1 ceRNA axes were obtained by constructing the ceRNA network. Patients with high expressions of DELs and DEGs in the above ceRNA axes had poor OS, while patients with the high expression of DEMs possessed excellent OS. CDK1 was also an RFS-related biomarker, with its high expression predicting poor RFS. The upregulation of LINC00346 and CDK1 but the downregulation of miR-10a-5p in HCC was validated in other microarray datasets and TCGA database.
conclusionThe LINC00346-miR-10a-5p-CDK1 axis may be an important mechanism for HBV-related HCC, and genes in this ceRNA axis may be potential prognostic biomarkers and therapeutic targets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.