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Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery

The use of many anticancer drugs is problematic due to severe adverse effects. While the recent clinical launch of several kinase inhibitors led to tremendous progress, these targeted agents tend to be of non-specific nature within the kinase target class. Moreover, target mediated adverse effects l...

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Autores principales: Albrecht, Hugo, Kübler, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781325/
https://www.ncbi.nlm.nih.gov/pubmed/31480803
http://dx.doi.org/10.3390/pharmaceutics11090454
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author Albrecht, Hugo
Kübler, Eric
author_facet Albrecht, Hugo
Kübler, Eric
author_sort Albrecht, Hugo
collection PubMed
description The use of many anticancer drugs is problematic due to severe adverse effects. While the recent clinical launch of several kinase inhibitors led to tremendous progress, these targeted agents tend to be of non-specific nature within the kinase target class. Moreover, target mediated adverse effects limit the exploitation of some very promising kinase targets, including mitotic kinases. A future strategy will be the development of nanocarrier-based systems for the active delivery of kinase inhibitors using cancer specific surface receptors. The G-protein-coupled-receptors (GPCRs) represent the largest cell surface receptor family and some members are known to be frequently overexpressed in various cancer types. In the presented study, we used ovarian cancer tissues as an example to systematically identify concurrently overexpressed GPCRs and kinases. The rationale of this approach will guide the future design of nanoparticles, which will dock to GPCRs on cancer cells via specific ligands and deliver anticancer compounds after receptor mediated internalization. In addition to this, the approach is expected to be most effective by matching the inhibitor profiles of the delivered kinase inhibitors to the observed kinase gene expression profiles. We validated the suggested strategy in a meta-analysis, revealing overexpression of selected GPCRs and kinases in individual samples of a large ovarian cancer data set. The presented data demonstrate a large untapped potential for personalized cancer therapy using high-end targeted nanopharmaceuticals with kinase inhibitors.
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spelling pubmed-67813252019-10-30 Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery Albrecht, Hugo Kübler, Eric Pharmaceutics Article The use of many anticancer drugs is problematic due to severe adverse effects. While the recent clinical launch of several kinase inhibitors led to tremendous progress, these targeted agents tend to be of non-specific nature within the kinase target class. Moreover, target mediated adverse effects limit the exploitation of some very promising kinase targets, including mitotic kinases. A future strategy will be the development of nanocarrier-based systems for the active delivery of kinase inhibitors using cancer specific surface receptors. The G-protein-coupled-receptors (GPCRs) represent the largest cell surface receptor family and some members are known to be frequently overexpressed in various cancer types. In the presented study, we used ovarian cancer tissues as an example to systematically identify concurrently overexpressed GPCRs and kinases. The rationale of this approach will guide the future design of nanoparticles, which will dock to GPCRs on cancer cells via specific ligands and deliver anticancer compounds after receptor mediated internalization. In addition to this, the approach is expected to be most effective by matching the inhibitor profiles of the delivered kinase inhibitors to the observed kinase gene expression profiles. We validated the suggested strategy in a meta-analysis, revealing overexpression of selected GPCRs and kinases in individual samples of a large ovarian cancer data set. The presented data demonstrate a large untapped potential for personalized cancer therapy using high-end targeted nanopharmaceuticals with kinase inhibitors. MDPI 2019-09-02 /pmc/articles/PMC6781325/ /pubmed/31480803 http://dx.doi.org/10.3390/pharmaceutics11090454 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Albrecht, Hugo
Kübler, Eric
Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery
title Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery
title_full Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery
title_fullStr Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery
title_full_unstemmed Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery
title_short Systematic Meta-Analysis Identifies Co-Expressed Kinases and GPCRs in Ovarian Cancer Tissues Revealing a Potential for Targeted Kinase Inhibitor Delivery
title_sort systematic meta-analysis identifies co-expressed kinases and gpcrs in ovarian cancer tissues revealing a potential for targeted kinase inhibitor delivery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781325/
https://www.ncbi.nlm.nih.gov/pubmed/31480803
http://dx.doi.org/10.3390/pharmaceutics11090454
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