Genomic Landscape of GNAQ and GNA11 Mutations in Metastatic Solid Tumors: A Real-World Data Analysis.

Abstract

Activating mutations in <i>GNAQ</i> and <i>GNA11</i> are recognized oncogenic drivers in uveal melanoma (UM); however, their prevalence across various cancers and their genomic context remain inadequately characterized. This study aimed to elucidate the genomic landscape of these mutations across a range of metastatic solid tumors. We conducted a pan-cancer analysis involving 5,416 patients with metastatic solid tumors who had undergone next-generation sequencing. Our evaluation encompassed mutational distribution, hotspot identification, tumor mutational burden (TMB), microsatellite instability (MSI), and coalterations. Mutations in <i>GNAQ</i> (n = 10) or <i>GNA11</i> (n = 16) were detected in 26 patients (0.48%). Aside from UM, these mutations were most frequently observed in colorectal cancer (38.5%), melanoma (15.4%), gastric cancer (11.5%), and neuroendocrine tumors (7.7%). A notable subset exhibited an immunogenic profile, with 42.3% classified as TMB-High (≥10 Mut/Mb) and 19.2% as MSI-High. This immunogenic subgroup was primarily associated with nonhotspot mutations (eg, p.Gln88His, p.Ala231Val), suggesting that these may represent bystander events in hypermutated tumors. Conversely, canonical hotspots (Q209, R183) were predominantly identified in TMB-Low/microsatellite stable tumors, such as UM. Notable coalterations included <i>NOTCH3</i> (80%), <i>FAT1</i> (70%), and <i>TP53</i> (37.5%-40%). Exploratory survival analysis suggested favorable OS in the immunogenic subgroup, supported by cases with durable ICI benefit including a treatment-free remission exceeding 21 months. This real-world analysis demonstrates that GNAQ and GNA11 mutations are not exclusive to UM, occurring across diverse solid tumors, particularly colorectal cancer. The strong association between nonhotspot mutations and high TMB/MSI status defines a distinct immunogenic subgroup, underscoring the need to differentiate canonical hotspot drivers from bystander mutations when selecting targeted pathway inhibitors versus immune checkpoint blockade.