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NCT Number: NCT04214119

EsophaCap for the Detection of Early Esophageal Carcinoma

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.

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Key information

Conditions

Barrett Esophagus Digestive System Diseases Digestive System Neoplasms Esophageal Cancer Esophageal Diseases Esophageal Neoplasms Gastric Cancer Gastrointestinal Diseases Gastrointestinal Neoplasms Head and Neck Neoplasms Neoplasms Neoplasms by Site Precancerous Conditions Stomach Diseases Stomach Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Bayview Medical Center, Baltimore, Maryland, United States

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About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Primary outcomes

  1. Difference in methylation of gene markers to discriminate Barrett's esophagus from non-pathological esophageal squamous and gastric cardia tissue.

    Time frame: 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.

  2. Difference in methylation of gene markers to discriminate esophageal carcinoma from non-pathological esophageal squamous and gastric cardia tissue.

    Time frame: 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.

  3. Difference in methylation of gene markers to discriminate gastric cancer from non-pathological esophageal squamous and gastric cardia tissue.

    Time frame: 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 outcomes

  1. Sensitivity of candidate biomarker p16

    Time frame: 1 day

    Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  2. Sensitivity of candidate biomarker NELL1

    Time frame: 1 day

    Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  3. Sensitivity of candidate biomarker AKAP12

    Time frame: 1 day

    Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  4. Sensitivity of candidate biomarker TAC1

    Time frame: 1 day

    Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  5. Sensitivity of candidate biomarker HPP1

    Time frame: 1 day

    Sensitivity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  6. Specificity of candidate biomarker p16

    Time frame: 1 day

    Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  7. Specificity of candidate biomarker NELL1

    Time frame: 1 day

    Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  8. Specificity of candidate biomarker AKAP12

    Time frame: 1 day

    Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  9. Specificity of candidate biomarker TAC1

    Time frame: 1 day

    Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

  10. Specificity of candidate biomarker HPP1

    Time frame: 1 day

    Specificity of each candidate biomarker will be calculated by measuring the area under receiver operating characteristic curve generated from methylation index data.

Study contacts

Contact information is provided by the study sponsor or research team.

Stephen J Meltzer, M.D.

CONTACT

[email protected]

4105026071

Sponsors and collaborators

Lead sponsor

Johns Hopkins University

Other

Collaborators

  • National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

Registry information

Important dates

Study start
2016
Primary completion
2028
Study completion
2028
First posted
Jan 2, 2020
Registry last updated
Dec 16, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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