The pan-tumor landscape, allelic status, and genomic complexity of SMARCA4 alterations
Matteo Repetto, Michael V. Gormally, Jason Chang, Pier Selenica, Andrea Gazzo, Qin Zhou, Alexia Iasonos, Viktoriya Paroder, Clare Wilhelm, Samuel A. Funt, Justin Jee, Allison L. Richards, Mark T.A. Donoghue, Adam Schoenfeld, Steven Maron, Carol Aghajanian, Britta Weigelt, Alexander Drilon, Robin GuoAbstract
Purpose: The clinical implications of distinct SMARCA4 alteration classes remain incompletely defined. We performed a pan-cancer analysis to characterize SMARCA4 mutation classes and their associations with allelic status, genomic context, and therapeutic outcomes. Patients and Methods: We analyzed 68,920 tumor–normal paired samples sequenced with the MSK-IMPACT next-generation sequencing assay between 2015 and 2023. Oncogenic or likely oncogenic SMARCA4 alterations were curated using OncoKB and classified based on prior functional and structural literature. Allele-specific copy number, ploidy, fraction of genome altered, loss of heterozygosity, and whole-genome doubling were calculated. Clinical outcomes were evaluated in selected tumor cohorts treated with platinum-based therapy or immune checkpoint blockade. Results: SMARCA4 alterations were most frequent in thymic epithelial tumors (10.7%), non–small cell lung cancer (NSCLC; 7.1%), bladder cancer (5.6%), and cervical cancer (5%). Class 1 and class 2 alterations occurred in 2.9% and 0.7% of tumors, respectively. Distinct patterns of genomic complexity, co-occurring alterations, and mutational signatures were observed across tumor types based on SMARCA4 alteration allelic state and class. In a phase I trial of the BRM degrader PRT3789, patients with monoallelic class 2 SMARCA4 alterations and preserved BRG1 expression saw clinical benefit, including one who attained a complete response. Conclusions: SMARCA4 alteration class and allelic status define biologically and clinically distinct subsets of tumors. These findings support incorporating allelic status and functional mutation class into patient selection strategies for emerging BRM-targeted therapies.