Investigating the Association Between Microbiota and Esophageal/Oropharyngeal Cancer

Study Overview
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Brief Summary
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Background: Esophageal cancer commonly occurs in middle-aged man. It is ranked to the 6th common cancer and 5th cancer-related death in Taiwanese male, and sometimes co-exist with oropharyngeal cancer, which impacts our national economics and productivity a lot. To improve the prognosis of esophageal cancer, we should contribute to early diagnosis and improved treatment of the disease. Recent studies showed oral and esophageal dysbiosis may lead to oropharyngeal and esophageal cancer. Aim: To investigate whether oral microbiota is similar to esophageal microbiota. To investigate whether oral microbiota can be a non-invasive biomarker of oropharyngeal cancer, esophageal cancer, synchronous cancer and chemoradiation resistance. And whether probiotic supplement can improve oral/esophageal dysbiosis in order to prevent esophageal cancer. Study design: This study compares the oral/esophageal microbiota composition between oropharyngeal cancer cases, esophageal cancer cases, synchronous cancer cases and non-cancer controls. In addition, the link between oral and esophageal microbiota will be explored. The study will identify the microbiota related with esophageal cancer development. We will also validate the effect of probiotic supplementation on improving oral/esophageal dysbiosis. Expected result and significance: Examination of oral microbiota has the potential to become a non-invasive tool for oropharyngeal cancer, esophageal cancer, and synchronous cancer. Probiotic supplementation has the potential to improve oral dysbiosis.

Detailed Description
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Esophageal cancer is one of the most common gastrointestinal malignant diseases worldwide with an estimated 456,000 incident cases annually. Esophageal cancer has a poor prognosis and high mortality rate. The 5-year survival rate is around 15%-25%. The treatment options of esophageal cancer can be divided into curative treatment and palliative treatment, while endoscopy, surgery and chemoradiotherapy were involved. However, 60-70% patients diagnosed with esophageal cancer are not eligible for curative treatment. In these patients, chemoradiotherapy is the standard for unresectable esophageal cancer, but the treatment outcome remains poor. In the literatures, the complete response rate of chemoradiotherapy in advanced esophageal cancer was about 20%, and the 2-year overall survival rate was 40%. Therefore, early detection and prediction of esophageal cancer are needed. Besides, the inconsistency of treatment effect of chemoradiotherapy may indicate some differences of esophageal cancer microenvironment among the patients. Finding out the affecting factors of microenvironment may help the decision making of treatment options and the prediction of disease prognosis. Furthermore, if we can change the affecting factors in microenvironment, we may be able to prevent the esophageal cancer formation or progression. Esophageal tumor initiation is associated with environmental exposures, chronic inflammation, and immune cells. Several genetic and environmental factors play key roles in the formation and progression of esophageal cancer. Refluxed gastric and bile acids induce chronic inflammation and the development of intestinal metaplasia (Barrett's esophagus), which is the precursor lesion to esophageal adenocarcinoma. Toxic agent like tobacco and alcohol can cause direct esophageal injury and production of reactive oxygen species (ROS). ROS production causes direct DNA damage and tumor-initiating mutations. Besides, some literatures had reported the possible correlation with microbiota and cancer formation. Commensal bacteria (the microbiota) normally live in the gastrointestinal tract with host cell. Disruption of the relationship (dysbiosis) can influence the metabolism, tissue development, and immune response, which may cause damage to epithelial barriers, inflammation, and inducing DNA and pro-oncogenic signaling, leading to carcinogenesis in the gastrointestinal tract. The role of microbiota in the esophagus has not been widely investigated. Increasing of gram-negative bacteria increases the production of lipopolysaccharide (LPS), leading to inflammation and increased gastric reflux. The gut microbiota is associated with nutrition, the immune system, and defense of the host. It produces short chain fatty acids via anaerobic fermentation of dietary fibers in the intestine. Compared with healthy individuals, the abundance of short chain fatty acids -producing bacteria decreased and the abundance of lipopolysaccharide (LPS) -producing bacteria increased in esophageal cancer patients. Butyrate, one of the short chain fatty acids, decreases LPS-induced cytokine expression and NF-κB activation in lamina propria mononuclear cells. Esophageal microbiota theoretically plays a role in esophageal carcinogenesis. Esophageal cancer is composed of esophageal adenocarcinoma and esophageal squamous cell carcinoma (ESCC). In esophageal adenocarcinoma, a decrease of Firmicutes, and an increase of Proteobacteria, Lactobacillus fermentum, and Tannerella forsythia have been reported. In esophageal squamous cell carcinoma, a reduction of Streptococcus species and an increase of Fusobacterium nucleatum and Porphyromonas gingivalis were observed. In Taiwan, patients with primary oropharyngeal cancer had ten times the risk of second esophageal cancer compared to the general population, and vice versa. Some specific bacteria may be associated with the co-existence of oropharyngeal cancer and esophageal cancer. However, diet is one of the most potent factors in determining microbiome integrity. Owing to the dietary difference between easterners and westerners, the dominant microbiota affecting esophageal cancer may be different. Finding out the esophageal cancer-associated specific bacteria of microbiota in Taiwan is important for further research and application for our patients. Previously, some microorganisms could not be cultured, which would make the microbiota detection incomplete. Nowadays, 16S ribosomal RNA (16S rRNA) sequences had replaced the culture methods in detection of microbiota. In our study, we aim to compare the microbiota among healthy individuals, patients with esophageal cancer, oropharyngeal cancer, and concurrent esophageal cancer with oropharyngeal cancer in Taiwan. Through the comparison, we may find the potential risky microbiota for cancer formation or progression in Taiwan.

Official Title
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Investigating the Association, Disease Mechanism, and Clinical Application Between Microbiota and Oropharyngeal and Esophageal Cancer

Conditions
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Microbial Colonization, Esophageal Cancer, Oropharyngeal Neoplasms, Synchronous Neoplasm

Intervention / Treatment
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* Diagnostic Test: Oral swab test


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Eligible participants included patients aged ≥ 20 years with oropharyngeal cancer, esophageal cancer, or dyspeptic patients without cancer. Exclusion Criteria: Patients with other cancer than esophageal cancer or oropharyngeal cancer. Patients with bleeding tendency, such as platelet < 50k, PTinr > 2, or using anti-coagulants. Patients with use of antibiotics within the past 2 weeks

Ages Eligible for Study
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Minimum Age: 20 Years
Maximum Age: 99 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Screening
Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Esophageal cancer group<br>patients aged ≥ 20 years with esophageal cancer | Diagnostic Test: Oral swab test<br>* In this study, we will perform tissue biopsy at esophageal tumor site in esophageal cancer patients and perform random biopsy at middle esophagus in patients without esophageal cancer. Besides, we will take oral swab in all participants.<br>* Other names: Esophageal mucosal tissue biopsy;|
| Experimental: Oropharyngeal cancer group<br>patients aged ≥ 20 years with oropharyngeal cancer | Diagnostic Test: Oral swab test<br>* In this study, we will perform tissue biopsy at esophageal tumor site in esophageal cancer patients and perform random biopsy at middle esophagus in patients without esophageal cancer. Besides, we will take oral swab in all participants.<br>* Other names: Esophageal mucosal tissue biopsy;|
| Experimental: Synchronous cancer group<br>patients aged ≥ 20 years with synchronous oropharyngeal cancer and esophageal cancer | Diagnostic Test: Oral swab test<br>* In this study, we will perform tissue biopsy at esophageal tumor site in esophageal cancer patients and perform random biopsy at middle esophagus in patients without esophageal cancer. Besides, we will take oral swab in all participants.<br>* Other names: Esophageal mucosal tissue biopsy;|
| Placebo Comparator: Control group<br>patients aged ≥ 20 years with symptoms of dysphagia without cancer | Diagnostic Test: Oral swab test<br>* In this study, we will perform tissue biopsy at esophageal tumor site in esophageal cancer patients and perform random biopsy at middle esophagus in patients without esophageal cancer. Besides, we will take oral swab in all participants.<br>* Other names: Esophageal mucosal tissue biopsy;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| To analyze the similarity of microbiota distribution between the buccal field and the esophageal area in the same patient | We will send one patient's oral swab and esophageal mucosal tissue for screening microbiota by sequencing 16S rRNA (measured as percentage abundance per microbial species and differences in percentage abundance between the esophagus and mouth). In order to compare the similarity of microbiota between mouth and esophagus. The raw tags of data will be transformed into high-quality clean tags through the QIIME quality control process. Both alpha- and beta-diversity will be calculated with QIIME software and display with R software. We will use the Ace index to assess the richness of OTUs community and the Shannon index to assess the evenness of community diversity. Weighted UniFrac will be implemented to manifest the phylogenetic relationship of beta-diversity. To find out different genera of bacterial composition between groups, the student's t-test will be employed. | 1 week | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| To analyze the distribution difference of microbiota among the patients with esophageal cancer/oropharyngeal cancer and non-cancer control | The study will compare the microbiota by sequencing 16S rRNA (measured as percentage abundance per microbial species and differences in percentage abundance between the control group and cancer group). In order to compare the difference of microbiota among esophageal cancer patients, oropharyngeal cancer patients, synchronous cancer patients, and non-cancer control. The raw tags of data will be transformed into high-quality clean tags through the QIIME quality control process. Both alpha- and beta-diversity will be calculated with QIIME software and display with R software. We will use the Ace index to assess the richness of OTUs community and the Shannon index to assess the evenness of community diversity. Weighted UniFrac will be implemented to manifest the phylogenetic relationship of beta-diversity. To find out different genera of bacterial composition between groups, the student's t-test will be employed. | 1 week |