Barrett Esophagus, Esophageal Cancer, Gastric Cancer
Conditions
Brief summary
This study is to identify potential biomarkers for the early detection of Barrett's Esophagus, esophageal carcinoma (both adenocarcinoma and squamous cell carcinoma), and gastric cancer via sponge cytology.
Detailed description
This study is to identify potential biomarkers for the early detection of Barrett's Esophagus, esophageal carcinoma (both adenocarcinoma and squamous cell carcinoma). Esophageal and gastric cytology will be collected via sponge capsule. Candidate genes will be tested with DNA isolated from these samples in order to identify optimal biomarkers to differentiate between Barrett's esophagus and esophageal/gastric cancer versus normal esophageal/gastric tissue.
Interventions
None listed
Sponsors
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Johns Hopkins University
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Undergoing esophagogastroduodenoscopy at Johns Hopkins Hospital from 1/2016 to 12/2025 * Age greater than 18 years * Patients must be able to swallow a capsule
Exclusion criteria
* Patients in either arm with extra-esophageal malignancies including head and neck and gastric cancer * Patients who have undergone esophagectomy * Patients who have undergone radiation to the chest * Patients who are younger than 18 * Patients with esophageal stents * Patients with esophageal strictures disabling passage of the capsule
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Difference in methylation of gene markers to discriminate Barrett's esophagus from non-pathological esophageal squamous and gastric cardia tissue. | 1 day | Using DNA methylation, we plan on identifying, from a pool of highly selected marker candidates, the best biomarkers that are aberrantly methylated in Barrett's esophagus versus control in order to differentiate between subjects who have Barrett's esophagus and those who do not have Barrett's esophagus. This is measure using methylation index and the calculated probability score from different methylation index values. |
| Difference in methylation of gene markers to discriminate esophageal carcinoma from non-pathological esophageal squamous and gastric cardia tissue. | 1 day | Using DNA methylation, we plan on identifying, from a pool of highly selected marker candidates, the best biomarkers that are aberrantly methylated in esophageal cancer versus control in order to differentiate between subjects who have esophageal cancer and those who do not. This is measure using methylation index and the calculated probability score from different methylation index values. |
| Difference in methylation of gene markers to discriminate gastric cancer from non-pathological esophageal squamous and gastric cardia tissue. | 1 day | Using DNA methylation, we plan on identifying, from a pool of highly selected marker candidates, the best biomarkers that are aberrantly methylated in gastric cancer versus control in order to differentiate between subjects who have gastric cancer and those who do not. This is measure using methylation index and the calculated probability score from different methylation index values. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity of candidate biomarker TAC1 | 1 day | Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Sensitivity of candidate biomarker HPP1 | 1 day | Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Specificity of candidate biomarker p16 | 1 day | Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Sensitivity of candidate biomarker p16 | 1 day | Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Specificity of candidate biomarker AKAP12 | 1 day | Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Specificity of candidate biomarker TAC1 | 1 day | Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Specificity of candidate biomarker HPP1 | 1 day | Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Specificity of candidate biomarker NELL1 | 1 day | Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Sensitivity of candidate biomarker NELL1 | 1 day | Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
| Sensitivity of candidate biomarker AKAP12 | 1 day | Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data. |
Countries
United States
Contacts
Primary ContactStephen J Meltzer, M.D.
Outcome results
None listed