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Multi-omics integrative molecular subtyping of melanoma. (A) Determination of the optimal clustering number based on two clustering statistics. (B) Integrative clustering using a fully Bayesian latent variable model identified three distinct clusters, showing overlap with previous TCGA classifications. (C) Distinct molecular patterns across different omics platforms: transcriptome expression, DNA methylation, CNA, and somatic mutation. (D, E) Kaplan–Meier survival plots showing the association of our classification with progression-free survival (PFS) and overall survival (OS).

Journal: Frontiers in Immunology

Article Title: Multi-omics-based subtyping of melanoma suggests distinct immune and targeted therapy strategies

doi: 10.3389/fimmu.2025.1601243

Figure Lengend Snippet: Multi-omics integrative molecular subtyping of melanoma. (A) Determination of the optimal clustering number based on two clustering statistics. (B) Integrative clustering using a fully Bayesian latent variable model identified three distinct clusters, showing overlap with previous TCGA classifications. (C) Distinct molecular patterns across different omics platforms: transcriptome expression, DNA methylation, CNA, and somatic mutation. (D, E) Kaplan–Meier survival plots showing the association of our classification with progression-free survival (PFS) and overall survival (OS).

Article Snippet: DNA methylation data (Illumina HumanMethylation450 BeadChip) were also obtained from UCSC Xena.

Techniques: Biomarker Discovery, Expressing, DNA Methylation Assay, Mutagenesis