Background Cutaneous melanoma is an aggressive malignancy characterized by a high metastatic potential and variable response to immune checkpoint blockade (ICB). The extracellular matrix protein proline/arginine-rich end leucine-rich repeat protein (PRELP), an extracellular matrix protein, contributes to stromal architecture and tumor–immune interactions. This study investigated whether PRELP expression drives transcriptomic remodeling, alternative splicing, interferon (IFN)-related signaling pathways to influence immunotherapy responsiveness in melanoma. Methods Bulk RNA sequencing was performed on PRELP-high and PRELP-low BUF1088 melanoma cells to assess differential gene expression and alternative splicing landscapes. Downstream pathway changes were characterized using hallmark enrichment analysis. The translational relevance of the profiles was assessed using publicly available single-cell RNA sequencing datasets and clinical melanoma ICB cohorts. Results Differential splicing analysis identified 274 significant splicing events across 230 genes, predominantly exon skipping events. Key differentially spliced genes included AAR2, SACM1L, CD22, ACTB, MYO5A, WARS1, BTN3A3, IL24, and HNRNPA3. In parallel, PRELP-high melanoma cells showed enrichment of IFN-gamma and IFN-alpha response pathways accompanied by increased expression of IFI27, IFI44, IRF7, and IFITM3. In publicly available clinical datasets, PRELP expression and a composite PRELP-related gene signature, (PRELP, IRF7, IFI27, IFI27L1, IFI44, IFITM3, WARS, and IL24) were significantly enriched in ICB responders versus non-responders. Single-cell mapping localized endogenous PRELP expression to specific stromal subsets, primarily extracellular matrix-remodeling myofibroblastic CAFs (myCAFs) and IFN-responsive CAFs. Conclusion These findings demonstrate that PRELP expression in melanoma orchestrates extensive transcriptomic remodeling, linking stromal matrix programs with IFN-associated antitumor signaling and alternative splicing landscapes. Consequently, PRELP-associated expression and splicing signatures represent promising predictive biomarkers to guide patient selection for immunotherapy response.
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Subbarayan et al. (2026) studied this question.
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