ArticleJournal of cancer research and clinical oncology2023
Construction and validation of a predictive nomogram for ferroptosis-related genes in osteosarcoma.
Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Iron-Related Metabolic Targets in the Treatment of Osteosarcoma: Research Progress and Prospects.Biomedicines · 2025Review
- Nrf2: A key regulator in chemoradiotherapy resistance of osteosarcoma.Genes & diseases · 2025Review
- Analysis and assessment of ferroptosis-related gene signatures and prognostic risk models in skin cutaneous melanoma.Translational cancer research · 2025Article
- Advances in understanding the role of squalene epoxidase in cancer prognosis and resistance.Molecular biology reports · 2025Review
- MT1G induces lipid droplet accumulation through modulation of H3K14 trimethylation accelerating clear cell renal cell carcinoma progression.British journal of cancer · 2024Article
- Integration of ubiquitination-related genes in predictive signatures for prognosis and immunotherapy response in sarcoma.Frontiers in oncology · 2024Article
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4 authors.
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Abstract
backgroundFerroptosis is a new type of cellular regulation of necrosis that has attracted great attention in recent years, which is different from the traditional mode of autophagy, apoptosis, and necrosis. Studies suggest that ferroptosis is key to the occurrence and development of tumors.
methodsHere, we investigated the prognostic significance of ferroptosis-related genes (FRGs) in osteosarcoma (OS) using RNA transcriptome data from 88 OS samples collected from the UCSC Xena platform. We defined the OS sample from the UCSC platform as the training cohort and the GEO dataset (GSE21257 and GSE16091) as the validation cohorts. We assessed 73 up-regulated and 63 down-regulated FRGs. We divided patients from the UCSC database into groups at high risk and low risk and built a prognostic risk model to assess prognosis using five FRGs: MT1G, G6PD, ARNTL, BNIP3, and SQLE.
resultsHigh-risk OS patients presented a lower survival rate. These results were confirmed in the validation groups. In the training group, the areas under the ROC curves (AUC) were as follows: 0.880 for 1 year, 0.833 for 3 years, and 0.818 for 5 years. In the GSE21257 validation cohort, the AUC were as follows: 0.770 for 1 year, 0.641 for 3 years, and 0.632 for 5 years survival, and in the GSE16091 were 0.729 for 1 year, 0.663 for 3 years, and 0.735 for 5 years survival.
conclusionsThese findings suggest that FRGs are associated with the prognosis of osteosarcoma. Moreover, our prognostic risk model can predict overall survival in osteosarcoma. This provides new ideas for the clinical diagnosis and personalized treatment of osteosarcoma.
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