3DRP-AML: 3D hydrogel-based ex vivo drug response profiling platform to personalize therapy in high-risk acute myeloid leukemia

• Applicant: Dr. Maximilian Fusenig
• Subject Area: Hematology, Oncology ; Biomaterials ; Cell Biology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 556416293

The proposed project targets the unmet clinical need of a high throughput screening (HTS) platform for the effective cell culture and drug response profiling of AML patient samples. We hypothesize that our HTS-compatible 3D starPEG-sGAG hydrogel system can uniquely mimic the biophysical and biochemical properties of the bone marrow, thereby supporting AML cell survival and clonal expansion ex vivo. Based on that, we intend to show that our system enables high-resolution drug response profiling of AML patient cells in 3D cultures. Our objectives are: (1) To establish 3D starPEG-sGAG hydrogel cultures of patient-derived AML cells for HTS, profiling and modeling the influence and interplay of the biophysical and biochemical properties of the 3D microenvironment on AML culture and drug response (3DRP-AML). (2) To validate 3DRP-AML cultures against published 2D reference setups by implementing high-resolution, time-resolved analyses via bright field microscopy, supernatant-based metabolic analyses and high-throughput multiparameter flow cytometry (HT-MFC). (3) To implement the 3DRP-AML platform with varied gel matrices (n=3), a diverse cohort from the Study Alliance Leukemia (SAL) biorepository (n=100) and a library of FDA-approved AML drugs (n=20). For a small cohort, we further plan to verify AML clonal heterogeneity upon expansion in 3DRP-AML cultures via single-cell 'DNA and Antibody Sequencing' proteogenomics (n=8, Dab-Seq). (4) To correlate high-resolution data of 3DRP-AML platform with multi-modal clinical parameters via machine learning-based models (classification and regression algorithms).

• DFG Programme: Research Grants