Exploring the prognostic value and constructing a clinical prediction model of lactate related genes in osteosarcoma based on TARGET and GEO databases

CHEN Qiu-yun; LU Hui

doi:10.3969/j.issn.2095-252X.2025.11.005

Abstract：Objective By using bioinformatics methods to construct and validate of a prognostic prediction model for genes related to lactate modification in osteosarcoma patients based on GEO and TARGET databases.Methods The GSE42352 dataset was downloaded from GEO database.The R language"limma"package was used to perform the differential analysis between osteosarcoma tissue samples and normal tissue samples.The differentially expressed genes were intersected with lactate related genes to obtain the differentially expressed lactate related genes.Firstly,the mRNA gene expression and clinical survival data of osteosarcoma patients from the Therapeutically Applicable Research to Generate Effective Treatments(TARGET)database were downloaded.Lactate related prognostic genes were screened by using univariate Cox regression and Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis.Secondly,a prognostic risk model was constructed based on the risk score of lactate modification related genes.Gene Set Enrichment Analysis(GSEA)was used to perform GO and KEGG enrichment analysis on lactate related prognostic risk models,to predict the potential biological functions and pathways involved.Finally,a clinical prognostic nomogram or osteosarcoma based on lactate related genes was constructed and validated in TARGET and GSE21257 cohorts respectively.Results A total of 852 differentially expressed genes were screened in the GSE42352 dataset,and we further intersected with lactate related genes by using Venn diagram and a total of 30 differentially expressed lactate related genes were obtained.The survival analysis results showed that WAS,NDUFB9,SLC7A7,ZYX,TPM4,and S100A4 were associated with the prognosis of osteosarcoma,and a prognostic risk model based on six lactate related genes was constructed.The overall survival rate of the low-risk group was significantly higher than that of the high-risk group(TARGET cohort P<0.001,GSE21257 cohort P=0.025).GSEA enrichment analysis results showed that the risk genes were mainly enriched in immune related biological processes.A prognostic nomogram for osteosarcoma was constructed by using risk scores and clinical characteristics with TARGET cohort and the area under receiver operating characteristic(ROC)curve(AUC),calibration curve,and decision curve analysis(DCA)all showed it had good clinical predictive performance,which was further validated in GSE21257 cohort.Conclusions The prognosis model of osteosarcoma constructed based on lactate related genes has clinical predictive value and can be used to guide individualized treatment of osteosarcoma patients.