Construction and Validation of a Prognosis Model for Osteosarcoma Based on Transfer Phenotyping Screening of Associated Differential Genes

Wang Dapeng; Zhang Jinchu; Qin Sen

doi:10.3969/j.issn.1004-5775.2025.23.002

Abstract：Objective:Based on differentially expressed genes(DEGs)derived from transfer phenotypes,to construct a prognostic model for osteosarcoma(OS)and investigate the expression of prognostic genes in OS and their relationship with patient prognosis.Methods:Transcriptome sequencing data and clinical information from 98 OS patients were obtained from the Targets database using bioinformatics methods.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were employed to investigate the functional characteristics of DEGs in OS.Single-factor Cox regression combined with Lasso regression was applied to screen for prognostic-related genes,and a prognostic prediction model was established based on these findings.Additionlly receiver operating characteristic(ROC)curve analysis identified independent prognostic factors for OS.Results:A total of 82 DEGs were identified.GO and KEGG enrichment analysis revealed that these differentially expressed genes were primarily enriched in pathways including extracellular matrix organization,regulation of apoptosis in epithelial and endothelial cells,cell chemotaxis,response to reactive oxygen species,and the Apelin signaling pathway.Using univariate Cox and Lasso regression models,two prognosis-associated DEGs were selected to construct a prognostic model:Rho GTPase Activator Protein 44(ARHGAP44)and Tryptophan 2,3-Dioxygenase 2(TDO2).Receiver operating characteristic(ROC)curves and survival analysis confirmed that the risk model constructed with these two DEGs demonstrated good predictive value for overall survival in patients.Conclusion:A successful OS prognostic model based on DEGs has been established,revealing that ARHGAP44 and TDO2 serve as prognostic biomarkers for OS patients.This finding provides valuable reference for clinical treatment and prognosis assessment in OS patients.