Evidence map›Paper›PMID 39766782›Full record

ArticleGenes2024

RNA Sequencing and Weighted Gene Co-Expression Network Analysis Highlight DNA Replication and Key Genes in Nucleolin-Depleted Hepatoblastoma Cells.

Hannes Steinkellner, Silvia Madritsch, Mara Kluge, Teresa Seipel, Victoria Sarne, Anna Huber, Markus Schosserer, Raimund Oberle, Winfried Neuhaus, Alexander V Beribisky and 1 more

Abstract read
In one paragraph

Article in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Hannes SteinkellnerCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-4438-6043
Silvia MadritschCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-4995-7351
Mara KlugeCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.
Teresa SeipelCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.
Victoria SarneCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0003-1053-4033
Anna HuberCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-8490-9630
Markus SchossererCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.
Raimund OberleCenter for Pathobiochemistry and Genetics, Institute of Medical Chemistry and Pathobiochemistry, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-6701-4130
Winfried NeuhausCompetence Unit Molecular Diagnostics, Center Health and Bioresources, AIT-Austrian Institute of Technology GmbH, 1210 Vienna, Austria.ORCID 0000-0002-6552-7183
Alexander V BeribiskyCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.
Franco LacconeCenter for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0001-9466-6441

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesNucleolin is a major component of the nucleolus and is involved in various aspects of ribosome biogenesis. However, it is also implicated in non-nucleolar functions such as cell cycle regulation and proliferation, linking it to various pathologic processes. The aim of this study was to use differential gene expression analysis and Weighted Gene Co-expression Network analysis (WGCNA) to identify nucleolin-related regulatory pathways and possible key genes as novel therapeutic targets for cancer, viral infections and other diseases.

methodsWe used two different siRNAs to downregulate the expression of nucleolin in a human hepatoblastoma (HepG2) cell line. We carried out RNA-sequencing (RNA-Seq), performed enrichment analysis of the pathways of the differentially expressed genes (DEGs) and identified protein-protein interaction (PPI) networks.

resultsBoth siRNAs showed high knockdown efficiency in HepG2 cells, resulting in the disruption of the nucleolar architecture and the downregulation of rRNA gene expression, both downstream hallmarks of a loss of nucleolin function. RNA-Seq identified 44 robust DEGs in both siRNA cell models. The enrichment analysis of the pathways of the downregulated genes confirmed the essential role of nucleolin in DNA replication and cell cycle processes. In addition, we identified seven hub genes linked to

conclusionsOur findings demonstrate the functional consequences of nucleolin depletion in HepG2 and confirm the importance of nucleolin in DNA replication and cell cycle processes. These data will further enhance our understanding of the molecular and pathologic mechanisms of nucleolin and provide new therapeutic perspectives in disease.

Indexed as

DNA ReplicationGene Expression Regulation, NeoplasticGene Regulatory NetworksHepatoblastomaLiver NeoplasmsNucleolinPhosphoproteinsRNA-Binding ProteinsHep G2 CellsHumansProtein Interaction MapsSequence Analysis, RNANucleolinPhosphoproteinsRNA-Binding ProteinsbioinformaticscancerDNA replicationhuman diseasenucleolinribosome biogenesisRNA Seq

Identifiers

PMID39766782
PMCPMC11675179

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Registered trials

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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.