TissueCypher(™): A systems biology approach to anatomic pathology

The Tissue Systems Pathology Test Objectively Risk-Stratifies Patients With Barrett's Esophagus: Results From a Multicenter US Clinical Experience Study

BACKGROUND

Barrett's esophagus (BE) is a diagnosis of esophageal intestinal metaplasia, which can progress to esophageal adenocarcinoma (EAC), and guidelines recommend endoscopic surveillance for early detection and treatment of EAC. However, current practices have limited effectiveness in risk-stratifying patients with BE.

AIM

This study aimed to evaluate use of the TSP-9 test in risk-stratifying clinically relevant subsets of patients with BE in clinical practice.

METHODS

TSP-9 results for tests ordered by 891 physicians for 8080 patients with BE with clinicopathologic data were evaluated. Orders were from nonacademic (94.3%) and academic (5.7%) settings for nondysplastic BE (NDBE; n=7586; 93.9%), indefinite for dysplasia (IND, n=312, 3.9%), and low-grade dysplasia (LGD, n=182, 2.3%).

RESULTS

The TSP-9 test scored 83.2% of patients with low risk, 10.6% intermediate risk, and 6.2% high risk, respectively, for progression to HGD/EAC within 5 years. TSP-9 provided significant risk-stratification independently of clinicopathologic features, within NDBE, IND, and LGD subsets, male and female, and short- and long-segment subsets of patients. TSP-9 identified 15.3% of patients with NDBE as intermediate/high-risk for progression, which was 6.4 times more than patients with a pathology diagnosis of LGD. Patients with NDBE who scored intermediate or high risk had a predicted 5-year progression risk of 8.1% and 15.3%, respectively, which are similar to and higher than published progression rates in patients with BE with confirmed LGD.

CONCLUSIONS

The TSP-9 test identified a high-risk subset of patients with NDBE who were predicted to progress at a higher rate than confirmed LGD, enabling early detection of patients requiring management escalation to reduce the incidence of EAC. TSP-9 scored the majority of patients with NDBE as low risk, providing support to adhere to 3- to 5-year surveillance per guidelines.

The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update

Significant advances in artificial intelligence (AI) over the past decade potentially may lead to dramatic effects on clinical practice. Digitized histology represents an area ripe for AI implementation. We describe several current needs within the world of gastrointestinal histopathology, and outline, using currently studied models, how AI potentially can address them. We also highlight pitfalls as AI makes inroads into clinical practice.

Advances in Screening for Barrett Esophagus and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC), the primary form of esophageal cancer in the United States, is a lethal cancer with exponentially increasing incidence. Screening for Barrett esophagus (BE), the only known precursor to EAC, followed by endoscopic surveillance to detect dysplasia and early-stage EAC and subsequent endoscopic treatment (to prevent progression of dysplasia to EAC and to treat early-stage EAC effectively) is recommended by several society guidelines. Sedated endoscopy (the primary current tool for BE screening) is both invasive and expensive, limiting its widespread use. In this review, we aim to provide a comprehensive review of recent innovations in the nonendoscopic detection of BE and EAC. These include swallowable cell sampling devices combined with protein and epigenetic biomarkers (which are now guideline endorsed as alternatives to sedated endoscopy), tethered capsule endomicroscopy, emerging peripheral blood-sampled molecular biomarkers, and exhaled volatile organic compounds. We also summarize progress and challenges in assessing BE and EAC risk, which is an important complementary component of the process for the clinical implementation of these innovative nonendoscopic tools, and propose a new paradigm for the strategy to reduce EAC incidence and mortality.

An Automated Tissue Systems Pathology Test Can Standardize the Management and Improve Health Outcomes for Patients With Barrett's Esophagus

INTRODUCTION

Low-grade dysplasia (LGD) in Barrett's esophagus (BE) is associated with an increased risk of progression to high-grade dysplasia or esophageal adenocarcinoma. However, because of substantial interobserver variability in the diagnosis of LGD, a patient's management plan and health outcome depend largely on which pathologist reviews their case. This study evaluated the ability of a tissue systems pathology test that objectively risk stratifies patients with BE (TissueCypher, TSP-9) to standardize management in a manner consistent with improved health outcomes for patients with BE.

METHODS

A total of 154 patients with BE with community-based LGD from the prospectively followed screening cohort of the SURF trial were studied. Management decisions were simulated 500 times with varying generalist (n = 16) and expert (n = 14) pathology reviewers to determine the most likely care plan with or without use of the TSP-9 test for guidance. The percentage of patients receiving appropriate management based on the known progression/nonprogression outcomes was calculated.

RESULTS

The percentage of patients with 100% of simulations resulting in appropriate management significantly increased from 9.1% for pathology alone, to 58.4% when TSP-9 results were used with pathology, and further increased to 77.3% of patients receiving appropriate management when only TSP-9 results were used. Use of the test results also significantly increased the consistency of management decisions for patients when their slides were reviewed by different pathologists ( P < 0.0001).

DISCUSSION

Management guided by the TSP-9 test can standardize care plans by increasing the early detection of progressors who can receive therapeutic interventions, while also increasing the percentage of nonprogressors who can avoid unnecessary therapy and be managed by surveillance alone.

The Tissue Systems Pathology Test Outperforms Pathology Review in Risk Stratifying Patients With Low-Grade Dysplasia

BACKGROUND & AIMS

Low-grade dysplasia (LGD) is associated with an increased risk of progression in Barrett's esophagus (BE); however, the diagnosis of LGD is limited by substantial interobserver variability. Multiple studies have shown that an objective tissue systems pathology test (TissueCypher Barrett's Esophagus Test, TSP-9), can effectively predict neoplastic progression in patients with BE. This study aimed to compare the risk stratification performance of the TSP-9 test vs benchmarks of generalist and expert pathology.

METHODS

A blinded cohort study was conducted in the screening cohort of a randomized controlled trial of patients with BE with community-based LGD. Biopsies from the first endoscopy with LGD were assessed by the TSP-9 test and independently reviewed by 30 pathologists from 5 countries per standard practice. The accuracy of the test and the diagnoses in predicting high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) were compared.

RESULTS

A total of 154 patients with BE (122 men), mean age 60.9 ± 9.8 years were studied. Twenty-four patients progressed to HGD/EAC within 5 years (median time of 1.7 years) and 130 did not progress to HGD/EAC within 5 years (median 7.8 years follow-up). The TSP-9 test demonstrated higher sensitivity (71% vs mean 63%, range 33%-88% across 30 pathologists), than the pathology review in detecting patients who progressed (P = .01186).

CONCLUSIONS

The TSP-9 test outperformed the pathologists in risk stratifying patients with BE with LGD. Care guided by the test can provide an effective solution to variable pathology review of LGD, improving health outcomes by upstaging care to therapeutic intervention for patients at high risk for progression, while reducing unnecessary interventions in low-risk patients.

Management of Post Ablative Barrett's Esophagus: a Review of Current Practices and Look at Emerging Technologies

Purpose of review

Endoscopic eradication therapy is an effective and durable treatment for Barrett's esophagus (BE) related neoplasia, but even after achieving successful eradication, these patients remain at risk for recurrence and require ongoing routine examinations. The optimal surveillance protocol including endoscopic technique, sampling strategy, and timing are still being refined. The aim of this review is to discuss current management principles for the post ablation patient and emerging technologies to guide clinical practice.

Recent findings

There is increasing evidence to support less frequent surveillance exams in the first year after complete eradication of intestinal metaplasia and a move towards targeted biopsies of visible lesions and sampling high-risk locations such as the gastroesophageal junction. Promising technologies on the horizon that could impact management include novel biomarkers, personalized surveillance intervals, and non-endoscopic approaches.

Summary

Ongoing high-quality examinations after endoscopic eradication therapy are key to limiting recurrent BE. Surveillance intervals should be based on the pretreatment grade of dysplasia. Future research should focus on technologies and surveillance practices that are most efficient for patients and the healthcare system.

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

BACKGROUND & AIMS

Prediction of progression risk in Barrett's esophagus (BE) may enable personalized management. We aimed to assess the adjunct value of a tissue systems pathology test (TissueCypher) performed on paraffin-embedded biopsy tissue, when added to expert pathology review in predicting incident progression, pooling individual patient-level data from multiple international studies METHODS: Demographics, clinical features, the TissueCypher risk class/score, and progression status were analyzed. Conditional logistical regression analysis was used to develop multivariable models predicting incident progression with and without the TissueCypher risk class (low, intermediate, high). Concordance (c-) statistics were calculated and compared with likelihood ratio tests to assess predictive ability of models. A risk prediction calculator integrating clinical variables and TissueCypher risk class was also developed.

RESULTS

Data from 552 patients with baseline no (n = 472), indefinite (n = 32), or low-grade dysplasia (n = 48) (comprising 152 incident progressors and 400 non-progressors) were analyzed. A high-risk test class independently predicted increased risk of progression to high-grade dysplasia/adenocarcinoma (odds ratio, 6.0; 95% confidence interval, 2.9-12.0), along with expert confirmed low-grade dysplasia (odds ratio, 2.9; 95% confidence interval, 1.2-7.2). Model prediction of progression with the TissueCypher risk class incorporated was significantly superior than without, in the whole cohort (c-statistic 0.75 vs 0.68; P < .0001) and the nondysplastic BE subset (c-statistic 0.72 vs 0.63; P < .0001). Sensitivity and specificity of the high risk TissueCypher class were 38% and 94%, respectively.

CONCLUSIONS

An objective tissue systems pathology test high-risk class is a strong independent predictor of incident progression in patients with BE, substantially improving progression risk prediction over clinical variables alone. Although test specificity was high, sensitivity was modest.

Diagnosis and Management of Barrett's Esophagus: An Updated ACG Guideline

Barrett's esophagus (BE) is a common condition associated with chronic gastroesophageal reflux disease. BE is the only known precursor to esophageal adenocarcinoma, a highly lethal cancer with an increasing incidence over the last 5 decades. These revised guidelines implement Grading of Recommendations, Assessment, Development, and Evaluation methodology to propose recommendations for the definition and diagnosis of BE, screening for BE and esophageal adenocarcinoma, surveillance of patients with known BE, and the medical and endoscopic treatment of BE and its associated early neoplasia. Important changes since the previous iteration of this guideline include a broadening of acceptable screening modalities for BE to include nonendoscopic methods, liberalized intervals for surveillance of short-segment BE, and volume criteria for endoscopic therapy centers for BE. We recommend endoscopic eradication therapy for patients with BE and high-grade dysplasia and those with BE and low-grade dysplasia. We propose structured surveillance intervals for patients with dysplastic BE after successful ablation based on the baseline degree of dysplasia. We could not make recommendations regarding chemoprevention or use of biomarkers in routine practice due to insufficient data.

Utility of ancillary studies in the diagnosis and risk assessment of Barrett's esophagus and dysplasia

Barrett's esophagus (BE) is a major risk factor for the development of esophageal adenocarcinoma (EAC). BE patients undergo periodic endoscopic surveillance with biopsies to detect dysplasia and EAC, but this strategy is imperfect owing to sampling error and inconsistencies in the diagnosis and grading of dysplasia, which may result in an inaccurate diagnosis or risk assessment for progression to EAC. The desire for more accurate diagnosis and better risk stratification has prompted the investigation and development of potential biomarkers that might assist pathologists and clinicians in the management of BE patients, allowing more aggressive endoscopic surveillance and treatment options to be targeted to high-risk individuals, while avoiding frequent surveillance or unnecessary interventions in those at lower risk. It is known that progression of BE to dysplasia and EAC is accompanied by a host of genetic alterations, and that exploration of these markers could be potentially useful to diagnose/grade dysplasia and/or to risk stratify BE patients. Several biomarkers have shown promise in identifying early neoplastic transformation and thus may be useful adjuncts to histologic evaluation. This review provides an overview of some of the currently available biomarkers and assays, including p53 immunostaining, Wide Area Transepithelial Sampling with Three-Dimensional Computer-Assisted Analysis (WATS^3D), TissueCypher, mutational load analysis (BarreGen), fluorescence in situ hybridization, and DNA content abnormalities as detected by DNA flow cytometry.

Independent Validation of a Tissue Systems Pathology Assay to Predict Future Progression in Nondysplastic Barrett's Esophagus: A Spatial-Temporal Analysis

An automated risk prediction assay has previously been shown to objectively identify patients with nondysplastic Barrett's esophagus (NDBE) who are at increased risk of malignant progression. To evaluate the predictive performance of the assay in 76 patients with NDBE of which 38 progressed to high-grade dysplasia/esophageal adenocarcinoma (progressors) and 38 did not (nonprogressors) and to determine whether assessment of additional (spatial) levels per endoscopy and/or multiple (temporal) time points improves assay performance.

Tissue Systems Pathology Test Objectively Risk Stratifies Barrett's Esophagus Patients With Low-Grade Dysplasia

INTRODUCTION

Low-grade dysplasia (LGD) is the best predictor of neoplastic progression in Barrett's esophagus (BE). Most LGD cases are downstaged to nondysplastic (ND) BE on expert pathologist review, which is prone to interobserver variation and not widely available. Recent studies indicate that a risk prediction assay (TissueCypher) risk stratifies patients with NDBE for neoplastic progression. We aimed to investigate whether this risk prediction assay predicts neoplastic progression in BE patients with LGD.

METHODS

A blinded, retrospective cohort study was derived from the screening cohort of a randomized controlled trial of SURveillance vs RadioFrequency ablation for BE patients with LGD. Hematoxylin and eosin and p53 immunohistochemistry slides from the first endoscopy with LGD were independently reviewed by 3 expert pathologists and tested by the risk prediction assay. Revision diagnoses of NDBE were considered low risk, although indefinite for dysplasia, and LGD were considered high risk for progression.

RESULTS

A total of 155 BE patients (123 men), mean age 61 ± 10 years, were analyzed. Thirty-four patients (22%) progressed to high-grade dysplasia/esophageal adenocarcinoma (median time 2.4 years) and 121 did not progress (median high-grade dysplasia/esophageal adenocarcinoma-free surveillance 7.9 years). The risk prediction assay sensitivity was 68% vs 76% for the 3 pathologists, and specificity was 79% vs 64%-77.0% for the pathologists. The assay detected 50%-56% of progressors that were downstaged to NDBE by the pathologists.

DISCUSSION

The risk prediction assay provided significant risk stratification in BE patients with LGD and identified progressors that the experts downstaged to NDBE. This objective assay provides an effective solution to the lack of standardization of expert pathology review of LGD.

TissueCypher Barrett's esophagus assay impacts clinical decisions in the management of patients with Barrett's esophagus

Background and study aims  The TissueCypher Barrett's Esophagus Assay is a novel tissue biomarker test, and has been validated to predict progression to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus (BE). The aim of this study was to evaluate the impact of TissueCypher on clinical decision-making in the management of BE. Patients and methods  TissueCypher was ordered for 60 patients with non-dysplastic (ND, n = 18) BE, indefinite for dysplasia (IND, n = 25), and low-grade dysplasia (LGD, n = 17). TissueCypher reports a risk class (low, intermediate or high) for progression to HGD or EAC within 5 years. The impact of the test results on BE management decisions was assessed. Results  Fifty-two of 60 patients were male, mean age 65.2 ± 11.8, and 43 of 60 had long segment BE. TissueCypher results impacted 55.0 % of management decisions. In 21.7 % of patients, the test upstaged the management approach, resulting in endoscopic eradication therapy (EET) or shorter surveillance interval. The test downstaged the management approach in 33.4 % of patients, leading to surveillance rather than EET. In the subset of patients whose management plan was changed, upstaging was associated with a high-risk TissueCypher result, and downstaging was associated with a low-risk result ( P  < 0.0001). Conclusions  TissueCypher was used as an adjunct to support a surveillance-only approach in 33.4 % of patients. Upstaging occurred in 21.7 % of patients, leading to therapeutic intervention or increased surveillance. These results indicate that the TissueCypher test may enable physicians to target EET for TissueCypher high-risk BE patients, while reducing unnecessary procedures in TissueCypher low-risk patients.

Independent Blinded Validation of a Tissue Systems Pathology Test to Predict Progression in Patients With Barrett's Esophagus

INTRODUCTION

A risk prediction test was previously validated to predict progression to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus (BE). The aim of our study was to independently validate this test to predict the risk of progression to HGD/EAC in BE patients with nondysplastic (ND), indefinite for dysplasia and low-grade dysplasia (LGD).

METHODS

A single-blinded, case-control study was conducted to stratify patients with BE as low, intermediate, or high risk for progression to HGD/EAC within 5 years using a previously described risk prediction test. Patients with BE who progressed to HGD/EAC after at least 1 year (n = 58) were matched to patients undergoing surveillance without progression (n = 210, median surveillance 7 years). Baseline biopsies with subspecialist diagnoses of ND, indefinite for dysplasia, or LGD were tested in a blinded manner, and the predictive performance of the test was assessed.

RESULTS

This risk prediction test stratified patients with BE based on progression risk with the high-risk group at 4.7-fold increased risk for HGD/EAC compared with the low-risk group (95% confidence interval 2.5-8.8, P < 0.0001). Prevalence-adjusted positive predictive value at 5 years was 23%. The high-risk class and male sex provided predictive power that was independent of pathologic diagnosis, age, segment length, and hiatal hernia. Patients with ND BE who scored high risk progressed at a higher rate (26%) than patients with subspecialist-confirmed LGD (21.8%) at 5 years.

DISCUSSION

A risk prediction test identifies patients with ND BE who are at high risk for progression to HGD/EAC and may benefit from early endoscopic therapy or increased surveillance.

Radiofrequency Ablation of Barrett's Esophagus: Have We Gone Too Far, or Not Far Enough?

PURPOSE OF REVIEW

Barrett's esophagus (BE) is a premalignant condition of the esophagus associated with an increased risk for esophageal adenocarcinoma (EAC). Radiofrequency ablation (RFA) is a safe and effective first-line treatment for dysplastic BE and early stage EAC. This report reviews clinically relevant evidence published over the last 3 years regarding RFA for BE.

RECENT FINDINGS

Our use of this technology has simultaneously gone too far, in that many patients who may not derive a benefit from these treatments are receiving them, and not far enough, in that many patients who would be eligible for ablative therapy never undergo screening exams to assess them for dysplastic BE, or do not have endoscopic therapy considered part of the treatment of superficial invasive cancer. Research to better identify patients with BE, risk stratify those patients, improve the quality of RFA treatment, and inform surveillance practices has the potential to optimize the benefit of RFA, and minimize the harms, costs, and risks.

A Cost-Effectiveness Analysis Of An Adenocarcinoma Risk Prediction Multi-Biomarker Assay For Patients With Barrett's Esophagus

Purpose

This study evaluates the cost-effectiveness of a quantitative multi-biomarker assay (the Assay) that stratifies patients with Barrett’s Esophagus (BE) by risk of progression to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC) and can be used to guide clinical decisions, versus the current guidelines (standard of care [SOC]) for surveillance and treatment of BE.

Patients and methods

Markov decision modeling and simulation were used to compare cost and quality-adjusted life-years (QALYs) from the perspective of a US health insurer with care delivered by an integrated health system. Model assumptions and disease progression probabilities were derived from the literature. Performance metrics for the Assay were from an independent clinical validation study. Cost of the Assay was based on reimbursement rates from multiple payers. Other costs were derived from Geisinger payment data.

Results

Base-case model results for a 5-year period comparing the Assay-directed care to the SOC estimated an incremental cost-effectiveness ratio (ICER) of $52,483/QALY in 2012 US dollars. Assay-directed care increased the use of endoscopic treatments by 58.4%, which reduced the progression to HGD, EAC and reduced EAC-related deaths by 51.7%, 47.1%, and 37.6%, respectively, over the 5-year period. Sensitivity analysis indicated that the probability of the Assay being cost-effective compared to the SOC was 57.3% at the $100,000/QALY acceptability threshold.

Conclusion

Given the model assumptions, the new Assay would be cost-effective after 5 years and improves patient outcomes due to improvement in the effectiveness of surveillance and treatment protocols resulting in fewer patients progressing to HGD and EAC and fewer EAC-related deaths.

Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections

Background

Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis followed by machine learning to identify vascular endothelial growth factor (VEGF) in kidney tissue that had been subjected to hypoxia.

Methods

Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF⁺ and VEGF⁻ cells.

Results

VEGF was detected and cells were counted with high sensitivity and specificity.

Conclusion

With great clinical, diagnostic, and research potential, automatic image analysis offers a new quantitative capability, thereby adding numerical information to a mostly qualitative diagnostic approach.

Barrett's Esophagus and Esophageal Carcinoma: Can Biomarkers Guide Clinical Practice?

PURPOSE OF REVIEW

Despite gastrointestinal societal recommendations for endoscopic screening and surveillance of Barrett's esophagus, the rates of esophageal adenocarcinoma continue to rise. Furthermore, this current practice is costly to patients and the medical system without clear evidence of reduction in cancer mortality. The use of biomarkers to guide screening, surveillance, and treatment strategies might alleviate some of these issues.

RECENT FINDINGS

Incredible advances in biomarker identification, biomarker assays, and minimally-invasive modalities to acquire biomarkers have shown promising results. We will highlight recently published, key studies demonstrating where we are with using biomarkers for screening and surveillance in clinical practice, and what is on the horizon regarding novel non-invasive and minimally invasive methods to acquire biomarkers. Proof-of principle studies using in silico models demonstrate that biomarker-guided screening, surveillance, and therapeutic intervention strategies can be cost-effective and can reduce cancer deaths in patients with Barrett's esophagus.

2017 David Sun Lecture: Screening and Surveillance of Barrett's Esophagus: Where Are We Now and What Does the Future Hold?

Barrett's esophagus and esophageal adenocarcinoma continue to present considerable management challenges in the Western world. Despite our best efforts to date, the prognosis of advanced esophageal adenocarcinoma remains poor and far too many individuals with esophageal adenocarcinoma have not had a prior endoscopy to detect Barrett's esophagus. As such, current strategies of screening for Barrett's esophagus and subsequent surveillance need to be further optimized. Screening today is limited to high definition white light endoscopy in high-risk patient populations and as such has multiple limitations. However, a variety of exciting new techniques including risk prediction tools, tethered capsule endomicroscopy, a cytology sponge, breath testing for exhaled volatile organic compounds, and assessment of the oral microbiome are now under study in an effort to develop less expensive population-based screening methods. Similarly, endoscopic surveillance, as currently practiced has a variety of limitations. Inexpensive readily available adjuncts are already available to optimize surveillance including increased inspection time in an effort to detect mucosal or vascular abnormalities, special attention to the right hemisphere of the esophagus, and utilization of narrow band imaging or other electronic chromoendoscopy techniques. To improve endoscopic surveillance, a variety of new paradigms are under study including wide area trans-epithelial sampling, advanced endoscopic imaging, molecular imaging, clinical risk stratification and utilization of biomarkers of increased risk. However, progress will be challenging due to the complexity of esophageal cancer biology and the rarity of progression to cancer among patients with nondysplastic Barrett's epithelium.

Precision care for Barrett's esophagus

Modern recognition and management of Barrett's esophagus, a precursor to esophageal adenocarcinoma depends on diagnostic accuracy, risk assessment, technical expertise and consideration of many options to best tailor therapy for every patient. Concomitant management of acid reflux is essential, frequently with proton pump inhibitors. Ablation and resection favorably affect the evolution towards cancer. Using precision medicine tools, such as imaging, molecular diagnostics and analytics may lead to cost- and comparatively-effective therapies ultimately aiming at cancer prevention. Knowledge of the risk factors for Barrett's esophagus and progression to dysplasia and cancer can help tailor a precision medicine approach with more aggressive screening and surveillance targeted at patients that are most likely to benefit.

Systems Biology Approaches in Cancer Pathology

The complex network of the tissue system, in both pre-neoplastic tissues and tumors, demonstrates the need for a systems biology approach to cancer pathology, in which quantification of key tissue system processes is combined with informatics tools to produce actionable scores to aid clinical decision-making. A systems biology approach to cancer pathology enables integration of key system features that are relevant to diagnoses, patient outcomes, and responses to therapies. Key tissue system features relevant to cancer pathology include molecular and morphologic abnormalities in epithelia, cellular changes in the stroma such as immune infiltrates, and relationships between components of the system, such as interactions and spatial relationships between epithelial and stromal components, and also between specific immune cell subsets. Here, we describe a method for objective quantification of multiple epithelial and stromal biomarkers in the context of tissue architecture to generate a high dimensional tissue profile that can be used to build multivariable predictive models for cancer pathology.

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.

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 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.

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 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, 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 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.

IMPACT

A tissue systems pathology test may provide an objective method to facilitate earlier identification of Barrett's esophagus patients requiring therapeutic intervention. Cancer Epidemiol Biomarkers Prev; 26(2); 240-8. ©2016 AACR.

Biologically Relevant Heterogeneity: Metrics and Practical Insights

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue

OBJECTIVE

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation.

METHODS

A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software.

RESULTS

Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively.

CONCLUSION

Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies.

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

BACKGROUND

Better methods are needed to predict risk of progression for Barrett's esophagus. We aimed to determine whether a tissue systems pathology approach could predict progression in patients with nondysplastic Barrett's 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 Barrett's 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 Barrett's 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 Barrett's esophagus than clinicopathologic variables.

IMPACT

The test has the potential to improve upon histologic analysis as an objective method to risk stratify Barrett's esophagus patients. Cancer Epidemiol Biomarkers Prev; 25(6); 958-68. ©2016 AACR.