Anticipating designer drug-resistant cancer cells

Mark L. Frangione; John H. Lockhart; Daniel T. Morton; Libia M. Pava; George Blanck

doi:10.1016/j.drudis.2015.02.005

Anticipating designer drug-resistant cancer cells

Mark L. Frangione, John H. Lockhart, Daniel T. Morton, Libia M. Pava, George Blanck

Research output: Contribution to journal › Short survey › peer-review

8 Scopus citations

Abstract

Successful use of anticancer designer drugs is likely to depend on simultaneous combinations of these drugs to minimize the development of resistant cancer cells. Considering the knowledge base of cancer signaling pathways, mechanisms of designer drug resistance should be anticipated, and early clinical trials could be designed to include arms that combine new drugs specifically with currently US Food and Drug Administration (FDA)-approved drugs expected to blunt alternative signaling pathways. In this review, we indicate examples of alternative signal pathways for recent anticancer drugs, and the use of original, Python-based software to systematically identify signaling pathways that could facilitate resistance to drugs targeting a particular protein. Pathway alternatives can be assessed at http://www.alternativesignalingpathways.com, developed with this review article.

Original language	English (US)
Article number	1581
Pages (from-to)	790-793
Number of pages	4
Journal	Drug Discovery Today
Volume	20
Issue number	7
DOIs	https://doi.org/10.1016/j.drudis.2015.02.005
State	Published - Jul 9 2015
Externally published	Yes

ASJC Scopus subject areas

Pharmacology
Drug Discovery

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.drudis.2015.02.005

Cite this

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title = "Anticipating designer drug-resistant cancer cells",

abstract = "Successful use of anticancer designer drugs is likely to depend on simultaneous combinations of these drugs to minimize the development of resistant cancer cells. Considering the knowledge base of cancer signaling pathways, mechanisms of designer drug resistance should be anticipated, and early clinical trials could be designed to include arms that combine new drugs specifically with currently US Food and Drug Administration (FDA)-approved drugs expected to blunt alternative signaling pathways. In this review, we indicate examples of alternative signal pathways for recent anticancer drugs, and the use of original, Python-based software to systematically identify signaling pathways that could facilitate resistance to drugs targeting a particular protein. Pathway alternatives can be assessed at http://www.alternativesignalingpathways.com, developed with this review article.",

author = "Frangione, {Mark L.} and Lockhart, {John H.} and Morton, {Daniel T.} and Pava, {Libia M.} and George Blanck",

note = "Publisher Copyright: {\textcopyright} 2015 Elsevier Ltd.",

year = "2015",

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doi = "10.1016/j.drudis.2015.02.005",

language = "English (US)",

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T1 - Anticipating designer drug-resistant cancer cells

AU - Frangione, Mark L.

AU - Lockhart, John H.

AU - Morton, Daniel T.

AU - Pava, Libia M.

AU - Blanck, George

PY - 2015/7/9

Y1 - 2015/7/9

N2 - Successful use of anticancer designer drugs is likely to depend on simultaneous combinations of these drugs to minimize the development of resistant cancer cells. Considering the knowledge base of cancer signaling pathways, mechanisms of designer drug resistance should be anticipated, and early clinical trials could be designed to include arms that combine new drugs specifically with currently US Food and Drug Administration (FDA)-approved drugs expected to blunt alternative signaling pathways. In this review, we indicate examples of alternative signal pathways for recent anticancer drugs, and the use of original, Python-based software to systematically identify signaling pathways that could facilitate resistance to drugs targeting a particular protein. Pathway alternatives can be assessed at http://www.alternativesignalingpathways.com, developed with this review article.

AB - Successful use of anticancer designer drugs is likely to depend on simultaneous combinations of these drugs to minimize the development of resistant cancer cells. Considering the knowledge base of cancer signaling pathways, mechanisms of designer drug resistance should be anticipated, and early clinical trials could be designed to include arms that combine new drugs specifically with currently US Food and Drug Administration (FDA)-approved drugs expected to blunt alternative signaling pathways. In this review, we indicate examples of alternative signal pathways for recent anticancer drugs, and the use of original, Python-based software to systematically identify signaling pathways that could facilitate resistance to drugs targeting a particular protein. Pathway alternatives can be assessed at http://www.alternativesignalingpathways.com, developed with this review article.

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DO - 10.1016/j.drudis.2015.02.005

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Anticipating designer drug-resistant cancer cells

Abstract

ASJC Scopus subject areas

UN SDGs

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