# Trajectory and Architecture of Tumor Intrinsic Drug Resistance in AML

> **NIH NIH U54** · OREGON HEALTH & SCIENCE UNIVERSITY · 2022 · $369,544

## Abstract

PROJECT SUMMARY/ABSTRACT: Project 1
Acute myeloid leukemia (AML) is a complex and genetically heterogenous disease and one of the most common
hematologic malignancies. After 30-40 years without new therapies, several recent drugs have been approved
for AML, including inhibitors of FLT3, IDH1/2, and BCL2. Despite improved initial response rates, none of these
regimens lead to durable remissions. Acquired resistance to these agents develops due to diverse mechanisms
that include tumor cell adaptation, often driven by microenvironmental signals. For the past decade, our
collaborative team has employed numerous techniques, models, and analytical approaches to studying acquired
drug resistance in AML – partly as a Center in the Drug Sensitivity and Resistance Network (DRSN) – the
predecessor to ARTNet. We have developed the largest-to-date functional genomics platform of primary AML
patient samples and implemented genome-wide CRISPR screening. Computational integration of these datasets
has generated many predictions for mechanisms of drug resistance and nominated rationally selected drug
combinations, some of which are in clinical trials. This analysis has led to a central hypothesis that tumor
intrinsic biology can adapt in the face of therapeutic pressure, often with support from cell extrinsic
signals, to undergo a multi-step process where early drug resistance is formed via cross-talk with
immune and stromal cells that leads to an eventual late, cell autonomous resistant state with features of
clonal evolution. For this project, our long-term goals are to optimize and translate the most effective drug
combinations into the clinic for patients with AML. Our immediate goals are to understand tumor
intrinsic mechanisms of acquired drug resistance. To accomplish these goals, three Aims are proposed: 1)
Next-generation genome-wide interrogation of key acquired resistance scenarios – We created a panel of AML
models of acquired drug resistance. These models have been generated with long-term drug exposure,
sometimes with support from extrinsic cytokines. We will subject these drug resistant cells to genome-wide
CRISPR screens with overlay of drugs or drug combinations. 2) Epigenomic evolution of acquired resistance –
We will use protocols for expansion of myeloid progenitor cells from primary AML patient samples to study
epigenetic adaptation. Using the same list of drugs and drug combinations as in Aim 1, we will profile shifts in
epigenetic landscape using single-cell sequencing. 3) Atlas of intrinsic drug resistance in AML – We have
expertise with broad data integration and modeling approaches. We will use these strategies to leverage our
existing functional genomic dataset combined with the new data generated in Aims 1 and 2 to generate an Atlas
of tumor intrinsic mechanisms of acquired drug resistance in AML. Cumulatively, we expect these innovative
analyses to have a major impact on our understanding of acquired drug resistance in AML, leading to...

## Key facts

- **NIH application ID:** 10517760
- **Project number:** 2U54CA224019-05
- **Recipient organization:** OREGON HEALTH & SCIENCE UNIVERSITY
- **Principal Investigator:** Jeffrey Wallace Tyner
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $369,544
- **Award type:** 2
- **Project period:** 2017-09-30 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10517760

## Citation

> US National Institutes of Health, RePORTER application 10517760, Trajectory and Architecture of Tumor Intrinsic Drug Resistance in AML (2U54CA224019-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10517760. Licensed CC0.

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