Background and Objectives: The relationship between the vaginal microbiota, human papillomavirus infection (HPV), and cervical precancerous lesions is a critical area of research, as it influences both the progression of HPV-related diseases and potential treatment strategies. New evidence suggests that Lactobacillus crispatus dominance in the microbiota may protect against HPV persistence and speed the elimination of HPV. This study aims to explore the relationship between the vaginal microbiota composition and HPV infection, focusing on the impact of these factors on the development of cervical precancerous lesions. Materials and Methods: A comprehensive literature review was conducted using the PubMed database, focusing on studies that analyzed the association between the vaginal microbiota and HPV infection in the context of cervical dysplasia. This study was primarily based on clinical data on HPV integration in women with low-grade squamous intraepithelial lesions (LSILs), high-grade squamous intraepithelial lesions (HSILs), and cervical cancer. Results: Different types of vaginal microbiota communities (CSTs) have different pathogenic or protective potential. Healthy women predominantly exhibited CST I, with Lactobacillus crispatus as the dominant microorganism. CST IV, associated with increased anaerobic bacteria, was most common in HSIL and cervical cancer patients. Statistical analysis revealed that bacterial vaginosis (BV) was significantly associated with HPV persistence, with studies reporting a 1.8–3.4-fold increased risk (p < 0.05) of persistent HR-HPV infection in BV-positive women. Conclusions: Our literature review suggests that the composition of the vaginal microbiota can modulate the local immune response, the expression of viral oncogenes, and the integrity of the epithelial barrier. Furthermore, certain bacterial genes or metabolic pathways can be associated with a favorable or unfavorable outcome of the disease. Analysis of the vaginal microbiota could serve as an additional risk assessment tool, helping to distinguish between regressing and progressive precancerous conditions.
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