A promising anoikis-related prognostic signature predicts prognosis of cutaneous melanoma

Abstract

Skin cutaneous melanoma (SKCM) is a highly aggressive disease with a poor prognosis, especially for advanced tumors. Anoikis, which prevents detached cells from re-attaching to a new substrate in an incorrect location and inhibits their unwanted growth, plays a crucial role in organismal defense. However, little research has focused on the impact of anoikis on prognosis in SKCM. To address this, our study utilized the 27 anoikis-related genes (ARGs) identified from gene set enrichment analysis (GSEA) to divide SKCM patients in the TCGA-SKCM cohort into two clusters, and obtain differentially expressed genes (DEGs) for each cluster. These DEGs were then used in stepwise Cox regression analysis to develop a prediction model for SKCM patients consisting of nine ARGs, called the Anoikis-Related Signature (ARS). Subsequently, we used the risk scores calculated from the ARS to divide SKCM patients into two groups and explored differences in immune microenvironment, immune checkpoint reactivity, and drug sensitivity between the groups. Our results revealed that immunotherapy was ineffective in patients with high ARS. In summary, the ARS can be used to classify the risk and predict the survival outcome of SKCM patients, providing a basis for targeted therapy in SKCM. Keywords: cutaneous melanoma, anoikis, immune response, risk model, prognosis.