INTRODUCTION: We sought to develop a minimally invasive, robust, accessible nonendoscopic strategy to diagnose Barrett's esophagus (BE), esophageal adenocarcinoma (EAC), and its immediate precursor lesion, high-grade dysplasia (HGD) based on methylated DNA biomarkers applied to a retrievable sponge-capsule device in a cohort representative of the BE population (i.e., mostly short-segment, nondysplastic BE [NDBE]). METHODS: We identified 12 candidate methylation markers to distinguish normal vs abnormal esophagus. These 12 markers were first assayed in 21-paired matched NDBE-normal esophageal tissues, then assessed in a case-control study of 234 esophageal samples collected using a sponge-capsule device. A classification algorithm was developed using the least absolute shrinkage and selection operator in a 199-patient training set and tested in an independent 35-patient test set. RESULTS: Twelve markers ( A1BG , C9orf50 , cg00720137 , FLI1 , GRAMD1B , HOXB13 , IRF4 , KCNQ3 , NTNG1 , SPX , TBC1D30 , and USP44 ) were significantly hypermethylated (i.e., all P <
  0.05) in BE vs matched normal esophageal biopsies. A discriminatory 3-gene least absolute shrinkage and selection operator panel ( USP44 , TBC1D30 , and NELL1 ), adjusted for age and sex, accurately distinguished HGD or EAC from normal control patients in both training (area under the receiver operating characteristic curve [AUC] 0.911, 95% confidence interval [CI] 0.863-0.959) and test (AUC 0.969, 95% CI 0.911-1.00) sets. In normal vs NDBE/LGD/HGD/EAC patients, this algorithm exhibited AUCs of 0.862 (95% CI 0.812-0.912) and 0.864 (95% CI 0.745-0.982) in training and test sets, respectively. In normal vs NDBE patients, the algorithm yielded AUCs of 0.819 (95% CI 0.748-0.889) and 0.776 (95% CI 0.583-0.968) in training and test sets, respectively. DISCUSSION: This discriminatory biomarker panel algorithm exemplifies a practical nonendoscopic strategy to diagnose BE, HGD, and EAC using a minimally invasive sponge-capsule device coupled with DNA methylation markers.
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