Abstract
Purpose To improve immunotherapy efficacy for melanoma, a coexpression network and key genes of M2 macrophages in melanoma were explored. A prognostic risk assessment model was established for M2-related coexpressed genes, and the role of M2 macrophages in the immune microenvironment of melanoma was elucidated. Method We obtained mRNA data from melanoma and peritumor tissue samples from The Cancer Genome Atlas-skin cutaneous melanoma (TCGA-SKCM). Then, we used CIBERSORT to calculate the proportion of M2 macrophage cells. A coexpression module most related to M2 macrophages in TCGA-SKCM was determined by analyzing the weighted gene coexpression network, and a coexpression network was established. After survival analysis, factors with significant results were incorporated into a Cox regression analysis to establish a model. The model's essential genes were analyzed using functional enrichment, GSEA, and subgroup and total carcinoma. Finally, external datasets GSE65904 and GSE78220 were used to verify the prognostic risk model. Results The yellow-green module was the coexpression module most related to M2 macrophages in TCGA-SKCM; NOTCH3, DBN1, KDELC2, and STAB1 were identified as the essential genes that promoted the infiltration of M2 macrophages in melanoma. These genes are concentrated in antigen treatment and presentation, chemokine, cytokine, the T cell receptor pathway, and the IFN-γ pathway. These factors were analyzed for survival, and factors with significant results were included in a Cox regression analysis. According to the methods, a model related to M2-TAM coexpressed gene was established, and the formula was risk score = 0.25∗NOTCH3 + 0.008∗ DBN1 − 0.031∗KDELC2 − 0.032∗STAB1. The new model was used to perform subgroup evaluation and external queue validation. The results showed good prognostic ability. Conclusion We proposed a Cox proportional hazards regression model associated with coexpression genes of melanoma M2 macrophages that may provide a measurement method for generating prognosis scores in patients with melanoma. Four genes coexpressed with M2 macrophages were associated with high levels of infiltration of M2 macrophages. Our findings may provide significant candidate biomarkers for the treatment and monitoring of melanoma.
Highlights
Melanoma is the most common type of skin tumor
Using the screening principle of p < 0:05, we obtained 214 melanoma samples accurately evaluated by M2 macrophages
We demonstrated the role of NOTCH receptor 3 (NOTCH3), drebrin 1 (DBN1), KDEL (Lys-Asp-GluLeu) containing 2 (KDELC2), and STAB1 in melanoma patients
Summary
Melanoma is the most common type of skin tumor. Because access to early screening and primary health care varies globally, the incidence and mortality rates associated with melanoma vary widely [1]. Melanoma possesses various inhibitory mechanisms that often act synergistically to evade surveillance and attack by innate and adaptive immunity For this reason, more effective treatments are needed to activate tumor-specific immunity [2]. The distribution of M2 TAM in melanoma tissues is involved in avoiding tumor cell death and immune surveillance, inducing angiogenesis and tumor cell activity [9]. Weighted gene coexpression network analysis (WGCNA) is an analytical software package used for high-throughput microarrays or RNA-seq datasets. The new approach to immunotherapy for melanoma in the future will involve preventing the generation of M2, the transition from M1 to M2, and the reversal of TAM polarization, to reduce melanoma drug resistance and prevent the progression and recurrence We hypothesized that this approach would affect the diagnosis and treatment of early and late metastatic melanoma
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