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Two subtypes of cutaneous melanoma with distinct mutational signatures and clinico-genomic characteristics

Background: To decipher mutational signatures and their associations with biological implications in cutaneous melanomas (CMs), including those with a low ultraviolet (UV) signature. Materials and Methods: We applied non-negative matrix factorization (NMF) and unsupervised clustering to the 96-class...

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Detalles Bibliográficos
Autores principales: Kim, Yoon-Seob, Lee, Minho, Chung, Yeun-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9557124/
https://www.ncbi.nlm.nih.gov/pubmed/36246650
http://dx.doi.org/10.3389/fgene.2022.987205
Descripción
Sumario:Background: To decipher mutational signatures and their associations with biological implications in cutaneous melanomas (CMs), including those with a low ultraviolet (UV) signature. Materials and Methods: We applied non-negative matrix factorization (NMF) and unsupervised clustering to the 96-class mutational context of The Cancer Genome Atlas (TCGA) cohort (N = 466) as well as other publicly available datasets (N = 527). To explore the feasibility of mutational signature-based classification using panel sequencing data, independent panel sequencing data were analyzed. Results: NMF decomposition of the TCGA cohort and other publicly available datasets consistently found two mutational signatures: UV (SBS7a/7b dominant) and non-UV (SBS1/5 dominant) signatures. Based on mutational signatures, TCGA CMs were classified into two clusters: UV-high and UV-low. CMs belonging to the UV-low cluster showed significantly worse overall survival and landmark survival at 1-year than those in the UV-high cluster; low or high UV signature remained the most significant prognostic factor in multivariate analysis. The UV-low cluster showed distinct genomic and functional characteristic patterns: low mutation counts, increased proportion of triple wild-type and KIT mutations, high burden of copy number alteration, expression of genes related to keratinocyte differentiation, and low activation of tumor immunity. We verified that UV-high and UV-low clusters can be distinguished by panel sequencing. Conclusion: Our study revealed two mutational signatures of CMs that divide CMs into two clusters with distinct clinico-genomic characteristics. Our results will be helpful for the clinical application of mutational signature-based classification of CMs.