Abstract
Background: According to the statistics of WHO/IARC, cervical cancer (CC) has become the fourth malignant cancer of female worldwide and it is one of the main causes of death of women in developing countries. Purpose: Potential plasma and metabolic biomarkers for CC precancerous lesions and cervicitis were indicated by LC-MS techniques, and their underlying mechanisms and functions were analyzed. Methods: Plasma samples were selected from healthy people (control), low-grade squamous intraepithelial lesions (LSIL), high-grade squamous intraepithelial lesions (HSIL), CC, and post-treatment patients. All polypeptide types and sequences were detected by LC-MS/MS and the results were normalized by using Pareto-scaling. Potential metabolic biomarkers were screened by applying MetaboAnalyst 4.0 software and XCMS software, and analysis of variance and enrichment analysis were performed. Metabolic pathway analysis and functional enrichment analysis were used to further investigate the significance and pathological mechanisms of potential biomarkers. Results: Compared with healthy people, 9 differentially expressed metabolites were screened, 4 of which were up-regulated and 5 were down-regulated. LSIL group screened 7 differentially expressed metabolites, 5 of which were up-regulated and 2 were down-regulated; CC group screened 12 differentially expressed metabolites were screened, of which 9 were up-regulated and 3 were down-regulated. Eight differentially expressed metabolites were screened in the IF group, of which 5 showed up-regulation and 3 showed down-regulation. In functional enrichment analysis, differential metabolism was found to be associated with addition and coagulation cascades. Among all potential biomarkers, 2-amino-3-methyl-1-butanol, L-carnitine, Asn Asn Gln Arg, Ala Cys Ser Trp, Soladulcidine, Ala Ile Gln Arg, 2-amino-3 -Methyl-1-butanol, L-carnitine, Asn Asn Gln Arg, Ala Cys Ser Trp, Soladulcidine, Ala Ile Gln Arg can be used as predictors of precancerous lesions at different stages of CC. Among all biomarkers, 6α-fluoro-11β1,17-dihydroxypren-4-ene-3,20-dione has higher expression in the CC and HSIL groups and lower expression in the treatment group. Conclusion: By applying molecular markers to assess the progression of the disease, the accuracy and specificity of the diagnosis can be improved, which has certain prospects in clinical applications.