Identification and Validation of Immune- and Stemness-Related Prognostic Signature of Melanoma.

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

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC8602573 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature