Analysis of prognostic immune and stromal- related genes in melanoma microenvironment

Abstract Increasing evidence has showed the immune response is an important indicator for predicting therapeutic efficacy, and the prognosis value of the infiltration degree of immune and stromal cells within the tumor microenvironment has been extensively explored. It is necessary to better understand the prognosis value of genes concerning the immune and stromal cells in melanoma patients. A total of 714 up-regulated genes in the high immune and stromal score groups compared with low immune and stromal score groups. Then, a total of 104 hub genes of these differential genes were screened by protein-protein interaction network, and their functional enrichment and signal pathway enrichment analysis showed that they mainly affected tumor microenvironment by cytokine and cytokine receptors interaction, chemokine signaling pathway and T cell receptor signaling pathway involved in regulating Th1, Th2, Th17 differentiation. a single factor risk analysis of survival was performed and found 59 low-risk genes. On this basis, multi-factor risk analysis was carried out, and 10 genes risk model was constructed in TCGA-SKCM. Compared with clinically relevant parameters, the risk models established by these 10 genes showed that these 10 genes could be used as independent factors to predict the prognosis of SKCM patients. The CIBERSORT algorithm was used to calculate immune cell subtypes. In the high-risk group, the infiltration of B cells naïve, monocytes and Macrophages M2 was significantly higher than that in the low-risk group. Finally, we validated these 10 gene in a different melanoma cohort extracted from the GEO database. we identified a list of melanoma immune-related genes that might predict outcomes of melanoma patients. These findings indicated that monitoring and manipulating the melanoma microenvironment could be a promising strategy for precision immunotherapy.