Clinical trial NCT06381583: A Liquid Biopsy for High-risk Pre-cancer Screening of Esophageal Adenocarcinoma
Official title: A Liquid Biopsy to Screen for Barrett's Esophagus, Dysplasia, and Esophageal Adenocarcinoma: the EMERALD Multi-center Study.
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Esophagus Cancer
Esophageal Cancer Stage
Esophageal Cancer
Esophageal Neoplasms
Esophagus Adenocarcinoma
Esophagus, Barrett
Barrett Esophagus
Barrett Adenocarcinoma
Barrett Epithelium
Barretts Esophagus With Dysplasia
Barrett's Esophagus Without Dysplasia
Barretts Esophagus With High Grade Dysplasia
Barretts Esophagus With Low Grade Dysplasia
Barrett Esophagus, Long-Segment
Barrett's Esophagus With Dysplasia, Unspecified
Barrett's Esophagus With Esophagitis
Gastroesophageal Reflux
Reflux Disease
Esophageal Adenocarcinoma
Esophageal Dysplasia
Esophageal Neoplasms Malignant
Keywords: Early detection
Micro RNA
miRNA
Liquid biopsy
Dysplasia
Artificial Intelligence
Cancer detection
Long segment Barrett Esophagus
Screening
Surveillance
Lead sponsor: City of Hope Medical Center
Sponsor class: OTHER
First posted: 2024-04-24
Enrollment: 658
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: CASE_CONTROL
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Four independent cohorts of individuals who belong to one of the following five

Negative endoscopic findings Barrett's esophagus, at least 3 cm long without low-grade dysplasia (at most) Barrett's esophagus, of any length, with low-grade dysplasia (at most) Barrett's esophagus, of any length, with high-grade dysplasia (at most) Esophageal adenocarcinoma (of any stage, including in situ \[Tis\]) Colorectal cancer

Brief summary: This study aims to develop a highly sensitive, specific, and cost-effective blood assay for the early detection of esophageal adenocarcinoma and its precursor lesions, using advanced machine learning and state-of-the-art biological analyses.

Detailed description: Esophageal adenocarcinoma (EAC) is a significant global health concern, ranking second in lethality (after pancreatic cancer). Despite being potentially preventable, it remains a leading cause of cancer-related deaths. Traditional screening methods have relied on an endoscopy-first approach to screen for the precursor of EAC, which is Barrett's esophagus (BE). After BE detection, BE is then regularly surveiled to monitor the development of dysplasia, which can be treated to prevent malignant transformation. An endoscopy-first approach is sensitive BE and, therefore, it lowers the risk of developing EAC but it also faces challenges such as invasiveness, cost, and patient compliance.

Non-invasive tests are more appealing to patients than invasive tests and can increase participation rates. Biomarker studies have shown promise, but existing tests lack sensitivity for early-stage EAC and, most importantly, to its precursor lesion BE. This is likely because they over-sampled analytes that are primarily expressed at the EAC end of the spectrum, but not in BE yet during the BE to EAC sequence.

This study proposes developing an innovative liquid biopsy test tailored for EAC and BE to address this. An ideal screening test should be minimally invasive, highly sensitive, and cost-effective. This test would optimize patient compliance and resource allocation by detecting both conditions from a single blood draw. More specifically, circulating microRNA (miRNA) analysis shows promise: tests based on cell-free microRNA (cf-miRNA) have demonstrated high sensitivity.

This study will develop a non-invasive blood test for BE and EAC in four phases:

1. In silico genome-wide profiling of tissue miRNA to select the best candidates for biomarker panels.
2. Prioritization of the biomarkers that are differentially expressed across the entire continuum of BE to EAC sequence, compared to the normal mucosa
3. Transition of these biomarkers to a liquid biopsy assay, confirming their detectability in blood as well as their differential expression in cases compared to controls
4. Utilizing machine learning to identify the most promising candidates and train algorithms for detecting EAC and BE, based on results from quantitative polymerase chain reaction (qPCR) analysis.
5. Independently validating these signatures using diverse cohorts to ensure broad applicability and compare the effectiveness of the blood assay to standard care through retrospective and prospective studies.

This study aims to develop a highly sensitive, specific, and cost-effective liquid biopsy for early detection of BE and EAC. Success could transform clinical practice by preventing EAC through early detection of pre-malignant lesions. Innovations include incorporating pre-malignant lesions into screening. This approach could potentially reduce EAC mortality and incidence and pave the way for new clinical trials.

Eligibility criteria: Inclusion Criteria:

* All individuals included in the study need to have had an endoscopic evaluation at the time of blood sampling.
* Received standard diagnostic and staging (as necessary) procedures as per local guidelines, and at least one sample was drawn before receiving any curative-intent treatment.
* Received standard pathological and endoscopic diagnosis and assessment for cohort assignment.

Exclusion Criteria:

* Lack of written informed consent.
* Short segment Barrett's esophagus with no evidence of dysplasia
* Ultra-short segment Barrett's esophagus with no evidence of dysplasia

Primary outcomes:
measure: Sensitivity
timeFrame: Through study completion, an average of 1 year
Secondary outcomes:
measure: Specificity
timeFrame: Through study completion, an average of 1 year
measure: Proportion of correct predictions (true positives and true negatives) among the total number of cases (i.e., accuracy)
timeFrame: Through study completion, an average of 1 year
Other outcomes:
Locations:
city: Duarte
country: United States
facility: City of Hope Medical Center
state: California
Study officials:
affiliation: City of Hope Medical Center
name: Ajay Goel, PhD
role: PRINCIPAL_INVESTIGATOR
References: