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Cited by 461

The DOI matches its Crossref record; 264 of the 264 references it cites were found in a registry or an index.

Strategies for optimizing the response of cancer and normal tissues to radiation

Open access
Moding, Everett J., Kastan, Michael B., Kirsch, David G.·2013·Nature Reviews Drug Discovery

Abstract

Approximately 50% of all patients with cancer receive radiation therapy at some point during the course of their treatment, and the majority of these patients are treated with curative intent. Despite recent advances in the planning of radiation treatment and the delivery of image-guided radiation therapy, acute toxicity and potential long-term side effects often limit the ability to deliver a sufficient dose of radiation to control tumours locally. In the past two decades, a better understanding of the hallmarks of cancer and the discovery of specific signalling pathways by which cells respond to radiation have provided new opportunities to design molecularly targeted therapies to increase the therapeutic window of radiation therapy. Here, we review efforts to develop approaches that could improve outcomes with radiation therapy by increasing the probability of tumour cure or by decreasing normal tissue toxicity.

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Crossref · 10.1038/nrd4003

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Metadata

Authors
Moding, E. J., Kastan, M. B., & Kirsch, D. G.
Venue
Nature Reviews Drug Discovery
Published
2013-07
Volume
12
Issue
7
Pages
526-542
ISSN
  • 1474-1776 (ISSN-L)
  • 1474-1784
OpenAlex
W1982415526
Cited by
461
References
264
FWCI
3.94
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Strategies for optimizing the response of cancer and normal tissues to radiation. https://app.cochat.ai/papers/10.1038/nrd4003
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Moding, E. J., Kastan, M. B., & Kirsch, D. G. (2013). Strategies for optimizing the response of cancer and normal tissues to radiation. Nature Reviews Drug Discovery. https://doi.org/10.1038/nrd4003

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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.