ArticleJournal of oncology2021
Construction and Validation of a Macrophage-Associated Risk Model for Predicting the Prognosis of Osteosarcoma.
Article in Journal of oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- Systematic pan-cancer analysis reveals context-dependent prognostic and immunological roles of WDR1 with divergent effects in renal and gastric cancers.Frontiers in immunology · 2026Article
- Development and validation of a novel prognostic signature for osteosarcoma.Translational cancer research · 2025Article
- Review
- Bayesian Optimization-Enhanced Machine Learning for Osteosarcoma Risk Stratification Based on Sphingolipid Metabolism.Human mutation · 2025Article
- The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients.Scientific reports · 2024Article
- Article
- Clinical significance and immune landscape of a novel ferroptosis-related prognosis signature in osteosarcoma.BMC cancer · 2023Article
- Outstanding prognostic value of novel ferroptosis-related genes in chemoresistance osteosarcoma patients.Scientific reports · 2022Article
- Metastatic Progression of Osteosarcomas: A Review of Current Knowledge of Environmental versus Oncogenic Drivers.Cancers · 2022Review
- Machine-Learning-Based m5C Score for the Prognosis Diagnosis of Osteosarcoma.Journal of oncology · 2021Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteosarcoma is one of the most common bone tumors among children. Tumor-associated macrophages have been found to interact with tumor cells, secreting a variety of cytokines about tumor growth, metastasis, and prognosis. This study aimed to identify macrophage-associated genes (MAGs) signatures to predict the prognosis of osteosarcoma.
methodsTotally 384 MAGs were collected from GSEA software C7: immunologic signature gene sets. Differential gene expression (DGE) analysis was performed between normal bone samples and osteosarcoma samples in GSE99671. Kaplan-Meier survival analysis was performed to identify prognostic MAGs in TARGET-OS. Decision curve analysis (DCA), nomogram, receiver operating characteristic (ROC), and survival curve analysis were further used to assess our risk model. All genes from TARGET-OS were used for gene set enrichment analysis (GSEA). Immune infiltration of osteosarcoma sample was calculated using CIBERSORT and ESTIMATE packages. The independent test data set GSE21257 from gene expression omnibus (GEO) was used to validate our risk model.
results5 MAGs (MAP3K5, PML, WDR1, BAMBI, and GNPDA2) were screened based on protein-protein interaction (PPI), DGE, and survival analysis. A novel macrophage-associated risk model was constructed to predict a risk score based on multivariate Cox regression analysis. The high-risk group showed a worse prognosis of osteosarcoma (
conclusionsA novel macrophage-associated risk score to differentiate low- and high-risk groups of osteosarcoma was constructed based on integrative bioinformatics analysis. Macrophages might affect the prognosis of osteosarcoma through macrophage differentiation pathways and bring novel sights for the progression and prognosis of osteosarcoma.
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Registered trials
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