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    The vaginal microbiome is an immune defense against reproductive diseases and can serve as an important biomarker for cervical cancer. However, the intrinsic relationship between the recurrence and the vaginal microbiome in patients with cervical cancer before and after concurrent chemoradiotherapy is poorly understood. Here, we analyzed 125 vaginal microbial profiles from a patient cohort of stage IB-IVB cervical cancer using 16S metagenomic sequencing and deciphered the microbial composition and functional characteristics of the recurrent and non-recurrent both before and after chemoradiotherapy. We demonstrated that the abundance of beneficial bacteria and stability of the microbial community in the vagina decreased in the recurrence group, implying the unique characteristics of the vaginal microbiome for recurrent cervical cancer. Moreover, using machine learning, we identified Lactobacillus iners as the most important biomarker, combined with age and other biomarkers (such as Ndongobacter massiliensis, Corynebacterium pyruviciproducens ATCC BAA-1742, and Prevotella buccalis), and could predict cancer recurrence phenotype before chemoradiotherapy. This study prospectively employed rigorous bioinformatics analysis and highlights the critical role of vaginal microbiota in post-treatment cervical cancer recurrence, identifying promising biomarkers with prognostic significance in the context of concurrent chemoradiotherapy for cervical cancer. The role of L. iners in determining chemoradiation resistance in cervical cancer warrants further detailed investigation. Our results expand our understanding of cervical cancer recurrence and help develop better strategies for prognosis prediction and personalized therapy. © 2024. The Author(s).

    Citation

    Yichen Wang, Tingzhang Wang, Dingding Yan, Hongxia Zhao, Meixia Wang, Tingting Liu, Xiaoji Fan, Xiaoxian Xu. Vaginal microbial profile of cervical cancer patients receiving chemoradiotherapy: the potential involvement of Lactobacillus iners in recurrence. Journal of translational medicine. 2024 Jun 17;22(1):575

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    PMID: 38886729

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