The Mechanism of Vaginal Flora and Its Metabolites in the Pathogenesis of Cervical Cancer
Conditions: Cervical Cancer
Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

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official title: The Mechanism of Vaginal Flora and Its
Metabolites in the Pathogenesis of Cervical Cancer
NCT number: SYSEC-KY-KS-2021-214
Document date：2021-09-06

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Study Protocol
Official Title: The Mechanism of Vaginal Flora and Its Metabolites
in the Pathogenesis of Cervical Cancer
Application Official：The Sun Yat-Sen Memorial Hospital of Sun
Yat-Sen University
Version：1.0
Date：2021-09-06
Project Leader: Rao Qunxian

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1. 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.
2. Research Background
Cervical cancer is the fourth most common gynecological malignancy in the
world, caused by carcinogenic human papillomavirus[1]. According to the statistics of
the World Health Organization in 2018, there are nearly 570, 000 new cases of
cervical cancer and about 311, 000 deaths worldwide every year. There are 106, 000
new cases of cervical cancer and about 48, 000 deaths in China every year. In recent

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years, a lot of data show that the incidence rate of cervical cancer in young women is
increasing gradually. Cervical cancer is becoming younger and younger[2], which
poses a great threat to the health of women.
At present, the etiology of cervical cancer is not clear. Studies at home and
abroad shew that the occurrence of cervical cancer is related to the age of first sexual
intercourse, the number of sexual partners, the age and frequency of first delivery,
personal hygiene conditions, smoking, oral contraceptives and other factors[3-5]. It has
been recognized that the persistent infection of high-risk human papillomavirus
(HR-HPV) is the necessary conditions for cervical intraepithelial neoplasia (cervical
intraepithelial neoplasia, CIN) and carcinogenesis. The progression from HPV
infection to cervical cancer is slow and complex, which takes about 5-10 years, and
only few patients eventually develop cervical precancerous or cancerous. Therefore,
there may be other carcinogenic factors or cooperate with HPV in this process[6-7]. The
factors increase the susceptibility of cervical epithelial cells to HPV, and increased
expression of HPV virus. Therefore ensure the persistence of HPV infection, and
finally lead to cancer. As an important factor to maintain the stability of vaginal
microenvironment, whether vaginal flora plays a certain role in the process of
HR-HPV continuous infection has always been concerned.
The vaginal microenvironment is mainly composed of endocrine regulation,
anatomical structure and microbial flora. Every 6 - 8 kinds of microorganisms can be
isolated from each woman of childbearing age, mainly including bacteria, fungi,
protozoa and viruses. Under normal conditions, these microorganisms are mainly
colonized in the vaginal mucosa. Among different microorganisms, microorganisms,
host, and environment adapt, restrict and coordinate with each other, to achieve a
dynamic micro-ecological balance. Under the action of some factors, such as
long-term use of immunosuppressants or antibiotics, vaginal flushing or surgery, the
vaginal micro-ecological balance is destroyed, which will lead to a variety of diseases
[8]. In recent years, more and more scholars believe that vaginal microorganisms may
play a key role in the occurrence of cervical lesions[9]. Exposure of the cervix to the
unbalanced vaginal microenvironment may promote microbial invasion and then

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cause cervical lesions [10]. Clinical studies have found that the vaginal flora diversity
of HPV positive people is higher than that of negative people, among which the
proportion of Lactobacillus is decreased, and a variety of anaerobic bacteria such as
Gardnerella are over proliferated[11-14]. Lactobacillus protects vaginal mucosal
epithelial cells from pathogens, secretes corresponding substances, promotes the
formation of biofilm, and can inhibit the adhesion and invasion of pathogens. With the
decline
of
Lactobacillus,
the
vaginal
micro-ecological
balance
is
destroyed,
inflammatory factors increased, and the susceptibility of cervical epithelium to HPV
is improved[15]. Lactobacillus can also interfere with the material metabolism of
cancer cells, inhibit the formation of carcinogens, effectively eliminate carcinogenic
factors to induce tumor cell apoptosis, and inhibit the proliferation of cancer cells by
secreting polysaccharides. Gardnerella can act on CD59 regulatory molecules,
activate inflammatory signaling pathways, release a large amount of cytolysin,
causing apoptosis of vaginal epithelial cells, reduce Lactobacillus colonization, and
increase the risk of imbalance of vaginal microenvironment[16].
Although a large number of research results shew that vaginal flora imbalance is
closely related to HPV infection, the causation relationship between vaginal flora and
its metabolites and cervical lesions is not clear. Prospective cohort studies and
laboratory studies are needed. In addition, in view of the complexity of vaginal
microenvironment and the diversity of influencing factors of cervical lesions, the
relationship and interaction between HPV infection and vaginal flora imbalance in
cervical lesions need to be further explored.
As mentioned in the review, this study intends to carry out cross-sectional
research and cohort research, obtain the basic information of the research objects
through questionnaire, and collect vaginal secretion and blood samples every time the
patients review the clincal department as scheduled. Therefore 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.

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3. Research Purpose (with clear objectives)
3.1 To explore the correlation between vaginal flora and its metabolites and
cervical cancer, and to build a risk assessment model of cervical cancer pathogenesis;
3.2
Explore the mechanism of the development and conversion of vaginal flora
and its metabolites in cervical cancer, and construct a prediction model of cervical
cancer outcome;
3.3 Screen the biomarkers related to the incidence of cervical cancer and
therefore provide new ideas for the screening and treatment of cervical cancer.
4. Research Design
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.
5. Research Scheme and Technical Route
5.1 Selection of the Study Population
5.1.1 Cross-Sectional Study

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5.1.1.1 Calculation of Sample Size
In the study of medical microbiome, microbiome is regarded as exposure and
disease is regarded as outcome in most cases. Therefore, traditional sample size
calculation methods are rarely used in microbiome research because previous
exposure (microbiome) information is difficult to obtain. The most commonly used
sample size and efficiency calculation methods in microbiome research include t-test,
analysis of variance χ 2 test and Dirichlet polynomial model [17]. Taking the t-test as
an example, the sample size and efficiency calculation are determined in three steps.
Firstly, a small amount of amplicon data are obtained through preliminary
experiments. Secondly, the R-package “vegan” was used to calculate the
α
Diversity parameter Shannon index of each sample[18]. Finally, the power.t.test()
function is used to calculate the sample size and efficiency. In the process of studying
Crohn's disease, Gonzalez A[19] calculated the sample size through the diversity
parameter Faith's PD of the microbial community: the PD of 100 B1 Crohn's disease
was normally distributed. The mean and standard error of PD were 13.5 and 3.45,
respectively (see Figure 1). In general, the statistical test level used in most studies is
5% and the degree of assurance is 80%. Therefore, 110 patients were enrolled (55 in
each group).
Figure 1: Standard sample size calculation. It was determined significant
differences in gut flora diversity (Faith PD) between groups B1 and B2 / B3, and
the degree of assurance is 80% at three effect values (PD difference 2,3,4,
equivalent to Cohen D 0.55,0.82, and 1.09).
The pre-experiment could not be carried out, so the αdiversity distribution of
the flora of patients with cervical cancer could not be obtained. In addition, no

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published articles were found to provide the data required for calculation. Therefore,
it is planned to design this study with reference to the sample size of the above study,
details as follows:
Recruit 300 premenopausal non-pregnant women, age 18-60, dividing them into
five groups, with 60 in each group (> 55, ensuring an effect value of 0.8, the
difference equivalent to 3 PD units): 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).
5.1.1.2 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.
5.1.1.3 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.
5.1.2 Cohort Study
The study subjects are patients first diagnosed with cervical cancer. A total of
100 patients (sample size estimated from the above cross-sectional study). 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

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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.
5.1.3.1 Inclusion Criteria: (1) Women first diagnosed with cervical cancer; (2) have a
history of sexual life for 3 years or more; (3) women not in the menstrual period,
pregnancy, or puerperium.
5.1.3.2 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.
5.1.4 Withdrawal / Early Stop of the study
(1) If the patient quits the study before completing the evaluation specified in the
study protocol, it is seemed to withdraw and stop the study early. (2) Patients can
withdraw / stop the study due to pregnancy. (3) If the patients requests to withdraw
from the project for their own reasons, they will withdraw / stop the study
unconditionally.
5.2 Research Technique
5.2.1 Informed Consent
Before starting the study, the researcher clearly and verbally explains
the details of the study and its potential risks and benefits to the patient or
her authorized person. The patient or her authorized person and the
researcher need to sign and date the informed consent form. Only after

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signing the informed consent can the patients enter the screening and then
participate in the study.
5.2.2 Questionnaire Survey
A
self-designed
questionnaire
survey
is
adopted.
After
the
questionnaire design is completed, a pre-survey is carried out to estimate
the rationality and feasibility of the questionnaire. The patient's informed
consent shall be obtained and sufficient time shall be given before the
investigation. The questionnaire shall be filled in face to face by the
trained investigator and the research object. During the filling process, no
situation of inducing or interfering are allowed. The quality of the
questionnaire shall be checked by another quality control person. If any
problem is found, it shall be immediately checked, supplemented or
corrected.
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.
5.2.3 Collection of Specimens
After emptying the urine, the subjects are asked to separate their legs, take the
lithotomy position and lie on the gynecological examination bed to fully expose the

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genitals and perineum. Open the vagina with a sterile vaginal speculum, use two
sterile vaginal cotton swabs to collect secretions at the vaginal dome or the side wall
of the middle part of the vagina, rotate for 10-15s, and put them into a dry sterile test
tube after the swab fully absorbs the secretion to avoid contacting the vaginal mouth
and vulva and prevent specimen pollution. Put the cotton swab into a dry sterile test
tube and store it in a refrigerator at - 80°C for the extraction of total bacterial DNA.
The vaginal pH value was measured with precision pH test paper.
Vaginal swabs were collected in quadruplicate, two for the metabolomics of
vaginal secretions, one for vaginal microorganisms and the other for reproductive
tract inflammatory factors.
Statistical Analysis Plan
5.2.4 Evaluation indicators and methods
1.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.
2.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.
3.16sDNA 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

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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).
4.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).
5.2.5 Statistical Method
R software will be used for statistical analysis. The data results are expressed as
mean ± standard deviation (x±s). The mean between the two groups is compared
by two independent sample t-test. Kruskal Wallis and Wilcoxon rank sum test are
used for statistical analysis of vaginal flora data; Spearman rank correlation is used
for correlation analysis. P < 0.05 is considered to have statistically significant
difference.
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