Single-Cell Imaging Using Radioluminescence Microscopy Reveals Unexpected Binding Target for [18F]HFB

Abstract

Purpose

Cell-based therapies are showing great promise for a variety of diseases, but remain hindered by the limited information available regarding the biological fate, migration routes and differentiation patterns of infused cells in trials. Previous studies have demonstrated the feasibility of using positron emission tomography (PET) to track single cells utilising an approach known as positron emission particle tracking (PEPT). The radiolabel hexadecyl-4-[18F]fluorobenzoate ([18F]HFB) was identified as a promising candidate for PEPT, due to its efficient and long-lasting labelling capabilities. The purpose of this work was to characterise the labelling efficiency of [18F]HFB in vitro at the single-cell level prior to in vivo studies.

Procedures

The binding efficiency of [18F]HFB to MDA-MB-231 and Jurkat cells was verified in vitro using bulk gamma counting. The measurements were subsequently repeated in single cells using a new method known as radioluminescence microscopy (RLM) and binding of the radiolabel to the single cells was correlated with various fluorescent dyes.

Results

Similar to previous reports, bulk cell labelling was significantly higher with [18F]HFB (18.75 ± 2.47 dpm/cell, n = 6) than 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) (7.59 ± 0.73 dpm/cell, n = 7; p ≤ 0.01). However, single-cell imaging using RLM revealed that [18F]HFB accumulation in live cells (8.35 ± 1.48 cpm/cell, n = 9) was not significantly higher than background levels (4.83 ± 0.52 cpm/cell, n = 12; p > 0.05) and was 1.7-fold lower than [18F]FDG uptake in the same cell line (14.09 ± 1.90 cpm/cell, n = 13; p < 0.01). Instead, [18F]HFB was found to bind significantly to fragmented membranes associated with dead cell nuclei, suggesting an alternative binding target for [18F]HFB.

Conclusion

This study demonstrates that bulk analysis alone does not always accurately portray the labelling efficiency, therefore highlighting the need for more routine screening of radiolabels using RLM to identify heterogeneity at the single-cell level.

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References

  1. 1.

    Slavin S, Nagler A, Naparstek E et al (1998) Nonmyeloablative stem cell transplantation and cell therapy as an alternative to conventional bone marrow transplantation with lethal cytoreduction for the treatment of malignant and nonmalignant hematologic diseases. Blood 91:756–763

    CAS  PubMed  Google Scholar 

  2. 2.

    Koc NO, Gerson LS, Cooper WB et al (2016) Rapid hematopoietic recovery after coinfusion of autologous-blood stem cells and culture-expanded marrow mesenchymal stem cells in advanced breast. J Clin Oncologia 18:307–316

    Article  Google Scholar 

  3. 3.

    Maus MV, Grupp SA, Porter DL, June CH (2014) Antibody modified T cells: CARs take the front seat for hematologic malignancies. Blood 123:2625–2635

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Robbins PF, Lu Y-C, El-Gamil M et al (2013) Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells. Nat Med 19:747–752

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Hsu FJ, Benike C, Fagnoni F et al (1996) Vaccination of patients with B-cell lymphoma using autologous antigen-pulsed dendritic cells. Nat Med 2:2338–2344

    Google Scholar 

  6. 6.

    Nestle FO, Alijagic S, Gilliet M et al (1998) Vaccination of melanoma patients with peptide- or tumor lysate-pulsed dendritic cells. Nat Med 4:201–206

    Article  Google Scholar 

  7. 7.

    Lo Celso C, Fleming HE, Wu JW et al (2009) Live-animal tracking of individual haematopoietic stem/progenitor cells in their niche. Nature 457:92–96

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Doherty WP, Bushberg TJ, Lipton JM et al (1978) The use of indium-111-labeled leukocytes for abscess detection. Clin Nucl Med 3:108–110

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Sharpe M, Mount N (2015) Genetically modified T cells in cancer therapy : opportunities and challenges. Dis Model Mech 8:337–350

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Griessinger CM, Kehlbach R, Bukala D et al (2014) In vivo tracking of Th1 cells by PET reveals quantitative and temporal distribution and specific homing in lymphatic tissue. J Nucl Med 2:301–307

    Article  Google Scholar 

  11. 11.

    Yaghoubi SS, Jensen MC, Satyamurthy N et al (2012) Noninvasive detection of therapeutic cytolytic T cells with PET in a glioma patient. Nat Rev Clin Oncologia 6:53–58

    Article  Google Scholar 

  12. 12.

    Rodriguez-porcel M, Kronenberg MW, Henry TD et al (2012) Cell tracking and the development of cell-based therapies: a view from the Cadiovascular Cell Therapty Research Network. JACC Cardiovasc Imaging 5:559–565

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Kircher MF, Gambhir SS, Grimm J (2011) Noninvasive cell-tracking methods. Nat Rev Clin Oncol 8:677–688

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Adonai NN, Nguyen KN, Walsh J et al (2002) Ex vivo cell labeling with 64Cu-pyruvaldehyde-bis(N4-methylthiosemicarbazone) for imaging cell trafficking in mice with positron-emission tomography. Proc Natl Acad Sci 99:3030–3035

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Hofmann M, Wollert KC, Meyer GP et al (2005) Monitoring of bone marrow cell homing into the infarcted human myocardium. Circulation 111:2198–2202

    Article  PubMed  Google Scholar 

  16. 16.

    Gambhir SS, Bauer E, Black ME et al (2000) A mutant herpes simplex virus type 1 thymidine kinase reporter gene shows improved sensitivity for imaging reporter gene expression with positron emission tomography. Proc Natl Acad Sci 97:2785–2790

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Kang JH, Lee DS, Paeng JC et al (2005) Development of a sodium/iodide symporter (NIS)-transgenic mouse for imaging of cardiomyocyte-specific reporter gene expression. J Nucl Med 46:479–483

    CAS  PubMed  Google Scholar 

  18. 18.

    Moroz MA, Serganova I, Zanzonico P et al (2007) Imaging hNET reporter gene expression with 124I-MIBG. J Nucl Med 48:827–836

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Ma B, Hankenson KD, Dennis JE et al (2005) A simple method for stem cell labeling with fluorine 18. Nucl Med Biol 32:701–705

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Lee KS, Kim TJ, Pratx G (2015) Single-cell tracking with PET using a novel trajectory reconstruction algorithm. IEEE Trans Med Imaging 34:994–1003

    Article  PubMed  Google Scholar 

  21. 21.

    Langford ST, Wiggins CS, Santos R et al (2017) Three-dimensional spatiotemporal tracking of fluorine-18 radiolabeled yeast cells via positron emission particle tracking. PLoS One 12:7

    Article  Google Scholar 

  22. 22.

    Wiggins C, Santos R, Ruggles A (2016) A novel clustering approach to positron emission particle tracking. Nucl Instrum Methods Phys Res Sect A 811:18–24

    CAS  Article  Google Scholar 

  23. 23.

    Parker DJ, Broadbent CJ, Fowles P et al (1993) Positron emission particle tracking—a technique for studying flow within engineering equipment. Nucl Inst Methods Phys Res A 326:592–607

    Article  Google Scholar 

  24. 24.

    Bemrose CR, Fowles P, Hawkesworth MR, O’Dwyer MA (1988) Application of positron emission tomography to particulate flow measurement in chemical engineering processes. Nucl Instrum Methods Phys Res A 273:874–880

    Article  Google Scholar 

  25. 25.

    Patel N, Wiggins C, Ruggles A (2017) Positron emission particle tracking in pulsatile flow. Exp Fluids 58:42

    Article  Google Scholar 

  26. 26.

    Ouyang Y, Kim TJ, Pratx G (2016) Evaluation of a BGO-based PET system for single-cell tracking performance by simulation and phantom studies. Mol Imaging 15:1–8

    CAS  Article  Google Scholar 

  27. 27.

    Zhang Y, DaSilva JN, Hadizad T et al (2012) F-18-FDG cell labeling may underestimate transplanted cell homing: more accurate, efficient, and stable cell labeling with hexadecyl-4-[F-18]fluorobenzoate for in vivo tracking of transplanted human progenitor cells by positron emission tomography. Cell Transplant 21:1821–1835

    Article  PubMed  Google Scholar 

  28. 28.

    Pratx G, Chen K, Sun C et al (2012) Radioluminescence microscopy: measuring the heterogeneous uptake of radiotracers in single living cells. PLoS One 7:1–9

    Article  Google Scholar 

  29. 29.

    Pratx G, Chen K, Sun C et al (2013) High-resolution radioluminescence microscopy of 18F-FDG uptake by reconstructing the β-ionization track. J Nucl Med 54:1841–1846

    CAS  Article  PubMed  Google Scholar 

  30. 30.

    Kim TJ, Türkcan S, Pratx G (2017) Modular low-light microscope for imaging cellular bioluminescence and radioluminescence. Nat Protoc 12:1055–1076

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Wu M, Kwon HY, Rattis F et al (2017) Imaging hematopoietic precursor division in real time. Cell Stem Cell 1:541–554

    Article  Google Scholar 

  32. 32.

    Chang HH, Hemberg M, Barahona M et al (2008) Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 453:544–547

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Ravin R, Hoeppner DJ, Munno DM et al (2008) Potency and fate specification in CNS stem cell populations in vitro. Cell Stem Cell 3:670–680

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Naumova AV, Modo M, Moore A et al (2014) Clinical imaging in regenerative medicine. Nat Biotechnol 32:804–818

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Ahmadi A, Thorn SL, Alarcon EI et al (2015) PET imaging of a collagen matrix reveals its effective injection and targeted retention in a mouse model of myocardial infarction. Biomaterials 49:18–26

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Kim MH, Woo SK, Lee KC et al (2015) Longitudinal monitoring adipose-derived stem cell survival by PET imaging hexadecyl-4-124I-iodobenzoate in rat myocardial infarction model. Biochem Biophys Res Commun 456:13–19

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    Kim MH, Woo SK, Kim KI et al (2015) Simple methods for tracking stem cells with 64 cu-labeled DOTA-hexadecyl-benzoate. ACS Med Chem Lett 6:528–530

  38. 38.

    Natarajan A, Türkcan S, Gambhir SS, Pratx G (2015) Multiscale framework for imaging radiolabeled therapeutics. Mol Pharm 12:4554–4560

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Kim TJ, Tuerkcan S, Ceballos A, Pratx G (2015) Modular platform for low-light microscopy. Biomed Opt Express 6:4585–4598

    Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Sengupta D, Pratx G (2016) Single-cell characterization of FLT uptake with radioluminescence microscopy. J Nucl Med 2764:1136–1141

    Article  Google Scholar 

  41. 41.

    Kim MH, Lee KC, Il AG et al (2015) Evaluation of safety and efficacy of adipose-derived stem cells in rat myocardial infarction model using hexadecyl-4-[(124)I]iodobenzoate for cell tracking. Appl Radiat Isot 108:116–123

    Article  PubMed  Google Scholar 

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Funding

This work was funded in part by NIH grants to Dr. Pratx (5R21HL127900 and 5R01CA186275) and by a NIH training grant to Dr. Kim (T32CA11868).

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Correspondence to Guillem Pratx.

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Kiru, L., Kim, T.J., Shen, B. et al. Single-Cell Imaging Using Radioluminescence Microscopy Reveals Unexpected Binding Target for [18F]HFB. Mol Imaging Biol 20, 378–387 (2018). https://doi.org/10.1007/s11307-017-1144-0

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Key words

  • Cell tracking
  • Radioluminescence microscopy (RLM)
  • Single-cell imaging
  • Hexadecyl-4-[18F]fluorobenzoate ([18F]HFB)