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Pharmaceutics. 2019 Sep 2;11(9). pii: E454. doi: 10.3390/pharmaceutics11090454.

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

Author information

1
Drug Discovery and Development Group, Centre for Cancer Diagnostics and Therapeutics, Cancer Research Institute, University of South Australia, Adelaide 5000, Australia.
2
Institute for Chemistry and Bioanalytics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland FHNW, 4132 Muttenz, Switzerland. eric.kuebler@fhnw.ch.

Abstract

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.

KEYWORDS:

GPCR; cancer; kinase; personalized medicine; targeted drug delivery

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