Ovarian cancer has the highest mortality rate among all gynecologic malignancies. HER2 ovarian cancer is a subtype that is aggressive and associated with metastasis to distant sites such as the lungs. Therefore, accurate biological characterization of metastatic lesions is vital as it helps physicians select the most effective treatment strategy. Functional imaging of ovarian cancer with PET/CT is routinely used in the clinic to detect metastatic disease and evaluate treatment response. However, this imaging method does not provide information regarding the presence or absence of cancer-specific cell surface biomarkers such as HER2. As a result, this method does not help physicians decide whether to choose immunotherapy to treat metastasis. To differentiate the HER2 from HER2¯ lesions in ovarian cancer lung metastasis, AbXCGd vector composed of a HER2 targeting affibody and XTEN peptide was genetically engineered. It was then labeled with gadolinium (Gd) via a stable linker. The vector was characterized physicochemically and biologically to determine its purity, molecular weight, hydrodynamic size and surface charge, stability in serum, endotoxin levels, relaxivity and ability to target the HER2 antigen. Then, SCID mice were implanted with SKOV-3 (HER2) and OVASC-1 (HER2¯) tumors in the lungs and injected with the Gd-labeled HER2 targeted AbXC:Gd vector. The mice were imaged using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), followed by R1-mapping and quantitative analysis of the images. Our data demonstrate that the developed HER2-targeted vector can differentiate HER2 lung metastasis from HER2¯ lesions using DCE-MRI. The developed vector could potentially be used in conjunction with other imaging modalities to prescreen patients and identify candidates for immunotherapy while triaging those who may not be considered responsive.
Copyright © 2021. Published by Elsevier B.V.