Analysis of pyroptosis, ferroptosis, and necroptosis associated lncRNAs in osteosarcoma prognosis and screening of antitumor drugs

Aims: We aimed to find out potential novel biomarkers for osteosarcoma prognosis. Materials & methods: We collected 88 osteosarcoma patients and 122 normal patients from the TARGET and GETx databases and obtained corresponding clinical data. Pearson correlation algorithm could obtain corresponding lncRNAs (|Pearson R|>0.4, P<0.01). Univariate regression Cox analysis could obtain lncRNAs related to osteosarcoma prognosis (P < 0.05). Three machine learning algorithms (SVM-RF-GLM) were used to screen feature genes. CIBERSORT analysis and GSEA were applied to examine immune infiltration of low- and high-risk groups and anti-osteosarcoma drug screening was carried out based on signature genes. AUC values of 1, 3, and 5-year survival probabilities were 0.949, 0.907, and 0.831. Results and conclusion: Findings examined a worse prognosis for the high-risk group. Five clusters were constructed by non-negative matrix decomposition clustering, and the results showed the variances between immune infiltration and microenvironment. Quantitative polymerase chain reaction (qPCR) experiments displayed that four lncRNAs were highly expressed in osteosarcoma. Inhibition of osteosarcoma cell proliferation by knocking down LINC01517 results. The ferroptosis-, necroptosis- and pyroptosis-related lncRNA (FNP-RlncRNA) signature is a possible osteosarcoma carcinogenic prognostic biomarker.