Development of a targeted recombinant vector for MRI-assisted characterization of ovarian cancer
Creators: name: Nomani, Alireza
Publisher: name: No Publisher Supplied
Year: 2021

description: Ovarian cancer has the highest rate of mortality among all gynecologic malignancies. To decrease the mortality rate, there is an urgent need for robust diagnosis protocols for ovarian cancer to detect that at the earlier stages and stratify the patients according to their tumor microenvironment characteristics and molecular biology for personalized therapy. Functional imaging of ovarian cancer with PET/CT or ultrasound is routinely used in the clinic to detect metastatic disease and evaluate treatment response. However, these imaging methods do not provide information regarding the presence or absence of cancer-specific cell surface biomarkers such as HER2. As a result, these methods do not help physicians decide whether to choose immunotherapy to treat metastasis. In the first part of this study, we developed a diagnostic technique based on magnetic resonance imaging to detect HER2+ ovarian cancer. Like multiple other types of cancers, HER2+ ovarian cancer is an aggressive subtype associated with metastasis to distant sites such as the lungs. Therefore, accurate biological characterization of the metastatic lesions is vital as it helps the physicians select the most effective treatment strategy. To differentiate the HER2+ from HER2¯ lesions in ovarian cancer lung metastasis, a vector composed of a HER2 targeting affibody and XTEN peptide was genetically engineered and 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 HER2 antigen. Then, SCID mice were implanted with SKOV-3 (HER2+), and OVASC-1 (HER2¯) tumors in the lungs, injected with Gd-labeled HER2 targeted vector and imaged by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). An in-house MATLAB code was also developed for T1 mapping and quantitative analysis of the MRI scans. Our data demonstrated that the HER2-targeted vector could differentiate the HER2+ lung metastasis from HER2¯ ones using DCE-MRI. The developed vector can 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. In the second part of this dissertation, we expanded the developed DCE-MRI platform application to evaluate the enhanced-permeability and retention effect (EPR) of three ovarian tumor models in mice. Decades of extensive research on the nano-sized chemotherapeutic agents for treating solid tumors have resulted in only a few commercially available nano-sized drugs. Generally, it was believed that nanomedicines permeate out of the tumor vasculature, diffuse through all regions of the tumor, and then come in close contact with the tumor cells to react with or eradicate them. However, it is now evident that solid tumors exhibit a high variation in EPR towards the nano-sized therapeutics. This issue results in a lack of response to the administered nanomedicines in a majority of the patients. Therefore, it is necessary to detect the non-responsive tumors from the responsive in advance to arrive at alternatives for non-responsive patients. In this study, we used our new DCE- MRI platform to quantitatively evaluate the EPR status during tumor growth and development in three different ovarian tumor models. We measured the kinetic of macromolecular Gd contrast agent in the prepared ovarian xenograft tumor models at their different tumor sizes, using the DCE-MRI protocol. Next, the Tofts pharmacokinetic modeling was used to fit the Gd concentration data and estimate two mathematical parameters of Ktrans and Ve corresponding to the perfusion and retention of the nanotherapeutics, respectively. Our data estimated that OVASC-1 (a patient-derived tumor) was the least responsive tumor to the nanomedicine administration among the evaluated ovarian tumor models. Although the SKOV-3 tumor was less responsive to the nanomedicines at the smaller tumor sizes (&lt; 200 mm3), it became significantly responsive when the tumor grew. The practical outcome of this part of the study could be a reliable and clinically viable method for measuring the EPR effect in detected tumors, which would help predict the tumor response to the nanotherapeutics. Predicting the outcome of nanotherapy at the earlier stages of treatment would enable the inclusion of only the patients deemed responsive to the therapy protocol. Consequently, those patients’ lives and costs would be saved.