Therefore, in this study, a robust analysis, comprised of weighted gene co-expression network, least absolute shrinkage and selection operator (LASSO), and random forest machine learning, was applied to screen CAFs-related gene panel associated with anti-PD-1 therapeutic response in melanoma, aiming to understand the potential functions of these genes in TME and evaluate their anti-PD-1 therapeutic response prediction performance. This evidence concerns the gene PDCD1 and melanoma.