ArticleDiscover oncology2022
Construction and validation of a prognostic model for osteosarcoma patients based on autophagy-related genes.
Article in Discover oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- AnGenes · 2026Article
- Lipid metabolism-related gene expression predicts prognostic outcomes in lung adenocarcinoma.Translational cancer research · 2026Article
- LncRNA-associated ceRNA Network Revealing the Potential Regulatory Roles of Ferroptosis and Immune Infiltration in Osteosarcoma as well as Construction of the Prognostic Model.Current medicinal chemistry · 2025Article
- Autophagy Modulation as a Potential Therapeutic Strategy in Osteosarcoma: Current Insights and Future Perspectives.International journal of molecular sciences · 2023Review
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteosarcoma is the most frequent primary bone malignancy with a poor prognosis because of pulmonary metastasis. Autophagy is strongly associated with tumor metastasis, and it is valuable to construct an autophagy-related gene risk model for predicting the prognosis of osteosarcoma.
methodsWe obtained ARGs from the Human Autophagy Database and RNA-sequencing data of osteosarcoma patients from the Gene Expression Omnibus (GEO) database. Subsequently, univariate and multivariate cox regression analyses were performed to construct a three-gene prognostic model and its accuracy was further confirmed in the Therapeutic Applications Research to Generate Effective Treatments (TARGET) database. Afterward, we detected the expression levels and effects on osteosarcoma cells metastasis of MYC and MBTPS2, which were involved in the model.
resultsIn both training and verification cohorts, patients with lower risk scores had longer OS, and the model was identified as an independent prognostic factor in osteosarcoma. Besides, the ROC curve demonstrated the reliability of the model. Furthermore, RT-qPCR, Western Blotting and IHC results indicated that MYC and MBTPS2 were differently expressed in osteosarcoma tissues and cell lines. MYC knockdown or MBTPS2 overexpression prevented the capacity of migration and invasion in osteosarcoma cell lines through inhibiting cellular autophagy.
conclusionThe risk model based on three ARGs had a strong ability to predict the prognosis of osteosarcoma patients. Our findings also suggested that MYC and MBTPS2 were two major factors regulating autophagy in osteosarcoma, and could serve as potential therapeutic targets for osteosarcoma.
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