Evidence map›Paper›PMID 33973625›Full record

ReviewDisease models & mechanisms2021

The liver metastatic niche: modelling the extracellular matrix in metastasis.

James Drew, Laura M Machesky

Open access · goldAbstract readReview
In one paragraph

Review in Disease models & mechanisms, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

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  16. Identification andJournal of thoracic disease · 2022
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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 at 1 institution in 1 country.

James DrewCRUK Beatson Institute, Switchback Road, Bearsden, Glasgow G61 1BD, UK.ORCID 0000-0002-2864-7987
Laura M MacheskyCRUK Beatson Institute, Switchback Road, Bearsden, Glasgow G61 1BD, UK.ORCID 0000-0002-7592-9856
Cancer Research UK Scotland Institute · GB

Funding

Cancer Research UK 24452Cancer Research UK A24452
6 · The paper itself

Abstract

Dissemination of malignant cells from primary tumours to metastatic sites is a key step in cancer progression. Disseminated tumour cells preferentially settle in specific target organs, and the success of such metastases depends on dynamic interactions between cancer cells and the microenvironments they encounter at secondary sites. Two emerging concepts concerning the biology of metastasis are that organ-specific microenvironments influence the fate of disseminated cancer cells, and that cancer cell-extracellular matrix interactions have important roles at all stages of the metastatic cascade. The extracellular matrix is the complex and dynamic non-cellular component of tissues that provides a physical scaffold and conveys essential adhesive and paracrine signals for a tissue's function. Here, we focus on how extracellular matrix dynamics contribute to liver metastases - a common and deadly event. We discuss how matrix components of the healthy and premetastatic liver support early seeding of disseminated cancer cells, and how the matrix derived from both cancer and liver contributes to the changes in niche composition as metastasis progresses. We also highlight the technical developments that are providing new insights into the stochastic, dynamic and multifaceted roles of the liver extracellular matrix in permitting and sustaining metastasis. An understanding of the contribution of the extracellular matrix to different stages of metastasis may well pave the way to targeted and effective therapies against metastatic disease.

Indexed as

Models, BiologicalAnimalsEpithelial-Mesenchymal TransitionExtracellular MatrixHumansLiver NeoplasmsNeoplasm MetastasisNeoplastic Cells, CirculatingCancer metastasisExtracellular matrixLiver metastasisMetastatic niche

Identifiers

PMID33973625
PMCPMC8077555
OpenAlexW3157376430

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.