Establishment of Cohort Under the Guidance of the Pathogenesis of Cancer Toxin in Traditional Chinese Medicine
September 22, 2024 updated by: Ying Zhang
Research on the Scientific Connotation of Cancer Toxin Pathogenesis Based on the Interaction Between Flora and Tumor-Establishment of Cohort Under the Guidance of the Pathogenesis of Cancer Toxin in Traditional Chinese Medicine
The study aims to investigate the potential mechanisms by which the interaction between the microbiota and tumors leads to the occurrence and development of cancer by collecting clinical information and biological samples from healthy individuals and cancer patients.
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Detailed Description
Study Design Types: A prospective, multicenter, observational study.
Observation Content:1.Healthy Individuals:General Information (Demographic Data), Traditional Chinese Medicine Physical Quality Scale, Biological Samples (Fecal, Blood, Tongue Coating, Tongue Appearance Photos, Tissues). 2.Malignant Tumor Patients: General Information (Demographic Data, Disease Information, ECOG Performance Status Score, MDASI Anderson Symptom Inventory), Traditional Chinese Medicine Cancer Toxin Syndrome Scale, Traditional Chinese Medicine Physical Quality Scale, Laboratory and Examination Data, Biological Samples (Fecal, Blood, Tongue Coating, Tongue Appearance Photos, Tissues).
Observation Time Points:1.Healthy Individuals: At the time of enrollment. 2.Malignant Tumor Patients: At the time of enrollment, 1 month after enrollment, every 3 months thereafter until tumor progression.
Study Type
Observational
Enrollment (Estimated)
500
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Yi Xie, PhD
- Phone Number: 18810537596
- Email: 18810537596@163.com
Study Contact Backup
- Name: Ying Zhang, PhD
- Phone Number: 13311027150
- Email: zylzy501@163.com
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
N/A
Sampling Method
Probability Sample
Study Population
Healthy individuals and cancer patients.
Description
Inclusion Criteria:
Inclusion criteria for healthy individuals:
- Age ≥ 18 years old;
- Informed consent and signed informed consent form.
Inclusion criteria for patients with malignant tumors:
- Patients with malignant tumors diagnosed by pathology or cytology;
- Advanced stage patients who have not received modern medical treatment in the past, or early to mid-stage patients who have completed postoperative radiochemotherapy for ≥ 1 month;
- Age ≥ 18 years old;
- Informed consent and signed informed consent form.
Exclusion Criteria:
Exclusion criteria for healthy individuals:
- Patients with malignant tumors diagnosed by pathology or cytology;
- Those who have taken any antibiotics/probiotics within 1 month before biological sample collection;
- Those with other immune or infectious diseases;
- Those with severe damage to the heart, liver, lungs, or kidney functions;
- Pregnant women, or those with mental illnesses such as depression or schizophrenia;
- Those deemed ineligible for the study by the researcher.
Exclusion criteria for patients with malignant tumors:
- Patients with multiple primary cancers;
- Those who have taken any antibiotics/probiotics within 1 month before biological sample collection;
- Those with other immune or infectious diseases;
- Those with severe damage to the heart, liver, lungs, or kidney functions;
- Pregnant women, or those with mental illnesses such as depression or schizophrenia;
- Those deemed ineligible for the study by the researcher.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
healthy individuals and cancer patients
Comparing the microbiota characteristics of healthy individuals and cancer patients, revealing the differences in microbiota between healthy individuals and cancer patients.
|
This study observed differences in microbiota among different groups and therefore did not involve intervention.
|
|
Patients with different traditional Chinese medicine cancer toxicity syndrome types
According to the classification of traditional Chinese medicine cancer toxin syndrome types, compare the differences in microbiota between the heat toxin syndrome group, dampness toxin syndrome group, stasis toxin syndrome group, phlegm toxin syndrome group, wind toxin syndrome group, and cold toxin syndrome group in cancer patients, and explore the influence of different cancer toxin syndrome types on microbiota composition.
|
This study observed differences in microbiota among different groups and therefore did not involve intervention.
|
|
Patients with different traditional Chinese medicine constitutions
According to the traditional Chinese medicine constitution classification, compare the differences in microbiota among tumor patients with qi stagnation constitution group, phlegm dampness constitution group, damp heat constitution group, blood stasis constitution group, qi deficiency constitution group, yang deficiency constitution group, yin deficiency constitution group, characteristic constitution group, and peaceful constitution group, and explore the influence of different constitution types on the microbiota composition of tumor patients.
|
This study observed differences in microbiota among different groups and therefore did not involve intervention.
|
|
Patients with different tumor burden
Divide tumor patients into tumor bearing group and tumor free group, and explore their microbiota characteristics and differential patterns.
|
This study observed differences in microbiota among different groups and therefore did not involve intervention.
|
|
Patients with different symptom burdens
According to the MDASI Anderson Symptom Scale, compare the differences in microbiota between individuals with mild and severe symptom burdens, and explore the impact of different symptom burdens on the microbiota composition of cancer patients.
|
This study observed differences in microbiota among different groups and therefore did not involve intervention.
|
|
Patients with different treatment and outcome outcomes
Based on the application of different treatment methods and the resulting outcomes in cancer patients, compare the characteristic differences of microbiota between groups and explore the differential expression of microbiota.
|
This study observed differences in microbiota among different groups and therefore did not involve intervention.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
16S rDNA
Time Frame: 2 years (from enrollment to disease progression).
|
16S rDNA detection is a commonly used method in microbial molecular biology for identification and classification of bacteria.
It can identify and classify bacteria.
|
2 years (from enrollment to disease progression).
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
microbiota metagenomics
Time Frame: 2 years (from enrollment to disease progression).
|
Metagenomic Sequencing is a technique that studies the total genetic material of all microorganisms in environmental samples.
This method does not rely on traditional microbial isolation and cultivation, but instead directly extracts total DNA from environmental samples to obtain new functional genes and bioactive substances by constructing and screening metagenomic libraries.
|
2 years (from enrollment to disease progression).
|
|
Untargeted metabolomics
Time Frame: 2 years (from enrollment to disease progression).
|
Untargeted Metabolomics is a research method that does not rely on prior knowledge of specific metabolites.
Instead, it explores the overall patterns and changes of metabolites by analyzing all detectable metabolites in biological samples.
|
2 years (from enrollment to disease progression).
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
September 22, 2024
Primary Completion (Estimated)
February 28, 2027
Study Completion (Estimated)
February 28, 2027
Study Registration Dates
First Submitted
September 19, 2024
First Submitted That Met QC Criteria
September 22, 2024
First Posted (Actual)
September 25, 2024
Study Record Updates
Last Update Posted (Actual)
September 25, 2024
Last Update Submitted That Met QC Criteria
September 22, 2024
Last Verified
September 1, 2024
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- CI2023C025YL
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
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