MR Molecular Imaging of Extradomain-B Fibronectin for Assessing Progression and Therapy Resistance of Prostate Cancer

Amita Vaidya, Aman Shankardass, Megan Buford, Ryan Hall, Peter Qiao, Helen Wang, Songqi Gao, Jiaoti Huang, Michael F. Tweedle and Zheng-Rong Lu*, 
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Abstract

Accurate assessment and characterization of the progression and therapy response of prostate cancer are essential for precision healthcare of patients diagnosed with the disease. MRI is a clinical imaging modality routinely used for diagnostic imaging and treatment planning of prostate cancer. Extradomain B fibronectin (EDB-FN) is an oncofetal subtype of fibronectin highly expressed in the extracellular matrix of aggressive cancers, including prostate cancer. It is a promising molecular target for the detection and risk-stratification of prostate cancer with high-resolution MR molecular imaging (MRMI). In this study, we investigated the effectiveness of MRMI with an EDB-FN specific contrast agent MT218 for assessing the progression and therapy resistance of prostate cancer. Low grade LNCaP prostate cancer cells became an invasive phenotype LNCaP-CXCR2 with elevated EDB-FN expression after acquisition of the C-X-C motif chemokine receptor 2 (CXCR2). MT218-MRMI showed brighter signal enhancement in LNCaP-CXCR2 tumor xenografts with a ∼2-fold contrast-to-noise (CNR) increase than in LNCaP tumors in mice. Enzalutamide-resistant C4-2-DR prostate cancer cells were more invasive, with higher EDB-FN expression than parental C4-2 cells. Brighter signal enhancement with a ∼2-fold CNR increase was observed in the C4-2-DR xenografts compared to that of C4-2 tumors in mice with MT218-MRMI. Interestingly, when invasive PC3 prostate cancer cells developed resistance to paclitaxel, the drug-resistant PC3-DR cells became less invasive with reduced EDB-FN expression than the parental PC3 cells. MT218-MRMI detected reduced brightness in the PC3-DR xenografts with more than 2-fold reduction of CNR compared to PC3 tumors in mice. The signal enhancement in all tumors was supported by the immunohistochemical staining of EDB-FN with the G4 monoclonal antibody. The results indicate that MRMI of EDB-FN with MT218 has promise for detection, risk stratification, and monitoring the progression and therapy response of invasive prostate cancer.

Abstract Image

用于评估前列腺癌进展和耐药性的外域-B 纤维连接蛋白磁共振分子成像技术
准确评估和描述前列腺癌的进展和治疗反应,对于为确诊患者提供精准医疗服务至关重要。核磁共振成像是一种常规用于前列腺癌诊断成像和治疗规划的临床成像模式。外域B纤连蛋白(EDB-FN)是纤连蛋白的一种胎盘亚型,在侵袭性癌症(包括前列腺癌)的细胞外基质中高度表达。它是利用高分辨率磁共振分子成像(MRMI)检测前列腺癌并对其进行风险分级的一个很有前景的分子靶点。在本研究中,我们研究了使用 EDB-FN 特异性造影剂 MT218 进行 MRMI 评估前列腺癌进展和耐药性的有效性。低级别 LNCaP 前列腺癌细胞在获得 C-X-C motif 趋化因子受体 2(CXCR2)后成为侵袭性表型 LNCaP-CXCR2,EDB-FN 表达升高。与小鼠 LNCaP 肿瘤相比,MT218-MRMI 在 LNCaP-CXCR2 肿瘤异种移植中显示出更明亮的信号增强,对比度-噪声(CNR)增加了 2 倍。耐恩扎鲁胺的 C4-2-DR 前列腺癌细胞更具侵袭性,其 EDB-FN 表达高于亲本 C4-2 细胞。与使用 MT218-MRMI 的小鼠 C4-2 肿瘤相比,在 C4-2-DR 异种移植物中观察到更亮的信号增强,CNR 增加了 2 倍。有趣的是,当侵袭性 PC3 前列腺癌细胞对紫杉醇产生抗药性时,与亲代 PC3 细胞相比,耐药 PC3-DR 细胞侵袭性降低,EDB-FN 表达减少。与小鼠 PC3 肿瘤相比,MT218-MRMI 在 PC3-DR 异种移植物中检测到的亮度降低,CNR 降低了 2 倍多。用 G4 单克隆抗体对 EDB-FN 进行免疫组化染色也证实了所有肿瘤的信号增强。结果表明,用MT218对EDB-FN进行磁共振成像有望用于浸润性前列腺癌的检测、风险分层、进展和治疗反应监测。
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来源期刊
Chemical & Biomedical Imaging
Chemical & Biomedical Imaging 化学与生物成像-
CiteScore
1.00
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0.00%
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期刊介绍: Chemical & Biomedical Imaging is a peer-reviewed open access journal devoted to the publication of cutting-edge research papers on all aspects of chemical and biomedical imaging. This interdisciplinary field sits at the intersection of chemistry physics biology materials engineering and medicine. The journal aims to bring together researchers from across these disciplines to address cutting-edge challenges of fundamental research and applications.Topics of particular interest include but are not limited to:Imaging of processes and reactionsImaging of nanoscale microscale and mesoscale materialsImaging of biological interactions and interfacesSingle-molecule and cellular imagingWhole-organ and whole-body imagingMolecular imaging probes and contrast agentsBioluminescence chemiluminescence and electrochemiluminescence imagingNanophotonics and imagingChemical tools for new imaging modalitiesChemical and imaging techniques in diagnosis and therapyImaging-guided drug deliveryAI and machine learning assisted imaging
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