A genomic biomarker-based model for cancer risk stratification of non-dysplastic Barrett’s esophagus patients after extended follow up; results from Dutch surveillance cohorts.

Abstract

Barrett's esophagus is the only known mucosal precursor for the highly malignant esophageal adenocarcinoma. Malignant degeneration of non-dysplastic Barrett's esophagus occurs in < 0.6% per year in Dutch surveillance cohorts. Therefore, it has been proposed to increase the surveillance intervals from 3 to 5 years, potentially increasing development of advanced stage interval cancers. To prevent such cases robust biomarkers for more optimal stratification over longer follow up periods for non-dysplastic Barrett's patients are required. In this multi-center study, aberrations for chromosomes 7, 17, and structural abnormalities for c-MYC, CDKN2A, TP53, Her-2/neu and 20q assessed by DNA fluorescence in situ hybridization on brush cytology specimens, were used to determine marker scores and to perform clonal diversity measurements, as described previously. In this study, these genetic biomarkers were combined with clinical variables and analyzed to obtain the most efficient cancer prediction model after an extended period of follow-up (median time of 7 years) by applying Cox regression modeling, bootstrapping and leave-one-out analyses. A total of 334 patients with Barrett's esophagus without dysplasia from 6 community hospitals (n = 220) and one academic center (n = 114) were included. The annual progression rate to high grade dysplasia and/or esophageal adenocarcinoma was 1.3%, and to adenocarcinoma alone 0.85%. A prediction model including age, Barrett circumferential length, and a clonicity score over the genomic set including chromosomes 7, 17, 20q and c-MYC, resulted in an area under the curve of 0.88. The sensitivity and specificity of this model were 0.91 and 0.38. The positive and negative predictive values were 0.13 (95% CI 0.09 to 0.19) and 0.97 (95% CI 0.93 to 0.99). We propose the implementation of the model to identify non-dysplastic Barrett's patients, who are required to remain in surveillance programs with 3-yearly surveillance intervals from those that can benefit from less frequent or no surveillance.

Prediction of Progression in Barrett’s Esophagus Using a Tissue Systems Pathology Test: A Pooled Analysis of International Multicenter Studies

“…15 A Dutch group assessed fluorescence in situ hybridization biomarkers, in a prospective cohort of 428 patients with 22 progressors, reporting a sensitivity of 86% and a specificity of 54%. 16 Other investigators have used polymerase chain reaction-based technology and next-generation sequencing to discover promising biomarkers. 8,17 Challenges with some technologies include the need for fresh frozen tissue or endoscopic brushings, lack of independent validation beyond the initial study describing the markers (falling in the Early Detection Research Network phase 2, retrospective phase 3 categories), 18 and challenges with scaling assay technology.…”

Somatic whole genome dynamics of precancer in Barrett’s Esophagus

“…The importance of TP53 alterations to ESAD progression risk has been well established 9,18,33,45 A current goal of clinical management of BE is to incorporate somatic genomic-based cancer risk stratification to guide intervention strategies 11,24,[58][59][60] .The substantial spatial clonal heterogeneity observed in CO patients, with some biopsies indistinguishable from typical NCO biopsies, indicate a need for a multi-sample approach to early cancer detection or to ensure accurate ESAD risk assessment. Our finding of multi-clonal origins for the expanded BE segment in both CO and NCO based on levels of trunk mutations, as well as single-clonal origins, reflects this clonal heterogeneity occurring early during establishment of the BE segment.…”

AGA Clinical Practice Update on New Technology and Innovation for Surveillance and Screening in Barrett’s Esophagus: Expert Review

“…41 Other nonvalidated models using clinical variables have included the presence of esophagitis, lack of PPI use, being overweight, increasing age, and a known duration of BE of 10 years. [42][43][44][45][46] The panelists noted that several additional models were currently in development and noted that models incorporating both clinical and biomarker parameters would likely ultimately be needed to optimize predictive accuracy.…”