Abstract LB181: Quantitative deep mutational scanning (qDMS) enables accurate predictions of clinical drug resistance in CML

Abstract Targeted BCR-ABL inhibitors have turned chronic myeloid leukemia (CML) from a debilitating disease into a manageable condition, yet patients continue to acquire mutations within the ABL1 gene that confer drug resistance and drive treatment failure. While existing clinical guidelines (e.g. NCCN, ELN) provide treatment recommendations for a handful of the most prevalent ABL resistant mutations, there are hundreds of mutations identified in CML patients that have no clear guidance on how they will impact treatment response and overall disease prognosis.Here, we present quantitative deep mutational scanning (qDMS), a platform designed to comprehensively evaluate the clinical impact of every possible point mutation in a drug target. We conducted a massively multiplexed dose-response assay of a saturation mutagenesis BCR-ABL library in K562 cells that were treated with a 1st or 3rd generation TKI (imatinib or asciminib). We then leveraged error-corrected next-generation sequencing (NGS) to obtain accurate mutant allele frequencies of our BCR-ABL cell library samples. Finally, we translated these measurements into dose-calibrated predictions of clinical outcomes with near-perfect (∼98%) accuracy. Our clinical dose-calibrated qDMS platform produces reliable and actionable data on every possible point mutation in BCR-ABL, and will help clinicians make more informed treatment decisions that improve CML patient response and survival. qDMS can be applied to any drug∼target combination, but is especially powerful when evaluating small molecule modulators that have known mutational liabilities. We have made these initial results available in a lightweight website (dosewise.io), which we will continue to update with additional drugs and targets. Citation Format: Marta Tomaszkiewicz, Simon Beardsley, Justin Pritchard, Joshua Reynolds. Quantitative deep mutational scanning (qDMS) enables accurate predictions of clinical drug resistance in CML [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB181.