Potential association between vaginal microbiota and cervical carcinogenesis in korean women: A cohort study

Gi Ung Kang, Da Ryung Jung, Yoon Hee Lee, Se Young Jeon, Hyung Soo Han, Gun Oh Chong, Jae Ho Shin

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Convincing studies demonstrated that vaginal flora is one of the most impactful key components for the well‐-being of the genital tract in women. Nevertheless, the potential capability of vaginal‐-derived bacterial communities as biomarkers to monitor cervical carcinogenesis (CC) has yet to be studied actively compared to those of bacterial vaginosis (BV). We hypothesized that vaginal microbiota might be associated with the progression of CC. In this study, we enrolled 23 par-ticipants, including healthy controls (HC group; n = 7), patients with cervical intraepithelial neo-plasia (CIN) 2 and 3 (CIN group, n = 8), and patients with invasive cervical cancer (CAN group; n = 8). Amplicon sequencing was performed using the Ion Torrent PGM to characterize the vaginal mi-crobiota. Patients with CIN and CAN presented vaginal microbiota dysbiosis compared with HC. The alpha diversity analysis revealed that CC has a trend to be increased in terms of diversity in-dexes. Moreover, CC was associated with the abundance of specific microbes, of which Lactobacillus and Gardnerella were the most significantly different between HC and CIN, whereas Streptococcus was differentially abundant in CAN compared with CIN. We then evaluated their diagnostic abili-ties. Testing in terms of diagnostic ability using the three genera revealed considerably high performance with an area under the receiver‐-operating characteristic curve of 0.982, 0.953, and 0.922. The current study suggests that the presence of Gardnerella and Streptococcus may be involved in the advancment of CC.

Original languageEnglish
Article number294
Pages (from-to)1-11
Number of pages11
JournalMicroorganisms
Volume9
Issue number2
DOIs
StatePublished - Feb 2021

Keywords

  • CIN prediction
  • CIN severity
  • Vaginal microbiome
  • Vaginosis

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