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- Title
Molecular Landscape and Prognostic Value in the Post-Translational Ubiquitination, SUMOylation and Neddylation in Osteosarcoma: A Transcriptome Study.
- Authors
Jia, Chenguang; Yao, Xiaowei; Dong, Zhaoliang; Wang, Lianbo; Zhao, Fangchao; Gao, Jianguo; Cai, Tao
- Abstract
Background: Post-translational modifications (PTM) significantly influence the pathogenesis and progression of diverse neoplastic conditions. Nevertheless, there has been limited research focusing on the potential of PTM-related genes (PTMRGs) as tumor biomarkers for predicting the survival of specific patients. Methods: The datasets utilized in this research were obtained from the TARGET and GEO repositories, respectively. The gene signature was constructed through the utilization of LASSO Cox regression method. GSEA and GO was used to identify hub pathways associated with risk genes. The functionality of risk genes in osteosarcoma (OS) cell lines was verified through the implementation of the CCK-8 assay, cell cycle analysis, and immunofluorescence assay. Results: Two distinct PTM patterns and gene clusters were finally determined. Significant differences in the prognosis of patients were found among two different PTM patterns and gene clusters, so were in the function enrichment and the landscape of TME immune cell infiltration. Moreover, we examined two external immunotherapy cohorts and determining that patients in the low-risk group was more likely to profit from immunotherapy. In addition, we mapped the expression of the genes in the signature in distinct cells using single-cell analysis. Finally, CCK-8 assay, cell cycle analysis, and immunofluorescence assay were utilized to confirm that RAD21 was expressed and functioned in OS. Conclusion: In conclusion, this study elucidated the potential link between PTM and immune infiltration landscape of OS for the first time and provided a new assessment protocol for the precise selection of treatment strategies for patients with advanced OS.
- Subjects
POST-translational modification; TUMOR markers; GENE clusters; CELL cycle; CELL analysis
- Publication
Journal of Inflammation Research, 2024, Vol 17, p4315
- ISSN
1178-7031
- Publication type
Article
- DOI
10.2147/JIR.S440459