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MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma

  • Clinical Study
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Abstract

Purpose

Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients.

Methods

21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and l-Ferritin.

Results

Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the l-ferritin positivity percent (r = 0.56, p = 0.018) and the combination of tumor’s enhancing zone and necrotic core and the l-Ferritin positivity percent (r = 0.72; p = 0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p = 0.034) and CD86 (r = 0.7 p = 0.001), but not for CD206 (ρ = 0.09; p = 0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r = 0.6, p = 0.016). Similarly, mean R2* values significantly correlated with CD86 (r = 0.54, p = 0.03) but not with CD206 (r = 0.15, p = 0.5).

Conclusions

This study demonstrated the potential of MR quantitative susceptibility mapping as a non-invasive method for in vivo TAM quantification and phenotyping. Validation of these findings with large multicenter studies is needed.

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Data availability

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

References

  1. Thakkar JP, Dolecek TA, Horbinski C, Ostrom QT, Lightner DD, Barnholtz-Sloan JS et al (2014) Epidemiologic and molecular prognostic review of glioblastoma. Cancer Epidemiol, Biomark Prev 23:1985–199610

    CAS  Google Scholar 

  2. Pombo Antunes AR, Scheyltjens I, Duerinck J, Neyns B, Movahedi K, Van Ginderachter JA (2020) Understanding the glioblastoma immune microenvironment as basis for the development of new immunotherapeutic strategies. eLife 9:e52176

    PubMed  PubMed Central  Google Scholar 

  3. Chen Z, Hambardzumyan D (2018) Immune microenvironment in glioblastoma subtypes. Front Immunol 9:1004

    PubMed  PubMed Central  Google Scholar 

  4. Sampson JH, Gunn MD, Fecci PE, Ashley DM (2020) Brain immunology and immunotherapy in brain tumours. Nat Res 20:12–25

    CAS  Google Scholar 

  5. Morisse MC, Jouannet S, Dominguez-Villar M, Sanson M, Idbaih A (2018) Interactions between tumor-associated macrophages and tumor cells in glioblastoma: unraveling promising targeted therapies. Expert Rev Neurother 18(9):729–737

    CAS  PubMed  Google Scholar 

  6. Pfeifhofer-Obermair C, Tymoszuk P, Petzer V, Weiss G, Nairz M (2018) Iron in the tumor microenvironment-connecting the dots. Front Oncol 8:549

    PubMed  PubMed Central  Google Scholar 

  7. Recalcati S, Locati M, Marini A, Santambrogio P, Zaninotto F, De Pizzol M et al (2010) Differential regulation of iron homeostasis during human macrophage polarized activation. Eur J Immunol 40(3):824–835

    CAS  PubMed  Google Scholar 

  8. Sica A, Erreni M, Allavena P, Porta C (2015) Macrophage polarization in pathology. Birkhauser Verlag AG, Basel, pp 4111–4126

    Google Scholar 

  9. Leblond MM, Pérès EA, Helaine C, Gérault AN, Moulin D, Anfray C et al (2017) M2 macrophages are more resistant than M1 macrophages following radiation therapy in the context of glioblastoma. Oncotarget 8(42):72597–72612

    PubMed  PubMed Central  Google Scholar 

  10. Pollard JW (2004) Tumour-educated macrophages promote tumour progression and metastasis. European Association for Cardio-Thoracic Surgery, Windsor, pp 71–78

    Google Scholar 

  11. Wang Q, He Z, Huang M, Liu T, Wang Y, Xu H et al (2018) Vascular niche IL-6 induces alternative macrophage activation in glioblastoma through HIF-2α. Nat Commun 9(1):559

    PubMed  PubMed Central  Google Scholar 

  12. Zhou K, Cheng T, Zhan J, Peng X, Zhang Y, Wen J et al (2020) Targeting tumor-associated macrophages in the tumor microenvironment. Oncol Lett 20(5):234

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Aquino D, Gioppo A, Finocchiaro G, Bruzzone MG, Cuccarini V (2017) MRI in glioma immunotherapy: evidence, pitfalls, and perspectives. J Immunol Res 2017:5813951

    PubMed  PubMed Central  Google Scholar 

  14. Klemm F, Maas RR, Bowman RL, Kornete M, Soukup K, Nassiri S et al (2020) Interrogation of the microenvironmental landscape in brain tumors reveals disease-specific alterations of immune cells. Cell 181(7):1643-60e17

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Tan AC, Ashley DM, López GY, Malinzak M, Friedman HS, Khasraw M (2020) Management of glioblastoma: State of the art and future directions. Cancer J Clin 70(4):299–312

    Google Scholar 

  16. Haacke EM, Cheng NYC, House MJ, Liu Q, Neelavalli J, Ogg RJ et al (2005) Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging 23(1):1–25

    CAS  PubMed  Google Scholar 

  17. Liu C, Li W, Tong KA, Yeom KW, Kuzminski S (2015) Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain. Wiley, New York, pp 23–41

    Google Scholar 

  18. Duyn J (2013) MR susceptibility imaging. J Magn Reson 229:198–207

    CAS  PubMed  Google Scholar 

  19. Leftin A, Ben-Chetrit N, Klemm F, Joyce JA, Koutcher JA (2017) Iron imaging reveals tumor and metastasis macrophage hemosiderin deposits in breast cancer. PLoS ONE 12(9):e0184765

    PubMed  PubMed Central  Google Scholar 

  20. Leftin A, Zhao H, Turkekul M, de Stanchina E, Manova K, Koutcher JA (2017) Iron deposition is associated with differential macrophage infiltration and therapeutic response to iron chelation in prostate cancer. Sci Rep 7(1):11632

    PubMed  PubMed Central  Google Scholar 

  21. Schenck JF (1996) The role of magnetic susceptibility in magnetic resonance imaging: MRI magnetic compatibility of the first and second kinds. Med Phys 23(6):815–850

    CAS  PubMed  Google Scholar 

  22. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK et al (2016) The 2016 world health organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6):803–820

    PubMed  Google Scholar 

  23. Bankhead P, Loughrey MB, Fernández JA, Dombrowski Y, McArt DG, Dunne PD et al (2017) QuPath: ppen source software for digital pathology image analysis. Sci Rep 7(1):1–7

    CAS  Google Scholar 

  24. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31(3):1116–1128

    PubMed  Google Scholar 

  25. Liu T, Liu J, De Rochefort L, Spincemaille P, Khalidov I, Ledoux JR et al (2011) Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging. Magn Reson Med 66(3):777–783

    PubMed  Google Scholar 

  26. Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17(3):143–155

    PubMed  PubMed Central  Google Scholar 

  27. Bilgic B, Fan AP, Polimeni JR, Cauley SF, Bianciardi M, Adalsteinsson E et al (2014) Fast quantitative susceptibility mapping with L1-regularization and automatic parameter selection. Magn Reson Med 72(5):1444–1459

    PubMed  Google Scholar 

  28. Langkammer C, Schweser F, Shmueli K, Kames C, Li X, Guo L et al (2018) Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge. Magn Reson Med 79(3):1661–1673

    CAS  PubMed  Google Scholar 

  29. Sun H, Wilman AH (2014) Background field removal using spherical mean value filtering and Tikhonov regularization. Magn Reson Med 71(3):1151–1157

    PubMed  Google Scholar 

  30. Chavhan GB, Babyn PS, Thomas B, Shroff MM, Mark Haacke E (2009) Principles, techniques, and applications of T2*-based MR imaging and its special applications. Radiographics 29(5):1433–1449

    PubMed  PubMed Central  Google Scholar 

  31. Beard JL, Connor JR, Jones BC (1993) Iron in the brain. Oxford Academic, Oxford, pp 157–170

    Google Scholar 

  32. Connor JR, Menzies SL (1995) Cellular management of iron in the brain. J Neurol Sci 134(SUPPL):33–44

    CAS  PubMed  Google Scholar 

  33. Matsuda KM, Lopes-Calcas A, Honke ML, O’Brien-Moran Z, Buist R, West M et al (2017) Ex vivo tissue imaging for radiology-pathology correlation: a pilot study with a small bore 7-T MRI in a rare pigmented ganglioglioma exhibiting complex MR signal characteristics associated with melanin and hemosiderin. J Med Imaging (Bellingham, Wash) 4(3):036001

    Google Scholar 

  34. Leftin A, Ben-Chetrit N, Joyce JA, Koutcher JA (2019) Imaging endogenous macrophage iron deposits reveals a metabolic biomarker of polarized tumor macrophage infiltration and response to CSF1R breast cancer immunotherapy. Sci Rep 9(1):857

    PubMed  PubMed Central  Google Scholar 

  35. Iv M, Samghabadi P, Holdsworth S, Gentles A, Rezaii P, Harsh G et al (2019) Quantification of macrophages in high-grade gliomas by using ferumoxytol-enhanced MRI: a pilot study. Radiology 290(1):198–206

    PubMed  Google Scholar 

  36. Zhou J, Reddy MV, Wilson BKJ, Blair DA, Taha A, Frampton CM et al (2018) MR imaging characteristics associate with tumor-associated macrophages in glioblastoma and provide an improved signature for survival prognostication. Am J Neuroradiol 39(2):252–259

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Zhang M, Hutter G, Kahn SA, Azad TD, Gholamin S, Xu CY et al (2016) Anti-CD47 treatment stimulates phagocytosis of glioblastoma by M1 and M2 polarized macrophages and promotes M1 polarized macrophages in vivo. PLoS ONE 11(4):e0153550

    PubMed  PubMed Central  Google Scholar 

  38. Li F, Lv B, Liu Y, Hua T, Han J, Sun C et al (2018) Blocking the CD47-SIRPα axis by delivery of anti-CD47 antibody induces antitumor effects in glioma and glioma stem cells. OncoImmunology 7(2):e1391973

    PubMed  Google Scholar 

  39. Hoves S, Ooi CH, Wolter C, Sade H, Bissinger S, Schmittnaegel M et al (2018) Rapid activation of tumor-associated macrophages boosts preexisting tumor immunity. J Exp Med 215(3):859–876

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Urban-Wojciuk Z, Khan MM, Oyler BL, Fåhraeus R, Marek-Trzonkowska N, Nita-Lazar A et al (2019) The role of TLRs in anti-cancer Immunity and tumor rejection. Front Immunol 10:2388

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Alvarado AG, Thiagarajan PS, Mulkearns-Hubert EE, Silver DJ, Hale JS, Alban TJ et al (2017) Glioblastoma cancer stem cells evade innate immune suppression of self-renewal through reduced TLR4 expression. Cell Stem Cell 20(4):450-61e4

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Akkari L, Bowman RL, Tessier J, Klemm F, Handgraaf SM, de Groot M et al (2020) Dynamic changes in glioma macrophage populations after radiotherapy reveal CSF-1R inhibition as a strategy to overcome resistance. Sci Transl Med. https://doi.org/10.1126/scitranslmed.aaw7843

    Article  PubMed  Google Scholar 

  43. Pires-Afonso Y, Niclou SP, Michelucci A (2020) Revealing and harnessing tumour-associated microglia/macrophage heterogeneity in glioblastoma. Int J Mol Sci 21(3):689

    CAS  PubMed Central  Google Scholar 

  44. Shenoy G, Madhankumar A, Slagle-Webb B, Mrowczynski O, Schell T, Nesterova D et al (2019) TMIC-31. Impact of iron on macrophage immune phenotype in the glioblastoma tumor microenvironment. Neurooncology 21(Supplement_6):vi254-vi

    Google Scholar 

  45. Mukherjee S, Sonanini D, Maurer A, Daldrup-Link HE (2019) The yin and yang of imaging tumor associated macrophages with PET and MRI. Theranostics 9(25):7730–7748

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Ammer LM, Vollmann-Zwerenz A, Ruf V, Wetzel CH, Riemenschneider MJ, Albert NL et al (2020) The role of translocator protein TSPO in hallmarks of glioblastoma. Cancers 12(10):2973

    CAS  PubMed Central  Google Scholar 

  47. Adler DH, Wisse LEM, Ittyerah R, Pluta JB, Ding SL, Xie L et al (2018) Characterizing the human hippocampus in aging and Alzheimer’s disease using a computational atlas derived from ex vivo MRI and histology. Proc Natl Acad Sci USA 115(16):4252–4257

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H et al (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science (New York, NY) 344(6190):1396–1401

    CAS  Google Scholar 

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Funding

McCabe Fund Award granted to S.A.N from the Perelman School of Medicine, University of Pennsylvania.

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Authors

Contributions

Conceptualization: MN, AN, AN, SCG, YF, JBW, WRW, RR, SJB, AD, DMO, SB. Acquisition of data: AN, SCG, MP, JBW. Preprocessing of images: AN, SCG. Writing—original draft preparation: AN, SCG, AN. Writing—review and editing: AN, SCG, MP, JBW, HA, SKI, BFM, YF, WRW, RR, SJB, AD, DMO, SB, MN, AN.

Corresponding author

Correspondence to Ali Nabavizadeh.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments.

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Nazem, A., Guiry, S.C., Pourfathi, M. et al. MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma. J Neurooncol 156, 645–653 (2022). https://doi.org/10.1007/s11060-022-03947-3

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  • DOI: https://doi.org/10.1007/s11060-022-03947-3

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