ArticleAging2023
Construction and validation of an oxidative-stress-related risk model for predicting the prognosis of osteosarcoma.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Identification of novel therapeutic targets for diabetic neuropathy through integrated proteomics and transcriptomics approaches.World journal of diabetes · 2025Article
- Exploratory Analysis of Molecular Subtypes in Early-Stage Osteosarcoma: Identifying Resistance and Optimizing Therapy.Cancers · 2025Article
- Integrated analysis of single-cell and bulk transcriptomics reveals cellular subtypes and molecular features associated with osteosarcoma prognosis.BMC cancer · 2025Article
- T cell receptor signaling pathway subgroups and construction of a novel prognostic model in osteosarcoma.Heliyon · 2025Article
- UBE2L3 Suppresses Oxidative Stress-regulated Necroptosis to Accelerate Osteosarcoma Progression.Recent patents on anti-cancer drug discovery · 2025Article
- A novel prognostic signature related to programmed cell death in osteosarcoma.Frontiers in immunology · 2024Article
- Circadian rhythm-associated lncRNA RP11-414H17.5 as a key therapeutic target in osteosarcoma affects the tumor immune microenvironment and enhances malignancy.Journal of orthopaedic surgery and research · 2023Article
- Ferroptosis-related lncRNAs guiding osteosarcoma prognosis and immune microenvironment.Journal of orthopaedic surgery and research · 2023Article
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3 authors.
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Abstract
backgroundOsteosarcoma is the most common bone malignancy in teenagers, and warrants effective measures for diagnosis and prognosis. Oxidative stress (OS) is the key driver of several cancers and other diseases.
methodsThe TARGET-osteosarcoma database was employed as the training cohort and GSE21257 and GSE39055 was applied for external validation. The patients were classified into the high- and low-risk groups based on the median risk score of each sample. ESTIMATE and CIBERSORT were applied for the evaluation of tumor microenvironment immune infiltration. GSE162454 of single-cell sequencing was employed for analyzing OS-related genes.
resultsBased on the gene expression and clinical data of 86 osteosarcoma patients in the TARGET database, we identified eight OS-related genes, including MAP3K5, G6PD, HMOX1, ATF4, ACADVL, MAPK1, MAPK10, and INS. In both the training and validation sets, the overall survival of patients in the high-risk group was significantly worse than that in the low-risk group. The ESTIMATE algorithm revealed that patients in the high-risk group had higher tumor purity but lower immune score and stromal score. In addition, the CIBERSORT algorithm showed that the M0 and M2 macrophages were the predominant infiltrating cells in osteosarcoma. Based on the expression analysis of immune checkpoint, CD274(PDL1), CXCL12, BTN3A1, LAG3, and IL10 were identified as potential immune therapy targets. Analysis of the single cell sequencing data also revealed the expression patterns of OS-related genes in different cell types.
conclusionsAn OS-related prognostic model can accurately provide the prognosis of osteosarcoma patients, and may help identify suitable candidates for immunotherapy.
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