Comprehensive analysis and external validation of a glycolysis-related gene signature as a prognostic index for skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) is the third most common cause of cancer-related deaths globally. Today, precise biomarkers to predict melanoma prognosis are quite limited. Aerobic glycolysis serves as the primary metabolic pathway for malignancies to meet their rapid growth demands. This study built a glycolysis-associated gene (GAG) signature to evaluate prognosis and immunotherapy response of SKCM. Data acquired from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases were evaluated to obtain differentially expressed GAGs. With machine learning techniques, four key GAGs ( GOT2 , CLN6 , GYS1 , and IDUA ) were pinpointed as candidate prognostic biomarkers. Subsequently, a risk model was constructed by incorporating these four GAGs. The risk model could effectively forecast SKCM patient survival and treatment efficacy. Also, the elevated risk scores correlated with diminished immune cell infiltration and impaired immune functions. In addition, the four GAGs all showed influence on immune cell infiltrations of SKCM. Then, the role of predominant hub gene GYS1 and CLN6 was validated using in vitro models. The overexpression of GYS1 and CLN6 could promote viability, invasion, and proliferation of melanoma cells. ELISA and western blot experiments demonstrated that the overexpression of GYS1 lead to higher secretion of proinflammatory cytokine TNF-α and IL-1β, activated the nuclear factor kappa B signaling pathway, and promoted an immunosuppressive microenvironment. Collectively, this study initially pinpointed glycolysis-related genes as prognostic biomarkers for melanoma and elucidated the facilitating role of GYS1 and CLN6 in melanoma, providing deeper insights into pathogenesis of melanoma.