Abstract
BACKGROUND: Cutaneous melanoma is a type of malignant tumor that is challenging to predict and is readily stimulated by various factors. Oxidative stress can induce damage and alterations in melanocytes, subsequently triggering immune responses. Given that oxidative stress is a prevalent tumor stimulus, we aimed to enhance melanoma prediction by identifying lncRNA signatures associated with oxidative stress. METHODS: We screened for oxidative stress-related lncRNAs that could improve melanoma patient prognosis using the TCGA and GTEx databases. Utilizing differentially expressed oxidative stress-related lncRNAs (DE-OSlncRNAs), we constructed a Lasso regression model. The accuracy of the model was validated using univariate and multivariate regression, Kaplan-Meier (K-M) curves, and ROC curves. Subsequently, we conducted immune infiltration analysis, immune checkpoint differential analysis, IC50 pharmaceutical analysis, and gene set enrichment analysis. Investigating the effects of the target gene on melanoma using fluorescence in situ hybridization (FISH), quantitative real-time PCR (qRT-PCR), Edu assay, wound healing assay, transwell assay, flow cytometry, and reactive oxygen species (ROS) detection. RESULTS: Thirteen lncRNAs were identified as significant prognostic factors. Four oxidative stress-related lncRNAs (COPDA1, LINC02132, LINC02812, and MIR205HG) were further validated by fluorescence in situ hybridization (FISH), with results consistent with our data analysis. LINC02132 and COPDA1 can influence the proliferation, invasion, migration, and apoptosis of melanoma. CONCLUSION: Our findings suggest that upregulation of the LINC02132 or COPDA1 genes elevates intracellular reactive oxygen species (ROS) levels in melanoma cells, suppresses tumor cell proliferation, migration, and invasion, and promotes apoptosis. These results suggest a novel therapeutic strategy for melanoma treatment.