Abstract
Purpose: Our aim was to construct a signature that accurately predicted the prognostic and immune response of melanoma.Methods: First, the weighted co-expression network analysis (WGCNA) algorithm was used to identify the hub genes related to clinical phenotypes of melanoma in the cancer genome atlas (TCGA) database. Nest, the least absolute shrinkage and selection operator (LASSO) analysis was used to dimensionality reduction of these hub genes and constructed a prognostic signature to predict the prognosis and immunosuppressive response of melanoma.Result: Through in-depth analysis, we constructed a 5-mRNA prognostic signature and verified its prognostic value in internal (TCGA-SKCM, n = 452) and external independent datasets (GSE53118, n = 79). Based on this signature, the tumor immune microenvironment (TME) of melanoma was characterized, and the result was found that patients in the high-risk group had lower CD8 T cell infiltration and immune checkpoint expression (PD-1, PD-L1, CTLA4), as well as higher M0/M2 macrophage infiltration. Our results also found the risk score based on a 5-mRNA signature was significantly associated with tumor mutational burden (TMB) and tumor stem cell markers (CD20, CD38, ABCB5, CD44, etc.). Lastly, we built a nomogram for clinician prediction for the prognosis of patients with melanoma.Conclusion: Our findings indicated that the 5-mRNA signature has an important predictive value for the overall survival of melanoma. By analyzing the tumor immune microenvironment and tumor stem cell marker between different groups, a new method is provided for the stratified diagnosis and treatment of melanoma.
Highlights
Melanoma is one of the most aggressive and fatal forms of skin tumor, it accounts for about 4% of all skin cancers, its mortality rate is as high as 80% (Kim et al, 2019)
We found that the risk of death in the training set and the validation set increased significantly with the increase of the risk score (Figures 3A,D, the middle panels), and the genes used to construct the 5-mRNA prognosis signature decreased with the increase of the risk score (Figures 3A,D, the lower panels)
The overall survival rates for metastatic melanoma have increased due to immunotherapy being widely used, but the efficacy of immunotherapy varied widely among different populations
Summary
Melanoma is one of the most aggressive and fatal forms of skin tumor, it accounts for about 4% of all skin cancers, its mortality rate is as high as 80% (Kim et al, 2019). Radiation therapy, and chemotherapy are common treatments for melanoma. For patients with metastatic melanoma, the 5-year survival rate is less than 10% due to the high rate of recurrence and lack of efficient biomarkers (Schadendorf et al, 2018). Current research shows that BRAF, NRAS, and C-Kit genes are closely related to the pathogenesis of melanoma (Ponti et al, 2017). As an emerging treatment in recent years, PD-1 has been shown to significantly improve the survival rate of melanoma patients. The identification of effective biomarkers that can estimate responses to immunotherapy for melanoma has become a new trend of research. Melanoma with BRAF mutations appears to benefit from targeted BRAF and MEK therapy. PDL1 can predict which patients will benefit from targeting CTLA-4 (Ponti et al, 2017)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
