Non-targeted metabolomic profiling reveals characteristic metabolic pro-file associated with development process of cervical cancer
10.3969/j.issn.1000-4718.2025.02.003
- VernacularTitle:非靶向代谢组学揭示宫颈癌发展进程的特征代谢谱研究
- Author:
Qingzhi ZHAI
1
;
Yunzhi MA
;
Mingxia YE
;
Mingyang WANG
;
Yang LI
;
Li LI
;
Yuanguang MENG
;
Lian LI
Author Information
1. 解放军总医院第七医学中心妇产科,北京 100005
- Publication Type:Journal Article
- Keywords:
cervical cancer;
high-grade squamous intraepithelial lesion;
cervical swab;
metabolic profile;
non-targeted metabolomics
- From:
Chinese Journal of Pathophysiology
2025;41(2):230-238
- CountryChina
- Language:Chinese
-
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.
