Cervicovaginal Microbiome Signatures Across Cervical Disease States: A Prospective Cross-Sectional Analysis.

Background/Objectives: The cervicovaginal microbiome has emerged as a critical determinant of cervical health. In this study, we aimed to characterize the cervicovaginal microbiome across a spectrum of cervical health states and to identify community-level features that distinguish invasive disease from precursor states. Methods: We analyzed cervicovaginal samples of 86 patients with normal epithelium, low-grade (LSIL) and high-grade (HSIL) intraepithelial lesions, and cervical carcinoma (CCU) and available HPV genotyping. Vaginal samples were subjected to full-length 16S rRNA gene sequencing and genus-level taxonomic profiles were generated using ONT-supported workflows. Microbiome diversity and composition were assessed using Aitchison-based beta-diversity, non-parametric testing, and PERMANOVA. Differential abundance was evaluated using ANCOM-BC2 with false discovery rate correction. Disease-associated community shifts were quantified using log-ratio indices and co-occurrence network analysis. Results: Microbial diversity increased with disease severity, with cervical cancer showing the highest alpha diversity and distinct community composition. Normal samples were uniformly dominated by Lactobacillus, whereas LSIL and HSIL exhibited transitional communities with partial loss of lactobacillar dominance and increasing representation of anaerobic taxa. Cervical cancer was associated with depletion of Lactobacillus and expansion of anaerobic consortia. A Lactobacillus-to-anaerobe log-ratio declined monotonically with disease severity and robustly discriminated invasive cancer from precursor states. Microbial co-occurrence networks became progressively more structured with disease severity, transitioning to dense anaerobic networks in cervical cancer. Conclusions: Cervicovaginal microbiome signatures reflect cervical disease stage and may complement existing screening and risk stratification strategies.