e15115 Background: Activating mutations in GNAQ and GNA11 are well-established oncogenic drivers in uveal melanoma (UM), typically occurring at the Q209 and R183 hotspots . However, their prevalence and genomic context across other metastatic solid tumors remain inadequately characterized . As targeted Gαq-pathway inhibitors enter clinical development, understanding the real-world distribution and immunogenic background of these mutations is essential for therapeutic stratification . Methods: We conducted a pan-cancer analysis of 5,416 patients with metastatic solid tumors who underwent comprehensive genomic profiling (TSO 500 or OCA Plus) at Samsung Medical Center between 2019 and 2025 . We analyzed mutational distribution, tumor mutational burden (TMB), microsatellite instability (MSI), and co-alterations to characterize the genomic landscape of GNAQ/11 -mutated tumors . Results: Mutations in GNAQ (N = 10) or GNA11 (N = 16) were identified in 26 patients (0.48%) . Outside of UM, these mutations were most frequent in colorectal cancer (38.5%), non-uveal melanoma (15.4%), gastric cancer (11.5%), and neuroendocrine tumors (7.7%) . A significant genomic dichotomy was observed between tumor types : Canonical hotspots (Q209, R183) were primarily associated with TMB-low and microsatellite stable (MSS) tumors, such as UM, where they act as primary drivers . Non-hotspot mutations (e.g., p.Gln88His, p.Ala231Val) were strongly linked to an immunogenic profile, with 42.3% of the total cohort being TMB-high (≥10 Mut/Mb) and 19.2% being MSI-high In colorectal cancer, 66.7% of GNA11 -mutated cases were MSI-high, suggesting these mutations likely represent bystander events arising from global genomic instability rather than isolated drivers . Frequent co-alterations included NOTCH3 (80%), FAT1 (70%), and TP53 (37.5–40%) . Conclusions: Our real-world analysis reveals that GNAQ/11 mutations are recurrent across various solid tumors beyond UM . The strong correlation between non-hotspot mutations and high TMB/MSI status indicates a distinct immunogenic subgroup . These findings underscore the importance of differentiating canonical hotspot drivers from bystander mutations to guide the selection between targeted Gαq-pathway inhibitors and immune checkpoint blockade in precision oncology .
Kwon et al. (Thu,) studied this question.