Cervical Cancer
Conditions
Keywords
cervical cancer, vaginal flora, metaboliomics
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.
Detailed description
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 group), high-grade squamous intraepithelial lesion (HSIL group) and newly diagnosed invasive cervical cancer (ICC group). Obtain basic information through the questionnaire, and collect vaginal secretion and blood samples every time the patients review the clincal department as scheduled. 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. Carry out the genital tract inflammation score calculating, blood inflammatory factors testing, biological information analyzing, and metabolite composition and content in vaginal secretions analyzing. The purpose of this study is to 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.
Interventions
OTHERThis project is a clinical observational study. No additional medication or surgical interventions are performed on the subjects.
This project is a clinical observational study. No additional medication or surgical interventions are performed on the subjects.
Sponsors
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
FEMALE
Age
18 Years to 60 Years
Healthy volunteers
Yes
Inclusion criteria
1. Age 18 to 60 years women; 2. have a history of sexual life for 3 years or more; 3. women not in the menstrual period, pregnancy, or puerperium.
Exclusion criteria
1. Women who received antibiotics and antifungal treatment within one month before the sample collection (records); 2. Women suffering from the following diseases: other cancer, vaginal infections, bacterial vaginosis, vulvar infections, urinary tract infections or sexually transmitted infections including chlamydia, gonorrhea, trichomoniasis and genital herpes, type I or type II diabetes, AIDS Virus positive; 3. Women with abnormal vaginal secretions or dirt in the vagina, and women who used flushing substances within three weeks before the sample collection; 4. Have sexual intercourse or use vaginal lubricant within 48 hours before sample collection.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Genital tract inflammation score | immediately after the sample collection | 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. |
| Blood inflammatory factors | immediately after the sample collection | 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. |
| 16sDNA sequencing and biological information analysis | immediately after the sample collection | 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). |
| The metabolite composition and content in vaginal secretions | immediately after the sample collection | 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). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| The content of the questionnaire | immediately after the first visit of the patients | The content of the questionnaire includes: 1. General information: name, place of origin, age, nationality, occupation, education level, family income, etc. 2. Marriage and childbirth history: menstruation, marital status, pregnancy and parity, history of sexual life, contraceptive methods, etc. 3. Lifestyle: smoking history, drinking history, sleep time, moderate to high-intensity physical activity, etc. 4. Disease history and family history: diabetes, hypertension, venereal history, history of gynecological tumors. 5. Testing and laboratory examinations: height, weight, gynecological examinations, HPV testing, TCT or cervical pathological diagnosis, etc. |
Countries
China
Contacts
Primary ContactRao Qunxian
Outcome results
None listed