Abstract 4248: Predictive signature of response to EGFR tyrosine kinase inhibitors in non-small-cell lung cancer cells by tyrosine kinase activity profiling
Authors: Naoki Izawa, Masakuni Serizawa, Faris Naji, Rik de Wijn, Riet Hilhorst, Rob Ruijtenbeek, Hirofumi Yasui, Takako Nakajima, Narikazu Boku, Yasuhiro Koh
Journal: Cancer Research (2014)

Abstract Background: There is an urgent need to develop companion diagnostics for response prediction to increase the success rate of anticancer drug development. Constitutively activated protein kinases are major targets for cancer treatment. However, blockade of target molecules may not necessarily lead to treatment response. Thus we attempted to investigate the consequences of target kinase inhibition by comprehensive tyrosine kinases activity profiling, which can be applied to establish a response prediction signature. Here we employed clinically validated EGFR-targeted inhibition as in vitro model utilizing PamChip® peptide micro-arrays. Methods: Eight lung cancer cell lines harboring either wild-type EGFR (A549, H1781 and H441) or mutant EGFR (HCC4006, PC9, HCC827, H1650 and H1975) were used. Chemosensitivity to EGFR inhibitors (gefitinib, erlotinib and afatinib) was evaluated by MTT assay and IC50 values were obtained. For assessment of protein tyrosine kinase activity, cell lysates were prepared, aliquoted and stored at -80°C until use. The tyrosine kinase activity of the lysates was measured with or without EGFR TKIs on PamChip® peptide micro-arrays, containing 144 peptides derived from known human phosphorylation sites. Data analysis was carried out on both basal and inhibition profiles. Inhibition profiles were calculated for each EGFR TKI by taking the log-ratio of peptide phosphorylation measured with or without EGFR TKIs using BioNavigator6 software. Peptides that did not show increase of signal in time (indicative of kinase activity) were excluded from the analysis. Results: Basal tyrosine kinase activity profiles showed a clear segregation between EGFR driven (HCC4006, PC9, and HCC827) and EGFR independent (H1650, H441 and A549) cells. Additionally, overall tyrosine kinase activities in EGFR mutant cells were higher than those in EGFR wild-type cells. Based on IC50 values for three EGFR TKIs, the cell lines were divided into responders (PC9, HCC4006 and HCC827 with IC50 values ≦0.1 μmol/L), non-responders (H1650, H441 and A549 with IC50 values &amp;gt;1 μmol/L) and intermediate responders. Basal phosphorylation signals on a number of peptides differed between responders and non-responders. The responders showed phosphorylation on sites responsible for activating RAF, ERK1/2 and MAPK7 and on sites for inactivating the phosphatases PP2AB and PTN11. The phosphorylation was absent in the non-responders, possibly as a consequence of constitutive activation of the RAS/RAF pathway. This peptide set was suggested to serve as a predictive signature of response to EGFR TKIs. Conclusions: Kinase activity profiles reflect the biochemical consequences of EGFR mutant non-small-cell lung cancer. Tyrosine kinase activity profiling may serve as companion diagnostic in drug development and this should be further explored. Citation Format: Naoki Izawa, Masakuni Serizawa, Faris Naji, Rik de Wijn, Riet Hilhorst, Rob Ruijtenbeek, Hirofumi Yasui, Takako Nakajima, Narikazu Boku, Yasuhiro Koh. Predictive signature of response to EGFR tyrosine kinase inhibitors in non-small-cell lung cancer cells by tyrosine kinase activity profiling. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4248. doi:10.1158/1538-7445.AM2014-4248