JS04.5.A HIGH RESOLUTION DRUG-RESISTANT MAPPING OF ALK FUSION VARIANTS USING PRIME EDITING

Abstract BACKGROUND Anaplastic lymphoma kinase (ALK) gene fusions are potent oncogenic drivers across diverse malignancies, including non-small cell lung cancer (NSCLC), anaplastic large cell lymphoma (ALCL), breast cancer, and glioma. These fusions lead to constitutive activation of the ALK tyrosine kinase domain (TKD), rendering tumors initially responsive to ALK tyrosine kinase inhibitors (TKIs)—primarily in NSCLC, but also in rare cases such as infant-type hemispheric glioma. However, resistance inevitably emerges, frequently due to acquired single nucleotide variants (SNVs) within the TKD. A significant proportion of these SNVs are classified as variants of uncertain significance (VUSs), highlighting the need for systematic functional annotation to inform precision therapy. MATERIAL AND METHODS We employed prime editing to introduce all possible SNVs across the ALK TKD (exons 20-28). High-throughput drug resistance screening was conducted against three generations of ALK TKIs: alectinib (second-generation), lorlatinib (third-generation), and zotizalkib (fourth-generation, previously evaluated in clinical trials). Resistance classification data were further assessed using Kaplan-Meier survival analyses to explore potential prognostic implications. RESULTS A total of 2,953 SNVs (99.2% of all possible variants in exons 20-28) were successfully introduced and profiled. Resistance phenotypes were comprehensively mapped for each variant across the three TKIs. Canonical resistance mutations such as G1202R and L1196M were accurately recapitulated, validating our screening platform. Moreover, several previously uncharacterized VUSs were identified as conferring differential resistance profiles. Structural modeling revealed mechanistic insights into altered TKI binding. These findings aligned with existing clinical and preclinical datasets and expanded the known spectrum of clinically actionable ALK resistance mutations. CONCLUSION This study presents the most comprehensive functional landscape to date of ALK TKD variants in the context of TKI resistance. Our data provide an invaluable resource for interpreting VUSs, optimizing TKI selection, and advancing personalized treatment in ALK fusion-positive cancers. Furthermore, the approach and insights are broadly applicable to other ALK-rearranged malignancies, including glioma.

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Journal
Neuro-Oncology
Published
2025-10-01
DOI
https://doi.org/10.1093/neuonc/noaf193.007
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
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article
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article

JS04.5.A HIGH RESOLUTION DRUG-RESISTANT MAPPING OF ALK FUSION VARIANTS USING PRIME EDITING

Hea Young Oh
Neuro-Oncology
Innovative Microfluidic and Catalytic Techniques Innovation
article

JS04.5.A HIGH RESOLUTION DRUG-RESISTANT MAPPING OF ALK FUSION VARIANTS USING PRIME EDITING

Hea Young Oh
article en

Abstract

Abstract BACKGROUND Anaplastic lymphoma kinase (ALK) gene fusions are potent oncogenic drivers across diverse malignancies, including non-small cell lung cancer (NSCLC), anaplastic large cell lymphoma (ALCL), breast cancer, and glioma. These fusions lead to constitutive activation of the ALK tyrosine kinase domain (TKD), rendering tumors initially responsive to ALK tyrosine kinase inhibitors (TKIs)—primarily in NSCLC, but also in rare cases such as infant-type hemispheric glioma. However, resistance inevitably emerges, frequently due to acquired single nucleotide variants (SNVs) within the TKD. A significant proportion of these SNVs are classified as variants of uncertain significance (VUSs), highlighting the need for systematic functional annotation to inform precision therapy. MATERIAL AND METHODS We employed prime editing to introduce all possible SNVs across the ALK TKD (exons 20-28). High-throughput drug resistance screening was conducted against three generations of ALK TKIs: alectinib (second-generation), lorlatinib (third-generation), and zotizalkib (fourth-generation, previously evaluated in clinical trials). Resistance classification data were further assessed using Kaplan-Meier survival analyses to explore potential prognostic implications. RESULTS A total of 2,953 SNVs (99.2% of all possible variants in exons 20-28) were successfully introduced and profiled. Resistance phenotypes were comprehensively mapped for each variant across the three TKIs. Canonical resistance mutations such as G1202R and L1196M were accurately recapitulated, validating our screening platform. Moreover, several previously uncharacterized VUSs were identified as conferring differential resistance profiles. Structural modeling revealed mechanistic insights into altered TKI binding. These findings aligned with existing clinical and preclinical datasets and expanded the known spectrum of clinically actionable ALK resistance mutations. CONCLUSION This study presents the most comprehensive functional landscape to date of ALK TKD variants in the context of TKI resistance. Our data provide an invaluable resource for interpreting VUSs, optimizing TKI selection, and advancing personalized treatment in ALK fusion-positive cancers. Furthermore, the approach and insights are broadly applicable to other ALK-rearranged malignancies, including glioma.

Neuro-OncologyVol. 27(Supplement_3)
Yonsei University (KR)
Openalex Percentile: Top 74%
Innovative Microfluidic and Catalytic Techniques Innovation
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