Abstract 1398: Modeling of drug-protein interactions to support clinical decision making for therapy-resistant <i>EGFR</i> or <i>ALK</i>-positive non-small cell lung carcinoma
Authors: Juliana F. Vilacha Madeira R Santos, Birgitta I. Hiddinga, Leon C. van Kempen, Arja ter Elst, Lucie B. Hijmering, Thijo J. Hiltermann, Ed Schuuring, Matthew R. Groves, Harry J. Groen, Anthonie J. van der Wekken
Journal: Cancer Research (2019)

Abstract Background Activating mutations in epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) rearrangements are drugable targets in respectively 10% and 4% of advanced non-small cell lung cancer (NSCLC) patients. Different EGFR and ALK inhibitors are available for target-dependent and sometimes independent drug resistance. Mutations in the EGFR or ALK kinase domain are major mechanisms of drug-induced resistance. Prediction of protein-drug interactions using protein modeling of these mutated domains in EGFR and ALK could provide valuable information for the selection of drugs for subsequent treatment. Methods Biopsies from advanced NSCLC patients with an activating EGFR mutation or ALK rearrangement that were taken at therapy resistance were analyzed by targeted panel sequencing. In case of unknown or accumulating mutations in the EGFR and ALK kinase domains, docking poses and binding affinities of drug-protein interactions were determined. The outcome of both calculations were used to create a likelihood ranking of currently available ALK and EGFR inhibitors to bind to specific mutated targets. Follow-up data was available for a limited number of patients who were treated based on this prediction. Results Prediction Protein-drug interactions were modeled for 59 EGFR mutations and 24 ALK mutations that were detected at therapy resistance. Prediction of therapeutic activities for gefitinib, afatinib, dacomitinib, for EGFR mutations, and alectinib, ceritinib, entrectinib and lorlatinib for ALK mutations will be shown. Case example Female (35y), never-smoker, cT1bN2M1c NSCLC with metastases in lymph nodes, liver, bones and asymptomatic brain metastases, ALK translocation-positive without known ALK gatekeeper mutations. Treatment with crizotinib was started, but unacceptable liver enzyme toxicity developed after 6 weeks. Switching therapy to alectinib resulted in a complete metabolic response with absence of brain metastases by MRI. After 9 months the patient progressed with liver, brain and leptomeningeal metastases. Treatment with ceritinib had no effect. A liver biopsy revealed the ALK p.(L1196M) gatekeeper mutation. The case was discussed in the molecular tumor board, because this gatekeeper variant was reported to be sensitive to ceritinib. In contrast, ALK-drug interaction modeling indicated a better binding profile of lorlatinib than ceritinib, not only based in binding affinity but also in the ability of lorlatinib to reproduce the bioactive conformation found in literature. The patient was treated with lorlatinib and recovered in 5 days with a persistent partial response at 2 month follow up and significant clinical benefit. Conclusion Modeling of the protein-drug interactions supports clinical decision making for treatment of NSCLC patients in case of therapy resistance to EGFR and ALK inhibitors. Citation Format: Juliana F. Vilacha Madeira R Santos, Birgitta I. Hiddinga, Leon C. van Kempen, Arja ter Elst, Lucie B. Hijmering, Thijo J. Hiltermann, Ed Schuuring, Matthew R. Groves, Harry J. Groen, Anthonie J. van der Wekken. Modeling of drug-protein interactions to support clinical decision making for therapy-resistant EGFR or ALK-positive non-small cell lung carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1398.