Identification of Prognostic Biomarkers KLK13 and SLC5A8 in Canine Melanoma via Transcriptomics and WGCNA Analysis

This study performed a bioinformatics analysis of transcriptome and chip datasets from canine melanoma to identify potential therapeutic targets and diagnostic biomarkers. The results showed significant enrichment in immune-related signaling pathways, suggesting that inflammation and immune regulation were crucial to tumor progression. Through weighted gene co-expression network analysis (WGCNA), gene modules related to prognosis were identified, and two core genes, KLK13 and SLC5A8, were discovered. We validated the potential of KLK13 and SLC5A8 as new biomarkers by integrating our findings with public data on human melanoma and conducting survival curve analysis. This study offers theoretical support for treating and diagnosing canine melanoma while providing valuable insights for human melanoma research.