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Fluorescence Molecular Imaging and Tomography of Matrix Metalloproteinase-Activatable Near-Infrared Fluorescence Probe and Image-Guided Orthotopic Glioma Resection

  • Li Li
  • Yang Du
  • Xinjian Chen
  • Jie Tian
Research Article
  • 187 Downloads

Abstract

Purpose

Malignant gliomas are major causes of cancer-related mortality and morbidity. Traditional surgery usually leads to incomplete resection of gliomas resulting in the high incidence of tumor recurrence. Advanced medical imaging technology, such as fluorescence imaging-guided surgery, combined with tumor-specific imaging probes allows the identification of tumor margins and improved surgery. However, there are two pressing issues that need to be addressed: first, few fluorescence imaging probes can specifically target gliomas; second, fluorescence molecular imaging (FMI) cannot get the in-depth information of deep-seated gliomas; both of which affect the complete removal of the gliomas.

Procedures

In this study, the biodistribution of smart matrix metalloproteinase (MMP) targeting near-infrared (NIR) fluorescent probe MMPSense 750 FAST (MMP-750) was examined in both U87MG-GFP-fLuc glioma xenograft and orthotopic mouse models using FMI. Then, CT and FMI images of orthotopic gliomas were acquired for the reconstruction of fluorescence molecular tomography (FMT) using a randomly enhanced adaptive subspace pursuit (REASP) algorithm. Furthermore, the resection of orthotopic glioma was performed using the fluorescence surgical navigation system after the injection of the MMP-750 probe. After surgery, bioluminescence imaging (BLI) and hematoxylin and eosin staining were carried out to confirm the precision resection of the tumor.

Results

FMI results showed that the MMP-750 probe can specifically target U87MG glioma in vivo. FMT presented the spatial information of the orthotopic glioma using the REASP reconstruction algorithm. Furthermore, MMP-750 could effectively delineate the tumor margin during glioma surgery leading to a complete resection of the tumors.

Conclusions

The smart MMP-750 specifically targets the glioma and FMT of MMP-750 provides 3D information for the spatial localization of the glioma. MMP-750 can work as an ideal fluorescence probe for guiding the intraoperative surgical resection of the glioma, possessing clinical translation.

Key words

Matrix metalloproteinase Image-guided surgery Glioma Fluorescence molecular tomography 

Notes

Acknowledgements

The authors thank Adjunct Assistant Professor Dr. Karen M. von Deneen from the University of Florida for her English editing of this paper.

Funding Information

This work was supported by the National Natural Science Foundation of China (81227901, 81470083, 81527805, and 61231004), the Research and Development Program of China (973) under Grant (2014CB748600, 2015CB755500), the Strategic Priority Research Program from the Chinese Academy of Sciences under Grant No. XDB02060010, the International Innovation Team of CAS under Grant No. 20140491524, Beijing Municipal Science & Technology Commission No. Z161100002616022, and Beijing Natural Science Foundation (Z16110200010000).

Compliance with Ethical Standards

All animal experiments were performed in accordance with the guidelines of the Institutional Animal Care and Use Committee (IACUC) at Peking University (Permit No.: 2011-0039).

Conflict of Interests

The authors declare that they have no conflict of interest.

Supplementary material

11307_2017_1158_MOESM1_ESM.pdf (476 kb)
ESM 1 (PDF 476 kb)

References

  1. 1.
    Avgeropoulos NG, Batchelor TT (1999) New treatment strategies for malignant gliomas. Oncologist 4(3):209–224PubMedGoogle Scholar
  2. 2.
    Nguyen QT, Olson ES, Aguilera TA, Jiang T, Scadeng M, Ellies LG, Tsien RY (2010) Surgery with molecular fluorescence imaging using activatable cell-penetrating peptides decreases residual cancer and improves survival. PNAS 107(9):4317–4322.  https://doi.org/10.1073/pnas.0910261107 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Chi C, Du Y, Ye J, Kou D, Qiu J, Wang J, Tian J, Chen X (2014) Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology. Theranostics 4(11):1072–1084.  https://doi.org/10.7150/thno.9899 CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Vahrmeijer AL, Hutteman M, Vorst JRVD et al (2013) Image-guided cancer surgery using near-infrared fluorescence. Nat Rev Clin Oncol 10(9):507–518.  https://doi.org/10.1038/nrclinonc.2013.123 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Ntziachristos V, Ripoll J, Wang LV, Weissleder R (2005) Looking and listening to light: the evolution of whole-body photonic imaging. Nat Biotechnol 23(3):313–320.  https://doi.org/10.1038/nbt1074 CrossRefPubMedGoogle Scholar
  6. 6.
    Nguyen QT, Tsien RY (2013) Fluorescence-guided surgery with live molecular navigation—a new cutting edge. Nat Rev Cancer 13(9):653–662.  https://doi.org/10.1038/nrc3566 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    van Dam GM, Themelis G, Crane LM, Harlaar NJ, Pleijhuis RG, Kelder W, Sarantopoulos A, de Jong JS, Arts HJ, van der Zee AG, Bart J, Low PS, Ntziachristos V (2011) Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-α targeting: first in-human results. Nat Med 17(10):1315–1319.  https://doi.org/10.1038/nm.2472 CrossRefPubMedGoogle Scholar
  8. 8.
    Vorst JRVD, Schaafsma BE, PhD MHM et al (2013) Near-infrared fluorescence-guided resection of colorectal liver metastases. Cancer 119(18):3411–3418.  https://doi.org/10.1002/cncr.28203 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Sugie T, Sawada T, Tagaya N, Kinoshita T, Yamagami K, Suwa H, Ikeda T, Yoshimura K, Niimi M, Shimizu A, Toi M (2013) Comparison of the indocyanine green fluorescence and blue dye methods in detection of sentinel lymph nodes in early-stage breast cancer. Ann Surg Oncol 20(7):2213–2218.  https://doi.org/10.1245/s10434-013-2890-0 CrossRefPubMedGoogle Scholar
  10. 10.
    Virostko J, Powers AC, Jansen ED (2007) Validation of luminescent source reconstruction using single-view spectrally resolved bioluminescence images. Appl Opt 46(13):2540–2547.  https://doi.org/10.1364/AO.46.002540 CrossRefPubMedGoogle Scholar
  11. 11.
    Deliolanis NC, Ntziachristos V (2013) Fluorescence molecular tomography of brain tumors in mice. Cold Spring Harb Protoc 2013:438CrossRefPubMedGoogle Scholar
  12. 12.
    Ntziachristos V, Tung CH, Bremer C, Weissleder R (2002) Fluorescence molecular tomography resolves protease activity in vivo. Nat Med 8(7):757–761.  https://doi.org/10.1038/nm729 CrossRefPubMedGoogle Scholar
  13. 13.
    Stearns ME, Wang M (1993) Type IV collagenase (M(r) 72,000) expression in human prostate: benign and malignant tissue. Cancer Res 53(4):878–883PubMedGoogle Scholar
  14. 14.
    Davies B, Waxman J, Wasan H et al (1993) Levels of matrix metalloproteases in bladder cancer correlate with tumor grade and invasion. Cancer Res 53:5365PubMedGoogle Scholar
  15. 15.
    Zucker S, Hymowitz M, Conner C et al (1999) Measurement of matrix metalloproteinases and tissue inhibitors of metalloproteinases in blood and tissues: clinical and experimental applications. Ann N Y Acad Sci 878(1 INHIBITION OF):212–227.  https://doi.org/10.1111/j.1749-6632.1999.tb07687.x CrossRefPubMedGoogle Scholar
  16. 16.
    Moses MA, Wiederschain D, Loughlin KR, Zurakowski D, Lamb CC, Freeman MR (1998) Increased incidence of matrix metalloproteinases in urine of cancer patients. Cancer Res 58(7):1395–1399PubMedGoogle Scholar
  17. 17.
    Bremer C, Bredow S, Mahmood U, Weissleder R, Tung CH (2001) Optical imaging of matrix metalloproteinase-2 activity in tumors: feasibility study in a mouse model. Radiology 221(2):523–529.  https://doi.org/10.1148/radiol.2212010368 CrossRefPubMedGoogle Scholar
  18. 18.
    Chi C, Zhang Q, Mao Y, Kou D, Qiu J, Ye J, Wang J, Wang Z, du Y, Tian J (2015) Increased precision of orthotopic and metastatic breast cancer surgery guided by matrix metalloproteinase-activatable near-infrared fluorescence probes. Sci Rep 5(1):14197.  https://doi.org/10.1038/srep14197 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Jacques SL (2013) Optical properties of biological tissues: a review. Phys Med Biol 58(11):R37–R61.  https://doi.org/10.1088/0031-9155/58/11/R37 CrossRefPubMedGoogle Scholar
  20. 20.
    Alexandrakis G, Rannou FR, Chatziioannou AF (2005) Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study. Phys Med Biol 50(17):4225–4241.  https://doi.org/10.1088/0031-9155/50/17/021 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Liu L, Du X, Cheng L (2013) Stable signal recovery via randomly enhanced adaptive subspace pursuit method. IEEE Signal Processing Letters 20:823–826CrossRefGoogle Scholar
  22. 22.
    Killion JJ, Radinsky R, Fidler IJ (1998) Orthotopic models are necessary to predict therapy of transplantable tumors in mice. Cancer Metastasis Rev 17(3):279–284.  https://doi.org/10.1023/A:1006140513233 CrossRefPubMedGoogle Scholar
  23. 23.
    Hu H, Liu J, Yao L et al (2012) Real-time bioluminescence and tomographic imaging of gastric cancer in a novel orthotopic mouse model. Oncol Rep 27:1937PubMedGoogle Scholar
  24. 24.
    Furnari FB, Fenton T, Bachoo RM, Mukasa A, Stommel JM, Stegh A, Hahn WC, Ligon KL, Louis DN, Brennan C, Chin L, DePinho RA, Cavenee WK (2007) Malignant astrocytic glioma: genetics, biology, and paths to treatment. Genes Dev 21(21):2683–2710.  https://doi.org/10.1101/gad.1596707 CrossRefPubMedGoogle Scholar
  25. 25.
    Wen PY, Kesari S (2008) Malignant gliomas in adults. NEJM 359(5):492–507.  https://doi.org/10.1056/NEJMra0708126 CrossRefPubMedGoogle Scholar
  26. 26.
    Sokolov K, Aaron J, Hsu B, Nida D, Gillenwater A, Follen M, MacAulay C, Adler-Storthz K, Korgel B, Descour M, Pasqualini R, Arap W, Lam W, Richards-Kortum R (2003) Optical systems for in vivo molecular imaging of cancer. Technol Cancer Res Treat 2(6):491–504.  https://doi.org/10.1177/153303460300200602 CrossRefPubMedGoogle Scholar
  27. 27.
    Cheong SJ, Lee CM, Kim EM, Uhm TB, Jeong HJ, Kim DW, Lim ST, Sohn MH (2011) Evaluation of the therapeutic efficacy of a VEGFR2-blocking antibody using sodium-iodide symporter molecular imaging in a tumor xenograft model. Nucl Med Biol 38(1):93–101.  https://doi.org/10.1016/j.nucmedbio.2010.05.009 CrossRefPubMedGoogle Scholar
  28. 28.
    Ntziachristos V (2006) Fluorescence molecular imaging. Annu Rev Biomed Eng 8(1):1–33.  https://doi.org/10.1146/annurev.bioeng.8.061505.095831 CrossRefPubMedGoogle Scholar
  29. 29.
    Alimohamadi M, Shirani M, Shariat-Moharreri R et al (2016) Application of awake craniotomy and intraoperative brain mapping for surgical resection of insular gliomas of the dominant hemisphere. World Neurosurg 92:151–158.  https://doi.org/10.1016/j.wneu.2016.04.079 CrossRefPubMedGoogle Scholar
  30. 30.
    Weissleder R (1999) Molecular imaging: exploring the next frontier. Radiology 212(3):609–614.  https://doi.org/10.1148/radiology.212.3.r99se18609 CrossRefPubMedGoogle Scholar
  31. 31.
    Ale A, Ermolayev V, Deliolanis NC, Ntziachristos V (2013) Fluorescence background subtraction technique for hybrid fluorescence molecular tomography/x-ray computed tomography imaging of a mouse model of early stage lung cancer. J Biomed Opt 18(5):56006.  https://doi.org/10.1117/1.JBO.18.5.056006 CrossRefPubMedGoogle Scholar
  32. 32.
    Kessenbrock K, Plaks V, Werb Z (2010) Matrix metalloproteinases: regulators of the tumor microenvironment. Cell 141(1):52–67.  https://doi.org/10.1016/j.cell.2010.03.015 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© World Molecular Imaging Society 2017

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringSoochow UniversitySuzhouChina
  2. 2.CAS Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of AutomationChinese Academy of SciencesBeijingChina

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