JoVE Journal > Cancer Research
Summary
Abstract
Introduction
Protocol
Results
Discussion
Disclosures
Acknowledgements
Materials
References
自动翻译
Please note that all translations are automatically generated. Click here for the English version.
癌症研究

患者源性肿瘤外植体作为预测患者耐药性的"实时"临床前平台

Published: February 07, 2021
doi:
10.3791/62130
, , , , , , , , , , ,
1Leicester Cancer Research Center,University of Leicester, 2MRC Toxicology Unit

Summary

本文描述了在实时的、与患者相关的临床前模型系统中评估肿瘤药物反应的患者来源的外植体的生成、药物治疗和分析方法。

Abstract

对耐药性的理解和开发对高度耐药性癌症致敏的新策略依赖于能够准确预测患者反应的合适临床前模型的可用性。现有临床前模型的缺点之一是无法在上下文中保留人类肿瘤微环境（TME）并准确表示肿瘤内异质性，从而限制了数据的临床翻译。相比之下，通过表示人类肿瘤活片段的培养物，患者来源的外植体（PDE）平台允许在三维（3D）环境中检查药物反应，该上下文尽可能密切地反映原始肿瘤的病理和结构特征。先前的PDE报告已经记录了该平台区分化学敏感性和化学抵抗性肿瘤的能力，并且已经表明这种分离可以预测患者对相同化疗的反应。同时，偏微分方程允许有机会询问预测药物反应的肿瘤的分子，遗传和组织学特征，从而确定用于患者分层的生物标志物以及使耐药性肿瘤致敏的新型介入方法。本文详细介绍了PDE方法，从患者样本的收集到终点分析。它提供了外植体衍生和培养方法的详细说明，在适当的情况下突出了特定肿瘤的定制条件。对于终点分析，重点是多重免疫荧光和多光谱成像，用于肿瘤和基质区域内关键生物标志物的空间分析。通过结合这些方法，可以生成定量和定性的药物反应数据，这些数据可能与各种临床病理学参数相关，因此可能用于生物标志物鉴定。

Introduction

开发有效和安全的抗癌药物需要适当的临床前模型，这些模型还可以深入了解作用机制，从而促进预测和药效学生物标志物的鉴定。已知肿瘤间和肿瘤内异质性1，2，3，4，5和TME 6，7，8，9，10，11，12影响抗癌药物反应，许多现有的临床前癌症模型，如细胞系，类器官和小鼠模型，无法完全适应这些至关重要的特征。”理想”模型可以概括肿瘤内恶性细胞与非恶性细胞的复杂空间相互作用，并反映肿瘤内的区域差异。本文重点介绍 PDE 作为可以满足其中许多要求的新兴平台13.

使用人类偏微分方程（也称为组织培养）的第一个例子可以追溯到20世纪80年代后期，当时霍夫曼等人产生了新鲜切除的人类肿瘤切片并将其培养在胶原蛋白基质14，15中。这涉及建立一个保留组织结构的3D培养系统，确保维持TME内的基质成分和细胞相互作用。在不解构原始肿瘤的情况下，Hoffman等人16预示着一种新的转化研究方法，从那时起，许多研究小组已经优化了不同的外植体方法，目的是保持组织的完整性并产生准确的药物反应数据17，18，19，20，21，22，23，24，尽管协议之间存在一些明显的差异。Butler等人在明胶海绵中培养外植体，以帮助营养物质和药物通过标本20，21，25扩散，而Majumder等人通过在存在来自同一患者的自体血清的情况下，在由肿瘤和基质蛋白组成的基质上培养外植体来创建肿瘤生态系统22， 23.

最近，我们的小组建立了一个方案，通过将肿瘤碎片化成2 – 3 mm3大小的块来生成外植体，然后在培养系统24的气液界面处的可渗透膜上放置没有附加组分。综上所述，这些大量研究表明，偏微分方程允许培养完整的活体人类肿瘤片段，这些片段保留了原始肿瘤的空间结构和区域异质性。在原始实验中，外植体或组织培养通常在药物治疗后进行均质化，之后对均质化样品进行各种活力测定，例如组织培养药物反应测定20，21，MTT（3-（6）-2，5-二苯基四唑溴化物测定，乳酸盐脱氢酶测定或基于刃天青的测定26，27，28.终点分析技术的最新进展，特别是数字病理学，现在已经扩大了可以在外植体29，30上进行的终点测试和测定的库。为了应用这些新技术，将外植体固定在福尔马林中，嵌入石蜡（FFPE），然后使用免疫染色技术进行分析，而不是均质化，从而进行空间分析。这种方法的例子已经记录在非小细胞肺癌（NSCLC），乳腺癌，结直肠癌和间皮瘤外植体中，其中免疫组织化学染色增殖标志物Ki67和凋亡标志物，切割的聚ADP核糖聚合酶（cPARP），用于监测细胞增殖和细胞死亡的变化24，31，32，33，34。

多重免疫荧光特别适合于在终点35处对外植体中的药物反应进行空间分析。例如，在药物治疗13，36，37，38时，可以测量TME内特定类别的免疫细胞（如巨噬细胞或T细胞）的重新定位和空间分布，并研究治疗剂是否可以有利于从”冷肿瘤”到”热肿瘤”的转变39.近年来，该小组专注于从不同肿瘤类型（NSCLC，肾癌，乳腺癌，结直肠癌，黑色素瘤）中提取PDEs，并测试一系列抗癌药物，包括化疗，小分子抑制剂和免疫检查点抑制剂（ICI）。终点分析方法已经过优化，包括多重免疫荧光，允许对生物标志物进行空间分析，以实现生存能力以及TME不同成分的生物标志物。

Protocol

1. 组织收集 手术后，将新鲜切除的人肿瘤标本转移到含有25mL新鲜培养基（Dulbecco的改良Eagle培养基，补充有4.5g / L葡萄糖和L-谷氨酰胺+ 1%（v / v）胎儿小牛血清+ 1%青霉素 – 链霉素）的管中，并储存在冰上。在手术后2小时内在无菌II级罩中处理外植体。 2. Explant制备 用70%工业甲基化精神（IMS）溶液清洁所有手术设备（移?…

Representative Results

mIF染色的组织学切片的多光谱成像允许识别和表型单个细胞群，并鉴定外植体TME中的肿瘤和基质成分（图2）。多光谱成像对于分析具有高固有自发荧光的组织（例如具有高胶原蛋白含量的组织）特别有用，因为它允许自发荧光信号从其他信号中解卷积并从后续分析中排除。随后的硅组织和细胞分割允许量化具有多种输出的药物反应，包括但不限于原始细胞数量（例如，阳性…

Discussion

本文介绍了偏微分方程的生成、药物治疗和分析方法，并重点介绍了该平台作为临床前模型系统的优势。新切除的肿瘤的离体培养，不涉及其解构，允许保留肿瘤结构13，24，从而保留TME中细胞成分的空间相互作用以及肿瘤内异质性。该方法展示了通过使用肿瘤特异性标记物，可以识别肿瘤组织区域与基质区域，从而在这些隔室内分离药物反应（<strong cl…

Disclosures

The authors have nothing to disclose.

Acknowledgements

我们感谢莱斯特大学医院NHS信托基金会的外科医生和病理学家提供手术切除的肿瘤组织。我们还感谢Core Biotechnology Services的组织学设施在FFPE组织块的组织处理和切片方面的帮助，以及Kees Straatman对使用Vectra Polaris的支持。这项研究得到了由四个合作伙伴组成的Explant联盟的支持和资助：莱斯特大学，MRC毒理学部门，癌症研究英国治疗发现实验室和LifeArc。CRUK-NIHR莱斯特实验癌症医学中心（C10604 / A25151）提供了额外的支持。GM，CD和NA的资金由Breast Cancer Now的催化剂计划（2017NOVPCC1066）提供，该计划由辉瑞公司提供资金支持。

Materials

Acetic acid Sigma 320099 Staining reagent
Antibody Diluent / Block, 1x Perkin Elmer ARD1001EA Antibody diluent/blocking buffer
Barnstead NANOpure Diamond Barnstead Ultra Pure (UP) H2O machine
Citric Acid Monohydrate Sigma-Aldrich C7129 Reagent for citrate buffer
Costar Multiple Well Cell Culture Plates Corning Incorporated 3516 6 multiwell plate
DAPI Dilactate Life Technologies D3571
100 x 17 mm Dish, Nunclon Delta ThermoFisher Scientific 150350 100 mm diameter dish for tissue culture
DMEM (1x) Dubelcco's Modified Eagle Medium + 4.5 g/L D-Glucose + 110 mg/mL Sodium Pyruvate Gibco (Life Technologies) 10569-010 Tissue culture medium (500 mL)
DPX mountant VWR 360294H Mounting medium
DPX mountant Merck 6522 Mounting medium
Ethylenediaminetetraacetic acid (EDTA) Sigma-Aldrich 3609 Reagent for TE buffer
Eosin CellPath RBC-0100-00A Staining reagent
Foetal Bovine Serum Gibco 10500-064 For use in tissue culture medium
37% Formaldehyde Fisher (Acros) 119690010 10% Formalin
iGenix, microwave oven IG2095 iGenix IG2095 Microwave used for antigen retreival
Industrial methylated spirit (IMS) Genta Medical 199050 99% Industrial Denatured Alcohol (IDA)
InForm Advanced Image Analysis Software Akoya Biosciences InForm
Leica ASP3000 Tissue Processor Leica Biosystems Automated Vacuum Tissue Processor
Leica Arcadia H and C Leica Biosystems Embedding wax bath
Leica RM2125RT Leica Biosystems Rotary microtome
Leica ST4040 Linear Stainer Leica Biosystems H&E stainer
Mayer's Haematoxylin Sigma GHS132-1L Staining reagent
Millicell Cell Culture Inserts, 30 mm, hydrophilic PTFE, 0.4 µm Merck Milipore PICMORG50 Organotypic culture insert disc
Novolink Polymer Detection System Leica Biosystems RE7150-K DAB staining kit
OPAL 480 Akoya Biosciences FP1500001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent
OPAL 520 Akoya Biosciences FP1487001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent
OPAL 570 Akoya Biosciences FP1488001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent
OPAL 620 Akoya Biosciences FP1495001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent
OPAL 650 Akoya Biosciences FP1496001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent
OPAL 690 Akoya Biosciences FP1497001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent
OPAL 780 / OPAL TSA-DIG Reagent Akoya Biosciences FP1501001KT Fluorophore with Dimethyl Sulfoxide (DMSO) diluent and TSA-DIG reagent
Opal Polymer HRP Ms Plus Rb, 1x Perkin Elmer ARH1001EA HRP polymer
Penicillin/streptomycin solution Fisher Scientific 11548876 For use in tissue culture medium
PhenoChart Whole Slide Contextual Viewer Akoya Biosciences PhenoChart Viewer software for scanned images
Phosphate Buffered Saline Tablets Thermo Scientific Oxoid BR0014G PBS
1x Plus Amplification Diluent Perkin Elmer FP1498 Fluorophore diluent
Prolong Diamond Antifade Mountant Invitrogen P36961 Mounting medium
Slide Carrier Perkin Elmer To load slides into Slide Carrier Hotel for scanning with Vectra Polaris
Sodium Chloride Fisher Scientific S/3160/63 10% Formalin
Sodium Hydroxide pellets Fisher Scientific S/4920/53 Reagent for citrate buffer
Tenatex Toughened Wax – Pink (500 g) KEMDENT 1-601 Dental wax surface
Thermo Scientific Shandon Sequenza Slide Rack for Immunostaining Center Fisher Scientific 10098889 Holder for slides and slide clips
Thermo Scientific Shandon Plastic Coverplates Fisher Scientific 11927774 Slide clips
Tris(hydroxymethyl)aminomethane (Tris) Sigma-Aldrich 252859 Reagent for TE buffer
VectaShield Vecta Laboratories H-1000-10 Mounting medium
Vectra Polaris Slide Scanner Perkin Elmer Vectra Polaris Slide scanner
Xylene Genta Medical XYL050 De-waxing agent
DOWNLOAD MATERIALS LIST

References

  1. Gerlinger, M., et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England Journal of Medicine. 366 (10), 883-892 (2012).
  2. Jamal-Hanjani, M., et al. Tracking the evolution of non-small-cell lung cancer. The New England Journal of Medicine. 376 (22), 2109-2121 (2017).
  3. McGranahan, N., Swanton, C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell. 27 (1), 15-26 (2015).
  4. Casey, T., et al. Molecular signatures suggest a major role for stromal cells in development of invasive breast cancer. Breast Cancer Research and Treatment. 114 (1), 47-62 (2009).
  5. Gerdes, M. J., et al. Emerging understanding of multiscale tumor heterogeneity. Frontiers in Oncology. 4, 366 (2014).
  6. Komohara, Y., Takeya, M. CAFs and TAMs: maestros of the tumour microenvironment. The Journal of Pathology. 241 (3), 313-315 (2017).
  7. Miyake, M., et al. CXCL1-mediated interaction of cancer cells with tumor-associated macrophages and cancer-associated fibroblasts promotes tumor progression in human bladder cancer. Neoplasia. 18 (10), 636-646 (2016).
  8. Hisamitsu, S., et al. Interaction between cancer cells and cancer-associated fibroblasts after cisplatin treatment promotes cancer cell regrowth. Human Cell. 32 (4), 453-464 (2019).
  9. Witz, I. P. The tumor microenvironment: the making of a paradigm. Cancer Microenvironment. 2, 9-17 (2009).
  10. Fu, X. T., et al. Tumor-associated macrophages modulate resistance to oxaliplatin via inducing autophagy in hepatocellular carcinoma. Cancer Cell International. 19, 71 (2019).
  11. Chen, D., Zhang, X. Tipping tumor microenvironment against drug resistance. Journal of Oncology Translational Research. 1 (1), 106 (2015).
  12. Roma-Rodrigues, C., Mendes, R., Baptista, P. V., Fernandes, A. R. Targeting tumor microenvironment for cancer therapy. International Journal of Molecular Sciences. 20 (4), 840 (2019).
  13. Powley, I. R., et al. Patient-derived explants (PDEs) as a powerful preclinical platform for anti-cancer drug and biomarker discovery. British Journal of Cancer. 122 (6), 735-744 (2020).
  14. Freeman, A. E., Hoffman, R. M. In vivo-like growth of human tumors in vitro. Proceedings of the National Academy of Sciences of United States of America. 83 (8), 2694-2698 (1986).
  15. Vescio, R., et al. A. al. In vivo-like drug responses of human tumors growing in three-dimensional gel-supported primary culture. Proceedings of the National Academy of Sciences of United States of America. 84 (14), 5029-5033 (1987).
  16. Hoffman, R. M. 3D Sponge-matrix histoculture: an overview. Methods in Molecular Biology. 1760, 11-17 (2018).
  17. Vescio, R. A., Connors, K. M., Kubota, T., Hoffman, R. M. Correlation of histology and drug response of human tumors grown in native-state three-dimensional histoculture and in nude mice. Proceedings of the National Academy of Sciences of United States of America. 88 (12), 5163-5166 (1991).
  18. Furukawa, T., Kubota, T., Hoffman, R. M. Clinical applications of the histoculture drug response assay. Clinical Cancer Research. 1 (3), 305-311 (1995).
  19. Centenera, M. M., Raj, G. V., Knudsen, K. E., Tilley, W. D., Butler, L. M. Ex vivo culture of human prostate tissue and drug development. Nature Reviews Urology. 10 (8), 483-487 (2013).
  20. Centenera, M. M., et al. Evidence for efficacy of new Hsp90 inhibitors revealed by ex vivo culture of human prostate tumors. Clinical Cancer Research. 18 (13), 3562-3570 (2012).
  21. Dean, J. L., et al. Therapeutic response to CDK4/6 inhibition in breast cancer defined by ex vivo analyses of human tumors. Cell Cycle. 11 (14), 2756-2761 (2012).
  22. Majumder, B., et al. Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity. Nature Communications. 6, 6169 (2015).
  23. Goldman, A., et al. Temporally sequenced anticancer drugs overcome adaptive resistance by targeting a vulnerable chemotherapy-induced phenotypic transition. Nature Communications. 6, 6139 (2015).
  24. Karekla, E., et al. Ex vivo explant cultures of non-small cell lung carcinoma enable evaluation of primary tumor responses to anticancer therapy. 癌症研究. 77 (8), 2029-2039 (2017).
  25. Ricciardelli, C., et al. Novel ex vivo ovarian cancer tissue explant assay for prediction of chemosensitivity and response to novel therapeutics. Cancer Letters. 421, 51-58 (2018).
  26. Yoshimasu, T., et al. Histoculture drug response assay (HDRA) guided induction concurrent chemoradiotherapy for mediastinal node-positive non-small cell lung cancer. Gan To Kagaku Ryoho. Cancer and chemotherapy. 30 (2), 231-235 (2003).
  27. Pirnia, F., et al. Ex vivo assessment of chemotherapy-induced apoptosis and associated molecular changes in patient tumor samples. Anticancer Research. 26, 1765-1772 (2006).
  28. Maund, S. L., Nolley, R., Peehl, D. M. Optimization and comprehensive characterization of a faithful tissue culture model of the benign and malignant human prostate. Laboratory Investigation. 94 (2), 208-221 (2014).
  29. Vasaturo, A., Galon, J. Multiplexed immunohistochemistry for immune cell phenotyping, quantification and spatial distribution in situ. Methods in Enzymology. 635, 51-66 (2020).
  30. Fuhrman, K., et al. Molecularly guided digital spatial profiling for multiplexed analysis of gene expression with spatial and single cell resolution. Journal of Biomolecular Techniques. 31, 14-15 (2020).
  31. Twiddy, D., et al. A TRAIL-R1-specific ligand in combination with doxorubicin selectively targets primary breast tumour cells for apoptosis. Breast Cancer Research. 12 (1), 58 (2010).
  32. Cai, H., et al. Cancer chemoprevention: Evidence of a nonlinear dose response for the protective effects of resveratrol in humans and mice. Science Translational Medicine. 7 (298), (2015).
  33. Busacca, S., et al. Resistance to HSP90 inhibition involving loss of MCL1 addiction. Oncogene. 35 (12), 1483-1492 (2016).
  34. Kolluri, K. K., et al. Loss of functional BAP1 augments sensitivity to TRAIL in cancer cells. Elife. 7, 30224 (2018).
  35. Toki, M. I., et al. High-plex predictive marker discovery for melanoma immunotherapy-treated patients using digital spatial profiling. Clinical Cancer Research. 25 (18), 5503-5512 (2019).
  36. Parra, E. R., et al. Validation of multiplex immunofluorescence panels using multispectral microscopy for immune-profiling of formalin-fixed and paraffin-embedded human tumor tissues. Scientific Reports. 7 (1), 13380 (2017).
  37. Park, I. J., et al. Prediction of radio-responsiveness with immune-profiling in patients with rectal cancer. Oncotarget. 8 (45), 79793-79802 (2017).
  38. Mezheyeuski, A., et al. Multispectral imaging for quantitative and compartment-specific immune infiltrates reveals distinct immune profiles that classify lung cancer patients. The Journal of Pathology. 244 (4), 421-431 (2018).
  39. Kather, J. N., et al. Topography of cancer-associated immune cells in human solid tumors. Elife. 7, 36967 (2018).
  40. Zollinger, D. R., Lingle, S. E., Sorg, K., Beechem, J. M., Merritt, C. R. GeoMx™ RNA assay: high multiplex, digital, spatial analysis of RNA in FFPE tissue. Methods in Molecular Biology. 2148, 331-345 (2020).
  41. Zugazagoitia, J., et al. Biomarkers associated with beneficial PD-1 checkpoint blockade in non-small cell lung cancer (NSCLC) identified using high-plex digital spatial profiling. Clinical Cancer Research. 26 (16), 4360-4368 (2020).
  42. Allo, B., Lou, X., Bouzekri, A., Ornatsky, O. Clickable and high-sensitivity metal-containing tags for mass cytometry. Bioconjugate Chemistry. 29 (6), 2028-2038 (2018).
  43. Gerdtsson, E., et al. Multiplex protein detection on circulating tumor cells from liquid biopsies using imaging mass cytometry. Convergent Science Physical Oncology. 4 (1), 015002 (2018).
  44. Reck, M., et al. Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer. The New England Journal of Medicine. 375 (19), 1823-1833 (2016).
  45. Le, D. T., et al. KEYNOTE-164: Phase 2 study of pembrolizumab for patients with previously treated, microsatellite instability-high advanced colorectal carcinoma. Journal of Clinical Oncology. 34, 3631 (2016).
  46. Diaz, L. A., et al. KEYNOTE-177: Randomized phase III study of pembrolizumab versus investigator-choice chemotherapy for mismatch repair-deficient or microsatellite instability-high metastatic colorectal carcinoma. Journal of Clinical Oncology. 35, 815 (2017).
  47. Long, G. V., et al. Impact of baseline serum lactate dehydrogenase concentration on the efficacy of pembrolizumab and ipilimumab in patients with advanced melanoma: data from KEYNOTE-006. European Journal of Cancer. 72, 122-123 (2017).
  48. Voong, K. R., Feliciano, J., Becker, D., Levy, B. Beyond PD-L1 testing-emerging biomarkers for immunotherapy in non-small cell lung cancer. Annals of Translational Medicine. 5 (18), 376 (2017).

Tags

Keywords: Patient-derived Tumor ExplantsPreclinical PlatformDrug Resistance Prediction3D Tumor ContextDrug ResponseDrug MetabolismPharmacodynamic BiomarkersOrganotypic CultureDrug TreatmentFormalin FixationHistological Processing
check_url/cn/62130?article_type=t

Play Video
PDF
DOI
DOWNLOAD MATERIALS LIST
Cite This Article
Viticchié, G., Powley, I., Demetriou, C., Cooper, J., Butterworth, M., Patel, M., Abid, N., Miles, G., Howells, L., Pringle, H., MacFarlane, M., Pritchard, C. Patient-Derived Tumor Explants As a “Live” Preclinical Platform for Predicting Drug Resistance in Patients. J. Vis. Exp. (168), e62130, doi:10.3791/62130 (2021).
Download Citation
Reprints and Permissions

View Video

✖

To prove you're not a robot, please enter the text in the image below

CAPTCHA Image
Play CAPTCHA Audio
Refresh Image