Evidence map›Paper›PMID 31547151›Full record

SynthesisCells2019

Meta-Analysis of Human and Mouse Biliary Epithelial Cell Gene Profiles.

Stefaan Verhulst, Tania Roskams, Pau Sancho-Bru, Leo A van Grunsven

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Cells, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

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  5. 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

4 authors at 3 institutions in 2 countries.

Stefaan VerhulstLiver Cell Biology research group, Department of Basic Biomedical Sciences, Vrije Universiteit Brussel, 1090 Brussels, Belgium. Stefaan.verhulst@vub.be.
Tania RoskamsDepartment of Imaging and Pathology, Translational Cell and Tissue Research, KU Leuven and University Hospitals, 3000 Leuven, Belgium. tania.roskams@kuleuven.be.
Pau Sancho-BruInstitut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), 08001 Barcelona, Spain. PSANCHO@clinic.cat.
Leo A van GrunsvenLiver Cell Biology research group, Department of Basic Biomedical Sciences, Vrije Universiteit Brussel, 1090 Brussels, Belgium. leo.van.grunsven@vub.be.
Vrije Universiteit Brussel · BEConsorci Institut D'Investigacions Biomediques August Pi I Sunyer · ESKU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic liver diseases are frequently accompanied with activation of biliary epithelial cells (BECs) that can differentiate into hepatocytes and cholangiocytes, providing an endogenous back-up system. Functional studies on BECs often rely on isolations of an BEC cell population from healthy and/or injured livers. However, a consensus on the characterization of these cells has not yet been reached. The aim of this study was to compare the publicly available transcriptome profiles of human and mouse BECs and to establish gene signatures that can identify quiescent and activated human and mouse BECs.

methodsWe used publicly available transcriptome data sets of human and mouse BECs, compared their profiles and analyzed co-expressed genes and pathways. By merging both human and mouse BEC-enriched genes, we obtained a quiescent and activation gene signature and tested them on BEC-like cells and different liver diseases using gene set enrichment analysis. In addition, we identified several genes from both gene signatures to identify BECs in a scRNA sequencing data set.

resultsComparison of mouse BEC transcriptome data sets showed that the isolation method and array platform strongly influences their general profile, still most populations are highly enriched in most genes currently associated with BECs. Pathway analysis on human and mouse BECs revealed the KRAS signaling as a new potential pathway in BEC activation. We established a quiescent and activated BEC gene signature that can be used to identify BEC-like cells and detect BEC enrichment in alcoholic hepatitis, non-alcoholic steatohepatitis (NASH) and peribiliary sclerotic livers. Finally, we identified a gene set that can distinguish BECs from other liver cells in mouse and human scRNAseq data.

conclusionsThrough a meta-analysis of human and mouse BEC gene profiles we identified new potential pathways in BEC activation and created unique gene signatures for quiescent and activated BECs. These signatures and pathways will help in the further characterization of this progenitor cell type in mouse and human liver development and disease.

Indexed as

AnimalsBiliary TractCell DivisionCell TransdifferentiationEpithelial CellsGene Expression ProfilingHepatocytesHigh-Throughput Nucleotide SequencingHumansLiverMiceMicroarray AnalysisRegenerationSequence Analysis, RNATranscriptomeBECgene signaturescRNAseqtranscriptome

Identifiers

PMID31547151
PMCPMC6829476
OpenAlexW2973357647

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.