Related Experiment Video
Updated: Oct 7, 2026

Creating Matched In vivo/In vitro Patient-Derived Model Pairs of PDX and PDX-Derived Organoids for Cancer Pharmacology Research
Published on: May 5, 2021
A platform of serially transplantable AML PDX models covering subgroups for which no cell lines exist
Binje Vick1,2, Vindi Jurinovic1,3,4, Kristina Kuhbandner5,6
1Research Unit Apoptosis in Hematopoietic Stem Cells Helmholtz Munich, German Research Center for Environmental Health (HMGU) Munich Germany.
Abstract:
Acute myeloid leukemia (AML) is a highly aggressive malignancy with poor prognosis, underlining the need for suitable model systems to develop novel treatments. To complement the few existing AML cell lines and restricted primografts, we transplanted more than 100 primary AML samples into immunocompromised mice and generated 23 exceptionally robust patient-derived xenograft (*PDX) models of AML that allow virtually unlimited serial transplantation and efficient genetic engineering. These models represent individuals of all age groups and several WHO subgroups. *PDX models substantially outperform AML cell lines in preserving leukemia biology and include AML subgroups for which no cell lines exist, such as cytogenetically normal or IDH1/2-mutant AML or simultaneous NPM1 mutation and FLT3-ITD. Their resilience to freeze-thaw cycles supports broad dissemination across research institutions through sharing via CancerModels.org. Using lentiviruses, we stably expressed luciferase for longitudinal, noninvasive, and sensitive real-time monitoring of leukemia burden and therapeutic response in vivo. This approach enabled rigorously controlled preclinical studies, including phase II-like trials, which demonstrated highly variable treatment responses between different *PDX models, mimicking the heterogeneity in patient cohorts. Long-term treatment, including repeated cytarabine exposure over 1 year, showed a yet undescribed decrease in leukemia's proliferation rate. These insights underscore the platform's distinctive capacity to study treatment dynamics over clinically relevant timeframes. Collectively, our unique resource represents a powerful, robust, and versatile platform with strong potential to accelerate translational AML research for the ultimate benefit of patients.
