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️ 85: Genomic landscape of virus-associated cancers
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️ Episode 85: Genomic landscape of virus-associated cancers
In this episode of PaperCast Base by Base, we explore the comparative genomic analysis of virus-positive and virus-negative tumors across nine cancer types linked to five oncogenic viruses uncovering epidemiological patterns, mutational signatures, and therapeutic implications.
Study Highlights:
The authors aggregated genomic data from 1,971 tumors spanning nine virus-associated cancers and performed comprehensive analyses of mutation burden and driver mutations across virus-positive and virus-negative cases. They identified that virus-positive tumors generally have a lower somatic mutation load but frequent mutations in RNA helicases DDX3X and EIF4A1 and distinct mutation signatures compared to virus-negative tumors. Epidemiological analysis revealed higher male incidence and geographic disparities for virus-positive cancers, while immunotherapy response data indicated improved outcomes for virus-positive gastric cancer and head and neck squamous cell carcinoma. Comparative copy number and structural variant analyses highlighted recurrent chromosomal losses and translocations associated with viral infection status.
Conclusion:
These findings provide a pan-cancer perspective on the distinct genomic and clinical landscapes of virus-associated malignancies and suggest RNA helicase mutations and viral status as potential biomarkers for targeted therapies.
Reference:
Nam Y, Gomez K, Reynier JB, Khamnei C, Aitken M, Zheng V, Lhakhang T, Casula M, Palmieri G, Cossu A, Levine A, Tiacci E, Rabadan R. Genomic landscape of virus-associated cancers. Nature Communications. 2025;16:5887. doi:10.1038/s41467-025-60836-9.
License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics.
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