Comparison of the Cancer Gene Targeting and Biochemical Selectivities of All Targeted Kinase Inhibitors Approved for Clinical Use

<div><p>The anti-proliferative activities of all twenty-five targeted kinase inhibitor drugs that are in clinical use were measured in two large assay panels: (1) a panel of proliferation assays of forty-four human cancer cell lines from diverse tumour tissue origins; and (2) a panel of more than 300 kinase enzyme activity assays. This study provides a head-on comparison of all kinase inhibitor drugs in use (status Nov. 2013), and for six of these drugs, the first kinome profiling data in the public domain. Correlation of drug activities with cancer gene mutations revealed novel drug sensitivity markers, suggesting that cancers dependent on mutant <i>CTNNB1</i> will respond to trametinib and other MEK inhibitors, and cancers dependent on <i>SMAD4</i> to small molecule EGFR inhibitor drugs. Comparison of cellular targeting efficacies reveals the most targeted inhibitors for EGFR, ABL1 and BRAF(V600E)-driven cell growth, and demonstrates that the best targeted agents combine high biochemical potency with good selectivity. For ABL1 inhibitors, we computationally deduce optimized kinase profiles for use in a next generation of drugs. Our study shows the power of combining biochemical and cellular profiling data in the evaluation of kinase inhibitor drug action.</p></div

Selective Targeting of <i>CTNNB1-</i>, <i>KRAS-</i> or <i>MYC-</i>Driven Cell Growth by Combinations of Existing Drugs

<div><p>The aim of combination drug treatment in cancer therapy is to improve response rate and to decrease the probability of the development of drug resistance. Preferably, drug combinations are synergistic rather than additive, and, ideally, drug combinations work synergistically only in cancer cells and not in non-malignant cells. We have developed a workflow to identify such targeted synergies, and applied this approach to selectively inhibit the proliferation of cell lines with mutations in genes that are difficult to modulate with small molecules. The approach is based on curve shift analysis, which we demonstrate is a more robust method of determining synergy than combination matrix screening with Bliss-scoring. We show that the MEK inhibitor trametinib is more synergistic in combination with the BRAF inhibitor dabrafenib than with vemurafenib, another BRAF inhibitor. In addition, we show that the combination of MEK and BRAF inhibitors is synergistic in <i>BRAF</i>-mutant melanoma cells, and additive or antagonistic in, respectively, <i>BRAF</i>-wild type melanoma cells and non-malignant fibroblasts. This combination exemplifies that synergistic action of drugs can depend on cancer genotype. Next, we used curve shift analysis to identify new drug combinations that specifically inhibit cancer cell proliferation driven by difficult-to-drug cancer genes. Combination studies were performed with compounds that as single agents showed preference for inhibition of cancer cells with mutations in either the <i>CTNNB1</i> gene (coding for β-catenin), <i>KRAS</i>, or cancer cells expressing increased copy numbers of <i>MYC</i>. We demonstrate that the Wnt-pathway inhibitor ICG-001 and trametinib acted synergistically in Wnt-pathway-mutant cell lines. The ERBB2 inhibitor TAK-165 was synergistic with trametinib in <i>KRAS</i>-mutant cell lines. The EGFR/ERBB2 inhibitor neratinib acted synergistically with the spindle poison docetaxel and with the Aurora kinase inhibitor GSK-1070916 in cell lines with <i>MYC</i> amplification. Our approach can therefore efficiently discover novel drug combinations that selectively target cancer genes.</p></div

Biochemical profiling of marketed kinase inhibitors.

<p>A: Hierarchical clustering of inhibitory profiles of all kinase drugs in a panel of more than 300 biochemical kinase assays (%-inhibition at 1 μM inhibitor concentration). Trametinib, everolimus and temsirolimus show only minor inhibition, as mTOR and MEK kinase assays are not included in the panel. B: Potent biochemical IC₅₀s on the biological target correlate with more potent cellular IC₅₀s. C: Biochemical selectivity leads to a more selective response in the cell panel. Biochemical selectivity was quantified by selectivity entropy <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092146#pone.0092146-Uitdehaag2" target="_blank">[33]</a> and the selectivity of targeting cell growth was expressed by the average IC₅₀ in the cell panel. Non-oncology drugs fasudil and tofacitinib were deleted from the analysis because of lack of response. Open circles: the mTOR and MEK inhibitors everolimus, temsirolimus and trametinib, respectively.</p

Comparison of the targeting efficacy of marketed inhibitors.

<p>Each circle represents a marketed kinase inhibitor and its targeted cell growth inhibition. A: Cell lines that overexpress <i>EGFR</i>. B: Cell lines containing the <i>BRAF(V600E)</i> mutation. C: Cell lines containing aberrant <i>ABL1</i> signalling. Compounds in the upper left corner of the plots have superior targeting. Statistically relevant associations after correction for multiple testing are coloured blue. D: Quantitative comparison of inhibitor targeting by standardization of IC₅₀ shifts between sensitive and non-sensitive cell lines.</p

2D structures of the kinase inhibitors profiled in this study.

<p>All are kinase inhibitors that were approved for clinical use at Nov. 2013.</p

Overview of marketed kinase inhibitors, their applications and biochemical characteristics.

1<p>Based on FDA label information.</p>2<p>based on biochemical data presented in this work and in ref. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092146#pone.0092146-Kitagawa1" target="_blank">[11]</a>. Calculation of selectivity entropy as outlined in ref. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092146#pone.0092146-Uitdehaag2" target="_blank">[33]</a>. Entropy numbers in italic were calculated from single concentration profilings.</p>3<p>ponatinib was recently withdrawn from US markets, but is still available outside the US.</p>4<p>temsirolimus and everolimus inhibit mTOR through complex formation with FKBP12, value indicates binding interaction with FKBP12 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092146#pone.0092146-Sedrani1" target="_blank">[55]</a>.</p

Cellular profiling of marketed kinase inhibitors.

<p>A: Tissue origin of cell lines in the Oncolines panel. B: Frequency of cancer gene changes in the cell panel, <i>i.e.</i>, mutations, translocations and copy number changes in the COSMIC Cell Line Project <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092146#pone.0092146-Garnett1" target="_blank">[4]</a>. C: Hierarchical clustering of profiling data of marketed kinase inhibitor drugs in the 44-cell line panel. Unscaled ¹⁰logIC₅₀s were used. Doxorubicin_123 is a triplicate profiling for control. Non-kinase inhibitors are coloured red. D: Kinase inhibitors have a greater selectivity in the cell panel than classic cytotoxic agents (5-fluorouracil, cisplatin, vincristine, doxorubicin, etoposide, docetaxel and bortezomib).</p

Anova analysis reveals novel drug response markers.

<p>A: the MEK inhibitor trametinib and B: the EGFR inhibitor afatinib. The volcano plots show the average IC₅₀ shift between mutant and non-mutant cell lines (x-axis) and the significance from the Anova test (y-axis). Significance was corrected for multiple-testing and all associations above the threshold level (dotted line) are coloured green. Areas of circles are proportional with the number of cell lines carrying mutations.</p

Setup of the curve shift synergy experiments.

<p><b>A</b>: First, concentrated mixtures are made of the single agents. Subsequently, dose response curves are generated. For the overlay, all concentrations are scaled relative to the measured IC₅₀s of the single agents. The example shown is the effect of the PI3-kinase inhibitor GDC-0941 (green) and the MEK inhibitor AZD-6244 (blue) on proliferation of the HCT 116 cell line. Mixture ratios used were 1:1, red; 4:1, orange; 1:4, yellow. <b>B</b>: Calculation of the Combination Index (CI). The fraction affected <i>(F)</i> is equivalent to 1/100 of the %-effect. If CI < 1, compounds show synergy. The fitted CIs at <i>F</i> = 0.5 (50% effect), for all mixtures, are reported as CI_0.5. <b>C</b>: Calculation of the isobologram [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125021#pone.0125021.ref007" target="_blank">7</a>]. Single agent concentrations needed to achieve 75% effect in the cell proliferation assay are displayed in blue dots and connected by the blue line. The concentrations where the combination curves achieve 75% growth effect are displayed in red, yellow and orange, where the x and y coordinates are the respective component concentrations. If the combination points lie below the blue line, there is synergy. <b>D</b>: Reproducibility of CI_0.5 measurements in a positive control of AZD-6244 / GDC-0941 (light bars, average 0.33, SD: 0.06, n = 12) and a negative control of doxorubicin / doxorubicin (dark bars, average 1.04, SD: 0.16, n = 15). Both were combined in the HCT 116 cell proliferation assay. Every bar represents an individual mixture ratio (yellow, red, orange) that was tested in duplicate. <b>E:</b> Curve shift experiment of the AZD-6244 / GDC-0941 combination in the RPE-1 fibroblast cell line, which is immortalized using hTERT. Here, the combination also shows synergy.</p

Synergy of neratinib (blue) and paclitaxel (green) in cells containing a <i>MYC</i> amplification.

<p><b>A:</b><i>MYC</i>-amplified. <b>B:</b> non-<i>MYC</i>-amplified. <b>C:</b> isobologram of results in panel A, at the 75% effect cut-off level. Yellow, red, orange are mixture curves as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125021#pone.0125021.g001" target="_blank">Fig 1</a>.</p