ArticleScientific reports2025
Leveraging diverse cell death patterns in osteosarcoma patients and identification of the function of FADS2 in osteosarcoma cells.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Osteosarcoma (OS) is the most common bone malignancy in children and adolescents. The 5-year survival rate is only approximately 20% in patients with metastatic and recurrent OS. There is an urgent need to explore novel therapeutic targets to improve the survivorship of OS patients. It has been reported that dysfunction of programmed cell death (PCD) plays an essential role in tumor malignancy. In this study, differentially expressed PCD genes (PCD-DEGs) in OS were identified. Functional enrichment and somatic mutation analysis were performed. Then we established a novel indicator, the cell death index (CDI), to predict therapeutic interventions, immunity responses, and prognosis concerning OS. The expression of PCD genes in osteosarcoma and normal tissues was determined by immunohistochemistry assays. A total of 265 PCD-DEGs were identified in OS, with 141 genes upregulated and 124 genes downregulated. After functional enrichment and somatic mutation analysis, a final PCD-related gene signature, involving the expression levels of CLTCL1, FADS2, and PLEKHF1, demonstrated significant predictive value. A nomogram including clinical characteristics and CDI was developed, which was verified to perform well. Further investigation showed CDI was strongly correlated with immunomodulators, tumor microenvironment, and drug sensitivity in OS. Immunohistochemistry assays illustrated that FADS2, CLTCL1, and PLEKHF1 were suppressed in OS tissues. Further experiments demonstrated that FADS2 inhibits migration and invasion of osteosarcoma cells, while FADS2 induces ferroptosis collaborating with Erastin in osteosarcoma cells. In conclusion, the PCD-related gene signature proposed in this study is a practical prognostic predictor for OS patients, which can make a notable difference in the assessment of clinical outcomes.
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