Distinct Transcriptomic and Tumor Microenvironment Profiles in Sinonasal Mucosal Melanoma and Aggressive Cutaneous Melanomas

• Published in: Cancers Vol. 16; no. 24; p. 4172
• Main Authors: Molina-García, Manuel, Rojas-Lechuga, María Jesús, Torres Moral, Teresa, Bagué, Jaume, Mateu, Judit, Langdon, Cristóbal, Lop, Joan, Gonçalves de Souza, Vinícius, Alós, Llúcia, López-Chacón, Mauricio, Podlipnik, Sebastian, Carrera, Cristina, Malvehy, Josep, Alobid, Isam, da Silva-Júnior, Rui Milton Patricio, Puig, Susana
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 14.12.2024; MDPI
• Subjects: Analysis; B cells; Binomial distribution; Cancer; Care and treatment; Cell cycle; Data processing; Development and progression; Genes; Immune system; Medical prognosis; Melanin; Melanocytes; Melanoma; Metadata; Metastasis; Mucosa; Mutation; Nose; Oncology; Patients; Prognosis; Skin; Skin cancer; Standard deviation; Standard scores; Transcriptomics; Tumor microenvironment; Spain; United States > US; cutaneous melanoma; tumor microenvironment; prognostic markers; transcriptomic profiles; gene expression; sinonasal mucosal melanoma
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers16244172

Background/Objectives: Sinonasal mucosal melanoma (SNMM) is a rare and aggressive melanoma subtype with a notably poor prognosis compared to cutaneous melanoma (CM). Despite advances in molecular characterization, SNMM remains underexplored, posing a clinical challenge and highlighting the need for detailed molecular profiling. This study aimed to identify the molecular features of SNMM, elucidate its clinical behavior and prognostic implications, and provide insights for improved therapeutic strategies. Methods: This retrospective study analyzed 37 primary melanoma tumors diagnosed at the Hospital Clinic of Barcelona. Gene expression was examined using 1402 immuno-oncology-related probes through next-generation sequencing. Hierarchical clustering analysis (HCA), differentially expressed genes (DEGs), gene set enrichment analysis (GSEA), and the xCell algorithm were performed. The statistical methods comprised descriptive statistics, clinical variable associations, and survival analyses. Results: HCA revealed two primary clusters. Cluster A exclusively contained CM tumors (20/24), while cluster B included all SNMMs (13/13) and some CMs (4/24). Cluster B showed a higher average age at diagnosis (p = 0.018), higher mitotic index (p = 0.0478), fewer BRAF mutations (p = 0.0017), and poorer melanoma-specific survival (p = 0.0029). Cluster B showed 602 DEGs with cell cycle pathways enriched, immune pathways diminished, lower immune scores (p < 0.0001), and higher stromal scores (p = 0.0074). Conclusions: This study revealed distinct molecular characteristics and an altered tumor microenvironment in SNMMs and certain aggressive CMs. Identifying specific genes and pathways involved in cell cycle progression and immune evasion suggests potential prognostic markers, offering new avenues for enhancing treatment strategies and improving patient survival rates.