水凝胶阵列可提高 3D 肿瘤模型中基质成分和治疗药物筛选效果的通量
Summary
本方案描述了一个实验平台，用于评估机械和生化线索对3D基质模拟培养物中患者来源的胶质母细胞瘤细胞的化疗反应的影响，使用定制的UV照明装置促进具有可调机械特征的水凝胶的高通量光交联。
Abstract
细胞基质相互作用通过生化、机械和几何线索介导复杂的生理过程，影响病理变化和治疗反应。在药物开发管道的早期考虑基质效应预计将增加新疗法临床成功的可能性。基于生物材料的策略在3D细胞培养中重述特定的组织微环境，但将这些与主要用于药物筛选的2D培养方法相结合一直具有挑战性。因此，这里介绍的方案详细介绍了在多孔板格式的小型化生物材料基质中进行3D培养的方法开发，以促进与现有药物筛选管道和常规细胞活力测定的集成。由于对于在培养细胞中保存临床相关表型至关重要的基质特征具有高度的组织和疾病特异性，因此有必要对基质参数进行组合筛选，以确定特定应用的适当条件。这里描述的方法使用小型化培养形式来评估癌细胞对基质力学和配体呈递的正交变化的反应。具体而言，这项研究展示了使用该平台来研究基质参数对患者来源的胶质母细胞瘤（GBM）细胞对化疗反应的影响。
Introduction
开发新药的预期成本在过去十年中稳步上升，目前估计超过10亿美元1。这笔费用的一部分是进入临床试验的药物的高失败率。大约12%的候选药物最终在2019年获得美国食品和药物管理局（FDA）的批准。许多药物由于意想不到的毒性2而在I期失败，而其他通过安全性试验的药物可能由于缺乏疗效而失败3。由于无效而导致的这种损耗可以部分解释为，在药物开发过程中使用的癌症模型对临床疗效是出了名的不预测4。
体外和体内模型之间的功能差异可归因于从其天然微环境中去除癌细胞，包括非肿瘤细胞和物理ECM5，6。通常，研究小组使用市售的培养基质，例如Matrigel（一种来自小鼠肉瘤的蛋白质基底膜基质）为培养的肿瘤细胞提供3D基质微环境。与2D培养相比，膜基质中的3D培养提高了体外结果的临床相关性7，8。然而，来自去细胞化组织（包括膜基质）的培养生物材料通常表现出批次间的变异性，这可能影响重现性9。此外，衍生自具有不同组织起源的肿瘤的基质可能与所研究的那些基质10可能不提供适当的生理线索。最后，具有高度肿瘤内异质性的癌症具有微环境特征，这些特征在亚微米级尺度上变化，并且膜基质无法调整以重述11。
胶质母细胞瘤（GBM）是一种致死性均值的脑肿瘤，中位生存时间约为15个月，是一种治疗开发特别困难的癌症12，13。目前GBM的治疗标准包括原发性肿瘤切除术，然后放疗，然后使用替莫唑胺（TMZ）进行化疗14。然而，超过一半的临床GBM肿瘤通过各种机制表现出治疗耐药性15，16，17。预测治疗方案对个体患者的疗效是极其困难的。用于预测个体结果的标准临床前模型包括将患者来源的肿瘤细胞异位移植到免疫功能低下的小鼠中。虽然患者来源的异种移植物可以概括临床GBM肿瘤的许多方面，并且对于临床前模型18很有价值，但它们本质上是昂贵的，低通量的，耗时的，并且涉及伦理问题19。在2D塑料表面上或作为球体培养患者来源的细胞，大多避免了这些问题。虽然患者来源的细胞保留了遗传畸变，但它们在2D或悬浮球体中的培养物在很大程度上在啮齿动物和原始患者肿瘤中患者来源的异种移植物的代表性较差20。以前，我们和其他人已经证明，在模仿脑组织的机械和生化特性的3D ECM中培养的GBM细胞可以保留耐药表型10，21，22，23。
透明质酸（HA）是一种在脑ECM中丰富的多糖，在GBM肿瘤中过表达，其CD44受体调节体外耐药性的获得21，24，25，26，27之间的相互作用。例如，在柔软的3D培养物中加入HA增加了患者来源的GBM细胞获得治疗耐药性的能力。这种机械反应性取决于HA与GBM细胞21上的CD44受体的结合。此外，整合素与含RGD肽结合，并入3D培养基质中，以刚度依赖性方式扩增CD44介导的化学抗性21。除HA外，几种ECM蛋白的表达，其中许多含有RGD区域，在正常脑和GBM肿瘤28之间变化。例如，一项研究报告说，28种不同的ECM蛋白在GBM肿瘤中上调29。在这种复杂的肿瘤基质微环境中，癌细胞整合机械和生化线索以产生特定的抗性表型，这取决于Young的整合素结合肽的模量或密度28，29，30的相对较小的差异（例如，小于一个数量级）。
本方案描述了肿瘤细胞如何解释基质线索的独特组合，并鉴定促进治疗耐药性的复杂，患者特异性基质微环境（图1A）。用于生成用于3D培养的小型化，精确调谐的基质的光化学方法提供了一个大的正交可变空间。由微控制器运行的定制LED阵列被整合到384孔板格式中的光交联水凝胶中，以提高自动化和可重复性。暴露强度在井间变化，以改变所得水凝胶的微机械性质，如使用原子力显微镜（AFM）评估的那样。虽然本手稿并不侧重于构建照明阵列本身，但提供了电路图（图1B）和零件清单（材料表）作为器件再现的辅助工具。
该报告展示了在独特的3D微环境中培养的GBM细胞阵列的快速生成，其中Young的模量（单个数量级上的四个水平）和整合素结合肽含量（来自四种不同的ECM蛋白）正交变化。然后，该方法用于研究水凝胶力学和ECM特异性整合素参与对患者来源的GBM细胞的活力和增殖的相对贡献，因为它们对替莫唑胺（TMZ）化疗产生耐药性。
Protocol
患者来源的GBM细胞系（GS122和GS304）由David Nathanson教授（我们的合作者）提供，他根据加州大学洛杉矶分校机构审查委员会批准的方案（IRB# 10-000655）开发了这些细胞系。细胞被提供去识别化，以便细胞系不能与个体患者联系起来。 1. 水凝胶溶液的制备 通过将 HEPES 粉末以 20 mM 溶解在 Hank 的平衡盐溶液 （HBSS） 中来制备 HEPES 缓冲溶液。完全溶剂化后将pH值?…
Representative Results
AFM测量结果证实，使用定制的Arduino控制LED阵列，在光交联过程中，水凝胶力学的精确控制是紫外辐照度（mW/cm2）的函数（图2A）。该方案中使用的水凝胶制剂可以在表2中找到。提供的模板上LED的间距与384孔板的所有其他孔的间距相匹配，从而允许在板内形成凝胶（图2B）。对单个水凝胶表面微米级区域的AFM询问表明，平均杨氏模量…
Discussion
目前的工作提出了在基于HA的基质硬度和可用于整合素参与的肽中生成3D小型化培养物的方法。该技术能够系统地研究基质参数如何影响细胞表型（例如，暴露于化疗的癌细胞的活力），并提高通量。先前的方法，包括本文提出的方法，已经通过改变最终配方中总聚合物的百分比来调整水凝胶刚度，其中较硬的水凝胶具有更高的聚合物含量21，31。然而，…
Divulgations
The authors have nothing to disclose.
Acknowledgements
作者要特别感谢Carolyn Kim，Amelia Lao，Ryan Stoutamore和Itay Solomon对光凝胶化方案早期迭代的贡献。细胞系GS122和GS304由David Nathanson慷慨提供。所有数字都是用 BioRender.com 创建的。加州大学洛杉矶分校的核心设施，分子筛选共享资源以及纳米和Pico表征实验室对这项工作起到了重要作用。Chen Chia-Chun得到了加州大学洛杉矶分校Eli和Edythe Broad再生医学和干细胞研究培训计划中心的支持。Grigor Varuzhanyan得到了肿瘤细胞生物学培训计划NIH拨款（T32 CA 009056）的支持。
Materials
| 1.1 kOhm resistors, 6 W | Digikey | 35601k1ft | |
| 1.7 mL microcentrifuge tube | Genesse Scientific | 21-108 | |
| 15 mL conical tube | Fisher Scientific | 14-959-70C | |
| 365 nm LED | Digikey | ltpl-c034uvh365 | |
| 384 well plate | Bio Greiner One | 781090 | |
| 40 µm cell strainer | MTC bio | C4040 | |
| 4-Armed thiol terminated polyethlene glycol (20 kDa) | Laysan Bio | 4arm-PEG-SH-20K-1g | |
| 6 NPN BJTs | Digikey | 2n5550ta | |
| 80 Ohm resistors, 0.125 W | Digikey | erjj-6enf80r6v | |
| 8-Armed norbornene terminated polyethylene glycol (20 kDa) | Jenkem Technology | A7025-1 | |
| Accutase | Innovative Cell Technologies | AT104500 | cell dissociation reagent |
| AFM Probes | Novascan | 0.01 N/m Nominal spring constant, 2.5 µm SiO2 particle | |
| Arduino IDE | Arduino | 1.8.19 | |
| Arduino Nano | Makerfire | Mini Nano V3.0 ATmega328P Microcontroller Board | |
| bFGF | Peprotech | 100-18B | 20 ng/mL |
| CCK8 | Abcam | ab228554 | |
| Centrifuge | Thermoscientific | sorvall legend xtr | |
| CP100ST | Gilson | F148415 | Pipette tips for positive displacement pipette |
| Cubis Semi-Micro Balance | Sartorius | MSA225S100DI | |
| DMEM – F12 (50-50) | Life Technologies | 11330057 | 1x |
| DMSO | Fisher Scientific | BP231-100 | |
| DPBS Ca (-) Mg (-) | Genesse Scientific | 25-508 | |
| EGF | Peprotech | AF100-15 | 50 ng/mL |
| Ethanol, Anhydrous | Fisher Scientific | A405P | Add DI water to dilute to 70% |
| Fisherbrand Class B Amber Glass threaded vials | Fisher Scientific | 03-339-23C | |
| Fisherbrand Weighing Paper | Fisher Scientific | 09-898-12B | |
| G21 Supplement | Gemini Bio | 400-160 | 50x |
| Hanks Balanced Salt Solution | Thermo Fisher Scientific | 14175095 | |
| HCl, ACS, 12M | Sigma Aldrich | S25838A | Add DI water to dilute to 1 M |
| Heparin sodium salt from porcine intestinal mucosa | Sigma Aldrich | H3149-100Ku | 25 µg/mL |
| HEPES | Sigma Aldrich | H7006-100G | |
| Hot Air Gun | Wagner | HT1000 | |
| Integrin-binding sialoprotein (IBSP) peptide | Genscript | Custom Order | GCGYGGGGNGEPRGDTYRAY |
| Lithium phenyl-2,4,6 trimethylbenzoylphosphinate (LAP) , >95% | Sigma Aldrich | 900889-1G | |
| Magnetic stir plate | Thermo Scientific | SP194715 | |
| Microcentrifuge | Thermo Scientific | Sorvall legend micro 21R | |
| Microman E single Channel Pipettor | Gilson | FD10004 | Positive displacement pipette |
| Micropipette Tips | Various Manufacturs | Various sizes | |
| mLine micropipette | Sartorious | ||
| N-acetyl Cysteine | Sigma Aldrich | A7250-10G | |
| Nanowizard 4 | Bruker | AFM microscope | |
| NaOH | Fisher Scientific | ss255-1 | Add DI water to dilute to 1 M |
| Normoicin | Invivogen | ant-nr-1 | 500x |
| Osteopontin Peptide | Genscript | Custom Order | GCGYGTVDVPDGRGDSLAYG |
| Pipet Aid | Drummond | 4000102 | |
| Plain Microscope Slides | Globe Scientific | 1301 | |
| Press-To-Seal silicone Isolator, 12-4.5mm diam x 2mm deep | Grace Bio Labs | 664201-A | Cut so that 8 individual molds are made from a single sheet |
| Processing | Processing | 3.5.4 | |
| Repeater M4 | Eppendorf | 4982000322 | |
| Repeater Pipette Tips | Sartorious | 30089430 | 1 mL sizes |
| RGD Peptide | Genscript | GCGYGRGDSPG | |
| Scoth Tape | |||
| Serological Pipettes | Genesse Scientific | 12-102,12-104 | 5,10 mL Pipettes |
| Solder Paste | Digikey | 315-NC191LT15T5-ND | |
| Solder Wire | |||
| Straight dissecting forceps | VWR Scientific | 82027-408 | |
| Synergy H1 Plate Reader | Biotek | ||
| T-75 Cell Culture Treated Flask | Genesee Scientific | 25-209 | |
| Temozolomide | Sigma Aldrich | T2577 | Typically used from 10 µM to 100 µM |
| Tenascin-C Peptide | Genscript | GCGYGRSTDLPGLKAATHYTITIR GV |
|
| Thiolated Hyaluronic Acid (700 kDa), 6-8% modified | Lifecore Biomedical | HA700K5 | |
| VWR Spinbar, Flea Micro | VWR | 58948-375 |
References
- Scannell, J. W., Blanckley, A., Boldon, H., Warrington, B. Diagnosing the decline in pharmaceutical R&D efficiency. Nature Reviews Drug Discovery. 11 (3), 191-200 (2012).
- Waring, M. J., et al. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nature Reviews Drug Discovery. 14 (7), 475-486 (2015).
- Khozin, S., Liu, K., Jarow, J. P., Pazdur, R. Why do oncology drugs fail to gain US regulatory approval. Nature Reviews Drug Discovery. 14 (7), 450-451 (2015).
- Booth, B., Ma, P., Glassman, R. Oncology’s trials. Market indicators. Nature Reviews Drug Discovery. 2 (8), 609-610 (2003).
- Da Ros, M., et al. Glioblastoma chemoresistance: The double play by microenvironment and blood-brain barrier. International Journal of Molecular Sciences. 19 (10), 2879 (2018).
- Broekman, M. L., et al. Multidimensional communication in the microenvirons of glioblastoma. Nature Reviews Neurology. 14 (8), 482-495 (2018).
- Grundy, T. J., et al. Differential response of patient-derived primary glioblastoma cells to environmental stiffness. Scientific Reports. 6 (1), 1-10 (2016).
- Gomez-Roman, N., Stevenson, K., Gilmour, L., Hamilton, G., Chalmers, A. J. A novel 3D human glioblastoma cell culture system for modeling drug and radiation responses. Neuro-Oncology. 19 (2), 229-241 (2017).
- Simoni, R. D., et al. Basement membrane complexes with biological activity. Biochimie. 25 (2), 312-318 (2002).
- Xiao, W., et al. Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Recherche en cancérologie. 78 (5), 1358-1370 (2018).
- Aisenbrey, E. A., Murphy, W. L. Synthetic alternatives to Matrigel. Nature Reviews Materials. 5 (7), 539-551 (2020).
- Spinelli, C., et al. Molecular subtypes and differentiation programmes of glioma stem cells as determinants of extracellular vesicle profiles and endothelial cell-stimulating activities. Journal of Extracellular Vesicles. 7 (1), 1490144 (2018).
- Ostrom, Q. T., Cioffi, G., Waite, K., Kruchko, C., Barnholtz-Sloan, J. S. CBTRUS statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2014-2018. Neuro-Oncology. 23, (2021).
- Stupp, R., et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. New England Journal of Medicine. 352 (10), 987-996 (2005).
- Brennan, C. W., et al. The somatic genomic landscape of glioblastoma. Cell. 155 (2), 462-477 (2013).
- Tomczak, K., Czerwińska, P., Wiznerowicz, M. The Cancer Genome Atlas (TCGA): An immeasurable source of knowledge. Contemporary oncology. 19, 68-77 (2015).
- Lee, S. Y. Temozolomide resistance in glioblastoma multiforme. Genes and Diseases. 3 (3), 198-210 (2016).
- Joo, K. M., et al. Patient-specific orthotopic glioblastoma xenograft models recapitulate the histopathology and biology of human glioblastomas in situ. Cell Reports. 3 (1), 260-273 (2013).
- Levy, N. The use of animal as models: Ethical considerations. International Journal of Stroke. 7 (5), 440-442 (2012).
- Phon, B. W. S., Kamarudin, M. N. A., Bhuvanendran, S., Radhakrishnan, A. K. Transitioning preclinical glioblastoma models to clinical settings with biomarkers identified in 3D cell-based models: A systematic scoping review. Biomedicine & Pharmacotherapy. 145, 112396 (2022).
- Xiao, W., et al. Bioengineered scaffolds for 3D culture demonstrate extracellular matrix-mediated mechanisms of chemotherapy resistance in glioblastoma. Matrix Biology. 85-86, 128-146 (2020).
- Brancato, V., Oliveira, J. M., Correlo, V. M., Reis, R. L., Kundu, S. C. Could 3D models of cancer enhance drug screening. Biomaterials. 232, 119744 (2020).
- Xu, X., Farach-Carson, M. C., Jia, X. Three-dimensional in vitro tumor models for cancer research and drug evaluation. Biotechnology Advances. 32 (7), 1256-1268 (2014).
- Xiao, W., Ehsanipour, A., Sohrabi, A., Seidlits, S. K. Hyaluronic-acid based hydrogels for 3-dimensional culture of patient-derived Glioblastoma Cells. Journal of Visualized Experiments: JoVE. (138), e58176 (2018).
- Preston, M. Digestion products of the PH20 hyaluronidase inhibit remyelination. Annals of Neurology. 73 (2), 266-280 (2013).
- Kim, Y., Kumar, S. CD44-mediated adhesion to hyaluronic acid contributes to mechanosensing and invasive motility. Molecular Cancer Research. 12 (10), 1416-1429 (2014).
- Pibuel, M. A., Poodts, D., Díaz, M., Hajos, S. E., Lompardía, S. L. The scrambled story between hyaluronan and glioblastoma. The Journal of Biological Chemistry. 296, 100549 (2021).
- Xiao, W., Sohrabi, A., Seidlits, S. K. Integrating the glioblastoma microenvironment into engineered experimental models. Future Science OA. 3 (3), (2017).
- Trombetta-Lima, M., et al. Extracellular matrix proteome remodeling in human glioblastoma and medulloblastoma. Journal of Proteome Research. 20 (10), 4693-4707 (2021).
- Schregel, K., et al. Characterization of glioblastoma in an orthotopic mouse model with magnetic resonance elastography. NMR in Biomedicine. 31 (10), 3840 (2018).
- Xiao, W., Ehsanipour, A., Sohrabi, A., Seidlits, S. K. Hyaluronic-acid based hydrogels for 3-dimensional culture of patient-derived glioblastoma cells. Journal of Visualized Experiments: JoVE. (138), e58176 (2018).
- Guz, N., Dokukin, M., Kalaparthi, V., Sokolov, I. If cell mechanics can be described by elastic modulus: Study of different models and probes used in indentation experiments. Biophysical Journal. 107 (3), 564-575 (2014).
- Sneddon, I. N. The relation between load and penetration in the axisymmetric boussinesq problem for a punch of arbitrary profile. International Journal of Engineering Science. 3 (1), 47-57 (1965).
- Soofi, S. S., Last, J. A., Liliensiek, S. J., Nealey, P. F., Murphy, C. J. The elastic modulus of MatrigelTM as determined by atomic force microscopy. Journal of Structural Biology. 167 (3), 216-219 (2009).
- Mayerhöfer, T. G., Popp, J. Beer’s law – Why absorbance depends (almost) linearly on concentration. Chemphyschem: A European Journal of Chemical Physics and Physical Chemistry. 20 (4), 511-515 (2019).
- Puth, M. T., Neuhäuser, M., Ruxton, G. D. On the variety of methods for calculating confidence intervals by bootstrapping. Journal of Animal Ecology. 84 (4), 892-897 (2015).
- Lavrentieva, A. Gradient hydrogels. Advances in Biochemical Engineering/Biotechnology. 178, 227-251 (2020).
- Zhu, D., Trinh, P., Li, J., Grant, G. A., Yang, F. Gradient hydrogels for screening stiffness effects on patient-derived glioblastoma xenograft cellfates in 3D. Journal of Biomedical Materials Research. Part A. 109 (6), 1027-1035 (2021).
- da Hora, C. C., Schweiger, M. W., Wurdinger, T., Tannous, B. A. Patient-derived glioma models: From patients to dish to animals. Cells. 8 (10), 1177 (2019).
- Li, W., et al. Characterization and transplantation of enteric neural crest cells from human induced pluripotent stem cells. Molecular Psychiatry. 23 (3), 499-508 (2018).
- Scaringi, C., Minniti, G., Caporello, P., Enrici, R. M. Integrin inhibitor cilengitide for the treatment of glioblastoma: A brief overview of current clinical results. Anticancer Research. 32 (10), 4213-4224 (2012).
Citer Cet Article
Liang, J., Sohrabi, A., Epperson, M., Rad, L. M., Tamura, K., Sathialingam, M., Skandakumar, T., Lue, P., Huang, J., Popoli, J., Yackly, A., Bick, M., Wang, Z. Z., Chen, C., Varuzhanyan, G., Damoiseaux, R., Seidlits, S. K. Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models. J. Vis. Exp. (184), e63791, doi:10.3791/63791 (2022).