Evidence map›Paper›PMID 32952874›Full record

ReviewWorld journal of hepatology2020

Cell competition in liver carcinogenesis.

Fabio Marongiu, Ezio Laconi

Abstract readReview
In one paragraph

Review in World journal of hepatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
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  8. 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

2 authors.

Fabio MarongiuDepartment of Biomedical Sciences, Unit of Experimental Medicine, University of Cagliari, Cagliari 09124, Italy.
Ezio LaconiDepartment of Biomedical Sciences, Unit of Experimental Medicine, University of Cagliari, Cagliari 09124, Italy. elaconi@unica.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell competition is now a well-established quality control strategy to optimize cell and tissue fitness in multicellular organisms. While pursuing this goal, it is also effective in selecting against altered/defective cells with putative (pre)-neoplastic potential, thereby edging the risk of cancer development. The flip side of the coin is that the molecular machinery driving cell competition can also be co-opted by neoplastic cell populations to expand unchecked, outside the boundaries of tissue homeostatic control. This review will focus on information that begins to emerge regarding the role of cell competition in liver physiology and pathology. Liver repopulation by normal transplanted hepatocytes is an interesting field of investigation in this regard. The biological coordinates of this process share many features suggesting that cell competition is a driving force for the clearance of endogenous damaged hepatocytes by normal donor-derived cells, as previously proposed. Intriguing analogies between liver repopulation and carcinogenesis will be briefly discussed and the potential dual role of cell competition, as a barrier or a spur to neoplastic development, will be considered. Cell competition is in essence a cooperative strategy organized at tissue level. One facet of such cooperative attitude is expressed in the elimination of altered cells which may represent a threat to the organismal community. On the other hand, the society of cells can be disrupted by the emergence of selfish clones, exploiting the molecular bar codes of cell competition, thereby paving their way to uncontrolled growth.

Indexed as

AgingCell competitionClonal expansionLiver carcinogenesisLiver repopulationTissue homeostasis

Identifiers

PMID32952874
PMCPMC7475782

What OpenQuestion holds

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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.