Evidence map›Paper›PMID 38682432›Full record

ReviewZoological research2024

Role of cancer stem cell ecosystem on breast cancer metastasis and related mouse models.

Xilei Peng, Haonan Dong, Lixing Zhang, Suling Liu

Abstract readReview
In one paragraph

Review in Zoological research, 2024. 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. Article
  2. Article
  3. Article
  4. 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

4 authors.

Xilei PengFudan University Shanghai Cancer Center & Institutes of Biomedical Sciences.
Haonan DongFudan University Shanghai Cancer Center & Institutes of Biomedical Sciences.
Lixing ZhangFudan University Shanghai Cancer Center & Institutes of Biomedical Sciences.
Suling LiuFudan University Shanghai Cancer Center & Institutes of Biomedical Sciences.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer metastasis is responsible for most breast cancer-related deaths and is influenced by many factors within the tumor ecosystem, including tumor cells and microenvironment. Breast cancer stem cells (BCSCs) constitute a small population of cancer cells with unique characteristics, including their capacity for self-renewal and differentiation. Studies have shown that BCSCs not only drive tumorigenesis but also play a crucial role in promoting metastasis in breast cancer. The tumor microenvironment (TME), composed of stromal cells, immune cells, blood vessel cells, fibroblasts, and microbes in proximity to cancer cells, is increasingly recognized for its crosstalk with BCSCs and role in BCSC survival, growth, and dissemination, thereby influencing metastatic ability. Hence, a thorough understanding of BCSCs and the TME is critical for unraveling the mechanisms underlying breast cancer metastasis. In this review, we summarize current knowledge on the roles of BCSCs and the TME in breast cancer metastasis, as well as the underlying regulatory mechanisms. Furthermore, we provide an overview of relevant mouse models used to study breast cancer metastasis, as well as treatment strategies and clinical trials addressing BCSC-TME interactions during metastasis. Overall, this study provides valuable insights for the development of effective therapeutic strategies to reduce breast cancer metastasis.

Indexed as

Breast NeoplasmsNeoplasm MetastasisNeoplastic Stem CellsAnimalsDisease Models, AnimalFemaleHumansMiceTumor MicroenvironmentBreast cancerCancer stem cellEcosystemMetastasisMouse modelTumor microenvironment

Identifiers

PMID38682432
PMCPMC11188611

What OpenQuestion holds

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LicenceCC BY-NC
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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.