综合程序，以评估<em>在体内</em>癌症纳米医学的性能
Summary
The poor understanding of the in vivo performance of nanomedicines stymies their clinical translation. Procedures to evaluate the in vivo behavior of cancer nanomedicines at systemic, tissue, single-cell, and subcellular levels in tumor-bearing immunocompetent mice are described here. This approach may help researchers to identify promising cancer nanomedicines for clinical translation.
Abstract
在诊所以前的癌症纳米医学的成功的启发，研究人员已经在过去的十年中产生了大量新的配方。然而，只有纳米医学少数已被批准用于临床使用，而根据临床开发的大多数纳米医学的已产生令人失望的结果。到的新的癌症纳米医学成功临床翻译的一个主要障碍是缺乏其在体内表现的准确理解。本文设有严格的程序通过正电子发射断层扫描，计算机断层扫描（PET-CT），放射性量化方法的整合来表征在全身性的，组织，单细胞，和亚细胞水平荷瘤小鼠纳米医学的体内行为，流式细胞仪，荧光显微镜。使用这种方法，研究人员可以准确地评价着性相关的小鼠模型的新纳米制剂河这些协议可以具有高平移电位，以确定最有前途的癌症纳米医学或癌症纳米医学的供将来翻译优化以帮助的能力。
Introduction
纳米医学正在改变癌症治疗的发展1的范例。由以前的癌症纳米医学，如脂质体和基于白蛋白nanotherapies 2,3的巨大临床影响的启发，许多新的配方已在过去十年中产生的。然而，最近这些癌症纳米医学的临床转化成功的分析表明，只有少数已被批准用于临床4,5。以新的癌症纳米医学临床翻译的一个主要障碍是有限的治疗指数的提高与自由治疗化合物6直接管理比较。如在临床前动物模型中在全身性的，组织纳米医学，和细胞水平的体内性能等，准确的评价是IDENTIF必不可少Ÿ那些对未来临床翻译最佳的治疗指数。
纳米材料可以是放射性标记的用于在活的动物与正电子发射断层扫描（PET）成像，其具有所有的临床成像方式7之间极好的灵敏度和重现性定量表征。例如，89 Zr的标记的长循环纳米医学已经表征在小鼠模型中的癌症8，9，10，以及在其它疾病模型11。此外，该纳米医学的血半衰期和生物分布可广泛用在个人组织8利用体外放射性测量评估。因此，単允许纳米医学在全身和组织水平的定量评价。
重要的是，radiolabeleð纳米医学通常不能在单细胞或亚细胞水平进行分析，由于放射性信号的空间分辨率有限。因此，荧光标记证明是纳米颗粒的光学成像技术，如流式细胞仪和荧光显微镜12中的评价的互补方式。为此，标记放射性同位素和荧光标签纳米粒子可以定量在体内通过核成像评估和体外通过放射性计数，而且它们也可广泛表征在光学成像的细胞水平。
以前，我们已经开发了模块式程序，以放射性和荧光标记纳入各种纳米粒子，包括高密度脂蛋白（HDL）11，脂质体9，10，聚合物纳米颗粒，抗体片段，和nanoemulsions 10,13。这些标记纳米粒子已经允许在不同层次的相关动物模型，引导这些纳米材料的优化其具体应用定量表征。在目前的研究中，目的是利用纳米脂质体，最成熟的纳米平台14 -作为一个例子来证明综合程序生成双标记纳米颗粒，并把它在一个典型的同系黑色素瘤B16-F10小鼠模型15彻底表征。从结果来看，我们有信心这种纳米粒子的表征方法可以适用于评估相关的小鼠模型其它癌症纳米医学。
Protocol
Representative Results
Discussion
该议定书中的关键步骤：
双标记的脂质体的高品质的关键是产生在一段长期一致的结果。自由荧光染料或89 Zr离子可以产生完全不同的定位方式，而且必须在纯化步骤中被完全去除。另外，如果免疫系统显著影响实验癌症纳米性能，使用免疫小鼠模型的应该是优选的，如在C57BL / 6小鼠的B16-F10黑素瘤模型中，这是在本协议中使用。如果肿瘤微环境或遗传突变的特定组合是…
Disclosures
The authors have nothing to disclose.
Acknowledgements
The authors would like to thank Drs. Helene Salmon and Miriam Merad from Icahn School of Medicine at Mount Sinai for providing the B16-F10-YFP cells and for their expert advice on melanoma mouse models. The authors further thank the Animal Imaging Core Facility, the Radiochemistry and Molecular Imaging Probes Core Facility, and the Molecular Cytology Core Facility at Memorial Sloan Kettering Cancer Center (MSK) for their support. This work was supported by National Institutes of Health grants NIH 1 R01 HL125703 (W.J.M.M.), R01CA155432 (W.J.M.M.), K25 EB016673 (T.R.) and P30 CA008748 (MSK Center Grant). The authors also thank the Center for Molecular Imaging and Nanotechnology (CMINT) at MSK for their financial support (T.R.).
Materials
| DPPC | Avantilipids | 850355 | |
| Cholesterol | Sigma-Aldrich | C8667 | |
| DSPE-PEG2000 | Avantilipids | 880120P | |
| DSPE-DFO | Home made | 110634 | Perez-Medina et al, JNM, 2014 |
| DiIC12[5]-DS | AAT Bioquest | 22051 | |
| Centrifugal filter | Vivaproducts | VS2061 | |
| Rotary evaporator | Buchi | R-100 | |
| Radio-HPLC | Shimadzu HPLC with 2 LC-10AT pumps | N/A | |
| 89Zr-oxalate | MSKCC | Synthesized in house | TR19/9 variable beam cyclotron (Ebco Industries Inc) |
| Micro PET-CT | Siemens | Inveon Micro-PET/CT | |
| Gamma counter | PerkinElmer | 2470-0150 | |
| Flow cytometry | BD Biosciences | Fortessa | Any multi-parametric flow cytometry analyzers would suffice |
| C57BL/6 mice | Jackson Laboratories | ||
| B16-YFP melanoma cells | Home made | N/A | Salmon et al, Immunity, 2016 |
| Ly6C (clone HK1.4)–APC-Cy7 | 128025 | Biolegend | |
| MHCII (M5/114/152)–APC | 107613 | Biolegend | |
| CD45 (30-F11)–BV510 | 103137 | Biolegend | |
| CD64 (X54-5/7.1)–PE-Cy7 | 139313 | Biolegend | |
| CD11b (M1/70)–BV605 | 101237 | Biolegend | |
| CD3 (17A2)–BV711 | 100241 | Biolegend | |
| CD31 (13.3)–PE | 561073 | Biolegend | |
| CD11c (M418)–PerCP-Cy5.5 | 117327 | BD Biosciences | |
| CD31 (13.3) no fluorophore | 550274 | BD Biosciences |
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