Construction and validation of eight cuproptosis-related lncRNAs signature for predicting prognosis and immune response in melanoma

Abstract

Background: Skin cutaneous melanoma (SKCM) is the highly heterogeneous and fatal form of skin cancer with a very high incidence. A recently identified copper-dependent regulated cell death process called cuproptosis has been linked to apoptosis in several tumor species. Nevertheless, its role in melanoma metastasis is unclear. This investigation seeks to investigate the relationship between cuproptosis associated genes (CRGs) and the prognosis of melanoma patients. Methods: The TCGA database was used to find clinical information on patients with SKCM. 80% of the data was randomly selected for analysis. Long non-coding RNAs (lncRNAs) associated with cuproptosis were identified using the Pearson correlation algorithm. Genes related with cuproptosis were screened from previous studies, and lncRNAs related with them were validated as candidates for prognostic features of SKCM. The least absolute shrinkage selection operator (LASSO) algorithm and univariate as well as multivariate COX regression analyses were used in the study to develop a prognostic model. In addition, the efficacy of this model was confirmed using the remaining 20% of the data. Results: A new prognostic model was established by screening eight lncRNAs associated with cuproptosis. Furthermore, functional enrichment analysis, the immune microenvironment analysis, and immune escape analysis were carried out. The results demonstrated that in the landscape of the immunological microenvironment, the low-risk group exhibited greater immunocompetence than the high-risk group. Conclusions: The tests assessing the reliability and validity of the model demonstrated that the established prognostic model for CRGs can accurately predict the prognosis of melanoma and could be useful in guiding subsequent treatment.