LncRNAs regulates cell death in osteosarcoma - Ping’an Zou; Zhiwei Tao; Zhengxu Yang; Tao Xiong; Zhi Deng; Qincan Chen; Li Niu (Scientific Reports)
Abstract Despite improvements, prognosis in osteosarcoma patients remains poor, making it essential to identify additional and more robust therapeutic targets. Non-apoptotic receptor-mediated cell death (RCD), which plays a crucial role in the pathogenesis of OS, is one avenue actively pursued as an alternative therapeutic target in OS. Long non-coding RNAs (lncRNAs) also play a diverse role in OS pathogenesis, and numerous studies have shown that they are attractive therapeutic targets in OS. However, whether lncRNA also plays a role in non-apoptotic RCD in OS is currently unknown. The objective of the current study was to identify if a functional lncRNA-based gene signature exists that regulates non-apoptotic RCD. We systematically screened immune-related lncRNAs associated with ferroptosis, necroptosis, and pyroptosis using the Pearson correlation algorithm (|Pearson R|> 0.4, P < 0.01) on 88 osteosarcoma patients and 122 normal controls that were selected from the TARGET and GETx databases. Univariate Cox regression analysis was employed to identify lncRNAs associated with osteosarcoma treatment. Three machine learning algorithms—Support Vector Machine, Random Forest, and Generalized Linear Model—were utilized to select feature genes. In low- and high-risk groups, immune infiltration was analyzed using CIBERSORT and gene set enrichment analysis. To verify the mechanism of signature lncRNAs, proteins related to pyroptosis, ferroptosis, and necroptosis were assessed via a combination of in vitro assays. LASSO regression analysis led to constructing a prognostic risk model consisting of four lncRNAs: AC006033.2, AC124798.1, LINC01517, and L3MBTL4-AS1. The AUC values for 1-, 3-, and 5-year survival in the testing set were 0.739, 0.809, and 0.708, respectively, while in the entire cohort, the AUC values were 0.849, 0.881, and 0.776, respectively, indicating high reliability and accuracy of the risk model. The high-risk group exhibited a worse prognosis. Five clusters were identified through non-negative matrix factorization clustering, revealing differences in immune infiltration and the tumor microenvironment. Quantitative polymerase chain reaction analysis showed that four lncRNAs were highly expressed in osteosarcoma, with LINC01517 being particularly associated with poor prognosis. Notably, silencing LINC01517 inhibited in vitro cell proliferation, activated NLRP3/caspase-1/GSDMD-mediated pyroptosis, promoted ferroptosis, and enhanced necroptosis in osteosarcoma cells. The non-apoptotic RCD-related lncRNA signature identified in this study provides valuable insights that will aid future exploration of these prognostic biomarkers as potential therapeutic targets for osteosarcoma treatment.