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ATG16L1 is a Potential Prognostic Biomarker and Immune Signature for Osteosarcoma: A Study Based on Bulk RNA and Single-Cell RNA-Sequencing

BACKGROUND: Osteosarcoma is a common solid malignancy of the bone in children and adolescents, and its metastasis and recurrence are the principal causes of poor treatment outcomes. METHODS: Autophagy-related genes were used to cluster osteosarcoma patients by consensus clustering analysis using the...

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Detalles Bibliográficos
Autores principales: Qin, Zhaojie, Luo, Kai, Liu, Yun, Liao, Shijie, He, Juliang, He, Mingwei, Xie, Tianyu, Jiang, Xiaohong, Li, Boxiang, Liu, Huijiang, Huang, Qian, Tang, Haijun, Feng, Wenyu, Zhan, Xinli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818976/
https://www.ncbi.nlm.nih.gov/pubmed/35140506
http://dx.doi.org/10.2147/IJGM.S341879
Descripción
Sumario:BACKGROUND: Osteosarcoma is a common solid malignancy of the bone in children and adolescents, and its metastasis and recurrence are the principal causes of poor treatment outcomes. METHODS: Autophagy-related genes were used to cluster osteosarcoma patients by consensus clustering analysis using the GSE21257 database. Differentially expressed genes (DEGs) were identified by limma package. Multiple-gene risk signature was constructed using least absolute shrinkage and selection operator (LASSO) analysis and Cox regression analyses. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to determine gene expression levels. Then, single-cell RNA-sequencing dataset GSE152048 were used to identify the correlation between the DEGs and effector molecules expressed in specific tumor-infiltrating immune cells. RESULTS: Two clusters were identified in the consensus clustering analysis, which were confirmed by principal component analysis. Limma analysis revealed that 15 genes were related, and 9 genes were screened using protein-protein interaction network and LASSO regression analysis. Cox regression analyses identified 5 genes. Combined with survival analysis, only the autophagy related 16 like 1 gene (ATG16L1) was significant. The results of qRT-PCR showed low expression levels of ATG16L1 in tumor cells group. Immune infiltration analysis revealed significantly lower expression of CD8(+) T cells in the high ATG16L1 gene expression group. ScRNA-seq revealed that in the ATG16L1(+)CD8(+) T cell group, the expression of GZMB was lower, whereas the expression of ITGA1 was higher. These results showed that ATG16L1 is an immune-related gene, which is associated with poor prognosis in patients with osteosarcoma. CONCLUSION: ATG16L1 is a potential prognostic biomarker and immune signature and may be a therapeutic target for osteosarcoma.