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Cited by 437

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Lethality to human cancer cells through massive chromosome loss by inhibition of the mitotic checkpoint

Open access
Kops, Geert J. P. L., Foltz, Daniel R., Cleveland, Don W.·2004·Proceedings of the National Academy of Sciences

Abstract

A compromised mitotic checkpoint, the primary mechanism for ensuring that each new cell receives one copy of every chromosome, has been implicated as a contributor to carcinogenesis. However, a checkpoint response is shown here to be essential for cell survival, including that of chromosomally instable colorectal cancer cells. Reducing the levels of the checkpoint proteins BubR1 or Mad2 in human cancer cells or inhibiting BubR1 kinase activity provokes apoptotic cell death within six divisions except when cytokinesis is also inhibited. Thus, suppression of mitotic checkpoint signaling is invariably lethal as the consequence of massive chromosome loss, findings that have implications for inhibiting proliferation of tumor cells.

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Crossref · 10.1073/pnas.0401142101

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Metadata

Authors
Kops, G. J. P. L., Foltz, D. R., & Cleveland, D. W.
Venue
Proceedings of the National Academy of Sciences
Published
2004-05-24
Volume
101
Issue
23
Pages
8699-8704
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2118562565
Cited by
437
References
1
FWCI
10.09
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Lethality to human cancer cells through massive chromosome loss by inhibition of the mitotic checkpoint. https://app.cochat.ai/papers/10.1073/pnas.0401142101
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Kops, G. J. P. L., Foltz, D. R., & Cleveland, D. W. (2004). Lethality to human cancer cells through massive chromosome loss by inhibition of the mitotic checkpoint. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0401142101

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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.