A sweeping genetic map of drug resistance in chronic myeloid leukemia has revealed that cancer cells can evade asciminib through mutations scattered across much more of the BCR::ABL1 protein than scientists previously realized. The study identified 279 asciminib-resistance mutations, including changes in regulatory regions far outside the enzyme’s drug-binding pocket, and uncovered a particularly powerful combination of two individually modest mutations that together produced strong resistance. The findings challenge the assumption that asciminib resistance is mainly a problem of alterations within the kinase domain and point to a common physical mechanism linking many apparently unrelated mutations: keeping BCR::ABL1 in an open, active shape when the drug tries to lock it shut.
Asciminib is a newer kind of treatment for chronic myeloid leukemia, or CML, a blood cancer driven by the abnormal BCR::ABL1 fusion protein. Earlier tyrosine kinase inhibitors, including imatinib, compete with ATP at the enzyme’s active site. Asciminib works differently. It occupies a myristoyl-binding pocket on the opposite side of the ABL1 kinase domain, mimicking the effect of a natural lipid modification that helps fold normal ABL1 into an inactive configuration. When asciminib binds, it is expected to reinforce an autoinhibited, “closed” structure in which the kinase cannot efficiently transmit growth signals. That allosteric strategy allows the drug to overcome several mutations that defeat active-site inhibitors, but it also creates a new evolutionary target: any change that prevents the protein from adopting or maintaining its closed state could allow leukemia cells to survive.
To search for those changes systematically, Ivan Sokirniy, Zeyu Yang and Justin Pritchard at Pennsylvania State University combined two complementary functional-genomics techniques in CML cell models. First, they used an adenosine base-editing screen containing 1,555 guide RNAs tiled across the BCR::ABL1 gene. Base editors can make selected A-to-G DNA changes without cutting both strands of DNA, allowing researchers to examine how mutations arising at endogenous genomic sites affect the survival of a large cell population under drug pressure. The team treated edited K562 leukemia cells with asciminib and used next-generation sequencing to identify guide RNAs that became more abundant, a signature that the associated mutations allowed cells to keep growing. An imatinib screen served as a comparison: as expected, imatinib resistance was concentrated mainly in the kinase domain, whereas asciminib resistance appeared in the SH3, SH2 and kinase domains, as well as the linker connecting them.
The base-editing screen provided breadth, but its chemistry imposes limits. It can efficiently create only certain nucleotide substitutions and can produce nearby bystander edits, making it difficult to catalog every possible amino-acid change at a promising site. The researchers therefore followed the initial screen with deep mutational scanning. In this approach, they constructed libraries containing every possible single amino-acid substitution at selected resistance hotspots, introduced those libraries into K562 cells and exposed the cells to 125 nanomolar asciminib, a concentration chosen to approximate clinically relevant exposure after accounting for serum protein binding. Variants were tracked by sequencing before and after treatment, and each mutation was assigned a growth score. The two independent scans correlated strongly, with a Pearson correlation of 0.92, and known clinical resistance mutations such as M244V, M351T, V468F and I502L behaved as expected. Using a stringent threshold for strong resistance, the study found 279 additional variants.
Some of the most striking mutations clustered within the αI′ helix that helps form the myristoyl pocket. At positions F497, I502, V506 and L510, many different amino-acid substitutions allowed cells to resist asciminib. The pattern suggests that resistance does not always depend on a single chemical clash with the drug. Instead, mutations may distort the helix or alter the hydrophobic core of the pocket, preventing asciminib from producing the structural rearrangement required for inhibition. The results included seemingly subtle examples: V506L and V506T caused strong resistance, whereas the chemically similar V506I did not. Proline substitutions formed an unusual “resistance band,” consistent with proline’s ability to kink protein helices. A previously unrecognized E505G mutation, detected by both screening methods, also produced high-level resistance. Several variants retained positive growth even at 1,000 nanomolar asciminib, well above the clinically relevant unbound concentration used for comparison in the study.
The researchers also found that the protein’s regulatory architecture is a major vulnerability. The SH3 and SH2 domains normally clamp against the kinase domain and help stabilize ABL1’s inactive form. Mutations in the SH3 domain, including changes affecting its interaction with the SH2-kinase linker, disrupted this internal brake. The linker contains proline residues, particularly P223 and P230, that fit into binding sites on the SH3 domain; altering these residues can weaken the contact and favor kinase activation. A loss-of-function SH3 mutation, P112L, was sufficient to generate high-level asciminib resistance. In the SH2 domain, the canonical phosphotyrosine-binding residue R152 was not required for resistance, suggesting that the domain’s role in this process is structural rather than simply related to its standard signaling function. Instead, mutations around Y139, Y342 and H375 appeared to disrupt a tripartite interaction at the SH2-kinase interface, destabilizing the closed state.
The most revealing result emerged when the team tested epistasis, the phenomenon in which the combined effect of two mutations differs sharply from what would be expected from their individual effects. They began with Y253H, a P-loop mutation commonly associated with resistance to imatinib. On its own, Y253H caused only a modest increase in asciminib resistance in the experimental system. The researchers then introduced a library of additional mutations into cells already carrying Y253H, creating what they describe as an “edit-on-edit” screen. Most mutations behaved similarly in cells with or without Y253H, indicating that strong epistatic interactions were uncommon. Two exceptions stood out: Y139C in the SH2 domain and V73A in the SH3 domain. V73A alone produced near-wild-type sensitivity, but when combined with Y253H, the double mutant became strongly resistant. In K562 cells, a product model assuming independent effects predicted that only about 3 percent of cells would remain viable at the bottom of the dose-response curve. The measured value was approximately 25 percent, a highly significant departure from that prediction. In Ba/F3 cells engineered to express the variants, the predicted half-maximal effective concentration was 13 nanomolar, while the observed value for the double mutant was 40 nanomolar, comparable to the clinically important M244V resistance mutation.
To understand what these mutations were doing physically, the researchers built a live-cell Förster resonance energy transfer, or FRET, biosensor for BCR::ABL1. The sensor placed a green fluorescent protein derivative, mStayGold, within the SH2 domain and a red fluorescent protein, mScarlet3, at the end of the kinase domain. When BCR::ABL1 is closed, the two fluorophores are close enough to exchange energy efficiently, producing a high FRET signal. When the protein opens, the fluorophores move farther apart and the signal falls. In cells carrying unmodified BCR::ABL1, increasing asciminib concentrations increased FRET, consistent with the drug stabilizing the closed conformation. Resistance mutations in the myristoyl pocket and kinase N-lobe reduced this drug-induced conformational shift, leaving the protein in a more open state. The V73A-Y253H double mutant showed a FRET profile similar to M244V, despite the mutations occurring at distant sites. Across nine resistance variants, the FRET measurement correlated strongly with drug sensitivity: the relationship between FRET ratio and asciminib half-maximal effective concentration had a Pearson correlation of -0.82.
That convergence gives the findings their clinical significance, although the experiments were performed in immortalized K562, Ba/F3 and HEK293T cell systems rather than in patients. The study suggests that resistance surveillance should examine the SH3 and SH2 domains, not only the kinase domain, especially as asciminib is used earlier in treatment and patients receive different inhibitors sequentially. It also complicates the design of drug combinations. Asciminib and imatinib act at different binding sites, and combining drugs with genuinely non-overlapping resistance profiles can suppress escape. But the screens found eight guide RNAs that conferred resistance to both drugs, supporting clinical evidence that some mutations, including alterations around F359, can create cross-resistance. A combination that misses such shared vulnerabilities could therefore select for cells able to withstand both therapies. The broader lesson is that resistance is not determined solely by where a drug binds. Mutations distributed throughout a protein can converge on a single mechanical failure—in this case, the inability of BCR::ABL1 to close. Mapping that failure across genetic backgrounds could help clinicians anticipate resistance before it appears and guide the design of treatment sequences that leave fewer evolutionary escape routes.
Subject of Research: Asciminib resistance mechanisms in the BCR::ABL1 fusion kinase associated with chronic myeloid leukemia
Subject of Research: Medicine
Article Title: Dual functional genomics reveals a broad and convergent landscape of asciminib resistance in BCR::ABL1
Article References: Sokirniy, I., Yang, Z., & Pritchard, J. (2026). Dual functional genomics reveals a broad and convergent landscape of asciminib resistance in BCR::ABL1. Genome Medicine, 18(1), Article 114. https://doi.org/10.1186/s13073-026-01679-x
Image Credits: AI Generated
DOI: 10.1186/s13073-026-01679-x
Keywords: asciminib, drug resistance, BCR::ABL1, chronic myeloid leukemia, deep mutational scanning, base editing, epistasis, FRET biosensor, SH3 domain, SH2 domain
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Rowan B. (August 28, 2026). Functional genomics maps broad, convergent asciminib resistance mechanisms in BCR::ABL1. Scienmag. https://scienmag.com/functional-genomics-maps-broad-convergent-asciminib-resistance-mechanisms-in-bcrabl1/
Rowan B. “Functional genomics maps broad, convergent asciminib resistance mechanisms in BCR::ABL1.” Scienmag, 28 August 2026, https://scienmag.com/functional-genomics-maps-broad-convergent-asciminib-resistance-mechanisms-in-bcrabl1/. Accessed 28 August 2026.
Rowan B. “Functional genomics maps broad, convergent asciminib resistance mechanisms in BCR::ABL1.” Scienmag. August 28, 2026. https://scienmag.com/functional-genomics-maps-broad-convergent-asciminib-resistance-mechanisms-in-bcrabl1/
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