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Clin Cancer Res. 2019 Jan 22. pii: clincanres.3696.2018. doi: 10.1158/1078-0432.CCR-18-3696. [Epub ahead of print]

Methylation Biomarker Panel Performance in EsophaCap Cytology Samples for Diagnosing Barrett's Esophagus: A Prospective Validation Study.

Author information

1
Gastrointestinal Surgery, First Affiliated Hospital of Sun Yat-sen University.
2
Department of Medicine, Hellen Diller Family Comprehensive Cancer Center, UCSF Medical Center.
3
Gasteroenterology and Hepatology, Johns Hopkins University School of Medicine.
4
Division of Gastroenterology and Hepatology, Johns Hopkins University School of Medicine.
5
Division of Gastroenterology, Department of Medicine,, Johns Hopkins University School of Medicine.
6
Division of Gastroenterology, Department of Medicine and Sidney Kimmel Comprehensive Cancer Center,, Johns Hopkins University School of Medicine.
7
Department of Pathology, First Affiliated Hospital of Xi' an Jiaotong University.
8
Department of Surgery, Johns Hopkins University.
9
Surgery, Johns Hopkins Medicine.
10
Departments of Mechanical Engineering and Biomedical Engineering,, Whiting School of Engineering, Johns Hopkins University.
11
Oncology, The Johns Hopkins Univeristy.
12
Biostatistics and Bioinformatics, Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center.
13
Gastroenterology, Johns Hopkins University School of Medicine.
14
Gastroenterology and Hepatology, Johns Hopkins Hospital.
15
Biomedical Engineering, Johns Hopkins School of Medicine.
16
Division of Gastroenterology and Hepatology, Johns Hopkins University School of Medicine smeltzer@jhmi.edu.

Abstract

PURPOSE:

Barrett's esophagus (BE) is the only known precursor of esophageal adenocarcinoma (EAC). Although endoscopy and biopsy are standard methods for BE diagnosis, their high cost and risk limit their use as a screening modality. Here, we sought to develop a BE detection method based on methylation status in cytology samples captured by EsophaCap using a streamlined sensitive technique, methylation on beads (MOB).

EXPERIMENTAL DESIGN:

We conducted a prospective cohort study on 80 patients (52 in the training set; 28 in the test set). We employed MOB to extract and bisulfite-convert DNA, followed by qMSP to assess methylation levels of 8 previously selected candidate markers. Lasso regression was applied to establish a prediction model in the training set, which was then tested on the independent test set.

RESULTS:

In the training set, 5 of 8 candidate methylation biomarkers (p16, HPP1, NELL1, TAC1, and AKAP12) were significantly higher in BE patients than in controls. We built a 4-biomarker-plus-age lasso regression model for BE diagnosis. The AUC was 0.894, with sensitivity 94.4% (95% CI 71%~99%) and specificity 62.2% (95% CI 44.6%~77.3%) in the training set. This model also performed with high accuracy for BE diagnosis in an independent test set: AUC= 0.929 (P<0.001, 95% CI 0.810~1), with sensitivity = 78.6% (95% CI 48.8%~94.3%) and specificity = 92.8% (95% CI 64.1%~99.6%).

CONCLUSIONS:

EsophaCap, in combination with an epigenetic biomarker panel and the MOB method, is a promising, well-tolerated, low-cost esophageal sampling strategy for BE diagnosis. This approach merits further prospective studies in larger populations.

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