Amir Nazem1,2, Samantha C Guiry1,3, MacLean Nasrallah4,5, Ali Nabavizadeh6,7, Mehrdad Pourfathi1,8,9, Jeffrey B Ware1, Hannah Anderson1, Srikant Kamesh Iyer1, Brianna F Moon1, Yi Fan10, Walter R Witschey1, Rahim Rizi1, Stephen J Bagley11,5, Arati Desai11,5, Donald M O'Rourke11,8,5, Steven Brem11,8,5. 1. Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, 1 Silverstein Building, 3400 Spruce St., Philadelphia, PA, 19104, USA. 2. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55901, USA. 3. New York Medical College School of Medicine, Valhalla, NY, 10595, USA. 4. Division of Neuropathology, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. 5. Glioblastoma Translational Center of Excellence, University of Pennsylvania, Philadelphia, PA, 19104, USA. 6. Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, 1 Silverstein Building, 3400 Spruce St., Philadelphia, PA, 19104, USA. ali.nabavizadeh@pennmedicine.upenn.edu. 7. Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, 19104, USA. ali.nabavizadeh@pennmedicine.upenn.edu. 8. Department of Neurosurgery, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA. 9. Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA. 10. Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. 11. Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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.
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.
Authors: Florian Klemm; Roeltje R Maas; Robert L Bowman; Mara Kornete; Klara Soukup; Sina Nassiri; Jean-Philippe Brouland; Christine A Iacobuzio-Donahue; Cameron Brennan; Viviane Tabar; Philip H Gutin; Roy T Daniel; Monika E Hegi; Johanna A Joyce Journal: Cell Date: 2020-05-28 Impact factor: 41.582
Authors: Ana Rita Pombo Antunes; Isabelle Scheyltjens; Johnny Duerinck; Bart Neyns; Kiavash Movahedi; Jo A Van Ginderachter Journal: Elife Date: 2020-02-04 Impact factor: 8.140