Selection of Protein Kinase Inhibitors Based on Tumor Tissue Kinase Activity Profiles in Patients with Refractory Solid Malignancies: An Interventional Molecular Profiling Study

Mariette Labots, Johannes C Van der Mijn, Henk Dekker, Rita Ruijter, Thang V Pham, Hans J Van der Vliet, Jacobus J M Van der Hoeven, Gerrit A Meijer, Henk M W Verheul, Mariette Labots, Johannes C Van der Mijn, Henk Dekker, Rita Ruijter, Thang V Pham, Hans J Van der Vliet, Jacobus J M Van der Hoeven, Gerrit A Meijer, Henk M W Verheul

Abstract

Lessons learned: Clinically applicable tools are needed for treatment selection and repurposing of available protein kinase inhibitors (PKIs) in patients with advanced solid tumors refractory to standard treatment.Using a tyrosine kinase peptide substrate microarray, observed inhibitory activity in vitro could not sufficiently predict clinical benefit of treatment with the selected PKI.

Background: This exploratory molecular profiling study determined the feasibility and benefit of the selection of protein kinase inhibitors (PKIs) based on kinase activity profiling in patients with refractory solid malignancies.

Methods: Adult patients with biopsy-accessible refractory solid tumors were eligible. Per patient, the inhibitory potency of sunitinib, dasatinib, erlotinib, sorafenib, everolimus, and lapatinib was determined in tumor lysates from fresh biopsies using a tyrosine kinase peptide substrate microarray. The most active PKI in this in vitro assay was selected for treatment.

Results: Thirteen patients were enrolled in the feasibility part and underwent tumor biopsy. Of 12 patients in whom kinase activity profiling was performed, 11 started treatment with a selected PKI: dasatinib in 8, sunitinib in 2, and erlotinib in 1 patient(s). Eight patients were evaluable for response. One patient had stable disease (SD) >4 months on sunitinib; one patient had SD at 6 weeks but progressive disease (PD) at 12 weeks. The remaining patients had PD after 6 weeks of treatment.

Conclusion: Kinase inhibition profiles of multiple PKIs can be reliably determined using fresh tumor biopsies from patients with refractory solid tumors. However, the current in vitro microarray selection approach insufficiently predicted clinical benefit of PKI treatment in these patients.

Trial registration: ClinicalTrials.gov NCT01190241.

© AlphaMed Press; the data published online to support this summary are the property of the authors.

Figures

Figure 1.
Figure 1.
Two of thirteen patients who gave informed consent could not start treatment; one patient progressed rapidly before completion of tumor profiling, and one patient became ineligible after profiling. Three patients for whom dasatinib was selected were not evaluable for response due to early clinical progression (n = 2) and patient's refusal of selected treatment (n = 1). Abbreviations: PD, progressive disease; PFS, progression‐free survival; PKI, protein kinase inhibitor; SD, stable disease.
Figure 2.
Figure 2.
Kinase activity measurement based on the PamChip (tyrosine kinase peptide substrate) microarray using a PamStation12 instrument. Per patient, control and inhibition samples were measured in triplicate using 5 µg lysate protein input per sample. Each run, based on three chips with four microarrays each, allows for simultaneous measurement of 12 samples. Shortly before application on the microarray, tumor lysate is mixed with kinase reaction buffer, containing the fluorescein‐labeled antiphosphotyrosine antibody pY20 as well as ATP, for phosphate transfer. In addition, for the inhibition samples, protein kinase inhibitors (PKIs) were spiked to the sample mix. Hereafter, incubation of the microarrays at 30°C is started for 60 cycles, during which the sample mix is transferred through the porous array once per minute. As a result of lysate kinase activity, (target) peptide substrates on chip will be phosphorylated at the tyrosine residue (Y), leading to phosphotyrosine formation, to which the fluorescein‐labeled antibody will bind. A 12‐bit charge‐coupled device camera monitors fluorescence intensities resulting from binding of the antiphosphotyrosine antibody over time. End levels of signal intensity, expressed in arbitrary units, after 60 minutes of incubation were determined for PKI‐spiked and control lysates. For each PKI, the percentage inhibition for all 144 peptide substrates on chip was calculated by dividing the mean end‐level signal intensity of the PKI‐spiked sample triplicates by the mean end‐level signal intensity of the control sample triplicates (end‐level intensity PKI/control). Peptide phosphorylation inhibition was considered to be significant if the p value calculated from a Student's t test was <.05. Kinase enzymatic activity can be inferred from recorded intensity of peptide phosphorylation over time. XXXXXXYXXXXXX denotes peptide sequence context with tyrosine (Y) substrate flanked by six other amino‐acids. Abbreviations: ATP, adenosine triphosphate; P‐peptide, phosphorylated peptide.
Figure 3.
Figure 3.
Per PKI, extrapolation of the ex‐vivo potency to their (potential) activity in patients was based on an algorithm considering the number of significantly inhibited peptides (columns) with, in the rows, their individual average percentage of inhibition (left). A PKI was considered to demonstrate no (significant) phosphorylation inhibition if the sum of the scores obtained from the algorithm was 0, low inhibition if the sum of the scores was 1, intermediate if 2 or 3, high if 4 or 5, and very high inhibition if this score was ≥6. In vitro, a PKI should at least result in intermediate phosphorylation inhibition to be considered significant and to thus be selected for therapy (right). In case ≥2 PKIs would display intermediate to very high inhibition, the agent with the highest cumulative score was selected for treatment of the patient. In case of equal scores, the least toxic drug was selected for treatment. Abbreviation: PKI, protein kinase inhibitor.

References

    1. Piersma SR, Labots M, Verheul HM et al. Strategies for kinome profiling in cancer and potential clinical applications: Chemical proteomics and array‐based methods. Anal Bioanal Chem 2010;397:3163–3171.
    1. Perner F, Schnoder TM, Fischer T et al. Kinomics screening identifies aberrant phosphorylation of CDC25C in FLT3‐ITD‐positive AML. Anticancer Res 2016;36:6249–6258.
    1. van der Sligte NE, Scherpen FJ, Meeuwsen‐de Boer TG et al. Kinase activity profiling reveals active signal transduction pathways in pediatric acute lymphoblastic leukemia: A new approach for target discovery. Proteomics 2015;15:1245–1254.
    1. van Oostrum J, Calonder C, Rechsteiner D et al. Tracing pathway activities with kinase inhibitors and reverse phase protein arrays. Proteomics Clin Appl 2009;3:412–422.
    1. Sereni MI, Baldelli E, Gambara G et al. Kinase‐driven metabolic signalling as a predictor of response to carboplatin‐paclitaxel adjuvant treatment in advanced ovarian cancers. Br J Cancer 2017;117:494–502.
    1. Baldelli E, Calvert V, Hodge A et al. Reverse phase protein microarrays. Methods Mol Biol 2017;1606:149–169.
    1. Versele M, Talloen W, Rockx C et al. Response prediction to a multitargeted kinase inhibitor in cancer cell lines and xenograft tumors using high‐content tyrosine peptide arrays with a kinetic readout. Mol Cancer Ther 2009;8:1846–1855.
    1. Sikkema AH, Diks SH, den Dunnen WF et al. Kinome profiling in pediatric brain tumors as a new approach for target discovery. Cancer Res 2009;69:5987–5995.
    1. Labots M, Gotink KJ, Dekker H et al. Evaluation of a tyrosine kinase peptide microarray for tyrosine kinase inhibitor therapy selection in cancer. Exp Mol Med 2016;48:e279.
    1. Yi JH, Thongprasert S, Lee J et al. A phase II study of sunitinib as a second‐line treatment in advanced biliary tract carcinoma: A multicentre, multinational study. Eur J Cancer 2012;48:196–201.
    1. Lemeer S, Zorgiebel C, Ruprecht B et al. Comparing immobilized kinase inhibitors and covalent ATP probes for proteomic profiling of kinase expression and drug selectivity. J Proteome Res 2013;12:1723–1731.
    1. Rovithi M, Verheul HMW. Pulsatile high‐dose treatment with antiangiogenic tyrosine kinase inhibitors improves clinical antitumor activity. Angiogenesis 2017;20:287–289.
    1. Gotink KJ, Broxterman HJ, Labots M et al. Lysosomal sequestration of sunitinib: A novel mechanism of drug resistance. Clin Cancer Res 2011;17:7337–7346.
    1. Amanchy R, Periaswamy B, Mathivanan S et al. A curated compendium of phosphorylation motifs. Nat Biotechnol 2007;25:285–286.
    1. Marx H, Lemeer S, Schliep JE et al. A large synthetic peptide and phosphopeptide reference library for mass spectrometry‐based proteomics. Nat Biotechnol 2013;31:557–564.
    1. Lankheet NA, Schaake EE, Burgers SA et al. Concentrations of erlotinib in tumor tissue and plasma in non‐small‐cell lung cancer patients after neoadjuvant therapy. Clin Lung Cancer 2015;16:320–324.
    1. Petty WJ, Dragnev KH, Memoli VA et al. Epidermal growth factor receptor tyrosine kinase inhibition represses cyclin D1 in aerodigestive tract cancers. Clin Cancer Res 2004;10:7547–7554.
    1. Mammatas LH, Verheul HM, Hendrikse NH et al. Molecular imaging of targeted therapies with positron emission tomography: The visualization of personalized cancer care. Cell Oncol (Dordr) 2015;38:49–64.
    1. Yaqub M, Bahce I, Voorhoeve C et al. Quantitative and simplified analysis of 11C‐erlotinib studies. J Nucl Med 2016;57:861–866.
    1. Labots M, van der Mijn JC, Beekhof R et al. Phosphotyrosine‐based‐phosphoproteomics scaled‐down to biopsy level for analysis of individual tumor biology and treatment selection. J Proteomics 2017;162:99–107.

Source: PubMed

3
Iratkozz fel