Functional and sensitivity profiling of theKITMutation Landscape in Melanoma
Sai Fung YeungiD, Mandy Sze Man Chan, Cherie Tsz‐Yiu Law, Alex Chun Ho Law, Carol Lee, Allen Ming Fai Leung, Mary Po Ki Chau, Helen Hoi Yin Chan, July Xi Chen, Ben C.B. KoiD, Karen K.L. Chan, William C. ChoiD, Stephen Kwok‐Wing TsuiiD
Abstract
Melanoma in Asia presents a unique epidemiological profile, with a higher prevalence of acral and mucosal subtypes compared to Western populations. While KIT mutations are found in up to 15% of Asian melanoma cases, clinical outcomes with KIT inhibitors have been modest due to heterogeneous mutation profiles and a lack of specific patient selection criteria. This study characterizes the landscape of KIT mutations in melanoma using the GENIE database, identifying 86 recurrent hotspots, many of which are variants of unknown significance (VUS). We validated drug sensitivities for key mutations using in vitro and in vivo models. Our results indicate that while the L576P mutation is highly sensitive to multiple inhibitors, the N822K mutation shows resistance to imatinib but responds to sunitinib, nilotinib, and nintedanib. These findings highlight the necessity of genotype-guided therapeutic strategies and provide a rationale for future clinical trials combining broad-spectrum KIT inhibitors with immune checkpoint inhibitors. Translational SignificanceMelanoma subtypes prevalent in Asia, specifically acral and mucosal melanoma, frequently harbor KIT mutations but show poor response rates (23-26%) to the standard-of-care inhibitor, imatinib. This study challenges the current clinical practice of treating all KIT-mutated melanomas uniformly. We demonstrate that specific recurrent mutations, such as N822K, are intrinsically resistant to imatinib but highly sensitive to broad-spectrum inhibitors like sunitinib and nintedanib. By establishing a comprehensive "lookup table" of drug sensitivities for both common and previously uncharacterized KIT variants, this work provides the evidence base required to transition from a "one-size-fits-all" approach to a genotype-guided precision medicine strategy. Furthermore, validating these targets informs the design of next-generation clinical trials, particularly those combining optimal KIT inhibitors with immune checkpoint blockade to improve survival in currently underserved patient populations.
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