ArticleiLIVER2025
MAGI2-AS3/miR-450b-5p/COLEC10 interaction network: A potential therapeutic and prognostic marker in hepatocellular carcinoma.
Article in iLIVER, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Are we ready for a molecular diagnostics-driven era in hepatobiliary surgery?Hepatobiliary surgery and nutrition · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Hepatocellular carcinoma (HCC) is a prevalent malignancy with poor prognosis. This study uses integrated bioinformatic analyses to explore potential competing endogenous RNA (ceRNA) network chains in HCC. Methods: HCC expression profile data were obtained from the Gene Expression Omnibus dataset, and differential expression analysis was conducted to identify differentially expressed mRNAs (DEmRNAs), microRNAs (DEmiRNAs), and long non-coding RNAs (DElncRNAs) between HCC and normal liver tissue samples. Univariate Cox regression analysis was performed to identify mRNAs associated with the prognosis of HCC patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were used to classify the identified genes functionally. Cytoscape software was used to construct a protein-protein interaction network. Using the intersection method, a ceRNA network was established to align data from two databases (miRTarBase and miRcode). Pearson correlation analysis was conducted to evaluate the relationships between lncRNAs and mRNAs. Results: A total of 106 prognosis-related DEmRNAs were identified between HCC and normal samples. A total of 132 DEmiRNAs and 42 DElncRNAs were dysregulated in HCC. A ceRNA network of three lncRNAs, six miRNAs, and eight mRNAs was constructed. High expression of MCM10, CDKN3, RRM2, KIF3A, and ALYREF correlated with a poor prognosis, while high expression of CPEB2, COLEC10, and PBLD was associated with a better prognosis for HCC patients. Expression analysis confirmed the differential expression of these genes in HCC samples. Correlation analysis revealed that a MAGI2-AS3/hsa-miR-450b-5p/COLEC10 axis might play a crucial role in the progression of HCC. Conclusion: The ceRNA network constructed could provide insight into HCC tumorigenesis and might lead to new molecular biomarkers for diagnosing and treating HCC.
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.