Integrative analysis of cuproptosis-related lncRNAs: Unveiling prognostic significance, immune microenvironment, and copper-induced mechanisms in prostate cancer.

Background: Long non-coding ribonucleic acids (lncRNAs) regulate messenger RNA (mRNA) expression and influence cancer development and progression. Cuproptosis, a newly discovered form of cell death, plays an important role in cancer. Nonetheless, additional research investigating the association between cuproptosis-related lncRNAs and prostate cancer (PCa) prognosis is required. Methods: Sequencing data and copy number variant data were obtained from 492 patients with PCa from The Cancer Genome Atlas (TCGA) Program. Prognostic models of PCa based on cuproptosis-related lncRNAs were constructed using a multi-level attention graph neural network (MLA-GNN) deep learning algorithm. Immune escape scoring was performed using Tumor Immune Dysfunction and Exclusion. Cellular experiments were conducted to explore the correlation between key lncRNAs and cuproptosis. Results: Data from 492 patients with PCa were randomized into two groups at a 1:1 ratio. Prognostic modeling was successfully established using MLA-GNN. Survival analysis suggested that patients could be divided into high- and low-risk groups according to model scores and that there was a significant difference in disease-free survival (DFS) ( Conclusions: This study identified cuproptosis-related lncRNAs that were strongly associated with PCa prognosis. Key lncRNAs could affect copper metabolism and may serve as new therapeutic targets.