Development of a Risk Model and Genotyping Patterns Based on Disulfidptosis-Related lncRNAs to Predict Prognosis and Immune Landscape in Osteosarcoma

作者：Ke Zhang, Shenyi Lu, Mingyang Jiang, Xiaochong Zou, Chuanliang Chen, Yuanyuan Lan, Huaan Zhao, Ruilan Ma, Haiwei Yan · 发表于：Frontiers in Bioscience-Landmark · 年份：2024 · DOI：10.31083/j.fbl2905193 · 被引用次数：8 · 研究领域：Ferroptosis and cancer prognosis、Cancer-related molecular mechanisms research、MicroRNA in disease regulation

BACKGROUND: Osteosarcoma (OS) is the most prevalent orthopedic malignancy with a dismal prognosis. Disulfidptosis-related lncRNAs (DRLncs) may be related to the progression of OS, but their potential molecular regulatory role is still unclear. METHODS: Based on the data collected from The Cancer Genome Atlas (TCGA), we conducted correlation analysis and the univariate Cox analysis to screen prognosis-related DRLncs, followed by developing genotyping patterns and corresponding classifier. Subsequently, the survival analysis, enrichment analysis, drug sensitivity analysis and immune infiltration analysis were performed. Afterward, multivariate Cox regression was used to construct a risk model, which was further validated by the receiver operating characteristic (ROC) curve. The aberrant expression of hub DRLncs in OS was validated using the Reverse Transcription Polymerase Chain Reaction (RT-qPCR) assay. RESULTS: We identified 262 DRLncs and eleven prognosis-related DRLncs through filtering. We then constructed two distinct expression patterns of prognosis-related DRLncs and developed a classifier. We obtained 393 differentially expressed genes (DEGs) between different subtypes, which were significantly enriched in biological processes related to the extracellular matrix, integrin binding, focal adhesion, and Wnt signaling pathways. Through immune infiltration analysis, the activated CD4 memory T cells, resting natural killer (NK) cells, M1 macrophages, and resting dendritic ce...