Evidence map›Paper›PMID 39764737›Full record

ArticleCancer reports (Hoboken, N.J.)2025

The miRNA-mRNA Regulatory Network in Human Hepatocellular Carcinoma by Transcriptomic Analysis From GEO.

Razieh Heidari, Vahideh Assadollahi, Seyedeh Negar Marashi, Fatemeh Elahian, Seyed Abbas Mirzaei

Abstract read
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Kinesin Spindle Protein (KIF11) in Mitosis and Cancer.International journal of molecular sciences · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Razieh HeidariCancer Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran.ORCID 0000-0002-8085-8386
Vahideh AssadollahiDepartment of Tissue Engineering & Applied Cell Sciences, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.ORCID 0000-0001-9623-1986
Seyedeh Negar MarashiDepartment of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.ORCID 0009-0001-5415-2566
Fatemeh ElahianDepartment of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.ORCID 0000-0002-1489-4047
Seyed Abbas MirzaeiDepartment of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.ORCID 0000-0003-0307-3750

Funding

Shahrekord University of Medical Sciences SKUMS-7370
6 · The paper itself

Abstract

backgroundBioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.

aimIn this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs). METHODS AND

resultsCommon DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes. The reduced levels of tumor suppressor miRNAs or down regulated DEmiRs may be increased levels of oncogenes, the oncomirs or up regulated DEmiRs may be decreased levels of tumor suppressor genes in cancerous cells. According to this strategy, increased and decreased DEGs, also increased and decreased DEmiRs were selected. The multimir package was employed to predict target genes for DEmiRs then DEmiRs-hub gene network created. We identified approximately 1000 overlapping DEGs and 60 DEmiRs. Hub genes included RRM2, MELK, KIF11, KIF23, NCAPG, DLGAP5, BUB1B, AURKB, CCNB1, KIF20A, CCNA2, TTK, PBK, TOP2A, CDK1, MAD2L1, BIRC5, ASPM, CDCA8, and CENPF, all associated with significantly worse survival in HCC. miR-224, miR-24, miR-182, miRNA-1-3p, miR-30a, miR-27a, and miR-214 were identified as important DEmiRs with targeting more than six hub genes.

conclusionGenerally, our findings offer insight into the interaction of hub genes and miRNAs in the development of HCC by bioinformatics analysis, information that may prove useful in identifying biomarkers and therapeutic targets in HCC.

Indexed as

Carcinoma, HepatocellularComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksLiver NeoplasmsMicroRNAsRNA, MessengerBiomarkers, TumorDatabases, GeneticHumansProtein Interaction MapsTranscriptomeBiomarkers, TumorMicroRNAsRNA, MessengerbioinformaticsbiomarkerHCChepatocellular carcinomamicroarraymicroRNA

Identifiers

PMID39764737
PMCPMC11705453

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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.