Construction and validation of a prognostic model for endometrial carcinoma based on lactate metabolism-related genes

ZHANG Wuyang; WEI Wei

doi:10.3969/j.issn.1009-0460.2025.10.005

Abstract：Objective To construct a prognostic risk model based on lactate metabolism-related genes using The Cancer Genome Atlas(TCGA)database,and to identify key biomarkers while validating their clinical significance in endometrial carcinoma(EC).Methods Transcriptionic,clinical,and survival data from 35 normal endometrial tissues and 546 EC tissues were obtained from the Uterine Corpus Endometrial Carcinoma(UCEC)project of TCGA.The 546 cancer tissue samples were randomly divided into a training set and a validation set at a 1:1 ratio.By comparing transcriptionic data between normal tissues and the cancer tissues in the training cohort,differentially expressed genes were identified and intersected with 344 lactate metabolism-related genes from the Molecular Signatures Database to derive a candidate gene set.Subsequently,univariate Cox regression analysis was initially used to screen for prognosis-related genes,followed by Least Absolute Shrinkage and Selection Operator(LASSO)-Cox regression for further dimensionality reduction,ultimately constructing a final risk score model.Patients were stratified into high-risk and low-risk groups based on the median risk score from the model.Differences in clinical characteristics between the high-risk and low-risk groups were compared using the Wilcoxon rank-sum test and the chi-square test,while survival differences between the groups were assessed via Kaplan-Meier survival analysis and the log-rank test.Additionally,the oncoPredict R package was employed to predict and compare the sensitivity to commonly used anticancer drugs,measured by the half-maximal inhibitory concentration value,between the high-risk and low-risk groups.Results A total of 7 008 differentially expressed genes were identified from the TCGA-UCEC database.Focusing on lactate metabolism-related genes,a prognostic risk model comprising three genes,solute carrier family 16 member 1(SLC16A1),GATA binding protein 2(GATA2),and anaplastic lymphoma kinase(ALK),was constructed using univariate and LASSO-Cox regression analyses.The results showed that patients in the high-risk group were older and had more advanced FIGO stages(all P<0.05).Survival analysis confirmed that,compared to the low-risk group,patients in the high-risk group had significantly shorter overall survival in both the training set(P<0.001)and the validation set(P=0.034).Drug sensitivity analysis further revealed that the low-risk group exhibited higher sensitivity to paclitaxel,docetaxel,and cyclophosphamide(all P<0.05),whereas no statistically significant differences in sensitivity to platinum-based drugs or topotecan were observed between the two groups(P>0.05).Conclusion The three-gene risk model,comprising SLC16A1,GATA2,and ALK,establishes lactate metabolism as a key predictor of prognosis in endometrial carcinoma and lays the groundwork for personalized treatment strategies.