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Cited by 650

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Chemokines and chemokine receptors: new insights into cancer-related inflammation

Open access
Lazennec, Gwendal, Richmond, Ann·2010·Trends in Molecular Medicine

Abstract

Chemokines are involved in cellular interactions and tropism in situations frequently associated with inflammation. Recently, the importance of chemokines and chemokine receptors in inflammation associated with carcinogenesis has been highlighted. Increasing evidence suggests that chemokines are produced by tumor cells and also by cells of the tumor microenvironment including cancer-associated fibroblasts, mesenchymal stem cells, endothelial cells, tumor-associated macrophages and more recently tumor-associated neutrophils. In addition to having effects on tumor cell proliferation, angiogenesis and metastasis, chemokines also appear to modulate senescence and cell survival. Here, we review recent progress on the roles of chemokines and chemokine receptors in cancer-related inflammation, and we discuss the mechanisms underlying chemokine action in cancer that might facilitate the development of novel therapies in the future.

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Metadata

Authors
Lazennec, G., & Richmond, A.
Venue
Trends in Molecular Medicine
Publisher
Elsevier BV
Published
2010-03
Volume
16
Issue
3
Pages
133-144
ISSN
1471-4914 (ISSN-L)
OpenAlex
W2086159554
Cited by
650
References
9
FWCI
5.53
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Chemokines and chemokine receptors: new insights into cancer-related inflammation. https://app.cochat.ai/papers/10.1016/j.molmed.2010.01.003
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Lazennec, G., & Richmond, A. (2010). Chemokines and chemokine receptors: new insights into cancer-related inflammation. Trends in Molecular Medicine. https://doi.org/10.1016/j.molmed.2010.01.003

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.