A novel risk model based on anoikis: Predicting prognosis and immune infiltration in cutaneous melanoma

Abstract

Cutaneous melanoma (CM) is a highly aggressive malignancy with a dimal prognosis and limited treatment options. Anoikis is believed to involve in the regeneration, migration, and metastasis of tumor. The exact role of anoikis-related genes (ARGs) in the development and progression of cutaneous melanoma, however, remains elusive. Four ARGs (SNAI2, TFDP1, IKBKG, and MCL1) with significant differential expression were selected through Cox regression and LASSO analyses. Data for internal and external cohorts validated the accuracy and clinical utility of the prognostic risk model based on ARGs. The Kaplan–Meier curve indicated a much better overall survival rate of low-risk patients. Notably, we also found that the action of ARGs in the CM was mediated by immune-related signaling pathways. Consensus clustering and TIME landscape analysis also indicated that the low-risk score patients have excellent immune status. Moreover, the results of immunotherapy response and drug sensitivity also confirmed the potential implications of informing individualized immune therapeutic strategies for CM. Collectively, the predictive risk model constructed based on ARGs provides an excellent and accurate prediction tool for CM patients. This present research provides a rationale for the joint application of targeted therapy and immunotherapy in CM treatment. The approach could have great therapeutic value and make a contribution to personalized medicine therapy.