Signature of immune infiltration-related ferroptosis genes to predict the prognosis of patients with osteosarcoma.
AI interpretation is pending for this paper.
Open original publication →What the AI sees
Not AI summarized yet.
Research significance
Pending deeper interpretation.
Source abstract
Osteosarcoma (OS) is the most prevalent malignant bone tumor among children and adolescents, and ferroptosis has been implicated in tumor immune infiltration. The present study aimed to explore the role of ferroptosis-related genes in immune infiltration and to develop a prognostic signature for osteosarcoma (OS). In the present study, two immune subtypes of OS were identified and demonstrated to be reproducible and effective. Building upon the distinction between high and low immunity, six common differentially expressed immune infiltration-related ferroptosis genes (DEIIRFGs) were identified. After which, univariate Cox regression (UCR) analysis was employed to identify DEIIRFGs associated with overall survival. Next, using Gene Ontology analysis, it was revealed that the six mRNAs were enriched in the immune-associated functions and pathway. Subsequently, using UCR analysis and the iterative Least Absolute Shrinkage and Selection Operator Cox regression analysis based on two ferroptosis genes (interferon-γ and toll-like receptor 4), a model was established. Additionally, it was confirmed that the risk model was an independent prognostic factor for overall survival. Furthermore, the results were verified using a Gene Expression Omnibus dataset. Finally, the content of tumor-infiltrating immune cells demonstrated that the high-risk group was significantly associated with immune cell infiltration, compared with the low-risk group. Moreover, the expression of immune checkpoint inhibitors was significantly upregulated in the low-risk cohort compared with in the high-risk cohort. Finally, using gene set enrichment analysis, it was demonstrated that the risk score was associated with the toll-like receptor signaling pathway, antigen processing and presentation, and cytokine-cytokine receptor interaction. In summary, a signature of DEIIRFGs to predict prognosis in patients with OS was developed. Moreover, it was demonstrated that the molecular mechanisms responsible in the high-risk group may influence immune infiltration-related biological processes.