Investigation of factors affecting the efficacy of 3C23K, a human monoclonal antibody targeting MISIIR
Metrics: PDF 1173 views | HTML 2409 views | ?
Sarah E. Gill1, Qing Zhang1, Gary L. Keeney2, William A. Cliby1 and S. John Weroha3
1Department of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota, USA
2Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
3Department of Medical Oncology, Mayo Clinic, Rochester, Minnesota, USA
S. John Weroha, email: [email protected]
Keywords: 3C23K, mullerian inhibiting substance receptor, ovarian cancer, targeted therapy, patient-derived xenograft
Received: December 14, 2016 Accepted: July 03, 2017 Published: July 27, 2017
MISIIR is a potential target for ovarian cancer (OC) therapy due to its tissue-specific pattern of expression. 3C23K is a novel therapeutic monoclonal anti-MISIIR antibody designed to recruit effector cells and promote cell death through ADCC (antibody dependent cell-mediated cytotoxicity). Our objective was to determine the tolerability and efficacy of 3C23K in OC patient-derived xenografts (PDX) and to identify factors affecting efficacy. Quantitative RT-PCR, immunohistochemistry (IHC), and flow cytometry were used to categorize MISIIR expression in established PDX models derived from primary OC patients. We selected two high expressing models and two low expressing models for in vivo testing. One xenograft model using an MISIIR over-expressing SKOV3ip cell line (Z3) was a positive control. The primary endpoint was change in tumor size. The secondary endpoint was final tumor mass. We observed no statistically significant differences between control and treated animals. The lack of response could be secondary to a number of variables including the lack of known biomarkers of response, the low membrane expression of MISIIR, and a limited ability of 3C23K to induce ADCC in PDX models. Further study is needed to determine the magnitude of ovarian cancer response to 3C23K and also if there is a threshold surface expression to predict response.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.