Genetic Insight into Expression-Defined Melanoma Subtypes and Network Mechanisms: An in Silico Study

Background: Melanoma is a highly heterogeneous neoplasia in which transcriptional profile encodes much of the biological diversity that determines tumor progression and therapeutic response. To refine its molecular stratification and profiles characterization, we conducted an in silico transcriptomic analysis. Methods: Public microarray datasets from the GEO and ArrayExpress were examined, and the E-MTAB-6697 expression dataset was selected. We used a K-Means clustering algorithm to stratify 194 tumor samples into expression-driven subgroups and analyzed each one to define their transcriptional and biological profiles. Differential expression analysis between identified clusters and controls was performed. Additionally, we applied Weighted-Gene correlation analysis to identify coordinated expression hubs in the tumor dataset and tested the resulting modules for correlation with the identified clusters. Results: Unsupervised clustering of melanoma transcriptomic profiles identified three distinct molecular subtypes characterized by divergent biological programs. While all clusters shared the dysregulation of pathways involved in epidermal differentiation, immune response, and lipid metabolism, they diverged in proliferation, phenotypic plasticity, metabolic adaptation, and apoptotic regulation. Cluster A was characterized by enrichment in DNA replication, repair, and mitochondrial metabolism modules, suggesting a proliferative yet genomically stable state. Cluster B showed enrichment in immune and cytokine signaling pathways alongside reduced proliferative activity, consistent with a quiescent or transitional phenotype. Cluster C displayed coordinated enrichment in cell-cycle, DNA-maintenance, and neuroectodermal reprogramming pathways, indicating a highly plastic and proliferative subtype. Despite these molecular distinctions, all clusters retained an "immunologically hot" profile (IPS 7-8), indicating potential responsiveness to immunotherapy. Conclusions: These findings provide an overview of the functional characteristics of melanoma heterogeneity and identify biological processes that could be targeted by drugs for the development of tailored therapies for each subtype. Nevertheless, future studies in independent clinically annotated cohorts would be required.