Rebecca J. Critchley-Thorne

A Tissue Systems Pathology Assay for High-Risk Barrett's Esophagus

Background: Better methods are needed to predict risk of progression for Barretts esophagus. We aimed to determine whether a tissue systems pathology approach could predict progression in patients with nondysplastic Barretts esophagus, 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 Barretts esophagus to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC), based upon quantification of epithelial and stromal variables in baseline biopsies. Data were collected from Barretts esophagus patients at four 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 [HR, 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 Barretts esophagus than clinicopathologic variables. Impact: The test has the potential to improve upon histologic analysis as an objective method to risk stratify Barretts esophagus patients. Cancer Epidemiol Biomarkers Prev; 25(6); 958–68. ©2016 AACR.

TissueCypher™: A systems biology approach to anatomic pathology

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 Barretts 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 Barretts 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.

A Tissue Systems Pathology Test Detects Abnormalities Associated with Prevalent High-Grade Dysplasia and Esophageal Cancer in Barrett's Esophagus

Background: There is a need for improved tools to detect high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barretts esophagus. In previous work, we demonstrated that a 3-tier classifier predicted risk of incident progression in Barretts 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 Barretts esophagus 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 Barretts esophagus patients. The risk classifier was evaluated in ND, IND, and LGD biopsies from Barretts esophagus patients diagnosed with HGD/EAC on repeat endoscopy (prevalent cases, n = 30, median time to HGD/EAC diagnosis 140.5 days) and nonprogressors (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 [OR, 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. Conclusions: A tissue systems pathology test better predicts prevalent HGD/EAC in Barretts esophagus patients than pathologic variables. The results indicate that molecular and cellular changes associated with malignant transformation in Barretts esophagus 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 Barretts esophagus patients requiring therapeutic intervention. Cancer Epidemiol Biomarkers Prev; 26(2); 240–8. ©2016 AACR.

High-throughput profiling of tissue and tissue model microarrays: Combined transmitted light and 3-color fluorescence digital pathology.

For many years pathologists have used Hematoxylin and Eosin (H&E), single marker immunohistochemistry (IHC) and in situ hybridization with manual analysis by microscopy or at best simple digital imaging. There is a growing trend to update pathology to a digital workflow to improve objectivity and productivity, as has been done in radiology. There is also a need for tissue-based multivariate biomarker assays to improve the accuracy of diagnostic, prognostic, and predictive testing. Multivariate tests are not compatible with the traditional single marker, manual analysis pathology methods but instead require a digital platform with brightfield and fluorescence imaging, quantitative image analysis, and informatics. Here we describe the use of the Hamamatsu NanoZoomer Digital Pathology slide scanner with HCImage software for combined brightfield and multiplexed fluorescence biomarker analysis and highlight its applications in biomarker research and pathology testing. This combined approach will be an important aid to pathologists in making critical diagnoses.