Sikao Wu1, Xuewen Ding1, Ying Kong1, Sanam Acharya1, Huaqian Wu1, Chunning Huang1, Yuanyuan Liang1, Xianxian Nong1, Hong Chen2. 1. Department of Gynecology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. 2. Department of Gynecology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: doctorchen2016@hotmail.com.
Abstract
OBJECTIVES: The aim of this study was to characterize cervical microbiome feature of reproductive-age women in the progression of squamous intraepithelial lesions (SIL) to cervical cancer. METHODS: We characterized the 16S rDNA cervical mucus microbiome in 94 participants (age from 18 to 52), including 13 cervical cancer (CA), 31 high-grade SIL (HSIL), 10 low-grade SIL (LSIL), 12 HPV-infected (NH) patients and 28 healthy controls (NN). Alpha (within sample) diversity was examined by Shannon and Simpson index, while Beta (between sample) diversity by principle coordinate analysis (PCoA) of weighted Unifrac distances. Relative abundance of microbial taxa was compared using Linear Discriminant Analysis Effect Size (LEfSe). Co-occurrence analysis was performed to identify correlation among marker genera, and Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) to explore functional features and pathways of cervical microbiota. RESULTS: Alpha diversity(p < 0.05) was higher in severer cervical pathology with lower relative abundance of Lactobacillus as well as higher of anaerobes. Beta diversity (p < 0.01) was significantly different. Marker genera were identified including Porphyromonas, Prevotella and Campylobacter of CA and Sneathia of HSIL. The correlation of differential functional pathways with Prevotella was opposite to that with Lactobacillus. CONCLUSION: Our study suggests differences in cervical microbiota diversity and relative abundance of reproductive-age females in different stages of cervical carcinogenesis. Marker genera might participate in the lesion progression and will be helpful for diagnosis, prevention and treatment. These findings may lead the way to further study of the cervical microbiome in development of cervical cancer.
OBJECTIVES: The aim of this study was to characterize cervical microbiome feature of reproductive-age women in the progression of squamous intraepithelial lesions (SIL) to cervical cancer. METHODS: We characterized the 16S rDNA cervical mucus microbiome in 94 participants (age from 18 to 52), including 13 cervical cancer (CA), 31 high-grade SIL (HSIL), 10 low-grade SIL (LSIL), 12 HPV-infected (NH) patients and 28 healthy controls (NN). Alpha (within sample) diversity was examined by Shannon and Simpson index, while Beta (between sample) diversity by principle coordinate analysis (PCoA) of weighted Unifrac distances. Relative abundance of microbial taxa was compared using Linear Discriminant Analysis Effect Size (LEfSe). Co-occurrence analysis was performed to identify correlation among marker genera, and Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) to explore functional features and pathways of cervical microbiota. RESULTS: Alpha diversity(p < 0.05) was higher in severer cervical pathology with lower relative abundance of Lactobacillus as well as higher of anaerobes. Beta diversity (p < 0.01) was significantly different. Marker genera were identified including Porphyromonas, Prevotella and Campylobacter of CA and Sneathia of HSIL. The correlation of differential functional pathways with Prevotella was opposite to that with Lactobacillus. CONCLUSION: Our study suggests differences in cervical microbiota diversity and relative abundance of reproductive-age females in different stages of cervical carcinogenesis. Marker genera might participate in the lesion progression and will be helpful for diagnosis, prevention and treatment. These findings may lead the way to further study of the cervical microbiome in development of cervical cancer.
Authors: Barbara Gardella; Marianna Francesca Pasquali; Marco La Verde; Stefano Cianci; Marco Torella; Mattia Dominoni Journal: Int J Mol Sci Date: 2022-06-28 Impact factor: 6.208