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Automated Assessment of Cancer Drug Efficacy On Breast Tumor Spheroids in Aggrewell™400 Plates Using Image Cytometry

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Abstract

Tumor spheroid models have proven useful in the study of cancer cell responses to chemotherapeutic compounds by more closely mimicking the 3-dimensional nature of tumors in situ. Their advantages are often offset, however, by protocols that are long, complicated, and expensive. Efforts continue for the development of high-throughput assays that combine the advantages of 3D models with the convenience and simplicity of traditional 2D monolayer methods. Herein, we describe the development of a breast cancer spheroid image cytometry assay using T47D cells in Aggrewell™400 spheroid plates. Using the Celigo® automated imaging system, we developed a method to image and individually track thousands of spheroids within the Aggrewell™400 microwell plate over time. We demonstrate the use of calcein AM and propidium iodide staining to study the effects of known anti-cancer drugs Doxorubicin, Everolimus, Gemcitabine, Metformin, Paclitaxel and Tamoxifen. We use the image cytometry results to quantify the fluorescence of calcein AM and PI as well as spheroid size in a dose dependent manner for each of the drugs. We observe a dose-dependent reduction in spheroid size and find that it correlates well with the viability obtained from the CellTiter96® endpoint assay. The image cytometry method we demonstrate is a convenient and high-throughput drug-response assay for breast cancer spheroids under 400 μm in diameter, and may lay a foundation for investigating other three-dimensional spheroids, organoids, and tissue samples.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the first author on reasonable request.

Code Availability

Not applicable.

References

  1. Selby M et al (2017) 3D Models of the NCI60 Cell Lines for Screening Oncology Compounds. SLAS Discov 22:473–483

    Article  CAS  PubMed  Google Scholar 

  2. Close DA et al (2018) Implementation of the NCI-60 Human Tumor Cell Line Panel to Screen 2260 Cancer Drug Combinations to Generate >3 Million Data Points Used to Populate a Large Matrix of Anti-Neoplastic Agent Combinations (ALMANAC) Database. SLAS DISCOVERY: Advancing the Science of Drug Discovery 24:242–263

    Article  Google Scholar 

  3. Fang Y, Eglen RM (2017) Three-dimensional cell cultures in drug discovery and development. Slas discovery: Advancing Life Sciences R&D 22:456–472

    Article  CAS  Google Scholar 

  4. Sant S, Johnston PA (2017) The production of 3D tumor spheroids for cancer drug discovery. Drug Discov Today Technol 23:27–36

    Article  PubMed  PubMed Central  Google Scholar 

  5. Riedl A et al (2017) Comparison of cancer cells in 2D vs 3D culture reveals differences in AKT–mTOR–S6K signaling and drug responses. J Cell Sci 130:203–218

    CAS  PubMed  Google Scholar 

  6. Mirab F, Kang YJ, Majd S (2019) Preparation and characterization of size-controlled glioma spheroids using agarose hydrogel microwells. PLoS ONE 14:e0211078–e0211078

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Mortensen ACL, Morin E, Brown CJ, Lane DP, Nestor M (2020) Enhancing the therapeutic effects of in vitro targeted radionuclide therapy of 3D multicellular tumor spheroids using the novel stapled MDM2/X-p53 antagonist PM2. EJNMMI Res 10:38–38

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ballangrud ÅM et al (2001) Response of LNCaP Spheroids after Treatment with an α-Particle Emitter (<sup>213</sup>Bi)-labeled Anti-Prostate-specific Membrane Antigen Antibody (J591). Can Res 61:2008–2014

    CAS  Google Scholar 

  9. Sirenko O et al (2015) High-Content Assays for Characterizing the Viability and Morphology of 3D Cancer Spheroid Cultures. Assay Drug Dev Technol 13:402–414

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. LaBonia GJ, Lockwood SY, Heller AA, Spence DM, Hummon AB (2016) Drug penetration and metabolism in 3D cell cultures treated in a 3D printed fluidic device: assessment of irinotecan via MALDI imaging mass spectrometry. Proteomics 16:1814–1821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Liu X, Weaver EM, Hummon AB (2013) Evaluation of therapeutics in three-dimensional cell culture systems by MALDI imaging mass spectrometry. Anal Chem 85:6295–6302

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hagemann J et al (2017) Spheroid-based 3D Cell Cultures Enable Personalized Therapy Testing and Drug Discovery in Head and Neck Cancer. Anticancer Res 37:2201–2210

    Article  CAS  PubMed  Google Scholar 

  13. Palubeckaitė I et al (2020) Mass spectrometry imaging of endogenous metabolites in response to doxorubicin in a novel 3D osteosarcoma cell culture model. J Mass Spectrom. 55:e4461

  14. Vinci M, Box C, Eccles SA (2015) Three-Dimensional (3D) Tumor Spheroid Invasion Assay. JoVE. e52686 https://doi.org/10.3791/52686

  15. Vinci M, Box C, Zimmermann M, Eccles S (2013) Tumor Spheroid-Based Migration Assays for Evaluation of Therapeutic Agents. Methods Mol Biol 986:253–266

    Article  CAS  PubMed  Google Scholar 

  16. Scherliess R (2011) The MTT assay as tool to evaluate and compare excipient toxicity in vitro on respiratory epithelial cells. Int J Pharm 411:98–105

    Article  CAS  PubMed  Google Scholar 

  17. Larsson P et al (2020) Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens. Sci Rep 10:5798

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Eilenberger C et al (2018) Optimized alamarBlue assay protocol for drug dose-response determination of 3D tumor spheroids. MethodsX 5:781–787

    Article  PubMed  PubMed Central  Google Scholar 

  19. Lang SH, Sharrard RM, Stark M, Villette JM, Maitland NJ (2001) Prostate epithelial cell lines form spheroids with evidence of glandular differentiation in three-dimensional Matrigel cultures. Br J Cancer 85:590–599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Dadgar N et al (2020) A microfluidic platform for cultivating ovarian cancer spheroids and testing their responses to chemotherapies. Microsyst Nanoeng 6:93

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ware MJ et al (2016) Generation of Homogenous Three-Dimensional Pancreatic Cancer Cell Spheroids Using an Improved Hanging Drop Technique. Tissue Eng Part C Methods 22:312–321

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ingram M et al (1997) Three-dimensional growth patterns of various human tumor cell lines in simulated microgravity of a NASA bioreactor. In Vitro Cell Dev Biol Anim 33:459–466

    Article  CAS  PubMed  Google Scholar 

  23. Howes AL, Richardson RD, Finlay D, Vuori K.(2014) 3-Dimensional culture systems for anti-cancer compound profiling and high-throughput screening reveal increases in EGFR inhibitor-mediated cytotoxicity compared to monolayer culture systems. PloS One. 9(9):e108283

  24. Vinci M et al (2012) Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation. BMC Biol 10:29

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lee JM et al (2018) Generation of uniform-sized multicellular tumor spheroids using hydrogel microwells for advanced drug screening. Sci Rep 8:1–10

    Article  Google Scholar 

  26. Jeon O, Marks R, Wolfson D, Alsberg E (2016) Dual-crosslinked hydrogel microwell system for formation and culture of multicellular human adipose tissue-derived stem cell spheroids. Journal of Materials Chemistry B 4:3526–3533

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Fukuda J et al (2006) Micromolding of photocrosslinkable chitosan hydrogel for spheroid microarray and co-cultures. Biomaterials 27:5259–5267

    Article  CAS  PubMed  Google Scholar 

  28. Okuyama T et al (2010) Preparation of arrays of cell spheroids and spheroid-monolayer cocultures within a microfluidic device. J Biosci Bioeng 110:572–576

    Article  CAS  PubMed  Google Scholar 

  29. Seo J et al (2018) High-throughput approaches for screening and analysis of cell behaviors. Biomaterials 153:85–101

    Article  CAS  PubMed  Google Scholar 

  30. Sun Q et al (2018) Microfluidic Formation of Coculture Tumor Spheroids with Stromal Cells As a Novel 3D Tumor Model for Drug Testing. ACS Biomater Sci Eng 4:4425–4433

    Article  CAS  PubMed  Google Scholar 

  31. Madoux F et al (2017) A 1536-Well 3D Viability Assay to Assess the Cytotoxic Effect of Drugs on Spheroids. SLAS DISCOVERY: Advancing the Science of Drug Discovery 22:516–524

    Article  CAS  Google Scholar 

  32. Mathews LA et al (2012) A 1536-well quantitative high-throughput screen to identify compounds targeting cancer stem cells. J Biomol Screen 17:1231–1242

    Article  PubMed  PubMed Central  Google Scholar 

  33. Tung Y-C et al (2011) High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array. Analyst 136:473–478

    Article  CAS  PubMed  Google Scholar 

  34. Raghavan S et al (2015) Formation of stable small cell number three-dimensional ovarian cancer spheroids using hanging drop arrays for preclinical drug sensitivity assays. Gynecol Oncol 138:181–189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Razian G, Yu Y, Ungrin M (2013) Production of large numbers of size-controlled tumor spheroids using microwell plates. JoVE J Visual Exp. 81:e50665. https://doi.org/10.3791/50665

  36. Chan LL, Wilkinson AR, Paradis BD, Lai N (2012) Rapid Image-based Cytometry for Comparison of Fluorescent Viability Staining Methods. J Fluoresc 22:1301–1311

    Article  CAS  PubMed  Google Scholar 

  37. Chan LL-Y, Kuksin D, Laverty DJ, Saldi S, Qiu J (2015) Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method. Cytotechnology 67:461–473

    Article  CAS  PubMed  Google Scholar 

  38. Cribbes S, Kessel S, McMenemy S, Qiu J, Chan LL-Y (2017) A Novel Multiparametric Drug-Scoring Method for High-Throughput Screening of 3D Multicellular Tumor Spheroids Using the Celigo Image Cytometer. SLAS DISCOVERY: Advancing the Science of Drug Discovery 22:547–557

    Article  CAS  Google Scholar 

  39. Pereira P et al (2017) Cancer cell spheroids are a better screen for the photodynamic efficiency of glycosylated photosensitizers. PLoS ONE. 12

  40. Gaskell H et al (2016) Characterization of a Functional C3A Liver Spheroid Model. Toxicol. Res. 5 

  41. Gong X et al (2015) Generation of Multicellular Tumor Spheroids with Microwell-Based Agarose Scaffolds for Drug Testing. Plos One 10:e0130348

  42. Lewis N et al (2017) Magnetically levitated mesenchymal stem cell spheroids cultured with a collagen gel maintain phenotype and quiescence. Journal of Tissue Engineering 8:204173141770442

    Article  Google Scholar 

  43. Singh M, Close DA, Mukundan S, Johnston PA, Sant S (2015) Production of Uniform 3D Microtumors in Hydrogel Microwell Arrays for Measurement of Viability, Morphology, and Signaling Pathway Activation. Assay Drug Dev Technol 13:570–583

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Singh M, Mukundan S, Jaramillo M, Oesterreich S, Sant S (2016) Three-Dimensional Breast Cancer Models Mimic Hallmarks of Size-Induced Tumor Progression. Can Res 76:3732–3743

    Article  CAS  Google Scholar 

  45. Thakuri PS, Gupta M, Plaster M, Tavana H (2019) Quantitative Size-Based Analysis of Tumor Spheroids and Responses to Therapeutics. Assay Drug Dev Technol 17:140–149

    Article  CAS  PubMed  Google Scholar 

  46. Yang W et al (2012) Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res 41:D955–D961

    Article  PubMed  PubMed Central  Google Scholar 

  47. Ariaans G, Jalving M, Vries EG, Jong S (2017) Anti-tumor effects of everolimus and metformin are complementary and glucose-dependent in breast cancer cells. BMC Cancer 17:232

    Article  PubMed  PubMed Central  Google Scholar 

  48. Serrano MJ et al (2002) Evaluation of a Gemcitabine-Doxorubicin-Paclitaxel Combination Schedule through Flow Cytometry Assessment of Apoptosis Extent Induced in Human Breast Cancer Cell Lines. Jpn J Cancer Res 93:559–566

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Bashmail HA et al (2018) Thymoquinone synergizes gemcitabine anti-breast cancer activity via modulating its apoptotic and autophagic activities. Sci Rep 8:11674

    Article  PubMed  PubMed Central  Google Scholar 

  50. Durbin KR, Nottoli MS, Jenkins GJ (2020) Effects of microtubule-inhibiting small molecule and antibody-drug conjugate treatment on differentially-sized A431 squamous carcinoma spheroids. Sci Rep 10:907

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

This research was conducted with support under Grant No. R01EB012521 awarded by the National Institutes of Health.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA

    Shilpaa Mukundan, Matthew Teryek & Biju Parekkadan

  2. Department of Advanced Technology R&D, Nexcelom Bioscience LLC, Lawrence, MA, 01843, USA

    Jordan Bell, Charles Hernandez, Andrea C. Love & Leo Li-Ying Chan

  3. Department of Medicine, Rutgers Biomedical Health Sciences, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA

    Biju Parekkadan

Authors
  1. Shilpaa Mukundan
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  2. Jordan Bell
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  6. Biju Parekkadan
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Contributions

SM and JB: Conceptualization; data curation; formal analysis; investigation; methodology; visualization; writing original draft; writing-review and editing. MT: data curation; formal analysis. CH and ACL: Methodology; writing-review and editing. BP and LLC: Project administration; resources; supervision; conceptualization; visualization; writing original draft; writing-review and editing.

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Correspondence to Leo Li-Ying Chan.

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Conflict of Interest

The authors JB, CH, ACL, and LLC declare competing financial interests. The tumor spheroid detection method development in this manuscript is for reporting on a biological application using an instrument of Nexcelom Bioscience, LLC. The work demonstrated a high-throughput method for the characterization of tumor spheroids in Aggrewell plates using the Celigo® Image Cytometer.

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Mukundan, S., Bell, J., Teryek, M. et al. Automated Assessment of Cancer Drug Efficacy On Breast Tumor Spheroids in Aggrewell™400 Plates Using Image Cytometry. J Fluoresc 32, 521–531 (2022). https://doi.org/10.1007/s10895-021-02881-3

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  • DOI: https://doi.org/10.1007/s10895-021-02881-3

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