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Cited by 552

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Proteolytic networks in cancer

Open access
Mason, Steven D., Joyce, Johanna A.·2011·Trends in Cell Biology

Abstract

Proteases are important for multiple processes during malignant progression including tumor angiogenesis, invasion and metastasis. Recent evidence reveals that tumor-promoting proteases function as part of an extensive multidirectional network of proteolytic interactions, in contrast to the unidirectional caspase cascade. These networks involve different constituents of the tumor microenvironment, and key proteases — such as cathepsin B, urokinase-type plasminogen activator and several matrix metalloproteinases — occupy central nodes for amplifying proteolytic signals passing through the network. The proteolytic network interacts with other important signaling pathways in tumor biology, involving chemokines, cytokines, and kinases. Viewing these proteolytic interactions as a system of activating and inhibiting reactions provides insight into tumor biology and reveals relevant pharmaceutical targets. This review will examine recent advances in understanding proteases in cancer, and summarize how their network of activity is co-opted to promote tumor progression.

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Metadata

Authors
Mason, S. D., & Joyce, J. A.
Venue
Trends in Cell Biology
Publisher
Elsevier BV
Published
2011-04
Volume
21
Issue
4
Pages
228-237
ISSN
0962-8924 (ISSN-L)
OpenAlex
W1997104566
Cited by
552
References
7
FWCI
2.03
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Proteolytic networks in cancer. https://app.cochat.ai/papers/10.1016/j.tcb.2010.12.002
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Mason, S. D., & Joyce, J. A. (2011). Proteolytic networks in cancer. Trends in Cell Biology. https://doi.org/10.1016/j.tcb.2010.12.002

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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.