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.
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.
Study Type
OBSERVATIONAL
Enrollment
2,500
Bayview Medical Center
Baltimore, Maryland, United States
RECRUITINGJohns Hopkins Hospital
Baltimore, Maryland, United States
RECRUITINGDifference in methylation of gene markers to discriminate Barrett's esophagus from non-pathological esophageal squamous and gastric cardia tissue.
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.
Time frame: 1 day
Difference in methylation of gene markers to discriminate esophageal carcinoma from non-pathological esophageal squamous and gastric cardia tissue.
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.
Time frame: 1 day
Difference in methylation of gene markers to discriminate gastric cancer from non-pathological esophageal squamous and gastric cardia tissue.
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.
Time frame: 1 day
Sensitivity of candidate biomarker p16
Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
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Sensitivity of candidate biomarker NELL1
Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Sensitivity of candidate biomarker AKAP12
Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Sensitivity of candidate biomarker TAC1
Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Sensitivity of candidate biomarker HPP1
Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Specificity of candidate biomarker p16
Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Specificity of candidate biomarker NELL1
Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Specificity of candidate biomarker AKAP12
Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Specificity of candidate biomarker TAC1
Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day
Specificity of candidate biomarker HPP1
Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.
Time frame: 1 day