ArticleAging2024
Construction of an oxidative phosphorylation-related gene signature for predicting prognosis and identifying immune infiltration in osteosarcoma.
Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Multi-tissue analysis identifies mitochondrial genes in chicken aging-induced productivity decline.Journal of animal science and biotechnology · 2026Article
- Single-Cell RNA and Transcriptome Sequencing to Analyze the Role of Lactate Metabolism in Traumatic Brain Injury Astrocytes.Brain and behavior · 2025Article
- Targeting LHPP in neoadjuvant chemotherapy resistance of gastric cancer: insights from single-cell and multi-omics data on tumor immune microenvironment and stemness characteristics.Cell death & disease · 2025Article
- Construction and validation of a prognostic signature using WGCNA-identified key genes in osteosarcoma for treatment evaluation.Translational cancer research · 2025Article
- Integrated analysis of single-cell and bulk RNA sequencing data reveals prognostic characteristics of lysosome-dependent cell death-related genes in osteosarcoma.BMC genomics · 2024Article
- A novel hypoxia- and lactate metabolism-related prognostic signature to characterize the immune landscape and predict immunotherapy response in osteosarcoma.Frontiers in immunology · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteosarcoma is a prevalent malignant tumor that originates from mesenchymal tissue. It typically affects children and adolescents. Although it is known that the growth of osteosarcoma relies on oxidative phosphorylation for energy production, limited attention has been paid to exploring the potential of oxidative phosphorylation-related genes in predicting the prognosis of individuals suffering from osteosarcoma.
methodsAll the data were retrieved from the UCSC Xena and GEO (GENE EXPRESSION OMNIBUS). Identification of the oxidative phosphorylation genes linked to the prognosis of individuals with osteosarcoma was done by means of univariate COX and LASSO regression analyses. Following that, patients were categorized into a high-risk group and a low-risk group as per the risk score determined by the identified oxidative phosphorylation genes. Furthermore, a comparison was made in terms of the survival and immune infiltration between both groups, and the prognostic model was established.
resultsFive oxidative phosphorylation genes (ATP6V0D1, LHPP, COX6A2, MTHFD2, NDUFB9) associated with the prognosis of individuals with osteosarcoma were identified and the risk prognostic models were constructed. In the current research, the analysis of the ROC curves indicated a superior predictive accuracy exhibited by the risk model. The prognosis was adversely affected by immune infiltration in the high-risk group in comparison with the low-risk group. The function of the oxidative phosphorylation-related prognostic gene set was verified by GO and KEGG analysis. Furthermore, the link between oxidative phosphorylation-related genes and osteosarcoma immune infiltration was examined by GSEA analysis.
conclusionsIn this study, a prognostic model that demonstrated good predictive performance was constructed. Additionally, this study highlighted a correlation between oxidative phosphorylation-related genes and immune infiltration.
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