Reports indicate that the use of anti-programmed cell death-1 (PD-1) and death ligand-1 (PD-L1) monoclonal antibodies for the treatment of patients diagnosed with melanoma has demonstrated promising efficacy. Nonetheless, this therapy is limited by the resistance induced by the tumor microenvironment (TME). As such, understanding the complexity of the TME is vital in enhancing the efficiency of immunotherapy. This study used four different methods to estimate the infiltrating level of immune cells. Besides, we analyzed their infiltration pattern in primary and metastatic melanoma obtained from The Cancer Genome Atlas (TCGA) database. As a consequence, we discovered a significantly higher infiltration of immune cells in metastatic melanoma compared to primary tumor. Consensus clustering identified four clusters in melanoma with different immune infiltration and clusters with higher immune infiltration demonstrated a better overall survival. To elucidate the underlying mechanisms of immune cell infiltration, the four clusters were subdivided into two subtypes denoted as hot and cold tumors based on immune infiltration and predicted immune response. Enrichment analysis of differentially expressed genes (DEGs) revealed different transcriptome alterations in two types of tumors. Additionally, we found tyrosinase-related protein1 (TYRP1) was negatively correlated with CD8A expression. In vitro experiments showed that knockdown TYRP1 promoted the expression of HLA-A, B, and C. Eventually, we constructed a prediction model which was validated in our external cohort. Notably, this model also performed effectively in predicting the survival of patients under immunotherapy. In summary, this work provides a deeper understanding of the state of immune infiltration in melanoma and a prediction model that might guide the clinical treatment of patients with melanoma.
Keywords: immune infiltration; immunotherapy; melanoma; prediction model; tumor microenvironment.
Copyright © 2021 Li, Zhu and Liu.