AUTHOR=Kawasaki Rie , Kukimoto Iwao , Nishio Eiji , Otani Sayaka , Nishizawa Haruki , Maeda Yasuhiro , Iwata Aya , Fujii Takuma 

TITLE=Distinct cervical microbiome and metabolite profiles before and after menopause: implications for cervical cancer progression

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2025.1589277

DOI=10.3389/fcimb.2025.1589277

ISSN=2235-2988

ABSTRACT=IntroductionCervical cancer is the fourth most common malignancy in women and is primarily caused by persistent infection with high-risk human papillomavirus (HPV). In addition, host immune responses, genetic factors, and lifestyle habits also have etiological roles. The cervicovaginal microbiome undergoes dynamic changes during menopause, which may be involved in the progression of cervical neoplasia. We aimed to elucidate the association between cervical microenvironmental changes and the progression of cervical neoplasia before and after menopause by integrating analyses of the cervical microbiome, related metabolites, cytokines, and microRNAs.MethodsA total of 248 HPV-positive women with cervical neoplasia, including 17 with cervical intraepithelial neoplasia (CIN1), 80 with CIN2, 82 with CIN3, and 69 with squamous cell carcinoma (SCC), were enrolled. As normal controls, 48 HPV-negative healthy women were included. Each group was stratified based on the mean menopausal age of 50 years. Cervical mucus was analyzed according to the methods outlined below. The microbiota was profiled by 16S rRNA gene sequencing, metabolites were analyzed by ultra-HPLC-tandem mass spectrometry, RT-qPCR was used for miRNA expression analysis, and RANTES levels were quantified by multiplex bead array. Data analysis was performed using MicrobiomeAnalyst and MetaboAnalyst.ResultsIn the SCC group, Prevotella and Atopobium were the key bacterial genera among the younger group, while Peptoniphilus, Fusobacterium, and Porphyromonas were more prevalent in elderly group (LDA score > 4.5). We observed a consistent positive correlation between Atopobium and xanthine in younger groups with CIN2 or worse (p < 0.0001). However, no such correlations were detected in elderly women. In addition, Atopobium, Adlercreutzia, and Gardnerella showed significant positive correlation with nicotinic acid in younger women with SCC compared to the elderly women (p < 0.0001). In the younger SCC women, several metabolites were significantly elevated in groups with high expression levels of RANTES, miR-20b-5p, and miR-155-5p.ConclusionThe cervical microbiome undergoes changes during menopause, and may influence disease progression by interacting with metabolites, cytokines, and miRNAs. These results highlight the potential for personalized medicine for cervical cancer that is tailored to different age groups.