Architecture and Trajectory of Acquired Resistance to Therapy in AML

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PROJECT SUMMARY: Overall The long-term goal of this Program is to define mechanisms of acquired drug resistance in acute myeloid leukemia (AML) so that novel drug combinations can be deployed to prevent disease relapse and improve patient outcomes. The overall five-year survival rate for AML remains 20%, an outcome that has not changed for several decades. Although seven new regimens have been approved for AML in recent years, the improved initial remission rates with these therapies do not lead to durable outcomes. Disease relapse is fueled by a complex cross-talk of tumor cells adapting with support from the bone marrow microenvironment. The investigators of this proposed ARTNet Center have collaborated for 15+ years, including as a Center in the DRSN consortium – the predecessor to ARTNet. Our prior work has involved development of the largest-to-date functional genomic dataset on AML patient samples, genome-wide CRISPR screens, broad studies of AML interactions with stromal and immune cells, and testing of diverse drug combinations. These studies have led to >150 collaborative publications, continuous collaborative funding for 15+ years, creation of numerous large datasets deposited into public repositories, and translation of findings into numerous clinical trials. Our overarching hypothesis is that the architecture of acquired drug resistance is governed by temporal extrinsic and intrinsic factors and elucidating this trajectory will allow for the identification of properly timed therapeutic strategies to stave off acquired resistance and stay ahead of tumor evolution and adaptation. This hypothesis will be tested through three well integrated Projects addressing the following questions: 1) How does AML tumor cell intrinsic biology adapt to evade therapeutic pressure? We will use genome-wide CRISPR platforms as well as long-term progenitor expansion of primary AML patient samples to understand feedback pathways and shifting epigenetic and cell state landscapes that can drive acquired drug resistance. 2) How does the stromal and immune microenvironment govern drug resistance? We will use co-culture and advanced bone marrow models to perform genome-wide screens and test the impact of single-agents on AML-microenvironment cross-talk. Through computational modeling, we will nominate targeting strategies to mitigate tumor extrinsic resistance signals and boost immune anti-tumor responses. 3) How can resistance signatures and drug combinations be effectively clinically translated? We will use high-throughput and advanced, engineered models of human bone marrow to test and prioritize drug combinations from targets in Projects 1 and 2. We will also study longitudinal specimens from patients enrolled on ongoing clinical trials. All of these data will inform and refine the work of Projects 1 and 2. Our Center will be supported by an Administrative Core and a Functional Phenotyping Core. Collectively, we will develop a comprehensive understanding of acquired drug resistance in AML and identify new regimens to treat patients at the earliest possible stage, prevent relapse, and achieve durable remissions.