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Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Severe autoimmune-mediated neuropathies, such as chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) and paranodopathies, often remain refractory to established immunotherapies. 1–3 Anti-CD19 chimeric antigen receptor (CAR) T cells have shown promising therapeutic potential in autoimmune conditions through substantial and sustained B-cell depletion. 4,5 Here, we report treatment of two patients with severe, treatment-refractory autoimmune neuropathies using autologous anti-CD19 CAR T cells ( appendix pp 2–3). In March, 2023, the patient first presented to our university hospital with rapid progression to symmetric tetraplegia despite extensive immunotherapy (intravenous immunoglobulin, corticosteroids, plasmapheresis, cyclophosphamide, rituximab, obinutuzumab, and bortezomib; appendix pp 4–6). JM declares stock ownership from Amgen, Bayer, and Sanofi; travel grants from Alnylam, Biogen Idec, Novartis, Teva, Eisai, Neuraxpharm, Bristol Myers Squibb, and Kyverna; consulting fees from Novartis and Alnylam; and research funding from Klaus Tschira Foundation, Ruhr-University Bochum (FoRUM program), Deutsche Multiple Sklerose Gesellschaft, Hertie Foundation, Novartis, and Kyverna, not related to this work.

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.