中国病理生理杂志2025，Vol.41Issue(2)：230-238,9.DOI:10.3969/j.issn.1000-4718.2025.02.003
非靶向代谢组学揭示宫颈癌发展进程的特征代谢谱研究
Non-targeted metabolomic profiling reveals characteristic metabolic pro-file associated with development process of cervical cancer
摘要
Abstract
AIM:The aim of our study is to investigate the metabolic profile differences during cervical lesion progression and evaluate their potential clinical value in assisting the diagnosis of cervical cancer(CC).METHODS:Ul-tra-high-performance liquid chromatography coupled with high-resolution mass spectrometry(UHPLC-HRMS)was em-ployed to conduct non-targeted metabolomic analysis of cervical swab samples from 43 CC patients,34 high-grade squa-mous intraepithelial lesion(HSIL)patients,and 43 healthy controls.Based on the distinct features among the three groups,principal component analysis(PCA)was used to identify the metabolic differences among CC,HSIL and healthy groups.MetaboAnalyst 5.0 was then employed to perform KEGG pathway enrichment analysis on the differential metabo-lites.Finally,random forest machine learning algorithm was used to construct classification prediction models for distin-guishing CC from healthy,HSIL from healthy,and CC from HSIL.The performance of these models was evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS:A total of 1 543 metabolites were identified across the healthy,HSIL and CC groups after filtration,with 407 metabolites differing between the groups.The study found that metabolite PGE2 was present in all three groups,with its expression levels progressively increasing with the progression of cervical lesions.Differential metabolite enrichment analysis demonstrated that CC is associated with specific cancer-relat-ed metabolic pathways,including the tricarboxylic acid cycle,tyrosine metabolism,tryptophan metabolism,and the pen-tose phosphate pathways.Additionally,the study developed three prediction models based on metabolic products for diag-nosing HSIL and CC:the full model,the simplified model,and the PGE2 model.The results indicated that metabolites ex-hibited strong diagnostic efficiency.Both the full model and the simplified model effectively distinguished CC from HSIL,CC from healthy,and HSIL from healthy.The AUC values for the full model were 0.90,0.92 and 0.84,respectively,while those for the simplified model were 0.81,0.95 and 0.85,respectively.Furthermore,the PEG2 model achieved AUC values of 0.74 and 0.80 for distinguishing CC from healthy and HSIL from healthy,respectively.CONCLUSION:The metabolic profiles of cervical cancer exhibit significant differences during the progression of cervical cancer,and these metabolites hold potential clinical value as biomarkers for cervical lesions.关键词
宫颈癌/高级别鳞状上皮内病变/宫颈拭子/代谢谱/非靶向代谢组学Key words
cervical cancer/high-grade squamous intraepithelial lesion/cervical swab/metabolic profile/non-targeted metabolomics分类
医药卫生引用本文复制引用
翟青枝,马韵之,叶明侠,王铭洋,李阳,李莉,孟元光,李立安..非靶向代谢组学揭示宫颈癌发展进程的特征代谢谱研究[J].中国病理生理杂志,2025,41(2):230-238,9.基金项目
中国人民解放军计生专项基金资助项目(No.22JSZ16 （）
No.24JSZ15) （）
解放军总医院第七医学中心2023年度创新培育基金资助项目(No.qzx-2023-22) （No.qzx-2023-22）
