A Comprehensive Analysis of Cutaneous Melanoma Patients in Greece Based on Multi-Omic Data

SIMPLE SUMMARY: Cutaneous melanoma (CM) accounts for the majority of skin cancer-related deaths and, during recent decades, its incidence has increased worldwide. Although early-stage disease is associated with favourable prognosis, a subgroup of tumours is characterised by increased aggressiveness. High inter- and intra-tumour heterogeneity could contribute to the establishment of such aggressive phenotypes, which are based both on the genomic background and the transcriptomic plasticity of melanoma cells. Molecular profiling of melanomas has expanded our knowledge about mechanisms related to disease onset and progression, and it is key to improving optimal management. In this study, we aimed to characterise patients with primary CM for both germline and somatic variations as well as alterations at the gene expression level, by applying whole exome, targeted, and transcriptomic approaches and integrative, multi-layered bioinformatics analysis. Oncogenic alterations were identified, and distinct phenotypic cell states could be inferred from transcriptomic data. ABSTRACT: Cutaneous melanoma (CM) is the most aggressive type of skin cancer, and it is characterised by high mutational load and heterogeneity. In this study, we aimed to analyse the genomic and transcriptomic profile of primary melanomas from forty-six Formalin-Fixed, Paraffin-Embedded (FFPE) tissues from Greek patients. Molecular analysis for both germline and somatic variations was performed in genomic DNA from peripheral blood and melanoma samples, respectively, exploiting whole exome and targeted sequencing, and transcriptomic analysis. Detailed clinicopathological data were also included in our analyses and previously reported associations with specific mutations were recognised. Most analysed samples (43/46) were found to harbour at least one clinically actionable somatic variant. A subset of samples was profiled at the transcriptomic level, and it was shown that specific melanoma phenotypic states could be inferred from bulk RNA isolated from FFPE primary melanoma tissue. Integrative bioinformatics analyses, including variant prioritisation, differential gene expression analysis, and functional and gene set enrichment analysis by group and per sample, were conducted and molecular circuits that are implicated in melanoma cell programmes were highlighted. Integration of mutational and transcriptomic data in CM characterisation could shed light on genes and pathways that support the maintenance of phenotypic states encrypted into heterogeneous primary tumours.