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Cited by 370

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Hypoxia, inflammation, and the tumor microenvironment in metastatic disease

Open access
Finger, Elizabeth C., Giaccia, Amato J.·2010·Cancer and Metastasis Reviews

Abstract

Metastasis, the leading cause of cancer deaths, is an intricate process involving many important tumor and stromal proteins that have yet to be fully defined. This review discusses critical components necessary for the metastatic cascade, including hypoxia, inflammation, and the tumor microenvironment. More specifically, this review focuses on tumor cell and stroma interactions, which allow cell detachment from a primary tumor, intravasation to the blood stream, and extravasation at a distant site where cells can seed and tumor metastases can form. Central players involved in this process and discussed in this review include integrins, matrix metalloproteinases, and soluble growth factors/matrix proteins, including the connective tissue growth factor and lysyl oxidase.

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Registry

Crossref · 10.1007/s10555-010-9224-5

Cites

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Citations

Cites

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Metadata

Authors
Finger, E. C., & Giaccia, A. J.
Venue
Cancer and Metastasis Reviews
Published
2010-04-15
Volume
29
Issue
2
Pages
285-293
ISSN
  • 0167-7659 (ISSN-L)
  • 1573-7233
OpenAlex
W2082639976
Cited by
370
References
11
FWCI
2.62
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Hypoxia, inflammation, and the tumor microenvironment in metastatic disease. https://app.cochat.ai/papers/10.1007/s10555-010-9224-5
The paper
Finger, E. C., & Giaccia, A. J. (2010). Hypoxia, inflammation, and the tumor microenvironment in metastatic disease. Cancer and Metastasis Reviews. https://doi.org/10.1007/s10555-010-9224-5

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.