Brief Summary

The disorder of vaginal microflora and its metabolites is considered to be a facilitating factor to human papillomavirus-mediated cervical cancer. However, the mechanism is still unclear. This study intends to carry out a cross-sectional study and a cohort study. The cross-sectional study intends to recruit 300 premenopausal non-pregnant women, dividing them into five groups, with 60 in each group: HPV negative \[Ctrl HPV (-)\], HPV positive \[Ctrl HPV (+)\], low-grade squamous Intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL) and newly diagnosed invasive cervical cancer (ICC). Obtain basic information through the questionnaire, and collect vaginal secretion and blood samples. At the same time, patients who are diagnosed with cervical cancer for the first time will be included in the cohort study. Collect the same kind of information. The follow-up period is set to be 3 years, and samples will be collected every six months. If any condition changes within the 3 years, samples should be collected. If new treatments are taken, samples should be taken before and after treatment. And if the lesion turns negative after treatment within the 3 years, complete the follow-up. Using 16S rRNA gene sequencing, metabolomics, and immunological methods to determine the vaginal microbiota and its metabolites and inflammation condition, select biomarkers related to the onset of cervical cancer. construct a cervical cancer risk model and outcome prediction model, and reveal the mechanism of vaginal flora and its metabolites in the pathogenesis and development of cervical cancer. Therefore provides a new direction for the prevention and treatment of cervical cancer.

Trial Health

At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date

Enrollment

300

participants targeted

Target at P75+ for all trials

Timeline

Completed

Started Apr 2022

Shorter than P25 for all trials

Geographic Reach

1 country

1 active site

Status

unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

9 months study duration

First Submitted

Initial submission to the registry

December 7, 2021

Completed

1 month until next milestone

First Posted

Study publicly available on registry

January 11, 2022

Completed

3 months until next milestone

Study Start

First participant enrolled

April 1, 2022

Completed

9 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

January 1, 2023

Completed

Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

January 1, 2023

Completed

Last Updated

January 25, 2022

Status Verified

December 1, 2021

Enrollment Period

9 months

First QC Date

December 7, 2021

Last Update Submit

January 23, 2022

Conditions

Cervical Cancer

Keywords

cervical cancervaginal florametaboliomics

Outcome Measures

Primary Outcomes (4)

Genital tract inflammation score
ELISA kit is used to detect the expression levels of 7 cytokines (IL-1α, IL-1β, IL-8, MIP-1β, CCL20, RANTES and TNF-α, etc.) in the vaginal secretions, and determine a cumulative score according to the level of each cytokine. If 3 or more than 3 of the 7 cytokines ranks in the upper quartile of all participants, it's considered high-level reproductive tract inflammation. A score of 5 to 7 is considered high-grade genital tract inflammation, 1 to 5 is low-grade genital tract inflammation, and a score of 0 is no inflammation.
immediately after the sample collection
Blood inflammatory factors
Use ELISA kit to detect 7 kinds of inflammatory factors (IL-1α, IL-1β, IL-8, MIP-1β, CCL20, RANTES and TNF-α.) in the blood sample.
immediately after the sample collection
16sDNA sequencing and biological information analysis
Extract DNA with a total bacterial DNA extraction kit, using bacterial DNA as a template, bacterial 16S rDNA V3\~V4 variable regions as targets, and barcode-equipped universal primers for PCR amplification. The PCR products will be sequenced using Illumina NovaSeq sequencing technology. After quality control, trimming, denoising, splicing, and chimera removal of the obtained raw data and reads, the high-throughput original base sequence is obtained, and the data will be analyzed using Qiime2 software. Data analysis includes operational unit (OTU) clustering, genetic enrichment analysis, principal component analysis (PCoA), community structure diversity (α and β diversity), and analysis of bacterial genus differences between groups (using linear discriminant effect analysis of LefSe ), correlation analysis, intestinal flora prediction model (random forest model).
immediately after the sample collection
The metabolite composition and content in vaginal secretions
The non-targeted metabolomics method is used to detect the metabolite composition and content in vaginal secretions. Quantitative analysis of metabolomics in each group, principal component analysis (PCOA, group analysis), differential metabolite spectrum analysis (increased/decreased metabolites in each group), correlation analysis (correlation analysis of inflammatory factors and metabolites). Correlation analysis between microbiology and metabolomics (including correlation analysis between different species and different metabolites, Scatter plot analysis, etc).
immediately after the sample collection

Secondary Outcomes (1)

The content of the questionnaire
immediately after the first visit of the patients