Department of Pharmaceutics, Rutgers University, Piscataway, NJ, USA.
Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA.
J Control Release. 2021 Sep 10;337:132-143. doi: 10.1016/j.jconrel.2021.07.022. Epub 2021 Jul 18.
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.
卵巢癌是妇科恶性肿瘤中死亡率最高的。HER2 卵巢癌是一种侵袭性亚型,与远处转移(如肺部)有关。因此,对转移性病变进行准确的生物学特征分析至关重要,因为这有助于医生选择最有效的治疗策略。正电子发射断层扫描(PET)/计算机断层扫描(CT)在临床上常用于检测卵巢癌的转移病变,并评估治疗反应。然而,这种成像方法并不能提供关于是否存在癌症特异性细胞表面标志物(如 HER2)的信息。因此,这种方法不能帮助医生决定是否选择免疫疗法来治疗转移。为了区分卵巢癌肺转移中的 HER2 和 HER2¯病变,我们通过基因工程构建了由 HER2 靶向亲和体和 XTEN 肽组成的 AbXCGd 载体。然后通过稳定的连接子用钆(Gd)标记该载体。对该载体进行物理化学和生物学特性表征,以确定其纯度、分子量、水动力粒径和表面电荷、在血清中的稳定性、内毒素水平、弛豫率以及靶向 HER2 抗原的能力。然后,将 SKOV-3(HER2)和 OVASC-1(HER2¯)肿瘤植入 SCID 小鼠肺部,并注射 Gd 标记的 HER2 靶向 AbXC:Gd 载体。使用动态对比增强磁共振成像(DCE-MRI)对小鼠进行成像,然后进行 R1 映射和图像的定量分析。我们的数据表明,开发的 HER2 靶向载体可以使用 DCE-MRI 区分 HER2 肺转移和 HER2¯病变。开发的载体可能与其他成像方式结合使用,用于对患者进行预筛选,并识别免疫治疗的候选者,同时对那些可能被认为没有反应的患者进行分类。