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Updated: Jul 8, 2026
Comparative Lesions Analysis Through a Targeted Sequencing Approach
Published on: November 5, 2019
Genomic Landscape of GNAQ and GNA11 Mutations in Metastatic Solid Tumors: A Real-World Data Analysis
Minsuk Kwon1, Yunjin Go2, Ji Eun Shin1
1Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Purpose:
Activating mutations in GNAQ and GNA11 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.
Materials And Methods:
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.
Results:
Mutations in GNAQ (n = 10) or GNA11 (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 NOTCH3 (80%), FAT1 (70%), and TP53 (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.
Conclusion:
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.
Insights
Activating GNAQ and GNA11 mutations occur beyond uveal melanoma, notably in colorectal cancer. Non-hotspot mutations indicate an immunogenic profile, guiding distinct treatment strategies for solid tumors.
Area of Science:
- Oncology
- Genomics
- Cancer Research
Background:
- Activating mutations in GNAQ and GNA11 are key drivers in uveal melanoma (UM).
- Their broader prevalence and genomic context across diverse cancers are not well understood.
Purpose of the Study:
- To investigate the genomic landscape of GNAQ and GNA11 mutations in a wide range of metastatic solid tumors.
- To characterize their distribution, mutational context, and potential clinical implications.
Main Methods:
- Pan-cancer analysis of 5,416 metastatic solid tumor patients using next-generation sequencing.
- Evaluation of mutation distribution, hotspot identification, tumor mutational burden (TMB), microsatellite instability (MSI), and co-alterations.
Main Results:
- GNAQ/GNA11 mutations were found in 0.48% of patients, most common in colorectal cancer (38.5%) outside of UM.
- A subset (42.3%) showed high TMB and 19.2% high MSI, linked to non-hotspot mutations.
- Canonical hotspots (Q209, R183) were associated with TMB-low/microsatellite stable tumors, unlike non-hotspot mutations.
- Frequent co-alterations included NOTCH3 (80%), FAT1 (70%), and TP53 (37.5%-40%).
- Immunogenic subgroup showed favorable overall survival (OS) and response to immune checkpoint inhibitors (ICI).
Conclusions:
- GNAQ and GNA11 mutations are present in various solid tumors, especially colorectal cancer, not just UM.
- Non-hotspot mutations define an immunogenic subgroup associated with high TMB/MSI.
- Distinguishing hotspot drivers from bystander mutations is crucial for selecting targeted therapy versus immune checkpoint blockade.
