We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
LGC Clinical Diagnostics

Download Mobile App




AI-Powered Test Predicts Risk of Developing Esophageal Cancer in Patients with Barrett’s Esophagus

By LabMedica International staff writers
Posted on 16 May 2023
Print article
Image: TissueCypher is a risk-stratification test to predict future development of esophageal cancer in patients with BE (Photo courtesy of Castle Biosciences)
Image: TissueCypher is a risk-stratification test to predict future development of esophageal cancer in patients with BE (Photo courtesy of Castle Biosciences)

Barrett's esophagus (BE) is a serious consequence of gastroesophageal reflux disease (GERD) and presents a risk for the onset of esophageal cancer, one of the fastest-increasing cancers in terms of incidence in the U.S., exhibiting a less than 20% five-year survival rate. Effective interventions such as ablation therapy are typically applied to patients with higher grades of BE to prevent its progression to esophageal cancer. However, a substantial number of BE patients are classified with lower grades of BE or as non-dysplastic. Despite population-based predictions indicating a low cancer development probability for these lower-grade patients, they constitute the majority of patients who ultimately progress to esophageal cancer. This discrepancy indicates a significant clinical need for personalized, biologically based risk-stratification information to ensure a better alignment between progression risk and the application of effective interventions.

Castle Biosciences’ (Pittsburgh, PA, USA) TissueCypher Barrett’s Esophagus test is the world’s first precision medicine test that predicts the future development of esophageal cancer in patients with BE. The TissueCypher test provides medical professionals with vital information regarding an individual patient's risk of progression to esophageal cancer based on advanced analysis of biopsy samples, thus enabling better-informed, risk-aligned patient management. Its clinical effectiveness has been validated through nine peer-reviewed publications involving BE progressor patients across leading clinical centers worldwide.

The TissueCypher test is designed for use in patients with endoscopic biopsy-confirmed BE that is graded as non-dysplastic, indefinite for dysplasia, or low-grade dysplasia. Precise and accurate prediction of progression from BE to high-grade dysplasia or esophageal adenocarcinoma is crucial, given the rapidly growing incidence of esophageal cancer. Since esophageal adenocarcinoma is highly fatal once diagnosed, early detection and advanced warning provided by the TissueCypher test in BE patients can offer crucial clinical decision support for physicians treating these patients. Castle Biosciences was selected as the winner of the “Best Use of Artificial Intelligence in Healthcare” award in the seventh annual MedTech Breakthrough Awards program for its innovative TissueCypher Barrett’s Esophagus test.

“Most cancer diagnoses and associated risk-stratification estimates are currently made by pathologists viewing tissue on glass slides via light microscopy. This approach is limited in its ability to evaluate multiple biomarkers and cell types within the tumor system and predict future development of cancer,” said James Johnson, managing director, MedTech Breakthrough. “TissueCypher utilizes artificial intelligence to predict the risk of developing esophageal cancer – one of the world’s most deadly cancers. Congratulations to the Castle team on winning the ‘Best Use of Artificial Intelligence in Healthcare’ award in 2023.”

Related Links:
Castle Biosciences 

Gold Member
Fully Automated Cell Density/Viability Analyzer
BioProfile FAST CDV
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Hemoglobin/Haptoglobin Assay
IDK Hemoglobin/Haptoglobin Complex ELISA
New
Epstein-Barr Virus Test
Mononucleosis Rapid Test

Print article

Channels

Clinical Chemistry

view channel
Image: The GlycoLocate platform uses multi-omics and advanced computational biology algorithms to diagnose early-stage cancers (Photo courtesy of AOA Dx)

AI-Powered Blood Test Accurately Detects Ovarian Cancer

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths in women, largely due to late-stage diagnoses. Although over 90% of women exhibit symptoms in Stage I, only 20% are diagnosed in... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more

Industry

view channel
Image: The collaboration aims to leverage Oxford Nanopore\'s sequencing platform and Cepheid\'s GeneXpert system to advance the field of sequencing for infectious diseases (Photo courtesy of Cepheid)

Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions

Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.