In silico analysis of gene expression signatures and drug repurposing associated with metastatic progression in melanoma (skin cancer).

Metastatic melanoma is an aggressive, heterogeneous cancer with early spread and poor prognosis. Transcriptomic analysis identifies potential therapeutic targets. In silico analysis of the GEO dataset GSE7553 compared primary vs metastatic melanoma using differential expression, enrichment (GO/KEGG/Reactome), PPI network construction, and hub-gene prioritization. Candidates were validated through survival analysis, mutation-associated analyses, and virtual screening using molecular docking with FDA-approved compounds. Transcriptomic results show divergence between primary and metastatic melanoma samples, with principal component analysis supporting clear group separation. In a total of 54,675 probe-level entries, 4868 were classified as upregulated and 10,269 as downregulated, indicating a predominance of downregulated transcriptional events in metastatic melanoma. Prioritized upregulated genes included CUL5, ZC3H14, SON, BRCC3, and H3-3B, whereas notable downregulated genes included ZNF709, CD84, STARD8, EPOR, and HAVCR2. The high-confidence PPI network comprised 625 nodes and 2661 edges, with a significant enrichment score. Enrichment analysis implicated immune/adhesion and translation pathways (e.g., Rap1, focal adhesion, T-cell activation). Survival: CUL5 (HR = 0.26) and ZC3H14 (HR = 0.60) are protective, while SON (HR = 2.4) is adverse. Mutation-linked transcriptomic analysis identified 10 significantly altered genes, including downregulated SNHG18 and upregulated LPCAT2. Virtual screening results show repurposable compounds, with Floxacrine showing strong predicted affinity for CUL5 and Dihydroergocristine showing favorable interaction with LPCAT2/ZC3H14-related targets. In silico docking results further supported CUL5-Floxacrine and LPCAT2-Dihydroergocristine as notable candidate interactions. Results show key transcriptomic drivers and targets (CUL5, ZC3H14, SON, BRCC3, LPCAT2) in metastatic melanoma. Results highlight a useful hypothesis-generating framework for biomarker prioritization and drug repurposing in melanoma. However, independent cohort validation and experimental confirmation are required before clinical translation.