Background Better methods are needed to predict risk of progression for Barrett's esophagus (BE). We aimed to determine whether a tissue systems pathology approach could predict progression in patients with non-dysplastic BE, indefinite for dysplasia, or low-grade dysplasia. Methods We performed a nested case–control study to develop and validate a test that predicts progression of BE to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC), based upon quantification of epithelial and stromal variables in baseline biopsies. Data were collected from BE patients at 4 institutions. Patients who progressed to HGD or EAC in ≥1 year (n=79) were matched with patients who did not progress (n=287). Biopsies were assigned randomly to training or validation sets. Immunofluorescence analyses were performed for 14 biomarkers and quantitative biomarker and morphometric features were analyzed. Prognostic features were selected in the training set and combined into classifiers. The top-performing classifier was assessed in the validation set. Results A 3-tier, 15-feature classifier was selected in the training set and tested in the validation set. The classifier stratified patients into low-, intermediate- and high-risk classes (hazard ratio, 9.42; 95% confidence interval, 4.6–19.24 (high-risk vs low-risk); P<0.0001). It also provided independent prognostic information that outperformed predictions based on pathology analysis, segment length, age, sex, or p53 overexpression. Conclusion We developed a tissue systems pathology test that better predicts risk of progression in BE than clinicopathologic variables. Impact The test has the potential to improve upon histologic analysis as an objective method to risk stratify BE patients.

Background:Current histologic methods for diagnosis are limited by intra- and inter-observer variability. Immunohistochemistry (IHC) methods are frequently used to assess biomarkers to aid diagnoses, however, IHC staining is variable and nonlinear and the manual interpretation is subjective. Furthermore, the biomarkers assessed clinically are typically biomarkers of epithelial cell processes. Tumors and premalignant tissues are not composed only of epithelial cells but are interacting systems of multiple cell types, including various stromal cell types that are involved in cancer development. The complex network of the tissue system highlights the need for a systems biology approach to anatomic pathology, in which quantification of system processes is combined with informatics tools to produce actionable scores to aid clinical decision-making.Aims:Here, we describe a quantitative, multiplexed biomarker imaging approach termed TissueCypher™ that applies systems biology to anatomic pathology. Applications of TissueCypher™ in understanding the tissue system of Barrett's esophagus (BE) and the potential use as an adjunctive tool in the diagnosis of BE are described.Patients and Methods:The TissueCypher™ Image Analysis Platform was used to assess 14 epithelial and stromal biomarkers with known diagnostic significance in BE in a set of BE biopsies with nondysplastic BE with reactive atypia (RA, n = 22) and Barrett's with high-grade dysplasia (HGD, n = 17). Biomarker and morphology features were extracted and evaluated in the confirmed BE HGD cases versus the nondysplastic BE cases with RA.Results:Multiple image analysis features derived from epithelial and stromal biomarkers, including immune biomarkers and morphology, showed significant differences between HGD and RA.Conclusions:The assessment of epithelial cell abnormalities combined with an assessment of cellular changes in the lamina propria may serve as an adjunct to conventional pathology in the assessment of BE.

Background There is a need for improved tools to detect high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus (BE). In previous work, we demonstrated that a 3-tier classifier predicted risk of incident progression in BE. Our aim was to determine if this risk classifier could detect a field effect in non-dysplastic (ND), indefinite for dysplasia (IND) or low-grade dysplasia (LGD) biopsies from BE patients with prevalent HGD/EAC. Methods We performed a multi-institutional case-control study to evaluate a previously developed risk classifier that is based upon quantitative image features derived from 9 biomarkers and morphology, and predicts risk for HGD/EAC in BE patients. The risk classifier was evaluated in ND, IND and LGD biopsies from BE patients diagnosed with HGD/EAC on repeat endoscopy (prevalent cases, n=30, median time to HGD/EAC diagnosis 140.5 days) and non-progressors (controls, n=145, median HGD/EAC-free surveillance time 2,015 days). Results The risk classifier stratified prevalent cases and non-progressor patients into low-, intermediate- and high-risk classes (odds ratio, 46.0; 95% confidence interval, 14.86–169 (high-risk vs low-risk); p<0.0001). The classifier also provided independent prognostic information that outperformed the subspecialist and generalist diagnosis. Conclusion A tissue systems pathology test better predicts prevalent HGD/EAC in BE patients than pathologic variables. The results indicate that molecular and cellular changes associated with malignant transformation in BE may be detectable as a field effect using the test. Impact A tissue systems pathology test may provide an objective method to facilitate earlier identification of BE patients requiring therapeutic intervention.

<p>Table S1. 15 Image Analysis Features Utilized by the Risk Classifier Table S2. Performance of Risk Classes Predicted by Test vs. Pathologic Diagnosis in Stratifying BE Patients with Prevalent HGD/EAC from Non-Progressor BE Patients. Figure S1. Representative Whole Slide Scan and Image Analysis Masks.</p>

<div>Abstract<p><b>Background:</b> There is a need for improved tools to detect high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus. In previous work, we demonstrated that a 3-tier classifier predicted risk of incident progression in Barrett's esophagus. Our aim was to determine whether this risk classifier could detect a field effect in nondysplastic (ND), indefinite for dysplasia (IND), or low-grade dysplasia (LGD) biopsies from Barrett's esophagus patients with prevalent HGD/EAC.</p><p><b>Methods:</b> We performed a multi-institutional case–control study to evaluate a previously developed risk classifier that is based upon quantitative image features derived from 9 biomarkers and morphology, and predicts risk for HGD/EAC in Barrett's esophagus patients. The risk classifier was evaluated in ND, IND, and LGD biopsies from Barrett's esophagus patients diagnosed with HGD/EAC on repeat endoscopy (prevalent cases, <i>n</i> = 30, median time to HGD/EAC diagnosis 140.5 days) and nonprogressors (controls, <i>n</i> = 145, median HGD/EAC-free surveillance time 2,015 days).</p><p><b>Results:</b> The risk classifier stratified prevalent cases and non-progressor patients into low-, intermediate-, and high-risk classes [OR, 46.0; 95% confidence interval, 14.86-169 (high-risk vs. low-risk); <i>P</i> < 0.0001]. The classifier also provided independent prognostic information that outperformed the subspecialist and generalist diagnosis.</p><p><b>Conclusions:</b> A tissue systems pathology test better predicts prevalent HGD/EAC in Barrett's esophagus patients than pathologic variables. The results indicate that molecular and cellular changes associated with malignant transformation in Barrett's esophagus may be detectable as a field effect using the test.</p><p><b>Impact:</b> A tissue systems pathology test may provide an objective method to facilitate earlier identification of Barrett's esophagus patients requiring therapeutic intervention. <i>Cancer Epidemiol Biomarkers Prev; 26(2); 240–8. ©2016 AACR</i>.</p></div>