Systematically Studying Kinase Inhibitor Induced Signaling Network Signatures by Integrating Both Therapeutic and Side Effects

<div><p>Substantial effort in recent years has been devoted to analyzing data based large-scale biological networks, which provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or compounds. In this work, we proposed a novel strategy to investigate kinase inhibitor induced pathway signatures by integrating multiplex data in Library of Integrated Network-based Cellular Signatures (LINCS), e.g. KINOMEscan data and cell proliferation/mitosis imaging data. Using this strategy, we first established a PC9 cell line specific pathway model to investigate the pathway signatures in PC9 cell line when perturbed by a small molecule kinase inhibitor GW843682. This specific pathway revealed the role of PI3K/AKT in modulating the cell proliferation process and the absence of two anti-proliferation links, which indicated a potential mechanism of abnormal expansion in PC9 cell number. Incorporating the pathway model for side effects on primary human hepatocytes, it was used to screen 27 kinase inhibitors in LINCS database and PF02341066, known as Crizotinib, was finally suggested with an optimal concentration 4.6 uM to suppress PC9 cancer cell expansion while avoiding severe damage to primary human hepatocytes. Drug combination analysis revealed that the synergistic effect region can be predicted straightforwardly based on a threshold which is an inherent property of each kinase inhibitor. Furthermore, this integration strategy can be easily extended to other specific cell lines to be a powerful tool for drug screen before clinical trials.</p></div

Leave-one-out cross-validation for PC9 cell line specific pathway model.

<p>Leave-one-out cross-validation for PC9 cell line specific pathway model.</p

Datasets in LINCS database.

<p>Datasets in LINCS database.</p

PC9 cell line specific pathway.

<p>PC9 cell line specific pathway.</p

Coefficient of variation analysis for parameters in PC9 cell line specific pathway.

<p>Coefficient of variation analysis for parameters in PC9 cell line specific pathway.</p

Six kinase inhibitors with highest effect index for PC9 cell line.

<p>Six kinase inhibitors with highest effect index for PC9 cell line.</p

Cell cycle related pathway extracted from literatures and pathway databases.

<p>Cell cycle related pathway extracted from literatures and pathway databases.</p

Combination effect of different kinase inhibitors.

<p>The combination effect is: I) synergy, if <i>CI_Bliss</i>(<i>x</i>,<i>y</i>)<1. II) additivity, if <i>CI_Bliss</i>(<i>x</i>,<i>y</i>) = 1. III) antagonism, if <i>CI_Bliss</i>(<i>x</i>,<i>y</i>)>1.</p

KINOMEscan data of GW843682 at 10 uM.

<p>KINOMEscan data of GW843682 at 10 uM.</p

Optimal concentration of each kinase inhibitor for PC9 cancer cell line treatment.

<p>Optimal concentration of each kinase inhibitor for PC9 cancer cell line treatment.</p