Preclinical activity of datopotamab deruxtecan, a novel TROP2 directed antibody-drug conjugate targeting trophoblast cell-surface antigen 2 (TROP2) in ovarian carcinoma

Introduction. Epithelial ovarian cancer (EOC) is associated with the highest gynecologic cancer mortality. The development of novel, effective combinations of targeted therapeutics remains an unmet medical need. We evaluated the preclinical activity of datopotamab deruxtecan (Dato-Dxd), a novel TROP2 targeting antibody drug conjugate (ADC) in ovarian cancer cell lines and xenografts with variable TROP2 expression. Methods. In vitro cell viability with Dato-DXd was assessed using flow-cytometry based assays against a panel of EOC primary cell lines with variable TROP2 expression. Fluorescent anti-phospho-histone H2A.X antibody was used to detect dsDNA breaks by flow-cytometry. The in vivo antitumor activity of Dato-DXd was tested in TROP2 overexpressing xenografts. Results. TROP2 overexpressing (3+) and moderate (2+) expressing EOC cell lines demonstrated higher sensitivity to Dato-DXd when compared to TROP2 negative tumors. Dato-DXd exposed TROP2+ EOC demonstrated increased dsDNA breaks and Annexin-V positivity (a marker of apoptosis) when compared to tumor cells exposed to the non-binding conjugate (p = 0.001 and p = 0.016, respectively). Dato-DXd induced significant antibody-dependent cellular cytotoxicity (ADCC) in the presence of peripheral-blood-lymphocytes. While negligible activity was detected against EOC cell lines with low TROP2 expression, Dato-DXd demonstrated significant bystander killing against tumor cells with low/negligible TROP2 when such cells were admixed with TROP2 3+ tumor cells in vitro. Dato-DXd showed tumor growth suppression against EOC cell line derived xenograft models that overexpress TROP2 at 3+ levels, prolonging survival when compared to controls, with minimal toxicity. Conclusion. Dato-DXd shows promising preclinical activity against TROP2 overexpressing ovarian cancers. Future clinical trials in ovarian cancer patients are warranted. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.