Implementing an integrated molecular classification for gastric cancer from endoscopic biopsies using on-slide tests

Area of Science:

• Oncology
• Molecular Pathology
• Gastroenterology

Background:

• Effective biological therapies can improve gastric cancer (GC) outcomes, but personalized treatment access is limited.
• Molecular classification of GC aids in identifying patients for specific therapies and offers prognostic insights.
• Current molecular classification methods are not widely accessible to most patients.

Purpose of the Study:

• To propose and assess a working molecular classification for GC using readily available on-slide tests.
• To evaluate the feasibility of implementing this classification in routine histopathology laboratories.
• To demonstrate the potential of this classification in guiding personalized biological therapy selection for GC patients.

Main Methods:

• Utilized eight on-slide tests: in situ hybridization (ISH) for Epstein-Barr virus-encoded small ribonucleic acid (EBER) and immunohistochemistry (IHC) for MLH1, PMS2, MSH2, MSH6, E-cadherin, β-catenin, and p53.
• Classified GC into six molecular subtypes: GC-EBV, GC-dMMR, GC-EMT, GC-CIN, GC-GS, and GC-NOS/indeterminate.
• Incorporated three companion diagnostic (CDx) tests (Her2, PD-L1 22C3, CLDN18.2) for biological therapy selection.

Main Results:

• Demonstrated the feasibility of a molecular classification system using on-slide tests in histopathology labs.
• Showcased the classification's applicability on small endoscopic biopsies of gastric and gastroesophageal junction adenocarcinoma.
• Indicated minimal impact on laboratory turnaround times and capacity with this classification system.

Conclusions:

• A practical molecular classification for GC can be implemented in routine diagnostic workflows.
• Widespread adoption of this classification can refine prognosis and guide appropriate biological therapy selection.
• This approach enhances personalized treatment strategies for gastric cancer patients.