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PO-456 Cell line panel profiling of all clinically approved kinase inhibitors for cancer treatment
Author(s) -
Jeffrey J. Kooijman,
Joost C.M. Uitdehaag,
J.A.D.M. De Roos,
Judith R.F. de Vetter,
Martine B.W. Prinsen,
Jelle Dylus,
J. de Man,
Suzanne J.C. van Gerwen,
Rogier C. Buijsman,
Guido J.R. Zaman
Publication year - 2018
Publication title -
esmo open
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.409
H-Index - 31
ISSN - 2059-7029
DOI - 10.1136/esmoopen-2018-eacr25.477
Subject(s) - profiling (computer programming) , medicine , cancer cell lines , cancer , cancer research , oncology , cancer cell , computer science , operating system
Profiling of drugs on cancer cell line panels can uncover new insights into the mechanisms of drug response. We have established a panel of 102 genetically well-characterised cell lines from distinct tumour origins, called Oncolines. Earlier work on kinase inhibitor profiling showed that our workflow generates highly reproducible data.1 Here we present the profiling of seventeen kinase inhibitors which have been approved since November 2014 in the Oncolines panel.2 Material and methods The profiled agents include the ALK inhibitors ceritinib, brigatinib, and alectinib, the CDK4/6 inhibitors palbociclib, abemaciclib, and ribociclib, the BTK inhibitors ibrutinib, and acalabrutinib, and nine other novel marketed inhibitors that were not profiled earlier.2 The cell lines were screened in parallel in a high-throughput proliferation assay based on ATP-lite read-out, at 9 duplicate concentrations of each inhibitor. Drug response was expressed as IC50 and GR50 values.3 Drug response metrics were associated with genomic alterations in the cell lines. These were retrieved from the Catalogue of Somatic Mutations in Cancer database and filtered for relevance in primary patient tumours. In addition, we calculated correlations between the log IC50s and basal gene expression levels of 18 900 genes, retrieved from the Cancer Cell Line Encyclopaedia. Correlations were filtered by the Oncolines database of 150 previously profiled anti-cancer agents.1 Results and discussions Of the ALK inhibitors, alectinib was more selective than ceritinib and brigatinib. Cell lines harbouring the NPM-ALK translocation were potently inhibited by all three inhibitors. There was a strong correlation between drug sensitivity and high ALK expression levels. Furthermore, elevated expression of JAK3 and other JAK-STAT signalling genes correlated with drug sensitivity, indicating a potential role of JAK-STAT signalling in response to ALK inhibitors. Elevated expression of the transcription factor MYCN was indicative of the sensitivity of NPM-ALK negative cell lines for ceritinib and brigatinib. Conclusion By profiling all clinically approved kinase inhibitors, we were able to compare their selectivity and identify novel response biomarkers. These data will be important in guiding novel applications of these inhibitors as well as future drug development in the kinase field. References Uitdehaag, et al. Mol. Cancer Therap 2016;15:3091–3109. Uitdehaag, et al. PLoS One 2014;9:e92146. Hafner, et al. Nat. Methods 2016;13:521–527.

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