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纳米技术与癌症:利用多模态介孔二氧化硅纳米颗粒改善膀胱癌的实时监测与分期

Nanotechnology and cancer: improving real-time monitoring and staging of bladder cancer with multimodal mesoporous silica nanoparticles.

作者信息

Sweeney Sean K, Luo Yi, O'Donnell Michael A, Assouline Jose

机构信息

Department of Biomedical Engineering, University of Iowa, 1402 Seamans Center for the Engineering Arts and Sciences, Iowa City, IA 52242 USA ; NanoMedTrix, LLC, 2500 Crosspark Road, Suite E119, Coralville, IA 52241-4710 USA.

Department of Urology, University of Iowa, Roy J. and Lucille A. Carver College of Medicine, 3204 Medical Education Research Facility, 375 Newton Road, Iowa City, IA 52242 USA.

出版信息

Cancer Nanotechnol. 2016;7:3. doi: 10.1186/s12645-016-0015-8. Epub 2016 Apr 27.

Abstract

BACKGROUND

Despite being one of the most common cancers, bladder cancer is largely inefficiently and inaccurately staged and monitored. Current imaging methods detect cancer only when it has reached "visible" size and has significantly disrupted the structure of the organ. By that time, thousands of cells will have proliferated and perhaps metastasized. Repeated biopsies and scans are necessary to determine the effect of therapy on cancer growth. In this report, we describe a novel approach based on multimodal nanoparticle contrast agent technology and its application to a preclinical animal model of bladder cancer. The innovation relies on the engineering core of mesoporous silica with specific scanning contrast properties and surface modification that include fluorescence and magnetic resonance imaging (MRI) contrast. The overall dimensions of the nano-device are preset at 80-180 nm, depending on composition with a pore size of 2 nm.

METHODS

To facilitate and expedite discoveries, we combined a well-known model of bladder cancer and our novel technology. We exposed nanoparticles to MB49 murine bladder cancer cells in vitro and found that 70 % of the cells were labeled by nanoparticles as measured by flow cytometry. The in vivo mouse model for bladder cancer is particularly well suited for T1- and T2-weighted MRI.

RESULTS

Under our experimental conditions, we demonstrate that the nanoparticles considerably improve tumor definition in terms of volumetric, intensity and structural characteristics. Important bladder tumor parameters can be ascertained, non-invasively, repetitively, and with great accuracy. Furthermore, since the particles are not biodegradable, repetitive injection is not required. This feature allows follow-up diagnostic evaluations during cancer treatment. Changes in MRI signals show that in situ uptake of free particles has predilection to tumor cells relative to normal bladder epithelium. The particle distribution within the tumors was corroborated by fluorescent microscopy of sections of excised bladders. In addition, MRI imaging revealed fibrous finger-like projections into the tumors where particles insinuated themselves deeply. This morphological characteristic was confirmed by fluorescence microscopy.

CONCLUSIONS

These findings may present new options for therapeutic intervention. Ultimately, the combination of real-time and repeated MRI evaluation of the tumors enhanced by nanoparticle contrast may have the potential for translation into human clinical studies for tumor staging, therapeutic monitoring, and drug delivery.

摘要

背景

尽管膀胱癌是最常见的癌症之一,但其分期和监测在很大程度上效率低下且不准确。目前的成像方法只有在癌症达到“可见”大小时且已严重破坏器官结构时才能检测到。到那时,数千个细胞已经增殖,甚至可能已经转移。需要反复进行活检和扫描来确定治疗对癌症生长的影响。在本报告中,我们描述了一种基于多模态纳米颗粒造影剂技术的新方法及其在膀胱癌临床前动物模型中的应用。该创新依赖于具有特定扫描对比特性的介孔二氧化硅工程核心以及包括荧光和磁共振成像(MRI)对比的表面修饰。纳米装置的整体尺寸根据组成预设为80 - 180纳米,孔径为2纳米。

方法

为了促进和加快研究发现,我们将一种著名的膀胱癌模型与我们的新技术相结合。我们在体外将纳米颗粒暴露于MB49小鼠膀胱癌细胞,通过流式细胞术测量发现70%的细胞被纳米颗粒标记。膀胱癌的体内小鼠模型特别适合T1加权和T2加权MRI。

结果

在我们的实验条件下,我们证明纳米颗粒在体积、强度和结构特征方面显著改善了肿瘤的清晰度。重要的膀胱肿瘤参数可以通过非侵入性、重复性且高精度地确定。此外,由于颗粒不可生物降解,不需要重复注射。这一特性允许在癌症治疗期间进行后续诊断评估。MRI信号的变化表明,相对于正常膀胱上皮,游离颗粒在原位对肿瘤细胞具有偏好性摄取。通过对切除膀胱切片的荧光显微镜检查证实了颗粒在肿瘤内的分布。此外,MRI成像显示纤维状指状突起深入肿瘤,颗粒深深嵌入其中。这一形态特征通过荧光显微镜得到证实。

结论

这些发现可能为治疗干预提供新的选择。最终,由纳米颗粒造影增强的肿瘤实时和重复MRI评估相结合可能有潜力转化为用于肿瘤分期、治疗监测和药物递送的人体临床研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e797/4846680/21eb82287d9a/12645_2016_15_Fig1_HTML.jpg

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