Human Epidermal Growth Factor Receptor 2 Quantification Using Computational Pathology to Identify Novel Biomarkers for Trastuzumab Deruxtecan-Treated Human Epidermal Growth Factor Receptor 2-Positive Gastric Cancer.

Abstract

PURPOSE: Trastuzumab deruxtecan (T-DXd) is an antibody-drug conjugate approved for human epidermal growth factor receptor 2 (HER2)-positive gastric cancer (GC) and gastroesophageal junction adenocarcinoma (GEJA). Eligibility for T-DXd therapy currently relies on conventional HER2 immunohistochemistry (IHC) scoring per ASCO/CAP guidelines. Computational pathology tools such as quantitative continuous scoring (QCS) offer precise quantification of HER2 expression, enabling improved scores reflective of T-DXd's mechanism of action. METHODS: We used HER2-QCS scoring to identify biomarker signatures in the DESTINY-Gastric01 cohort, with external validation in DESTINY-Gastric02. RESULTS: QCS-derived continuous spatial proximity score (cSPS) and density of HER2-positive cells in tumor epithelium (DPC) displayed significant survival benefits for biomarker-positive versus biomarker-negative patients in the DESTINY-Gastric01 T-DXd arm (Cox regression: P < .0001). These signatures were validated in the DESTINY-Gastric02 cohort (log-rank P < .0001). CONCLUSION: Our findings indicate that cSPS and DPC are predictive of T-DXd clinical outcomes, supporting the potential future use of QCS as a quantitative approach to identify patients with GC who might benefit most from T-DXd therapy.