A Liquid Biopsy for High-risk Pre-cancer Screening of Esophageal Adenocarcinoma

Overview

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.

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.