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

**Authors:** Alexandru Hamod, Oancea Mihaela, Mihaela Grigore, Ingrid-Andrada Vasilache, Ramona-Gabriela Ursu, Razvan Popovici, Ana-Maria Grigore, Ludmila Lozneanu, Dan-Constantin Andronic, Mitica Ciorpac, Manuela Ciocoiu

PMC · DOI: 10.3390/diagnostics16050753 · Diagnostics · 2026-03-03

## TL;DR

This study shows how the cervicovaginal microbiome changes with cervical disease severity, from normal to cancer, and identifies potential microbial markers for disease detection.

## Contribution

The study identifies a Lactobacillus-to-anaerobe log-ratio as a novel biomarker for distinguishing invasive cervical cancer from precursor states.

## Key findings

- Cervical cancer samples showed the highest microbial diversity and distinct community composition.
- A Lactobacillus-to-anaerobe log-ratio declined with disease severity and effectively discriminated cancer from precancerous states.
- Microbial co-occurrence networks became more structured and dense in cervical cancer.

## Abstract

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.

## Linked entities

- **Diseases:** cervical cancer (MONDO:0002974)
- **Species:** Lactobacillus (taxon 1578)

## Full-text entities

- **Diseases:** cancer (MESH:D009369), Cervical Disease (MESH:D002575), invasive (MESH:D009361), Cervical cancer (MESH:D002583), HSIL (MESH:D000081483)
- **Species:** Homo sapiens (human, species) [taxon 9606], Lactobacillus (genus) [taxon 1578]

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12985308/full.md

## References

34 references — full list in the complete paper: https://tomesphere.com/paper/PMC12985308/full.md

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Source: https://tomesphere.com/paper/PMC12985308