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Overcoming Treatment Toxicity through Sequential Therapy

descriptionPublicationkeyboard_double_arrow_right Article 01 Jun 2019 Denmark English Publisher:Elsevier BVJournal:Cancer Cell, volume 35, pages 821-822 (issn: 1535-6108, Copyright policy )
Authors: Benada, Jan; Ejlertsen, Bent; Sørensen, Claus Storgaard;

doi: 10.1016/j.ccell.2019.05.006

pmid: 31185206

Overcoming Treatment Toxicity through Sequential Therapy

Abstract

Combined inhibitions of PARP and DNA damage checkpoint have the potential for high anti-cancer efficacy, but concurrent inhibitions have been hampered by intolerable side effects. In this issue of Cancer Cell, Fang and colleagues (Fang et al., 2019) propose that sequential inhibitions of PARP and DNA damage checkpoint considerably widen the therapeutic window.

Country
Denmark
Related Organizations
Keywords

Neoplasms, Humans, Nuclear Proteins, Cell Cycle Proteins, Cell Cycle Checkpoints, Poly(ADP-ribose) Polymerase Inhibitors, Protein-Tyrosine Kinases

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
hybrid
Related to Research communities
Knowmad Institut
Cancer Research