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Liu P, Zeng YP, Qu H, Zheng WY, Zhou TX, Hang LF, Jiang GH. Multiparametric simultaneous hybrid 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ( 18F-FDG PET/MRI) incorporating intratumoral and peritumoral regions for grading of glioma. Quant Imaging Med Surg 2024; 14:5665-5681. [PMID: 39144048 PMCID: PMC11320556 DOI: 10.21037/qims-24-280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 05/30/2024] [Indexed: 08/16/2024]
Abstract
Background Preoperative grading gliomas is essential for therapeutic clinical decision-making. Current non-invasive imaging modality for glioma grading were primarily focused on magnetic resonance imaging (MRI) or positron emission tomography (PET) of the tumor region. However, these methods overlook the peritumoral region (PTR) of tumor and cannot take full advantage of the biological information derived from hybrid-imaging. Therefore, we aimed to combine multiparameter from hybrid 18F-fluorodeoxyglucose (18F-FDG) PET/MRI of the solid component and PTR were combined for differentiating high-grade glioma (HGG) from low-grade glioma (LGG). Methods A total of 76 patients with pathologically confirmed glioma (41 HGG and 35 LGG) who underwent simultaneous 18F-FDG PET, arterial spin labelling (ASL), and diffusion-weighted imaging (DWI) with hybrid PET/MRI were retrospectively enrolled. The relative maximum standardized uptake value (rSUVmax), relative cerebral blood flow (rCBF), and relative minimum apparent diffusion coefficient (rADCmin) for the solid component and PTR at different distances outside tumoral border were compared. Receiver operating characteristic (ROC) curves were applied to assess the grading performance. A nomogram for HGG prediction was constructed. Results HGGs displayed higher rSUVmax and rCBF but lower rADCmin in the solid component and 5 mm-adjacent PTR, lower rADCmin in 10 mm-adjacent PTR, and higher rCBF in 15- and 20-mm-adjacent PTR. rSUVmax in solid component performed best [area under the curve (AUC) =0.865] as a single parameter for grading. Combination of rSUVmax in the solid component and adjacent 20 mm performed better (AUC =0.881). Integration of all 3 indicators in the solid component and adjacent 20 mm performed the best (AUC =0.928). The nomogram including rSUVmax, rCBF, and rADCmin in the solid component and 5-mm-adjacent PTR predicted HGG with a concordance index (C-index) of 0.906. Conclusions Multiparametric 18F-FDG PET/MRI from the solid component and PTR performed excellently in differentiating HGGs from LGGs. It can be used as a non-invasive and effective tool for preoperative grade stratification of patients with glioma, and can be considered in clinical practice.
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Affiliation(s)
- Ping Liu
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital, Jinan University, Guangzhou, China
| | - Yu-Ping Zeng
- Department of Medical Imaging, Ganzhou People’s Hospital, Ganzhou, China
- Department of Nuclear Medicine, Guangzhou Universal Medical Imaging Diagnostic Center, Guangzhou, China
| | - Hong Qu
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital, Jinan University, Guangzhou, China
| | - Wan-Yi Zheng
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital, Jinan University, Guangzhou, China
| | - Tian-Xing Zhou
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Li-Feng Hang
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Gui-Hua Jiang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital, Jinan University, Guangzhou, China
- Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, China
- Guangzhou Key Laboratory of Molecular Functional Imaging and Artificial Intelligence for Major Brain Diseases, The Affiliated Guangdong Second Provincial General Hospital, Jinan University, Guangzhou, China
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Jiao C, Lao Y, Zhang W, Braunstein S, Salans M, Villanueva-Meyer JE, Hervey-Jumper SL, Yang B, Morin O, Valdes G, Fan Z, Shiroishi M, Zada G, Sheng K, Yang W. Multi-modal fusion and feature enhancement U-Net coupling with stem cell niches proximity estimation for voxel-wise GBM recurrence prediction . Phys Med Biol 2024; 69:10.1088/1361-6560/ad64b8. [PMID: 39019073 PMCID: PMC11308744 DOI: 10.1088/1361-6560/ad64b8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 07/17/2024] [Indexed: 07/19/2024]
Abstract
Objective.We aim to develop a Multi-modal Fusion and Feature Enhancement U-Net (MFFE U-Net) coupling with stem cell niche proximity estimation to improve voxel-wise Glioblastoma (GBM) recurrence prediction.Approach.57 patients with pre- and post-surgery magnetic resonance (MR) scans were retrospectively solicited from 4 databases. Post-surgery MR scans included two months before the clinical diagnosis of recurrence and the day of the radiologicaly confirmed recurrence. The recurrences were manually annotated on the T1ce. The high-risk recurrence region was first determined. Then, a sparse multi-modal feature fusion U-Net was developed. The 50 patients from 3 databases were divided into 70% training, 10% validation, and 20% testing. 7 patients from the 4th institution were used as external testing with transfer learning. Model performance was evaluated by recall, precision, F1-score, and Hausdorff Distance at the 95% percentile (HD95). The proposed MFFE U-Net was compared to the support vector machine (SVM) model and two state-of-the-art neural networks. An ablation study was performed.Main results.The MFFE U-Net achieved a precision of 0.79 ± 0.08, a recall of 0.85 ± 0.11, and an F1-score of 0.82 ± 0.09. Statistically significant improvement was observed when comparing MFFE U-Net with proximity estimation couple SVM (SVMPE), mU-Net, and Deeplabv3. The HD95 was 2.75 ± 0.44 mm and 3.91 ± 0.83 mm for the 10 patients used in the model construction and 7 patients used for external testing, respectively. The ablation test showed that all five MR sequences contributed to the performance of the final model, with T1ce contributing the most. Convergence analysis, time efficiency analysis, and visualization of the intermediate results further discovered the characteristics of the proposed method.Significance. We present an advanced MFFE learning framework, MFFE U-Net, for effective voxel-wise GBM recurrence prediction. MFFE U-Net performs significantly better than the state-of-the-art networks and can potentially guide early RT intervention of the disease recurrence.
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Affiliation(s)
- Changzhe Jiao
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Yi Lao
- Department of Radiation Oncology, UC Los Angeles, Los Angeles, CA 90095
| | - Wenwen Zhang
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Steve Braunstein
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Mia Salans
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | | | | | - Bo Yang
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Olivier Morin
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Gilmer Valdes
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Zhaoyang Fan
- Department of Radiology, University of Southern California, Los Angeles, CA 90033
| | - Mark Shiroishi
- Department of Radiology, University of Southern California, Los Angeles, CA 90033
| | - Gabriel Zada
- Department of Neurosurgery, University of Southern California, Los Angeles, CA 90033
| | - Ke Sheng
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
| | - Wensha Yang
- Department of Radiation Oncology, UC San Francisco, San Francisco, CA 94143
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Zhou J, Hou Z, Tian C, Zhu Z, Ye M, Chen S, Yang H, Zhang X, Zhang B. Review of tracer kinetic models in evaluation of gliomas using dynamic contrast-enhanced imaging. Front Oncol 2024; 14:1380793. [PMID: 38947892 PMCID: PMC11211364 DOI: 10.3389/fonc.2024.1380793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/29/2024] [Indexed: 07/02/2024] Open
Abstract
Glioma is the most common type of primary malignant tumor of the central nervous system (CNS), and is characterized by high malignancy, high recurrence rate and poor survival. Conventional imaging techniques only provide information regarding the anatomical location, morphological characteristics, and enhancement patterns. In contrast, advanced imaging techniques such as dynamic contrast-enhanced (DCE) MRI or DCE CT can reflect tissue microcirculation, including tumor vascular hyperplasia and vessel permeability. Although several studies have used DCE imaging to evaluate gliomas, the results of data analysis using conventional tracer kinetic models (TKMs) such as Tofts or extended-Tofts model (ETM) have been ambiguous. More advanced models such as Brix's conventional two-compartment model (Brix), tissue homogeneity model (TH) and distributed parameter (DP) model have been developed, but their application in clinical trials has been limited. This review attempts to appraise issues on glioma studies using conventional TKMs, such as Tofts or ETM model, highlight advancement of DCE imaging techniques and provides insights on the clinical value of glioma management using more advanced TKMs.
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Affiliation(s)
- Jianan Zhou
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zujun Hou
- The Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
| | - Chuanshuai Tian
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zhengyang Zhu
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Meiping Ye
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Sixuan Chen
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Huiquan Yang
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Xin Zhang
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
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Begagić E, Bečulić H, Džidić-Krivić A, Kadić Vukas S, Hadžić S, Mekić-Abazović A, Šegalo S, Papić E, Muchai Echengi E, Pugonja R, Kasapović T, Kavgić D, Nuhović A, Juković-Bihorac F, Đuričić S, Pojskić M. Understanding the Significance of Hypoxia-Inducible Factors (HIFs) in Glioblastoma: A Systematic Review. Cancers (Basel) 2024; 16:2089. [PMID: 38893207 PMCID: PMC11171068 DOI: 10.3390/cancers16112089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/25/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND The study aims to investigate the role of hypoxia-inducible factors (HIFs) in the development, progression, and therapeutic potential of glioblastomas. METHODOLOGY The study, following PRISMA guidelines, systematically examined hypoxia and HIFs in glioblastoma using MEDLINE (PubMed), Web of Science, and Scopus. A total of 104 relevant studies underwent data extraction. RESULTS Among the 104 studies, global contributions were diverse, with China leading at 23.1%. The most productive year was 2019, accounting for 11.5%. Hypoxia-inducible factor 1 alpha (HIF1α) was frequently studied, followed by hypoxia-inducible factor 2 alpha (HIF2α), osteopontin, and cavolin-1. Commonly associated factors and pathways include glucose transporter 1 (GLUT1) and glucose transporter 3 (GLUT3) receptors, vascular endothelial growth factor (VEGF), phosphoinositide 3-kinase (PI3K)-Akt-mechanistic target of rapamycin (mTOR) pathway, and reactive oxygen species (ROS). HIF expression correlates with various glioblastoma hallmarks, including progression, survival, neovascularization, glucose metabolism, migration, and invasion. CONCLUSION Overcoming challenges such as treatment resistance and the absence of biomarkers is critical for the effective integration of HIF-related therapies into the treatment of glioblastoma with the aim of optimizing patient outcomes.
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Affiliation(s)
- Emir Begagić
- Department of General Medicine, School of Medicine, University of Zenica, 72000 Zenica, Bosnia and Herzegovina
| | - Hakija Bečulić
- Department of Neurosurgery, Cantonal Hospital Zenica, 72000 Zenica, Bosnia and Herzegovina;
- Department of Anatomy, School of Medicine, University of Zenica, 72000 Zenica, Bosnia and Herzegovina
| | - Amina Džidić-Krivić
- Department of Neurology, Cantonal Hospital Zenica, 72000 Zenica, Bosnia and Herzegovina (S.K.V.)
| | - Samra Kadić Vukas
- Department of Neurology, Cantonal Hospital Zenica, 72000 Zenica, Bosnia and Herzegovina (S.K.V.)
| | - Semir Hadžić
- Department of Physiology, Faculty of Medicine, University of Tuzla, 75000 Tuzla, Bosnia and Herzegovina
| | - Alma Mekić-Abazović
- Department of Oncology, Cantonal Hospital Zenica, 72000 Zenica, Bosnia and Herzegovina
| | - Sabina Šegalo
- Department of Laboratory Technologies, Faculty of Health Studies, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina; (S.Š.); (E.P.)
| | - Emsel Papić
- Department of Laboratory Technologies, Faculty of Health Studies, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina; (S.Š.); (E.P.)
| | - Emmanuel Muchai Echengi
- College of Health Sciences, School of Medicine, Kenyatta University, Nairobi 43844-00100, Kenya
| | - Ragib Pugonja
- Department of Anatomy, School of Medicine, University of Zenica, 72000 Zenica, Bosnia and Herzegovina
| | - Tarik Kasapović
- Department of Physiology, Faculty of Medicine, University of Tuzla, 75000 Tuzla, Bosnia and Herzegovina
| | - Dalila Kavgić
- Department of Physiology, Faculty of Medicine, University of Tuzla, 75000 Tuzla, Bosnia and Herzegovina
| | - Adem Nuhović
- Department of General Medicine, School of Medicine, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina;
| | - Fatima Juković-Bihorac
- Department of Pathology, Cantonal Hospital Zenica, 72000 Zenica, Bosnia and Herzegovina
- Department of Pathology, School of Medicine, University of Zenica, 72000 Zenica, Bosnia and Herzegovina;
| | - Slaviša Đuričić
- Department of Pathology, School of Medicine, University of Zenica, 72000 Zenica, Bosnia and Herzegovina;
| | - Mirza Pojskić
- Department of Neurosurgery, University Hospital Marburg, 35033 Marburg, Germany
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Du S, Gong G, Liu R, Meng K, Yin Y. Advances in determining the gross tumor target volume for radiotherapy of brain metastases. Front Oncol 2024; 14:1338225. [PMID: 38779095 PMCID: PMC11109437 DOI: 10.3389/fonc.2024.1338225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/19/2024] [Indexed: 05/25/2024] Open
Abstract
Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.
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Affiliation(s)
- Shanshan Du
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Guanzhong Gong
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Rui Liu
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Kangning Meng
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yong Yin
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Álvarez-Torres MDM, Balaña C, Fuster-García E, Puig J, García-Gómez JM. Unlocking Bevacizumab's Potential: rCBV max as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients. Cancers (Basel) 2023; 16:161. [PMID: 38201588 PMCID: PMC10778147 DOI: 10.3390/cancers16010161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 12/27/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival. PURPOSES In this study, we aimed to analyze the influence of tumor vascularity on the benefit provided by BVZ and propose preoperative rCBVmax at the high angiogenic tumor habitat as a predictive biomarker to select patients who can benefit the most. METHODS Clinical and MRI data from 106 patients with glioblastoma IDH-wildtype have been analyzed. Thirty-nine of them received BVZ, and the remaining sixty-seven did not receive a second-line treatment. The ONCOhabitats method was used to automatically calculate rCBV. RESULTS We found a median survival from progression of 305 days longer for patients with moderate vascular tumors who received BVZ than those who did not receive any second-line treatment. This contrasts with patients with high-vascular tumors who only presented a median survival of 173 days longer when receiving BVZ. Furthermore, better responses to BVZ were found for the moderate-vascular group with a higher proportion of patients alive at 6, 12, 18, and 24 months after progression. CONCLUSIONS We propose rCBVmax as a potential biomarker to select patients who can benefit more from BVZ after tumor progression. In addition, we propose a threshold of 7.5 to stratify patients into moderate- and high-vascular groups to select the optimal second-line treatment.
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Affiliation(s)
- María del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Carmen Balaña
- Applied Research Group in Oncology (B-ARGO Group), Institut Catala d’Oncologia (ICO), Institut Investigació Germans Trias i Pujol (IGTP), 08916 Badalona, Spain;
| | - Elies Fuster-García
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Josep Puig
- Radiology Department CDI, Hospital Clinic of Barcelona, 08036 Barcelona, Spain;
| | - Juan Miguel García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
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7
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Trevisi G, Mangiola A. Current Knowledge about the Peritumoral Microenvironment in Glioblastoma. Cancers (Basel) 2023; 15:5460. [PMID: 38001721 PMCID: PMC10670229 DOI: 10.3390/cancers15225460] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 10/31/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
Glioblastoma is a deadly disease, with a mean overall survival of less than 2 years from diagnosis. Recurrence after gross total surgical resection and adjuvant chemo-radiotherapy almost invariably occurs within the so-called peritumoral brain zone (PBZ). The aim of this narrative review is to summarize the most relevant findings about the biological characteristics of the PBZ currently available in the medical literature. The PBZ presents several peculiar biological characteristics. The cellular landscape of this area is different from that of healthy brain tissue and is characterized by a mixture of cell types, including tumor cells (seen in about 30% of cases), angiogenesis-related endothelial cells, reactive astrocytes, glioma-associated microglia/macrophages (GAMs) with anti-inflammatory polarization, tumor-infiltrating lymphocytes (TILs) with an "exhausted" phenotype, and glioma-associated stromal cells (GASCs). From a genomic and transcriptomic point of view, compared with the tumor core and healthy brain tissue, the PBZ presents a "half-way" pattern with upregulation of genes related to angiogenesis, the extracellular matrix, and cellular senescence and with stemness features and downregulation in tumor suppressor genes. This review illustrates that the PBZ is a transition zone with a pre-malignant microenvironment that constitutes the base for GBM progression/recurrence. Understanding of the PBZ could be relevant to developing more effective treatments to prevent GBM development and recurrence.
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Affiliation(s)
- Gianluca Trevisi
- Department of Neurosciences, Imaging and Clinical Sciences, G. D’Annunzio University Chieti-Pescara, 66100 Chieti, Italy;
- Neurosurgical Unit, Ospedale Spirito Santo, 65122 Pescara, Italy
| | - Annunziato Mangiola
- Department of Neurosciences, Imaging and Clinical Sciences, G. D’Annunzio University Chieti-Pescara, 66100 Chieti, Italy;
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Wang X, Sun Y, Zhang DY, Ming GL, Song H. Glioblastoma modeling with 3D organoids: progress and challenges. OXFORD OPEN NEUROSCIENCE 2023; 2:kvad008. [PMID: 38596241 PMCID: PMC10913843 DOI: 10.1093/oons/kvad008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Glioblastoma (GBM) is the most aggressive adult primary brain tumor with nearly universal treatment resistance and recurrence. The mainstay of therapy remains maximal safe surgical resection followed by concurrent radiation therapy and temozolomide chemotherapy. Despite intensive investigation, alternative treatment options, such as immunotherapy or targeted molecular therapy, have yielded limited success to achieve long-term remission. This difficulty is partly due to the lack of pre-clinical models that fully recapitulate the intratumoral and intertumoral heterogeneity of GBM and the complex tumor microenvironment. Recently, GBM 3D organoids originating from resected patient tumors, genetic manipulation of induced pluripotent stem cell (iPSC)-derived brain organoids and bio-printing or fusion with non-malignant tissues have emerged as novel culture systems to portray the biology of GBM. Here, we highlight several methodologies for generating GBM organoids and discuss insights gained using such organoid models compared to classic modeling approaches using cell lines and xenografts. We also outline limitations of current GBM 3D organoids, most notably the difficulty retaining the tumor microenvironment, and discuss current efforts for improvements. Finally, we propose potential applications of organoid models for a deeper mechanistic understanding of GBM and therapeutic development.
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Affiliation(s)
- Xin Wang
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yusha Sun
- Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel Y Zhang
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Guo-li Ming
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hongjun Song
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- The Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- GBM Translational Center of Excellence, Abramson Cancer Center, University of Pennsylvania Philadelphia, PA 19104, USA
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Watowich MB, Gilbert MR, Larion M. T cell exhaustion in malignant gliomas. Trends Cancer 2023; 9:270-292. [PMID: 36681605 PMCID: PMC10038906 DOI: 10.1016/j.trecan.2022.12.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/20/2022] [Accepted: 12/22/2022] [Indexed: 01/21/2023]
Abstract
Despite advances in understanding tumor biology, malignant gliomas remain incurable. While immunotherapy has improved outcomes in other cancer types, comparable efficacy has not yet been demonstrated for primary cancers of the central nervous system (CNS). T cell exhaustion, defined as a progressive decrease in effector function, sustained expression of inhibitory receptors, metabolic dysfunction, and distinct epigenetic and transcriptional alterations, contributes to the failure of immunotherapy in the CNS. Herein, we describe recent advances in understanding the drivers of T cell exhaustion in the glioma microenvironment. We discuss the extrinsic and intrinsic factors that contribute to exhaustion and highlight potential avenues for reversing this phenotype. Our ability to directly target specific immunosuppressive drivers in brain cancers would be a major advance in immunotherapy.
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Affiliation(s)
- Matthew B Watowich
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mark R Gilbert
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mioara Larion
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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Zhang Q, Wu G, Yang Q, Dai G, Li T, Chen P, Li J, Huang W. Survival rate prediction of nasopharyngeal carcinoma patients based on MRI and gene expression using a deep neural network. Cancer Sci 2022; 114:1596-1605. [PMID: 36541519 PMCID: PMC10067413 DOI: 10.1111/cas.15704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 11/03/2022] [Accepted: 11/09/2022] [Indexed: 12/24/2022] Open
Abstract
To achieve a better treatment regimen and follow-up assessment design for intensity-modulated radiotherapy (IMRT)-treated nasopharyngeal carcinoma (NPC) patients, an accurate progression-free survival (PFS) time prediction algorithm is needed. We propose developing a PFS prediction model of NPC patients after IMRT treatment using a deep learning method and comparing that with the traditional texture analysis method. One hundred and fifty-one NPC patients were included in this retrospective study. T1-weighted, proton density and dynamic contrast-enhanced magnetic resonance (MR) images were acquired. The expression level of five genes (HIF-1α, EGFR, PTEN, Ki-67, and VEGF) and infection of Epstein-Barr (EB) virus were tested. A residual network was trained to predict PFS from MR images. The output as well as patient characteristics were combined using a linear regression model to provide a final PFS prediction. The prediction accuracy was compared with that of the traditional texture analysis method. A regression model combining the deep learning output with HIF-1α expression and Epstein-Barr infection provides the best PFS prediction accuracy (Spearman correlation R2 = 0.53; Harrell's C-index = 0.82; receiver operative curve [ROC] analysis area under the curve [AUC] = 0.88; log-rank test hazard ratio [HR] = 8.45), higher than a regression model combining texture analysis with HIF-1α expression (Spearman correlation R2 = 0.14; Harrell's C-index =0.68; ROC analysis AUC = 0.76; log-rank test HR = 2.85). The deep learning method does not require a manually drawn tumor region of interest. MR image processing using deep learning combined with patient characteristics can provide accurate PFS prediction for nasopharyngeal carcinoma patients and does not rely on specific kernels or tumor regions of interest, which is needed for the texture analysis method.
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Affiliation(s)
- Qihao Zhang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Gang Wu
- Department of Radiotherapy, Hainan General Hospital, Hainan, China
| | - Qianyu Yang
- Department of Radiology, Hainan General Hospital, Hainan, China
| | - Ganmian Dai
- Department of Radiology, Hainan General Hospital, Hainan, China
| | - Tiansheng Li
- Department of Radiology, Hainan General Hospital, Hainan, China
| | - Pianpian Chen
- Department of Pathology, Hainan General Hospital, Hainan, China
| | - Jiao Li
- Department of Pathology, Hainan General Hospital, Hainan, China
| | - Weiyuan Huang
- Department of Radiology, Hainan General Hospital, Hainan, China
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11
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Li X, Hu Y, Xie Y, Lu R, Li Q, Tao H, Chen S. Whole-tumor histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for soft tissue sarcoma: correlation with HIF-1alpha expression. Eur Radiol 2022; 33:3961-3973. [PMID: 36462043 DOI: 10.1007/s00330-022-09296-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 09/02/2022] [Accepted: 11/10/2022] [Indexed: 12/04/2022]
Abstract
OBJECTIVE To investigate the correlation of histogram metrics from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with HIF-1alpha expression in soft tissue sarcoma (STS). METHODS We enrolled 71 patients with STS who underwent 3.0-T MRI, including conventional MRI, DWI, and DCE-MRI sequences. Location, maximum tumor diameter, envelope, T2-weighted tumor heterogeneity, peritumoral edema, peritumoral enhancement, necrosis, tail-like pattern, bone invasion, and vessel/nerve invasion and/or encasement were determined using conventional MRI images. The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), Ktrans, Kep, and Ve maps. Independent-samples t test and one-way ANOVA were used for testing the differences between normally distributed categorical data with HIF-1alpha expression. Pearson and Spearman correlations and multiple linear regression analyses were performed to determine the correlations between histogram metrics and HIF-1alpha expression. Survival curves were plotted using the Kaplan-Meier method. RESULTS Regarding conventional MRI features, only highly heterogeneous on T2-weighted images (55.6 ± 19.9% vs. 45.4 ± 20.5%, p = 0.041) and more than 50% necrotic area (57.3 ± 20.4% vs. 43.9 ± 19.7%, p = 0.002) were prone to indicate STS with higher HIF-1alpha expression. Histogram metrics obtained from ADC (mean, median, 10th, and 25th percentile values), Ktrans (mean, median, 75th, and 90th percentile values), and Kep (90th percentile values) were significantly correlated with HIF-1alpha expression. Multiple linear regression analysis demonstrated that more than 50% necrosis, ADCskewness, Ktrans90th, and grade III were independently associated with HIF-1alpha expression. CONCLUSION DWI and DCE-MRI histogram parameters were significantly correlated with HIF-1alpha expression in STS. KEY POINTS • DWI and DCE-MRI histogram parameters are correlated with HIF-1alpha expression in STS. • More than 50% necrosis, ADCskewness, Ktrans90th, and grade III were independently associated with HIF-1alpha expression in STS.
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Affiliation(s)
- Xiangwen Li
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China
| | - Yiwen Hu
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China
| | - Yuxue Xie
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China
| | - Rong Lu
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China
| | - Qing Li
- MR Collaborations, Siemens Healthineers Ltd., Shanghai, China
| | - Hongyue Tao
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China.
| | - Shuang Chen
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China.
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, 2 middle Wulumuqizhong Road, Shanghai, China.
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12
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Assessment of Early Response to Lung Cancer Chemotherapy by Semiquantitative Analysis of Dynamic Contrast-Enhanced MRI. DISEASE MARKERS 2022; 2022:2669281. [PMID: 35915736 PMCID: PMC9338849 DOI: 10.1155/2022/2669281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/30/2022] [Accepted: 07/04/2022] [Indexed: 11/28/2022]
Abstract
Objective To evaluate the early chemotherapy response in patients with lung cancer using semiquantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). Methods Twenty-two patients with lung cancer treated with chemotherapy were subjected to DCE-MRI at two time points: before starting treatment and after one week of therapy. The image data were collected by DCE-MRI, and the semiquantitative parameters including positive enhancement integral (PEI), signal enhancement ratio (SER), maximum slope of increase (MSI), and time to peak (TTP) were calculated. After chemotherapy, the parameters and relevant variations between the responders and nonresponders were compared with Mann–Whitney U tests. Student's t-test for paired samples was used to evaluate the temporal changes between pre- and posttreatment images. Results The patients were categorized as 13 responders and 9 nonresponders based on the tumor response evaluation. After chemotherapy, the PEI, SER, and MSI were significantly increased in responders compared with the pretreatment values (P < 0.05), while no obvious decrease in TTP was observed (P > 0.05). However, 9 nonresponders showed no significant changes in PEI, SER, MSI, and TTP values, as compared with those of pretreatment (P > 0.05). Moreover, the increase of PEI was more dramatically in responders than in nonresponders (P < 0.05), but no significantly differences were observed in SER, MSI, and TTP (P > 0.05). Conclusion Semiquantitative analysis of DCE-MRI could provide a reliable noninvasive method for assessing early chemotherapy response in lung cancer patients.
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13
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Fatania K, Frood R, Tyyger M, McDermott G, Fernandez S, Shaw GC, Boissinot M, Salvatore D, Ottobrini L, Teh I, Wright J, Bailey MA, Koch-Paszkowski J, Schneider JE, Buckley DL, Murray L, Scarsbrook A, Short SC, Currie S. Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma. Cancers (Basel) 2022; 14:3485. [PMID: 35884545 PMCID: PMC9315674 DOI: 10.3390/cancers14143485] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/11/2022] [Accepted: 07/15/2022] [Indexed: 12/03/2022] Open
Abstract
Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.
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Affiliation(s)
- Kavi Fatania
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Russell Frood
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
| | - Marcus Tyyger
- Department of Medical Physics, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK; (M.T.); (G.M.)
| | - Garry McDermott
- Department of Medical Physics, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK; (M.T.); (G.M.)
| | - Sharon Fernandez
- Department of Clinical Oncology, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK;
| | - Gary C. Shaw
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Marjorie Boissinot
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Daniela Salvatore
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Segrate, Italy; (D.S.); (L.O.)
| | - Luisa Ottobrini
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Segrate, Italy; (D.S.); (L.O.)
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 20054 Segrate, Italy
| | - Irvin Teh
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - John Wright
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - Marc A. Bailey
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
- Leeds Vascular Institute, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK
| | - Joanna Koch-Paszkowski
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - Jurgen E. Schneider
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - David L. Buckley
- Biomedical Imaging Science Department, and Discovery & Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9TJ, UK; (I.T.); (J.W.); (M.A.B.); (J.K.-P.); (J.E.S.); (D.L.B.)
| | - Louise Murray
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
- Department of Clinical Oncology, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK;
| | - Andrew Scarsbrook
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
| | - Susan C. Short
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
- Department of Clinical Oncology, Leeds Teaching Hospitals Trust, St James’s University Hospital, Leeds LS9 7TF, UK;
| | - Stuart Currie
- Department of Radiology, Leeds Teaching Hospitals Trust, Leeds General Infirmary, Leeds LS1 3EX, UK; (R.F.); (A.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK; (G.C.S.); (M.B.); (L.M.); (S.C.S.)
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14
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Stumpo V, Guida L, Bellomo J, Van Niftrik CHB, Sebök M, Berhouma M, Bink A, Weller M, Kulcsar Z, Regli L, Fierstra J. Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions. Cancers (Basel) 2022; 14:cancers14051342. [PMID: 35267650 PMCID: PMC8909110 DOI: 10.3390/cancers14051342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Correspondence:
| | - Lelio Guida
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jacopo Bellomo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Christiaan Hendrik Bas Van Niftrik
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Moncef Berhouma
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, 69500 Lyon, France;
| | - Andrea Bink
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
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15
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Uceda-Castro R, van Asperen JV, Vennin C, Sluijs JA, van Bodegraven EJ, Margarido AS, Robe PAJ, van Rheenen J, Hol EM. GFAP splice variants fine-tune glioma cell invasion and tumour dynamics by modulating migration persistence. Sci Rep 2022; 12:424. [PMID: 35013418 PMCID: PMC8748899 DOI: 10.1038/s41598-021-04127-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 12/16/2021] [Indexed: 12/26/2022] Open
Abstract
Glioma is the most common form of malignant primary brain tumours in adults. Their highly invasive nature makes the disease incurable to date, emphasizing the importance of better understanding the mechanisms driving glioma invasion. Glial fibrillary acidic protein (GFAP) is an intermediate filament protein that is characteristic for astrocyte- and neural stem cell-derived gliomas. Glioma malignancy is associated with changes in GFAP alternative splicing, as the canonical isoform GFAPα is downregulated in higher-grade tumours, leading to increased dominance of the GFAPδ isoform in the network. In this study, we used intravital imaging and an ex vivo brain slice invasion model. We show that the GFAPδ and GFAPα isoforms differentially regulate the tumour dynamics of glioma cells. Depletion of either isoform increases the migratory capacity of glioma cells. Remarkably, GFAPδ-depleted cells migrate randomly through the brain tissue, whereas GFAPα-depleted cells show a directionally persistent invasion into the brain parenchyma. This study shows that distinct compositions of the GFAPnetwork lead to specific migratory dynamics and behaviours of gliomas.
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Affiliation(s)
- Rebeca Uceda-Castro
- Division of Molecular Pathology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jessy V van Asperen
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Claire Vennin
- Division of Molecular Pathology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jacqueline A Sluijs
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Emma J van Bodegraven
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Andreia S Margarido
- Division of Molecular Pathology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Pierre A J Robe
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, University Utrecht, Utrecht, The Netherlands
| | - Jacco van Rheenen
- Division of Molecular Pathology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
| | - Elly M Hol
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands.
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16
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Multiple Faces of the Glioblastoma Microenvironment. Int J Mol Sci 2022; 23:ijms23020595. [PMID: 35054779 PMCID: PMC8775531 DOI: 10.3390/ijms23020595] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 12/31/2021] [Accepted: 01/03/2022] [Indexed: 12/23/2022] Open
Abstract
The tumor microenvironment is a highly dynamic accumulation of resident and infiltrating tumor cells, responsible for growth and invasion. The authors focused on the leading-edge concepts regarding the glioblastoma microenvironment. Due to the fact that the modern trend in the research and treatment of glioblastoma is represented by multiple approaches that target not only the primary tumor but also the neighboring tissue, the study of the microenvironment in the peritumoral tissue is an appealing direction for current and future therapies.
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17
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van Asperen JV, Robe PA, Hol EM. GFAP Alternative Splicing and the Relevance for Disease – A Focus on Diffuse Gliomas. ASN Neuro 2022; 14:17590914221102065. [PMID: 35673702 PMCID: PMC9185002 DOI: 10.1177/17590914221102065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Glial fibrillary acidic protein (GFAP) is an intermediate filament protein that is
characteristic for astrocytes and neural stem cells, and their malignant analogues in
glioma. Since the discovery of the protein 50 years ago, multiple alternative splice
variants of the GFAP gene have been discovered, leading to different GFAP isoforms. In
this review, we will describe GFAP isoform expression from gene to protein to network,
taking the canonical isoforms GFAPα and the main alternative variant GFAPδ as the starting
point. We will discuss the relevance of studying GFAP and its isoforms in disease, with a
specific focus on diffuse gliomas.
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Affiliation(s)
- Jessy V. van Asperen
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Pierre A.J.T. Robe
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, University Utrecht, Utrecht, The Netherlands
| | - Elly M. Hol
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
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18
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Zou M, Zhao Z, Zhang B, Mao H, Huang Y, Wang C. Pulmonary lesions: correlative study of dynamic triple-phase enhanced CT perfusion imaging with tumor angiogenesis and vascular endothelial growth factor expression. BMC Med Imaging 2021; 21:158. [PMID: 34717573 PMCID: PMC8556962 DOI: 10.1186/s12880-021-00692-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 10/21/2021] [Indexed: 11/10/2022] Open
Abstract
Background To investigate value of the quantitative perfusion parameters of dynamic triple-phase enhanced CT in differential diagnosis of pulmonary lesions, and explore the correlation between perfusion parameters of lung cancer with microvessel density (MVD) and vascular endothelial growth factor (VEGF). Methods 73 consecutive patients with lung lesions who successfully underwent pre-operative CT perfusion examination with dynamic triple-phase enhanced CT and received a final diagnosis by postoperative pathology or a clinical follow-up. The cases were divided into malignant and benign groups according to the pathological results. CT perfusion parameters, such as Median, Mean, Standard deviation (Std), Q10, Q25, Q50, Q75, Q90 of pulmonary artery perfusion (PAP), bronchial artery perfusion (BAP), perfusion index (PI) and arterial enhancement fraction (AEF) were obtained by performing computed tomography perfusion imaging (CTPI). Computed tomography perfusion (CTP) parameters were compared between malignant and benign lesions. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CTP parameters in diagnosing malignant lesions. The correlations between CTP parameters with MVD and VEGF were analysed in 36 lung cancer patients who had extra sections be used for immunohistochemistry staining of CD34 and VEGF. Results BAP (Mean, Std, Q90) and PI Std of benign lesions were higher than malignant lesions (p < 0.05), and PAP (Q10, Q25), PI (Median, Mean, Q10, Q25, Q50) of malignant lesions were higher than the benign (p < 0.05). The area under the ROC curve of PI Mean, PI Q10 and PI Std was 0.722 (95% CI = [0.595–0.845]), 0.728 (95% CI = [0.612–0.844]) and 0.717 (95% CI = [0.598–0.835]) respectively. Partial perfusion parameters of BAP and AEF Q10 were positively correlated with MVD (p value range is < 0.001–0.037, ρ value range is 0.483–0.683), and partial perfusion parameters of PI were negatively correlated with MVD (p value range is 0.001–0.041,ρvalue range is − 0.523–− 0.343). Partial perfusion parameters of BAP and AEF Q10 were positively correlated with VEGF (p value range is 0.001–0.016, ρvalue range is 0.398–0.570), meanwhile some perfusion parameters of PAP and PI were negatively correlated with VEGF (p value range is 0.001–0.040, ρ value range is − 0.657–0.343). Conclusions Quantitative parameters of dynamic triple-phase enhanced CT can provide diagnostic basis for the differentiation of lung lesions, and there were connection with tumor angiogenesis and vascular endothelial growth factor expression.
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Affiliation(s)
- Mingyue Zou
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
| | - Zhenhua Zhao
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China.
| | - Bingqian Zhang
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
| | - Haijia Mao
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
| | - Yanan Huang
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
| | - Cheng Wang
- Department of Pathology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, 312000, China
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19
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Shen N, Zhang S, Cho J, Li S, Zhang J, Xie Y, Wang Y, Zhu W. Application of Cluster Analysis of Time Evolution for Magnetic Resonance Imaging -Derived Oxygen Extraction Fraction Mapping: A Promising Strategy for the Genetic Profile Prediction and Grading of Glioma. Front Neurosci 2021; 15:736891. [PMID: 34671241 PMCID: PMC8520989 DOI: 10.3389/fnins.2021.736891] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The intratumoral heterogeneity of oxygen metabolism and angiogenesis are core hallmarks of glioma, unveiling that genetic aberrations associated with magnetic resonance imaging (MRI) phenotypes may aid in the diagnosis and treatment of glioma. Objective: To explore the predictability of MRI-based oxygen extraction fraction (OEF) mapping using cluster analysis of time evolution (CAT) for genetic profiling and glioma grading. Methods: Ninety-one patients with histopathologically confirmed glioma were examined with CAT for quantitative susceptibility mapping and quantitative blood oxygen level–dependent magnitude-based OEF mapping and dynamic contrast-enhanced (DCE) MRI. Imaging biomarkers, including oxygen metabolism (OEF) and angiogenesis [volume transfer constant, cerebral blood volume (CBV), and cerebral blood flow], were investigated to predict IDH mutation, O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status, receptor tyrosine kinase (RTK) subgroup, and differentiation of glioblastoma (GBM) vs. lower-grade glioma (LGG). The corresponding DNA sequencing was also obtained. Results were compared with DCE-MRI using receiver operating characteristic (ROC) analysis. Results: IDH1-mutated LGGs exhibited significantly lower OEF and hypoperfusion than IDH wild-type tumors (all p < 0.01). OEF and perfusion metrics showed a tendency toward higher values in MGMT unmethylated GBM, but only OEF retained significance (p = 0.01). Relative prevalence of RTK alterations was associated with increased OEF (p = 0.003) and perfusion values (p < 0.05). ROC analysis suggested OEF achieved best performance for IDH mutation detection [area under the curve (AUC) = 0.828]. None of the investigated parameters enabled prediction of MGMT status except OEF with a moderate AUC of 0.784. Predictive value for RTK subgroup was acceptable by using OEF (AUC = 0.764) and CBV (AUC = 0.754). OEF and perfusion metrics demonstrated excellent performance in glioma grading. Moreover, mutational landscape revealed hypoxia or angiogenesis-relevant gene signatures were associated with specific imaging phenotypes. Conclusion: CAT for MRI-based OEF mapping is a promising technology for oxygen measurement and along with perfusion MRI can predict genetic profiles and tumor grade in a non-invasive and clinically relevant manner. Clinical Impact: Physiological imaging provides an in vivo portrait of genetic alterations in glioma and offers a potential strategy for non-invasively selecting patients for individualized therapies.
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Affiliation(s)
- Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ju Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Xie
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY, United States.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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20
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Tang X, Zuo C, Fang P, Liu G, Qiu Y, Huang Y, Tang R. Targeting Glioblastoma Stem Cells: A Review on Biomarkers, Signal Pathways and Targeted Therapy. Front Oncol 2021; 11:701291. [PMID: 34307170 PMCID: PMC8297686 DOI: 10.3389/fonc.2021.701291] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 06/25/2021] [Indexed: 12/12/2022] Open
Abstract
Glioblastoma (GBM) remains the most lethal and common primary brain tumor, even after treatment with multiple therapies, such as surgical resection, chemotherapy, and radiation. Although great advances in medical development and improvements in therapeutic methods of GBM have led to a certain extension of the median survival time of patients, prognosis remains poor. The primary cause of its dismal outcomes is the high rate of tumor recurrence, which is closely related to its resistance to standard therapies. During the last decade, glioblastoma stem cells (GSCs) have been successfully isolated from GBM, and it has been demonstrated that these cells are likely to play an indispensable role in the formation, maintenance, and recurrence of GBM tumors, indicating that GSCs are a crucial target for treatment. Herein, we summarize the current knowledge regarding GSCs, their related signaling pathways, resistance mechanisms, crosstalk linking mechanisms, and microenvironment or niche. Subsequently, we present a framework of targeted therapy for GSCs based on direct strategies, including blockade of the pathways necessary to overcome resistance or prevent their function, promotion of GSC differentiation, virotherapy, and indirect strategies, including targeting the perivascular, hypoxic, and immune niches of the GSCs. In summary, targeting GSCs provides a tremendous opportunity for revolutionary approaches to improve the prognosis and therapy of GBM, despite a variety of challenges.
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Affiliation(s)
- Xuejia Tang
- Department of Neurosurgery, University-Town Hospital of Chongqing Medical University, Chongqing, China.,Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Chenghai Zuo
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Pengchao Fang
- Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Guojing Liu
- Department of Neurosurgery, University-Town Hospital of Chongqing Medical University, Chongqing, China
| | - Yongyi Qiu
- Department of Neurosurgery, University-Town Hospital of Chongqing Medical University, Chongqing, China
| | - Yi Huang
- Department of Neurosurgery, The Ninth People's Hospital of Chongqing, Chongqing, China
| | - Rongrui Tang
- Department of Neurosurgery, University-Town Hospital of Chongqing Medical University, Chongqing, China
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21
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Jandrey EHF, Bezerra M, Inoue LT, Furnari FB, Camargo AA, Costa ÉT. A Key Pathway to Cancer Resilience: The Role of Autophagy in Glioblastomas. Front Oncol 2021; 11:652133. [PMID: 34178638 PMCID: PMC8222785 DOI: 10.3389/fonc.2021.652133] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 05/17/2021] [Indexed: 12/13/2022] Open
Abstract
There are no effective strategies for the successful treatment of glioblastomas (GBM). Current therapeutic modalities effectively target bulk tumor cells but leave behind marginal GBM cells that escape from the surgical margins and radiotherapy field, exhibiting high migratory phenotype and resistance to all available anti-glioma therapies. Drug resistance is mostly driven by tumor cell plasticity: a concept associated with reactivating transcriptional programs in response to adverse and dynamic conditions from the tumor microenvironment. Autophagy, or "self-eating", pathway is an emerging target for cancer therapy and has been regarded as one of the key drivers of cell plasticity in response to energy demanding stress conditions. Many studies shed light on the importance of autophagy as an adaptive mechanism, protecting GBM cells from unfavorable conditions, while others recognize that autophagy can kill those cells by triggering a non-apoptotic cell death program, called 'autophagy cell death' (ACD). In this review, we carefully analyzed literature data and conclude that there is no clear evidence indicating the presence of ACD under pathophysiological settings in GBM disease. It seems to be exclusively induced by excessive (supra-physiological) stress signals, mostly from in vitro cell culture studies. Instead, pre-clinical and clinical data indicate that autophagy is an emblematic example of the 'dark-side' of a rescue pathway that contributes profoundly to a pro-tumoral adaptive response. From a standpoint of treating the real human disease, only combinatorial therapy targeting autophagy with cytotoxic drugs in the adjuvant setting for GBM patients, associated with the development of less toxic and more specific autophagy inhibitors, may inhibit adaptive response and enhance the sensibility of glioma cells to conventional therapies.
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Affiliation(s)
| | - Marcelle Bezerra
- Molecular Oncology Center, Hospital Sírio-Libanês, São Paulo, Brazil
| | | | - Frank B. Furnari
- Ludwig Institute for Cancer Research, University of California San Diego (UCSD), San Diego, CA, United States
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22
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Keil VC, Gielen GH, Pintea B, Baumgarten P, Datsi A, Hittatiya K, Simon M, Hattingen E. DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study. Clin Neuroradiol 2021; 31:1049-1058. [PMID: 33900414 PMCID: PMC8648693 DOI: 10.1007/s00062-021-01015-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 03/22/2021] [Indexed: 12/29/2022]
Abstract
Purpose To explore the focal predictability of vascular growth factor expression and neovascularization using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in glioma. Methods 120 brain biopsies were taken in vital tumor, infiltration zone and normal brain tissue of 30 glioma patients: 17 IDH(isocitrate dehydrogenase)-wildtype glioblastoma (GBM), 1 IDH-wildtype astrocytoma °III (together prognostic group 1), 3 IDH-mutated GBM (group 2), 3 anaplastic astrocytomas IDH-mutated (group 3), 4 anaplastic oligodendrogliomas and 2 low-grade oligodendrogliomas (together prognostic group 4). A mixed linear model evaluated the predictabilities of microvessel density (MVD), vascular area ratio (VAR), mean vessel size (MVS), vascular endothelial growth factor and receptors (VEGF-A, VEGFR‑2) and vascular endothelial-protein tyrosine phosphatase (VE-PTP) expression from Tofts model kinetic and model-free curve parameters. Results All kinetic parameters were associated with VEGF‑A (all p < 0.001) expression. Ktrans, kep and ve were associated with VAR (p = 0.006, 0.004 and 0.01, respectively) and MVS (p = 0.0001, 0.02 and 0.003, respectively) but not MVD (p = 0.84, 0.74 and 0.73, respectively). Prognostic groups differed in Ktrans (p = 0.007) and ve (p = 0.004) values measured in the infiltration zone. Despite significant differences of VAR, MVS, VEGF‑A, VEGFR‑2, and VE-PTP in vital tumor tissue and the infiltration zone (p = 0.0001 for all), there was no significant difference between kinetic parameters measured in these zones. Conclusion The DCE-MRI kinetic parameters show correlations with microvascular parameters in vital tissue and also reveal blood-brain barrier abnormalities in the infiltration zones adequate to differentiate glioma prognostic groups. Supplementary Information The online version of this article (10.1007/s00062-021-01015-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vera C Keil
- Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany. .,Department of Radiology, Amsterdam University Medical Center, location VUmc, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Gerrit H Gielen
- Department of Neuropathology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, University Hospital BG Bergmannsheil, Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany.,Department of Neurosurgery, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Peter Baumgarten
- Department of Neurosurgery, University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany.,Institute of Neuropathology (Edinger Institute), University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
| | - Angeliki Datsi
- ITZ, Heinrich-Heine-University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Kanishka Hittatiya
- Center for Pathology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Matthias Simon
- Department of Neurosurgery, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Department of Neurosurgery, Ev. Krankenhaus Bielefeld, Haus Gilead I, Burgsteig 13, 33617, Bielefeld, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Department of Neuroradiology, University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
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23
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Park JH, Kim HJ, Kim CW, Kim HC, Jung Y, Lee HS, Lee Y, Ju YS, Oh JE, Park SH, Lee JH, Lee SK, Lee HK. Tumor hypoxia represses γδ T cell-mediated antitumor immunity against brain tumors. Nat Immunol 2021; 22:336-346. [PMID: 33574616 DOI: 10.1038/s41590-020-00860-7] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 12/18/2020] [Indexed: 01/30/2023]
Abstract
The anatomic location and immunologic characteristics of brain tumors result in strong lymphocyte suppression. Consequently, conventional immunotherapies targeting CD8 T cells are ineffective against brain tumors. Tumor cells escape immunosurveillance by various mechanisms and tumor cell metabolism can affect the metabolic states and functions of tumor-infiltrating lymphocytes. Here, we discovered that brain tumor cells had a particularly high demand for oxygen, which affected γδ T cell-mediated antitumor immune responses but not those of conventional T cells. Specifically, tumor hypoxia activated the γδ T cell protein kinase A pathway at a transcriptional level, resulting in repression of the activatory receptor NKG2D. Alleviating tumor hypoxia reinvigorated NKG2D expression and the antitumor function of γδ T cells. These results reveal a hypoxia-mediated mechanism through which brain tumors and γδ T cells interact and emphasize the importance of γδ T cells for antitumor immunity against brain tumors.
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MESH Headings
- Animals
- Apoptosis
- Brain Neoplasms/genetics
- Brain Neoplasms/immunology
- Brain Neoplasms/metabolism
- Brain Neoplasms/pathology
- CD8 Antigens/genetics
- CD8 Antigens/metabolism
- Cell Line, Tumor
- Coculture Techniques
- Cyclic AMP-Dependent Protein Kinases/metabolism
- Cytotoxicity, Immunologic
- Gene Expression Regulation, Neoplastic
- Genes, T-Cell Receptor delta
- Glioblastoma/genetics
- Glioblastoma/immunology
- Glioblastoma/metabolism
- Glioblastoma/pathology
- Humans
- Intraepithelial Lymphocytes/immunology
- Intraepithelial Lymphocytes/metabolism
- Intraepithelial Lymphocytes/pathology
- Lymphocytes, Tumor-Infiltrating/immunology
- Lymphocytes, Tumor-Infiltrating/metabolism
- Lymphocytes, Tumor-Infiltrating/pathology
- Male
- Mice, Inbred C57BL
- Mice, Inbred NOD
- Mice, Knockout
- Mice, Nude
- NK Cell Lectin-Like Receptor Subfamily K/genetics
- NK Cell Lectin-Like Receptor Subfamily K/metabolism
- Phenotype
- Signal Transduction
- Tumor Escape
- Tumor Hypoxia
- Tumor Microenvironment
- Mice
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Affiliation(s)
- Jang Hyun Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyun-Jin Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Chae Won Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyeon Cheol Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Yujin Jung
- Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea
| | - Hyun-Soo Lee
- Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea
| | - Yunah Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Young Seok Ju
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- BioMedical Research Center, KAIST, Daejeon, Republic of Korea
| | - Ji Eun Oh
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- BioMedical Research Center, KAIST, Daejeon, Republic of Korea
| | - Sung-Hong Park
- Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea
| | - Jeong Ho Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- BioMedical Research Center, KAIST, Daejeon, Republic of Korea
| | - Sung Ki Lee
- Department of Obstetrics and Gynecology, College of Medicine, Myunggok Medical Research Center, Konyang University, Daejeon, Republic of Korea
| | - Heung Kyu Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
- BioMedical Research Center, KAIST, Daejeon, Republic of Korea.
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24
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Gwilliam MN, Collins DJ, Leach MO, Orton MR. Quantifying MRI T1 relaxation in flowing blood: implications for arterial input function measurement in DCE-MRI. Br J Radiol 2021; 94:20191004. [PMID: 33507818 PMCID: PMC8011233 DOI: 10.1259/bjr.20191004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES To investigate the feasibility of accurately quantifying the concentration of MRI contrast agent in flowing blood by measuring its T1 in a large vessel. Such measures are often used to obtain patient-specific arterial input functions for the accurate fitting of pharmacokinetic models to dynamic contrast enhanced MRI data. Flow is known to produce errors with this technique, but these have so far been poorly quantified and characterised in the context of pulsatile flow with a rapidly changing T1 as would be expected in vivo. METHODS A phantom was developed which used a mechanical pump to pass fluid at physiologically relevant rates. Measurements of T1 were made using high temporal resolution gradient recalled sequences suitable for DCE-MRI of both constant and pulsatile flow. These measures were used to validate a virtual phantom that was then used to simulate the expected errors in the measurement of an AIF in vivo. RESULTS The relationship between measured T1 values and flow velocity was found to be non-linear. The subsequent error in quantification of contrast agent concentration in a measured AIF was shown. CONCLUSIONS The T1 measurement of flowing blood using standard DCE- MRI sequences are subject to large measurement errors which are non-linear in relation to flow velocity. ADVANCES IN KNOWLEDGE This work qualitatively and quantitatively demonstrates the difficulties of accurately measuring the T1 of flowing blood using DCE-MRI over a wide range of physiologically realistic flow velocities and pulsatilities. Sources of error are identified and proposals made to reduce these.
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Affiliation(s)
- Matthew N Gwilliam
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Trust, London, UK
| | - David J Collins
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Trust, London, UK
| | - Martin O Leach
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Trust, London, UK
| | - Matthew R Orton
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden NHS Trust, London, UK
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25
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Chédeville AL, Madureira PA. The Role of Hypoxia in Glioblastoma Radiotherapy Resistance. Cancers (Basel) 2021; 13:542. [PMID: 33535436 PMCID: PMC7867045 DOI: 10.3390/cancers13030542] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 01/25/2021] [Accepted: 01/29/2021] [Indexed: 02/07/2023] Open
Abstract
Glioblastoma (GB) (grade IV astrocytoma) is the most malignant type of primary brain tumor with a 16 months median survival time following diagnosis. Despite increasing attention regarding the development of targeted therapies for GB that resulted in around 450 clinical trials currently undergoing, radiotherapy still remains the most clinically effective treatment for these patients. Nevertheless, radiotherapy resistance (radioresistance) is commonly observed in GB patients leading to tumor recurrence and eventually patient death. It is therefore essential to unravel the molecular mechanisms underpinning GB cell radioresistance in order to develop novel strategies and combinational therapies focused on enhancing tumor cell sensitivity to radiotherapy. In this review, we present a comprehensive examination of the current literature regarding the role of hypoxia (O2 partial pressure less than 10 mmHg), a main GB microenvironmental factor, in radioresistance with the ultimate goal of identifying potential molecular markers and therapeutic targets to overcome this issue in the future.
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Affiliation(s)
- Agathe L. Chédeville
- INSERM, UMR 1287, Gustave Roussy, CEDEX 94805 Villejuif, France;
- Université Paris-Saclay, UMR 1287, Gustave Roussy, CEDEX 94805 Villejuif, France
- Gustave Roussy, UMR 1287, 114, Rue Edouard-Vaillant, CEDEX 94805 Villejuif, France
| | - Patricia A. Madureira
- Centre for Biomedical Research (CBMR), University of Algarve, Gambelas Campus, Building 8, Room 2.22, 9005-139 Faro, Portugal
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26
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Soft tissue sarcomas: IVIM and DKI correlate with the expression of HIF-1α on direct comparison of MRI and pathological slices. Eur Radiol 2021; 31:4669-4679. [PMID: 33416975 DOI: 10.1007/s00330-020-07526-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 10/21/2020] [Accepted: 11/16/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To investigate the correlation of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters with the expression of HIF-1α in soft tissue sarcoma (STS). METHODS This prospective study was approved by the institutional ethics committee. Written informed consent was obtained from all patients. Forty patients with STS who underwent 3.0 T MRI, including IVIM and DKI, were included in the study. Standard apparent diffusion coefficient (ADC), true ADC (Dslow), pseudo ADC (Dfast), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) of each lesion were independently analyzed by two observers. An MRI-pathology control method was used to ensure correspondence between the MRI slices and the pathological sections. Spearman analysis, independent sample t test, Mann-Whitney U test, chi-squared test, and receiver operating characteristic (ROC) curve analysis were performed. RESULTS Dslow and MD values showed a negative correlation with HIF-1α expression (r = - 0.469, - 0.588). MK and f values showed a positive correlation with HIF-1α expression (r = 0.779, 0.572). Dslow, MD, MK, and f values showed significant differences between the high- and low-expression groups. The MK value showed the best diagnostic ability. The optimal cut-off MK value of 0.604 was associated with 78.3% sensitivity and 88.2% specificity (area under the curve, 0.867). CONCLUSIONS This preliminary study demonstrated the association of IVIM and DKI parameters with the expression of HIF-1α in STS. KEY POINTS • IVIM and DKI parameters are correlated with the expression of HIF-1α in STS. • The MRI-pathology control method can be used in clinical studies to ensure correspondence between MRI slices and pathology sections.
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27
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Hu Y, Chen Y, Wang J, Kang JJ, Shen DD, Jia ZZ. Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI. Front Oncol 2020; 10:593102. [PMID: 33425744 PMCID: PMC7793903 DOI: 10.3389/fonc.2020.593102] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Accepted: 10/30/2020] [Indexed: 12/28/2022] Open
Abstract
Objectives To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods Chinese Glioma Genome Atlas (CGGA) database was wined for differential expression of VEGF in gliomas with different IDH genotypes. The VEGF expression and IDH1 genotypes of 56 glioma samples in our hospital were assessed by immunohistochemistry. Preoperative DCE-MRI data of glioma samples were reviewed. Regions of interest (ROIs) covering tumor parenchyma were delineated. Histogram parameters of volume transfer constant (Ktrans) and volume of extravascular extracellular space per unit volume of tissue (Ve) derived from DCE-MRI were obtained. Histogram parameters of Ktrans, Ve and VEGF expression of IDH1 mutant type (IDH1mut) gliomas were compared with the IDH1 wildtype (IDH1wt) gliomas. Receiver operating characteristic (ROC) curve analysis was performed to differentiate IDH1mut from IDH1wt gliomas. The correlation coefficients were determined between histogram parameters of Ktrans, Ve and VEGF expression in gliomas. Results In CGGA database, VEGF expression in IDHmut gliomas was lower as compared to wildtype counterpart. The immunohistochemistry of glioma samples in our hospital also confirmed the results. Comparisons demonstrated statistically significant differences in histogram parameters of Ktransand Ve [mean, standard deviation (SD), 50th, 75th, 90th. and 95th percentile] between IDH1mutand IDH1wtgliomas (P < 0.05, respectively). ROC curve analysis revealed that 50th percentile of Ktrans (0.019 min−1) and Ve (0.039) provided the perfect combination of sensitivity and specificity in differentiating gliomas with IDH1mutfrom IDH1wt. Irrespective of IDH1 mutation, histogram parameters of Ktransand Ve were correlated with VEGF expression in gliomas (P < 0.05, respectively). Conclusions VEGF expression is significantly lower in IDH1mut gliomas as compared to the wildtype counterpart, and it is non-invasively predictable with histogram analysis of DCE-MRI.
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Affiliation(s)
- Yue Hu
- Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China
| | - Yue Chen
- Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China
| | - Jie Wang
- Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China
| | - Jin Juan Kang
- Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China
| | - Dan Dan Shen
- Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China
| | - Zhong Zheng Jia
- Department of Medical Imaging, Affiliated Hospital of Nantong University, Nantong, China
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28
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Liu B, Sun Z, Ma WL, Ren J, Zhang GW, Wei MQ, Hou WH, Hou BX, Wei LC, Huan Y, Zheng MW. DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT. Front Oncol 2020; 10:585738. [PMID: 33194734 PMCID: PMC7658627 DOI: 10.3389/fonc.2020.585738] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 09/22/2020] [Indexed: 12/21/2022] Open
Abstract
Purpose To evaluate the predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters in treatment response to concurrent chemoradiotherapy (CCRT) for locally advanced cervical squamous cell carcinoma (LACSC). Methods and materials LACSC patients underwent CCRT had DCE-MRI before (e0) and after 3 days of treatment (e3). Extended Tofts Linear model with a user arterial input function was adopted to generate quantitative measurements. Endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), and fractional plasma volume (Vp) were calculated, and percentage changes ΔKtrans, ΔKep, ΔVe, and ΔVp were computed. The correlations of these measurements with the tumor regression rate were analyzed. The predictive value of these parameters on treatment outcome was generated by the receiver operating characteristic (ROC) curve. Univariate and multivariate logistic regression analyses were conducted to find the independent variables. Results Ktrans-e0, Kep -e0, ΔKtrans, and ΔVe were positively correlated with the tumor regression rate. Mean values of Ktrans-e0, Ktrans-e3, ΔKtrans, and ΔVe were higher in the non-residual tumor group than residual tumor group and were independent prognostic factors for predicting residual tumor occurrence. Ktrans-e3 showed the highest area under the curve (AUC) for treatment response prediction. Conclusions Quantitative parameters at e0 and e3 from DCE-MRI could be used as potential indicators for predicting treatment response of LACSC.
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Affiliation(s)
- Bing Liu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhen Sun
- Department of Orthopedic, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wan-Ling Ma
- Department of Radiology, Longgang District People's Hospital, Shenzhen, China
| | - Jing Ren
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Guang-Wen Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Meng-Qi Wei
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei-Huan Hou
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Bing-Xin Hou
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Li-Chun Wei
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yi Huan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Min-Wen Zheng
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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Hypoxia-Induced Glioma-Derived Exosomal miRNA-199a-3p Promotes Ischemic Injury of Peritumoral Neurons by Inhibiting the mTOR Pathway. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2020; 2020:5609637. [PMID: 33110474 PMCID: PMC7578720 DOI: 10.1155/2020/5609637] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 08/04/2020] [Indexed: 11/18/2022]
Abstract
The underlying molecular mechanisms that the hypoxic microenvironment could aggravate neuronal injury are still not clear. In this study, we hypothesized that the exosomes, exosomal miRNAs, and the mTOR signaling pathway might be involved in hypoxic peritumoral neuronal injury in glioma. Multimodal radiological images, HE, and HIF-1α staining of high-grade glioma (HGG) samples revealed that the peritumoral hypoxic area overlapped with the cytotoxic edema region and directly contacted with normal neurons. In either direct or indirect coculture system, hypoxia could promote normal mouse hippocampal neuronal cell (HT22) injury, and the growth of HT22 cells was suppressed by C6 glioma cells under hypoxic condition. For administrating hypoxia-induced glioma-derived exosomes (HIGDE) that could aggravate oxygen-glucose deprivation (OGD)/reperfusion neuronal injury, we identified that exosomes may be the communication medium between glioma cells and peritumoral neurons, and we furtherly found that exosomal miR-199a-3p mediated the OGD/reperfusion neuronal injury process by suppressing the mTOR signaling pathway. Moreover, the upregulation of miRNA-199a-3p in exosomes from glioma cells was induced by hypoxia-related HIF-1α activation. To sum up, hypoxia-induced glioma-derived exosomal miRNA-199a-3p can be upregulated by the activation of HIF-1α and is able to increase the ischemic injury of peritumoral neurons by inhibiting the mTOR pathway.
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30
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Shukla M, Forghani R, Agarwal M. Patient-Centric Head and Neck Cancer Radiation Therapy: Role of Advanced Imaging. Neuroimaging Clin N Am 2020; 30:341-357. [PMID: 32600635 DOI: 10.1016/j.nic.2020.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The traditional 'one-size-fits-all' approach to H&N cancer therapy is archaic. Advanced imaging can identify radioresistant areas by using biomarkers that detect tumor hypoxia, hypercellularity etc. Highly conformal radiotherapy can target resistant areas with precision. The critical information that can be gleaned about tumor biology from these advanced imaging modalities facilitates individualized radiotherapy. The tumor imaging world is pushing its boundaries. Molecular imaging can now detect protein expression and genotypic variations across tumors that can be exploited for tailoring treatment. The exploding field of radiomics and radiogenomics extracts quantitative, biologic and genetic information and further expands the scope of personalized therapy.
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Affiliation(s)
- Monica Shukla
- Department of Radiation Oncology, Froedtert and Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI 53226, USA
| | - Reza Forghani
- Augmented Intelligence & Precision Health Laboratory, Department of Radiology, Research Institute of McGill University Health Centre, 1001 Decarie Boulevard, Montreal, Quebec H4A 3J1, Canada
| | - Mohit Agarwal
- Department of Radiology, Section of Neuroradiology, Froedtert and Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA.
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31
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Fuchs Q, Pierrevelcin M, Messe M, Lhermitte B, Blandin AF, Papin C, Coca A, Dontenwill M, Entz-Werlé N. Hypoxia Inducible Factors' Signaling in Pediatric High-Grade Gliomas: Role, Modelization and Innovative Targeted Approaches. Cancers (Basel) 2020; 12:cancers12040979. [PMID: 32326644 PMCID: PMC7226233 DOI: 10.3390/cancers12040979] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 04/04/2020] [Accepted: 04/07/2020] [Indexed: 12/15/2022] Open
Abstract
The brain tumor microenvironment has recently become a major challenge in all pediatric cancers, but especially in brain tumors like high-grade gliomas. Hypoxia is one of the extrinsic tumor features that interacts with tumor cells, but also with the blood-brain barrier and all normal brain cells. It is the result of a dramatic proliferation and expansion of tumor cells that deprive the tissues of oxygen inflow. However, cancer cells, especially tumor stem cells, can endure extreme hypoxic conditions by rescheduling various genes' expression involved in cell proliferation, metabolism and angiogenesis and thus, promote tumor expansion, therapeutic resistance and metabolic adaptation. This cellular adaptation implies Hypoxia-Inducible Factors (HIF), namely HIF-1α and HIF-2α. In pediatric high-grade gliomas (pHGGs), several questions remained open on hypoxia-specific role in normal brain during gliomagenesis and pHGG progression, as well how to model it in preclinical studies and how it might be counteracted with targeted therapies. Therefore, this review aims to gather various data about this key extrinsic tumor factor in pHGGs.
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Affiliation(s)
- Quentin Fuchs
- UMR CNRS 7021, Laboratory Bioimaging and Pathologies, Tumoral Signaling and Therapeutic Targets team, Faculty of Pharmacy, 74 route du Rhin, 67405 Illkirch, France; (Q.F.); (M.P.); (M.M.); (B.L.); (M.D.)
| | - Marina Pierrevelcin
- UMR CNRS 7021, Laboratory Bioimaging and Pathologies, Tumoral Signaling and Therapeutic Targets team, Faculty of Pharmacy, 74 route du Rhin, 67405 Illkirch, France; (Q.F.); (M.P.); (M.M.); (B.L.); (M.D.)
| | - Melissa Messe
- UMR CNRS 7021, Laboratory Bioimaging and Pathologies, Tumoral Signaling and Therapeutic Targets team, Faculty of Pharmacy, 74 route du Rhin, 67405 Illkirch, France; (Q.F.); (M.P.); (M.M.); (B.L.); (M.D.)
| | - Benoit Lhermitte
- UMR CNRS 7021, Laboratory Bioimaging and Pathologies, Tumoral Signaling and Therapeutic Targets team, Faculty of Pharmacy, 74 route du Rhin, 67405 Illkirch, France; (Q.F.); (M.P.); (M.M.); (B.L.); (M.D.)
- Pathology Department, University Hospital of Strasbourg, 1 avenue Molière, 67098 Strasbourg, France
| | | | - Christophe Papin
- Inserm U1258, UMR CNRS 7104, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg, 67400 Illkirch, France;
| | - Andres Coca
- Neurosurgery, University Hospital of Strasbourg, 1 avenue Molière, 67098 Strasbourg, France;
| | - Monique Dontenwill
- UMR CNRS 7021, Laboratory Bioimaging and Pathologies, Tumoral Signaling and Therapeutic Targets team, Faculty of Pharmacy, 74 route du Rhin, 67405 Illkirch, France; (Q.F.); (M.P.); (M.M.); (B.L.); (M.D.)
| | - Natacha Entz-Werlé
- UMR CNRS 7021, Laboratory Bioimaging and Pathologies, Tumoral Signaling and Therapeutic Targets team, Faculty of Pharmacy, 74 route du Rhin, 67405 Illkirch, France; (Q.F.); (M.P.); (M.M.); (B.L.); (M.D.)
- Pediatric Onco-Hematology Department, Pediatrics, University hospital of Strasbourg, 1 avenue Molière, 67098 Strasbourg, France
- Correspondence: ; Tel.: +33-388128396; Fax: +33-388128092
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32
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Assessment of an scFv Antibody Fragment Against ELTD1 in a G55 Glioblastoma Xenograft Model. Transl Oncol 2020; 13:100737. [PMID: 32208341 PMCID: PMC7090355 DOI: 10.1016/j.tranon.2019.12.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 12/11/2019] [Accepted: 12/12/2019] [Indexed: 01/27/2023] Open
Abstract
Glioblastoma (GBM), the most common primary brain tumor found in adults, is extremely aggressive. These high-grade gliomas, which are very diffuse, highly vascular, and invasive, undergo unregulated vascular angiogenesis. Despite available treatments, the median survival for patients is dismal. ELTD1 (EGF, latrophilin, and 7 transmembrane domain containing protein 1) is an angiogenic biomarker highly expressed in human high-grade gliomas. Recent studies have demonstrated that the blood-brain barrier, as well as the blood-tumor barrier, is not equally disrupted in GBM patients. This study therefore aimed to optimize an antibody treatment against ELTD1 using a smaller scFv fragment of a monoclonal antibody that binds against the external region of ELTD1 in a G55 glioma xenograft glioma preclinical model. Morphological magnetic resonance imaging (MRI) was used to determine tumor volumes and quantify perfusion rates. We also assessed percent survival following tumor postdetection. Tumor tissue was also assessed to confirm and quantify the presence of the ELTD1 scFv molecular targeted MRI probe, as well as microvessel density and Notch1 levels. In addition, we used molecular-targeted MRI to localize our antibodies in vivo. This approach showed that our scFv antibody attached-molecular MRI probe was effective in targeting and localizing diffuse tumor regions. Through this analysis, we determined that our anti-ELTD1 scFv antibody treatments were successful in increasing survival, decreasing tumor volumes, and normalizing vascular perfusion and Notch1 levels within tumor regions. This study demonstrates that our scFv fragment antibody against ELTD1 may be useful and potential antiangiogenic treatments against GBM.
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33
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Akbari H, Rathore S, Bakas S, Nasrallah MP, Shukla G, Mamourian E, Rozycki M, Bagley SJ, Rudie JD, Flanders AE, Dicker AP, Desai AS, O'Rourke DM, Brem S, Lustig R, Mohan S, Wolf RL, Bilello M, Martinez-Lage M, Davatzikos C. Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma. Cancer 2020; 126:2625-2636. [PMID: 32129893 DOI: 10.1002/cncr.32790] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 12/10/2019] [Accepted: 01/22/2020] [Indexed: 11/11/2022]
Abstract
BACKGROUND Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP. METHODS We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients. RESULTS Patients who demonstrate TP on neuropathology are significantly different (P < .0001) from those with PsP, showing imaging features reflecting higher angiogenesis, higher cellularity, and lower water concentration. The accuracy of the proposed signature in leave-one-out cross-validation was 87% for predicting PsP (area under the curve [AUC], 0.92) and 84% for predicting TP (AUC, 0.83), whereas in the discovery/replication cohort, the accuracy was 87% for predicting PsP (AUC, 0.84) and 78% for TP (AUC, 0.80). The accuracy in the interinstitutional cohort was 75% (AUC, 0.80). CONCLUSION Quantitative mpMRI analysis via machine learning reveals distinctive noninvasive signatures of TP versus PsP after treatment of glioblastoma. Integration of the proposed method into clinical studies can be performed using the freely available Cancer Imaging Phenomics Toolkit.
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Affiliation(s)
- Hamed Akbari
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Saima Rathore
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - MacLean P Nasrallah
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.,Helen F. Graham Cancer Center and Research Institute, ChristianaCare, Newark, Delaware
| | - Elizabeth Mamourian
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Martin Rozycki
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Stephen J Bagley
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jeffrey D Rudie
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Adam E Flanders
- Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Medical College and Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Arati S Desai
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Robert Lustig
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ronald L Wolf
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Maria Martinez-Lage
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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Mapelli P, Picchio M. 18F-FAZA PET imaging in tumor hypoxia: A focus on high-grade glioma. Int J Biol Markers 2020; 35:42-46. [DOI: 10.1177/1724600820905715] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The presence of hypoxia is a typical feature of solid tumors and has been identified in many neoplasms, favouring the survival of malignant cells in a hostile environment and the expression of an aggressive phenotype. Malignant brain tumors have large proportions of hypoxic tissue, thus contributing to resistance to radiation and chemotherapy. Positron emission tomography (PET) is an attractive technique to gain a non-invasive assessment of tumor hypoxia within the whole tumor, with 18F-fluoromisonidazole (18F-FMISO) and 18F-flouroazomycin arabinoside (18F-FAZA) being the most promising radiotracers. In this short review, we aim to discuss the available clinical studies focused on the use of 18F-FAZA PET/computed tomography in patients affected by high-grade glioma.
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Affiliation(s)
- Paola Mapelli
- Vita-Salute San Raffaele University, Milan, Italy
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria Picchio
- Vita-Salute San Raffaele University, Milan, Italy
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
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35
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Kim HS, Kwon SL, Choi SH, Hwang I, Kim TM, Park CK, Park SH, Won JK, Kim IH, Lee ST. Prognostication of anaplastic astrocytoma patients: application of contrast leakage information of dynamic susceptibility contrast-enhanced MRI and dynamic contrast-enhanced MRI. Eur Radiol 2020; 30:2171-2181. [PMID: 31953664 DOI: 10.1007/s00330-019-06598-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 10/13/2019] [Accepted: 11/19/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE To examine the applicability of contrast leakage information from dynamic susceptibility contrast-enhanced (DSC) MRI and dynamic contrast-enhanced (DCE) MRI to determine which one is the most valuable surrogate imaging biomarker for predicting disease progression in anaplastic astrocytoma (AA) patients. MATERIALS AND METHODS This study was approved by the institutional review board (IRB), which waived informed consent. A total of seventy-three AA patients who had undergone preoperative DCE and DSC MRI and received standard treatment, including partial resection or biopsy followed by radiation therapy, were included in this retrospective study. Based on Response Assessment in Neuro-Oncology (RANO), patients were sorted into progression (n = 21) and non-progression (n = 52) groups. Tumor boundaries were defined as high-signal intensity (SI) lesions on fluid-attenuated inversion recovery (FLAIR) imaging, where we analyzed mean pharmacokinetic parameters (Ktrans, Vp, and Ve) from DCE MRI and contrast leakage information (mean extraction fraction (EF)) from DSC MRI. RESULTS Mean Ve and mean EF were significantly higher in patients with progression-free survival (PFS) < 18 months than in those with PFS ≥ 18 months. For distinguishing the group with PFS < 18 months, AUC values were calculated using the mean Ve value (AUC = 0.716). The Kaplan-Meier survival analysis revealed that mean Ve value was significantly correlated with PFS. In Cox proportional-hazards regression, only the mean Ve value was found to be significantly associated with PFS. CONCLUSION We found that the mean Ve value based on high-SI tumor lesions on FLAIR imaging was capable of predicting outcomes of AA patients as a potential surrogate imaging biomarker. KEY POINTS • Mean Ve(2.152 ± 1.857 vs. 1.173 ± 1.408) was significantly higher in anaplastic astrocytoma patients with PFS < 18 months that in those with PFS ≥ 18 months (p = 0.02). • Cox proportional-hazards regression showed that only mean Ve(p = 0.034) was significantly associated with PFS, regardless of IDH mutation status, in anaplastic astrocytoma patients.
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Affiliation(s)
- Hee Soo Kim
- College of Medicine, Seoul National University, Seoul, South Korea
| | - Se Lee Kwon
- College of Medicine, Seoul National University, Seoul, South Korea
| | - Seung Hong Choi
- Department of Radiology, College of Medicine, Seoul National University, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, South Korea.
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, South Korea.
- School of Chemical and Biological Engineering, Seoul National University, Seoul, 151-742, South Korea.
| | - Inpyeong Hwang
- Department of Radiology, College of Medicine, Seoul National University, 28, Yongon-dong, Chongno-gu, Seoul, 110-744, South Korea
- Center for Nanoparticle Research, Institute for Basic Science, Seoul, South Korea
| | - Tae Min Kim
- Department of Internal Medicine, Cancer Research Institute, College of Medicine, Seoul National University, Seoul, South Korea
| | - Chul-Kee Park
- Department of Neurosurgery, Biomedical Research Institute, College of Medicine, Seoul National University, Seoul, South Korea
| | - Sung-Hye Park
- Department of Pathology, College of Medicine, Seoul National University, Seoul, South Korea
| | - Jae-Kyung Won
- Department of Pathology, College of Medicine, Seoul National University, Seoul, South Korea
| | - Il Han Kim
- Department of Radiation Oncology, Cancer Research Institute, College of Medicine, Seoul National University, Seoul, South Korea
| | - Soon Tae Lee
- Department of Neurology, College of Medicine, Seoul National University, Seoul, South Korea
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Rathore S, Akbari H, Bakas S, Pisapia JM, Shukla G, Rudie JD, Da X, Davuluri RV, Dahmane N, O'Rourke DM, Davatzikos C. Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients. Front Comput Neurosci 2019; 13:81. [PMID: 31920606 PMCID: PMC6923885 DOI: 10.3389/fncom.2019.00081] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Accepted: 11/12/2019] [Indexed: 12/30/2022] Open
Abstract
Glioblastoma, the most frequent primary malignant brain neoplasm, is genetically diverse and classified into four transcriptomic subtypes, i. e., classical, mesenchymal, proneural, and neural. Currently, detection of transcriptomic subtype is based on ex vivo analysis of tissue that does not capture the spatial tumor heterogeneity. In view of accumulative evidence of in vivo imaging signatures summarizing molecular features of cancer, this study seeks robust non-invasive radiographic markers of transcriptomic classification of glioblastoma, based solely on routine clinically-acquired imaging sequences. A pre-operative retrospective cohort of 112 pathology-proven de novo glioblastoma patients, having multi-parametric MRI (T1, T1-Gd, T2, T2-FLAIR), collected from the Hospital of the University of Pennsylvania were included. Following tumor segmentation into distinct radiographic sub-regions, diverse imaging features were extracted and support vector machines were employed to multivariately integrate these features and derive an imaging signature of transcriptomic subtype. Extracted features included intensity distributions, volume, morphology, statistics, tumors' anatomical location, and texture descriptors for each tumor sub-region. The derived signature was evaluated against the transcriptomic subtype of surgically-resected tissue specimens, using a 5-fold cross-validation method and a receiver-operating-characteristics analysis. The proposed model was 71% accurate in distinguishing among the four transcriptomic subtypes. The accuracy (sensitivity/specificity) for distinguishing each subtype (classical, mesenchymal, proneural, neural) from the rest was equal to 88.4% (71.4/92.3), 75.9% (83.9/72.8), 82.1% (73.1/84.9), and 75.9% (79.4/74.4), respectively. The findings were also replicated in The Cancer Genomic Atlas glioblastoma dataset. The obtained imaging signature for the classical subtype was dominated by associations with features related to edge sharpness, whereas for the mesenchymal subtype had more pronounced presence of higher T2 and T2-FLAIR signal in edema, and higher volume of enhancing tumor and edema. The proneural and neural subtypes were characterized by the lower T1-Gd signal in enhancing tumor and higher T2-FLAIR signal in edema, respectively. Our results indicate that quantitative multivariate analysis of features extracted from clinically-acquired MRI may provide a radiographic biomarker of the transcriptomic profile of glioblastoma. Importantly our findings can be influential in surgical decision-making, treatment planning, and assessment of inoperable tumors.
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Affiliation(s)
- Saima Rathore
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Hamed Akbari
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Jared M Pisapia
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Division of Neurosurgery, Children Hospital of Philadelphia, Philadelphia, PA, United States
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Christiana Care Health System, Philadelphia, PA, United States
| | - Jeffrey D Rudie
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Xiao Da
- Brigham and Women's Hospital, Boston, MA, United States
| | - Ramana V Davuluri
- Department of Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Nadia Dahmane
- Department of Neurological Surgery, Weill Cornell Medicine, New York, NY, United States
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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37
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Hwang I, Choi SH, Park CK, Kim TM, Park SH, Won JK, Kim IH, Lee ST, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH. Dynamic Contrast-Enhanced MR Imaging of Nonenhancing T2 High-Signal-Intensity Lesions in Baseline and Posttreatment Glioblastoma: Temporal Change and Prognostic Value. AJNR Am J Neuroradiol 2019; 41:49-56. [PMID: 31806595 DOI: 10.3174/ajnr.a6323] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 10/02/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The prognostic value of dynamic contrast-enhanced MR imaging on nonenhancing T2 high-signal-intensity lesions in patients with glioblastoma has not been thoroughly elucidated to date. We evaluated the temporal change and prognostic value for progression-free survival of dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters on nonenhancing T2 high-signal-intensity lesions in patients with glioblastoma before and after standard treatment, including gross total surgical resection. MATERIALS AND METHODS This retrospective study included 33 patients who were newly diagnosed with glioblastoma and treated with gross total surgical resection followed by concurrent chemoradiation therapy and adjuvant chemotherapy with temozolomide in a single institution. All patients underwent dynamic contrast-enhanced MR imaging before surgery as a baseline and after completion of maximal surgical resection and concurrent chemoradiation therapy. On the whole nonenhancing T2 high-signal-intensity lesion, dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters (volume transfer constant [K trans], volume of extravascular extracellular space [v e], and blood plasma volume [vp ]) were calculated. The Cox proportional hazards regression model analysis was performed to determine the histogram features or percentage changes of pharmacokinetic parameters related to progression-free survival. RESULTS Baseline median K trans, baseline first quartile K trans, and posttreatment median K trans were significant independent variables, as determined by univariate analysis (P < .05). By multivariate Cox regression analysis including methylation status of O6-methylguanine-DNA methyltransferase, baseline median K trans was determined to be the significant independent variable and was negatively related to progression-free survival (hazard ratio = 1.48, P = .003). CONCLUSIONS Baseline median K trans from nonenhancing T2 high-signal-intensity lesions could be a potential prognostic imaging biomarker in patients undergoing gross total surgical resection followed by standard therapy for glioblastoma.
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Affiliation(s)
- I Hwang
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - S H Choi
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research .,Institute for Basic Science, and School of Chemical and Biological Engineering (S.H.C.)
| | - C-K Park
- Department of Neurosurgery and Biomedical Research Institute (P.C.-K.)
| | - T M Kim
- Department of Internal Medicine and Cancer Research Institute (T.M.K.)
| | - S-H Park
- Department of Pathology (S.-H.P., J.K.W.)
| | - J K Won
- Department of Pathology (S.-H.P., J.K.W.)
| | - I H Kim
- Department of Radiation Oncology and Cancer Research Institute (I.H.K.)
| | - S-T Lee
- Department of Neurology (S.-T.L.), Seoul National University Hospital, Seoul, Korea
| | - R-E Yoo
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - K M Kang
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - T J Yun
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - J-H Kim
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
| | - C-H Sohn
- From the Department of Radiology (I.H., S.H.C., R.-E.Y., K.M.K., T.J.Y., J.-H.K., C.-H.S.), Center for Nanoparticle Research
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38
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Álvarez‐Torres M, Juan‐Albarracín J, Fuster‐Garcia E, Bellvís‐Bataller F, Lorente D, Reynés G, Font de Mora J, Aparici‐Robles F, Botella C, Muñoz‐Langa J, Faubel R, Asensio‐Cuesta S, García‐Ferrando GA, Chelebian E, Auger C, Pineda J, Rovira A, Oleaga L, Mollà‐Olmos E, Revert AJ, Tshibanda L, Crisi G, Emblem KE, Martin D, Due‐Tønnessen P, Meling TR, Filice S, Sáez C, García‐Gómez JM. Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging 2019; 51:1478-1486. [DOI: 10.1002/jmri.26958] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 09/19/2019] [Indexed: 02/03/2023] Open
Affiliation(s)
- María Álvarez‐Torres
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Javier Juan‐Albarracín
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | | | - Fuensanta Bellvís‐Bataller
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - David Lorente
- Hospital Provincial de Castellón, Department of Medical Oncology Castellón de la Plana Castellón de la Plana Spain
| | - Gaspar Reynés
- Health Research Institute Hospital La FeCancer Research Group Valencia Spain
| | - Jaime Font de Mora
- Instituto de Investigación Sanitaria La Fe, Laboratory of Cellular and Molecular Biology Valencia Spain
| | | | - Carlos Botella
- Hospital Universitari i Politècnic La Fe, Área Clínica de Neurociencias Valencia Spain
| | - Jose Muñoz‐Langa
- Health Research Institute Hospital La FeCancer Research Group Valencia Spain
| | - Raquel Faubel
- Universitat de València, Departament de Fisioteràpia Valencia Spain
| | - Sabina Asensio‐Cuesta
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Germán A. García‐Ferrando
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Eduard Chelebian
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Cristina Auger
- Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Magnetic Resonance Unit, Department of Radiology Barcelona Spain
| | - Jose Pineda
- Hospital Clinic de Barcelona Barcelona Spain
| | - Alex Rovira
- Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Magnetic Resonance Unit, Department of Radiology Barcelona Spain
| | | | - Enrique Mollà‐Olmos
- Hospital Universitario de la Ribera, Departamento de Radiodiagnóstico Alzira Valencia Spain
| | | | - Luaba Tshibanda
- Centre Hospitalier Universitaire de Liège, Service médical de Radiodiagnostic Liège Belgium
| | - Girolamo Crisi
- Azienda Ospedaliero‐Universitaria di Parma, Neuroradiology Parma Italy
| | - Kyrre E. Emblem
- Oslo University Hospital, Department of Diagnostic Physics Oslo Norway
| | - Didier Martin
- Centre Hospitalier Universitaire de Liege, Service de Neurochirurugie Liège Belgium
| | | | - Torstein R. Meling
- Oslo University Hospital, Department of Neurosurgery Oslo Norway
- Geneva University Hospital, Department of Neurosurgery Geneva Switzerland
| | - Silvano Filice
- Azienda Ospedaliero‐Universitaria di Parma, Medical Physics Parma Italy
| | - Carlos Sáez
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Juan M. García‐Gómez
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
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Sun Z, Li Y, Wang Y, Fan X, Xu K, Wang K, Li S, Zhang Z, Jiang T, Liu X. Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas. Cancer Imaging 2019; 19:68. [PMID: 31639060 PMCID: PMC6805458 DOI: 10.1186/s40644-019-0256-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 09/25/2019] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVE To predict vascular endothelial growth factor (VEGF) expression in patients with diffuse gliomas using radiomic analysis. MATERIALS AND METHODS Preoperative magnetic resonance images were retrospectively obtained from 239 patients with diffuse gliomas (World Health Organization grades II-IV). The patients were randomly assigned to a training group (n = 160) or a validation group (n = 79) at a 2:1 ratio. For each patient, a total of 431 radiomic features were extracted. The minimum redundancy maximum relevance (mRMR) algorithm was used for feature selection. A machine-learning model for predicting VEGF status was then developed using the selected features and a support vector machine classifier. The predictive performance of the model was evaluated in both groups using receiver operating characteristic curve analysis, and correlations between selected features were assessed. RESULTS Nine radiomic features were selected to generate a VEGF-associated radiomic signature of diffuse gliomas based on the mRMR algorithm. This radiomic signature consisted of two first-order statistics or related wavelet features (Entropy and Minimum) and seven textural features or related wavelet features (including Cluster Tendency and Long Run Low Gray Level Emphasis). The predictive efficiencies measured by the area under the curve were 74.1% in the training group and 70.2% in the validation group. The overall correlations between the 9 radiomic features were low in both groups. CONCLUSIONS Radiomic analysis facilitated efficient prediction of VEGF status in diffuse gliomas, suggesting that using tumor-derived radiomic features for predicting genomic information is feasible.
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Affiliation(s)
- Zhiyan Sun
- Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China
| | - Yiming Li
- Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Fan
- Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China
| | - Kaibin Xu
- Chinese Academy of Sciences, Institute of Automation, Beijing, China
| | - Kai Wang
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shaowu Li
- Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China
| | - Zhong Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Jiang
- Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, China
| | - Xing Liu
- Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China.
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Dynamic contrast-enhanced perfusion parameters in ovarian cancer: Good accuracy in identifying high HIF-1α expression. PLoS One 2019; 14:e0221340. [PMID: 31437208 DOI: 10.1371/journal.pone.0221340] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 08/05/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Hypoxia significantly influences treatment response and clinical outcome in solid tumors. A noninvasive marker for hypoxia will help physicians in treatment planning and encourage the efficient use of hypoxia targeted therapies. The purpose of this study was to investigate whether pharmacokinetic dynamic contrast-enhanced (DCE) perfusion parameters are associated with a specific marker of hypoxia, hypoxia-inducible factor 1 alpha (HIF-1α) in ovarian cancer (OC). MATERIALS AND METHODS Thirty-eight patients with primary OC were enrolled in this prospective study approved by the local ethical committee. Patients underwent dynamic gadolinium-enhanced 3.0 T MRI as part of their staging investigations. Pharmacokinetic perfusion parameters, including a rate constant for transfer of contrast agent from plasma to extravascular extracellular space (EES) (Ktrans) and a rate constant from EES to plasma (Kep), were measured by drawing two types of regions of interest (ROIs): a large solid lesion (L-ROI) and a solid, most enhancing small area (S-ROI) (NordicICE platform). Tissue samples for immunohistochemical analysis were collected during surgery. Kruskal-Wallis, Mann-Whitney U and Chi-square tests were used in statistical analyses. Receiver Operating Characteristic curve analyzes were done for DCE parameters to discriminate high HIF-1α expression. RESULTS Pharmacokinetic perfusion parameters Ktrans and Kep were inversely associated with HIF-1α expression (Ktrans L-ROI P = 0.021; Ktrans S-ROI P = 0.018 and Kep L-ROI P = 0.032; Kep S-ROI P = 0.033). Ktrans and Kep showed good accuracy in identifying high HIF-1α expression (AUC = 0.832 Ktrans L-ROI; 0.840 Ktrans S-ROI; 0.808 Kep L-ROI and 0.808 Kep L-ROI). CONCLUSION This preliminary study demonstrated that pharmacokinetic DCE-MRI perfusion parameters are associated with the hypoxia specific marker, HIF-1α in OC. DCE-MRI may be a useful supplementary tool in the characterization of OC tumors in a staging investigation.
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Chidambaram S, Pannullo SC, Roytman M, Pisapia DJ, Liechty B, Magge RS, Ramakrishna R, Stieg PE, Schwartz TH, Ivanidze J. Dynamic contrast-enhanced magnetic resonance imaging perfusion characteristics in meningiomas treated with resection and adjuvant radiosurgery. Neurosurg Focus 2019; 46:E10. [DOI: 10.3171/2019.3.focus1954] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 03/25/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVEThere is a need for advanced imaging biomarkers to improve radiation treatment planning and response assessment. T1-weighted dynamic contrast-enhanced perfusion MRI (DCE MRI) allows quantitative assessment of tissue perfusion and blood-brain barrier dysfunction and has entered clinical practice in the management of primary and secondary brain neoplasms. The authors sought to retrospectively investigate DCE MRI parameters in meningiomas treated with resection and adjuvant radiation therapy using volumetric segmentation.METHODSA retrospective review of more than 300 patients with meningiomas resected between January 2015 and December 2018 identified 14 eligible patients with 18 meningiomas who underwent resection and adjuvant radiotherapy. Patients were excluded if they did not undergo adjuvant radiation therapy or DCE MRI. Demographic and clinical characteristics were obtained and compared to DCE perfusion metrics, including mean plasma volume (vp), extracellular volume (ve), volume transfer constant (Ktrans), rate constant (kep), and wash-in rate of contrast into the tissue, which were derived from volumetric analysis of the enhancing volumes of interest.RESULTSThe mean patient age was 64 years (range 49–86 years), and 50% of patients (7/14) were female. The average tumor volume was 8.07 cm3 (range 0.21–27.89 cm3). The median Ki-67 in the cohort was 15%. When stratified by median Ki-67, patients with Ki-67 greater than 15% had lower median vp (0.02 vs 0.10, p = 0.002), and lower median wash-in rate (1.27 vs 4.08 sec−1, p = 0.04) than patients with Ki-67 of 15% or below. Logistic regression analysis demonstrated a statistically significant, moderate positive correlation between ve and time to progression (r = 0.49, p < 0.05). Furthermore, there was a moderate positive correlation between Ktrans and time to progression, which approached, but did not reach, statistical significance (r = 0.48, p = 0.05).CONCLUSIONSThis study demonstrates a potential role for DCE MRI in the preoperative characterization and stratification of meningiomas, laying the foundation for future prospective studies incorporating DCE as a biomarker in meningioma diagnosis and treatment planning.
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Affiliation(s)
| | | | - Michelle Roytman
- 2Radiology, Division of Neuroradiology, Division of Molecular Imaging and Therapeutics; and
| | | | | | - Rajiv S. Magge
- 4Weill Cornell Medicine, Cornell University, New York, New York
| | | | | | | | - Jana Ivanidze
- 2Radiology, Division of Neuroradiology, Division of Molecular Imaging and Therapeutics; and
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Daimiel I. Insights into Hypoxia: Non-invasive Assessment through Imaging Modalities and Its Application in Breast Cancer. J Breast Cancer 2019; 22:155-171. [PMID: 31281720 PMCID: PMC6597408 DOI: 10.4048/jbc.2019.22.e26] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 04/15/2019] [Indexed: 12/11/2022] Open
Abstract
Oxygen is crucial to maintain the homeostasis in aerobic cells. Hypoxia is a condition in which cells are deprived of the oxygen supply necessary for their optimum performance. Whereas oxygen deprivation may occur in normal physiological processes, hypoxia is frequently associated with pathological conditions. It has been identified as a stressor in the tumor microenvironment, acting as a key mediator of cancer development. Numerous pathways are activated in hypoxic cells that affect cell signaling and gene regulation to promote the survival of these cells by stimulating angiogenesis, switching cellular metabolism, slowing their growth rate, and preventing apoptosis. The induction of dysregulated metabolism in cancer cells by hypoxia results in aggressive tumor phenotypes that are characterized by rapid progression, treatment resistance, and poor prognosis. A non-invasive assessment of hypoxia-induced metabolic and architectural changes in tumors is advisable to fully improve breast cancer (BC) patient management, by potentially reducing the need for invasive biopsy procedures and evaluating tumor response to treatment. This review provides a comprehensive overview of the molecular changes in breast tumors secondary to hypoxia and the non-invasive imaging alternatives to evaluate oxygen deprivation, with an emphasis on their application in BC and the advantages and limitations of the currently available techniques.
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Affiliation(s)
- Isaac Daimiel
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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43
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Chen NT, Barth ED, Lee TH, Chen CT, Epel B, Halpern HJ, Lo LW. Highly sensitive electron paramagnetic resonance nanoradicals for quantitative intracellular tumor oxymetric images. Int J Nanomedicine 2019; 14:2963-2971. [PMID: 31118615 PMCID: PMC6503311 DOI: 10.2147/ijn.s194779] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 03/11/2019] [Indexed: 01/25/2023] Open
Abstract
Purpose: Tumor oxygenation is a critical parameter influencing the efficacy of cancer therapy. Low levels of oxygen in solid tumor have been recognized as an indicator of malignant progression and metastasis, as well as poor response to chemo- and radiation therapy. Being able to measure oxygenation for an individual's tumor would provide doctors with a valuable way of identifying optimal treatments for patients. Methods: Electron paramagnetic resonance imaging (EPRI) in combination with an oxygen-measuring paramagnetic probe was performed to measure tumor oxygenation in vivo. Triarylmethyl (trityl) radical exhibits high specificity, sensitivity, and resolution for quantitative measurement of O2 concentration. However, its in vivo applications in previous studies have been limited by the required high dosage, its short half-life, and poor intracellular permeability. To address these limitations, we developed high-capacity nanoformulated radicals that employed fluorescein isothiocyanate-labeled mesoporous silica nanoparticles (FMSNs) as trityl radical carriers. The high surface area nanostructure and easy surface modification of physiochemical properties of FMSNs enable efficient targeted delivery of highly concentrated, nonself-quenched trityl radicals, protected from environmental degradation and dilution. Results: We successfully designed and synthesized a tumor-targeted nanoplatform as a carrier for trityl. In addition, the nanoformulated trityl does not affect oxygen-sensing capacity by a self-relaxation or broadening effect. The FMSN-trityl exhibited high sensitivity/response to oxygen in the partial oxygen pressure range from 0 to 155 mmHg. Furthermore, MSN-trityl displayed outstanding intracellular oxygen mapping in both in vitro and in vivo animal studies. Conclusion: The highly sensitive nanoformulated trityl spin probe can profile intracellular oxygen distributions of tumor in a real-time and quantitative manner using in vivo EPRI.
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Affiliation(s)
- Nai-Tzu Chen
- Institute of New Drug Development, China Medical University, Taichung 40402, Taiwan
| | - Eugene D Barth
- Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL 60637, USA.,Center for EPR Imaging In Vivo Physiology, University of Chicago, Chicago, IL 60637, USA
| | - Tsung-Hsi Lee
- Department of Biological Science and Technology, China Medical University, Taichung 40402, Taiwan
| | - Chin-Tu Chen
- Department of Radiology, University of Chicago, Chicago, IL 60637 USA
| | - Boris Epel
- Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL 60637, USA.,Center for EPR Imaging In Vivo Physiology, University of Chicago, Chicago, IL 60637, USA
| | - Howard J Halpern
- Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL 60637, USA.,Center for EPR Imaging In Vivo Physiology, University of Chicago, Chicago, IL 60637, USA
| | - Leu-Wei Lo
- Department of Radiology, University of Chicago, Chicago, IL 60637 USA.,Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan
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Xie Q, Wu J, Du Z, Di N, Yan R, Pang H, Jin T, Zhang H, Wu Y, Zhang Y, Yao Z, Feng X. DCE-MRI in Human Gliomas: A Surrogate for Assessment of Invasive Hypoxia Marker HIF-1Α Based on MRI-Neuronavigation Stereotactic Biopsies. Acad Radiol 2019; 26:179-187. [PMID: 29754996 DOI: 10.1016/j.acra.2018.04.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Revised: 03/31/2018] [Accepted: 04/12/2018] [Indexed: 12/15/2022]
Abstract
RATIONALE AND OBJECTIVES The purpose of this study was to correlate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with data from a specific marker of hypoxia, hypoxia-inducible factor 1α (HIF-1α), in human gliomas on a point-to-point basis by using coregistered magnetic resonance imaging and frameless stereotactic biopsies. MATERIALS AND METHODS Thirty-four patients with treatment-naive gliomas underwent DCE, axial T1-weighted, T2-weighted, T2-weighted fluid acquisition of inversion recovery, and three-dimensional T1-weighted brain volume with gadolinium contrast enhancement sequences on a 3.0-T magnetic resonance scanner before stereotactic surgery. Quantitative perfusion indices such as endothelial transfer constant, fractional extravascular extracellular space volume, fractional plasma volume, and reflux rate were measured at corresponding stereotactic biopsy sites. Each sample was considered an independent measurement, and its histology grade was diagnosed. HIF-1α expression was quantified from the point-to-point biopsy tissues. Analyses of receiver operating characteristic curves were done for HIF-1α to discriminate different grades of glioma. To look for correlations between immunohistochemical parameters and DCE indices, Spearman's correlation coefficient was used. RESULTS Seventy biopsy samples from 34 subjects were included in the analysis. Mean immunoreactivity scores of HIF-1α were 2.75 ± 1.11 for grade II (n = 24), 6.20 ± 2.33 for grade III (n = 20), and 10.46 ± 2.42 for grade IV (n = 26). HIF-1α showed very good-to-excellent accuracy in discriminating grade II from III, III from IV, and II from IV (area under the curve = 0.838, 0.862, and 0.994, respectively). Endothelial transfer constant and fractional extravascular extracellular space volume showed a significantly positive correlation with HIF-1α expression (r = 0.686, P < .001; r = 0.549, P < .001, respectively). CONCLUSION Our study demonstrated HIF-1α to be a significant predictor of different grades of gliomas with high sensitivity and specificity. DCE-MRI is a useful, noninvasive imaging tool for quantitative evaluation of HIF-1α, and its parameters may be used as a surrogate for HIF-1α expression.
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45
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Fuster-Garcia E, Juan-Albarracín J, García-Ferrando GA, Martí-Bonmatí L, Aparici-Robles F, García-Gómez JM. Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures. NMR IN BIOMEDICINE 2018; 31:e4006. [PMID: 30239058 DOI: 10.1002/nbm.4006] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 06/08/2023]
Abstract
Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent key information to understand tumor resistance against effective therapies of these neoplasms. Recently, hemodynamic tissue signature (HTS) markers based on MR perfusion images have been demonstrated to be useful for describing the heterogeneity of GBM at the voxel level, as well as demonstrating significant correlations with the patient's overall survival. In this work, we analyze the abilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, in both the regression and classification tests, show that inclusion of the HTS markers improves the reliability of prognostic models. The HTS method is fully automatic and it is available for research use at http://www.oncohabitats.upv.es.
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Affiliation(s)
- Elies Fuster-Garcia
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Javier Juan-Albarracín
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Germán A García-Ferrando
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Luis Martí-Bonmatí
- Medical Imaging Department, La Fe Polytechnics and University Hospital, València, Spain
- Imaging Research Group (GIBI230), La Fe Health Research Institute, València, Spain
| | - Fernando Aparici-Robles
- Medical Imaging Department, La Fe Polytechnics and University Hospital, València, Spain
- Imaging Research Group (GIBI230), La Fe Health Research Institute, València, Spain
| | - Juan M García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
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Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. Sci Rep 2018; 8:17062. [PMID: 30459364 PMCID: PMC6244161 DOI: 10.1038/s41598-018-34820-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 10/24/2018] [Indexed: 12/18/2022] Open
Abstract
Functional MRI may identify critical windows of opportunity for drug delivery and distinguish between early treatment responders and non-responders. Using diffusion-weighted, dynamic contrast-enhanced, and dynamic susceptibility contrast MRI, as well as pro-angiogenic and pro-inflammatory blood markers, we prospectively studied the physiologic tumor-related changes in fourteen newly diagnosed glioblastoma patients during standard therapy. 153 MRI scans and blood collection were performed before chemoradiation (baseline), weekly during chemoradiation (week 1–6), monthly before each cycle of adjuvant temozolomide (pre-C1-C6), and after cycle 6. The apparent diffusion coefficient, volume transfer coefficient (Ktrans), and relative cerebral blood volume (rCBV) and flow (rCBF) were calculated within the tumor and edema regions and compared to baseline. Cox regression analysis was used to assess the effect of clinical variables, imaging, and blood markers on progression-free (PFS) and overall survival (OS). After controlling for additional covariates, high baseline rCBV and rCBF within the edema region were associated with worse PFS (microvessel rCBF: HR = 7.849, p = 0.044; panvessel rCBV: HR = 3.763, p = 0.032; panvessel rCBF: HR = 3.984; p = 0.049). The same applied to high week 5 and pre-C1 Ktrans within the tumor region (week 5 Ktrans: HR = 1.038, p = 0.003; pre-C1 Ktrans: HR = 1.029, p = 0.004). Elevated week 6 VEGF levels were associated with worse OS (HR = 1.034; p = 0.004). Our findings suggest a role for rCBV and rCBF at baseline and Ktrans and VEGF levels during treatment as markers of response. Functional imaging changes can differ substantially between tumor and edema regions, highlighting the variable biologic and vascular state of tumor microenvironment during therapy.
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Rohilla S, Garg HK, Singh I, Yadav RK, Dhaulakhandi DB. rCBV- and ADC-based Grading of Meningiomas With Glimpse Into Emerging Molecular Diagnostics. Basic Clin Neurosci 2018; 9:417-428. [PMID: 30719256 PMCID: PMC6359681 DOI: 10.32598/bcn.9.6.417] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 02/25/2017] [Accepted: 05/05/2017] [Indexed: 11/20/2022] Open
Abstract
Introduction This study was conducted to grade meningiomas based on relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC) to help surgeons plan the approach and extent of operation as well as decide on the need of any adjuvant radio/chemo therapy. The current and evolving genomic, proteomic, and spectroscopic technologies are also discussed which can supplement the current radiologic methods and procedures in grading meningiomas. Methods A total of 35 patients with meningioma prospectively underwent basic MR sequences (T1W, T2W, T2W/FLAIR) in axial, sagittal and coronal planes followed by Diffusion Weighted (DW) imaging having b value of 1000 (minimum ADC values used for analysis). Then, gadobenate dimeglumine/meglumine gadoterate was administered (0.1 mmol/kg at a rate of 4 mL/s) followed by saline flush (20 mL at a rate of 4 mL/s). Next, T2*W/FFE dynamic images were acquired; dynamics showing maximum fall in intensity was used for creating rCBV and relative Cerebral Blood Flow (rCBF) maps and calculating rCBV. Results Both maximum rCBV and minimum ADC within the tumor were not significant for differentiating benign from malignant meningiomas. A cut-off maximum rCBV of 2.5 mL/100 g in peritumoral edema was 75% sensitive, 84.6% specific, and 83.3% accurate in differentiating benign from malignant meningiomas. Conclusion Benign and malignant meningiomas can be differentiated based on maximum rCBV in peritumoral edema but ADC values within the tumor are insignificant in differentiating benign and malignant tumors. rCBV values within tumor, however, may be helpful in subtyping meningiomas, especially transitional and meningothelial meningiomas.
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Affiliation(s)
- Seema Rohilla
- Department of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Sciences, Sharma University of Health Sciences, Rohtak, Haryana, India
| | - Harender K Garg
- Department of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Sciences, Sharma University of Health Sciences, Rohtak, Haryana, India
| | - Ishwar Singh
- Department of Neurosurgery, Post Graduate Institute of Medical Sciences, Sharma University of Health Sciences, Rohtak, Haryana, India
| | - Rohtas K Yadav
- Department of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Sciences, Sharma University of Health Sciences, Rohtak, Haryana, India
| | - Dhara B Dhaulakhandi
- Department of Biotechnology & Molecular Medicine, Post Graduate Institute of Medical Sciences, Regional Cancer Centre, Sharma University of Health Sciences, Rohtak, Haryana, India
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Bonnitcha P, Grieve S, Figtree G. Clinical imaging of hypoxia: Current status and future directions. Free Radic Biol Med 2018; 126:296-312. [PMID: 30130569 DOI: 10.1016/j.freeradbiomed.2018.08.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 07/30/2018] [Accepted: 08/14/2018] [Indexed: 12/20/2022]
Abstract
Tissue hypoxia is a key feature of many important causes of morbidity and mortality. In pathologies such as stroke, peripheral vascular disease and ischaemic heart disease, hypoxia is largely a consequence of low blood flow induced ischaemia, hence perfusion imaging is often used as a surrogate for hypoxia to guide clinical diagnosis and treatment. Importantly, ischaemia and hypoxia are not synonymous conditions as it is not universally true that well perfused tissues are normoxic or that poorly perfused tissues are hypoxic. In pathologies such as cancer, for instance, perfusion imaging and oxygen concentration are less well correlated, and oxygen concentration is independently correlated to radiotherapy response and overall treatment outcomes. In addition, the progression of many diseases is intricately related to maladaptive responses to the hypoxia itself. Thus there is potentially great clinical and scientific utility in direct measurements of tissue oxygenation. Despite this, imaging assessment of hypoxia in patients is rarely performed in clinical settings. This review summarises some of the current methods used to clinically evaluate hypoxia, the barriers to the routine use of these methods and the newer agents and techniques being explored for the assessment of hypoxia in pathological processes.
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Affiliation(s)
- Paul Bonnitcha
- Northern and Central Clinical Schools, Faculty of Medicine, Sydney University, Sydney, NSW 2006, Australia; Chemical Pathology Department, NSW Health Pathology, Royal Prince Alfred Hospital, Camperdown, NSW 2050, Australia; Kolling Institute of Medical Research, University of Sydney, St Leonards, New South Wales 2065, Australia.
| | - Stuart Grieve
- Sydney Translational Imaging Laboratory, Heart Research Institute, Charles Perkins Centre and Sydney Medical School, University of Sydney, NSW 2050, Australia
| | - Gemma Figtree
- Kolling Institute of Medical Research, University of Sydney, St Leonards, New South Wales 2065, Australia; Cardiology Department, Royal North Shore Hospital, St Leonards, New South Wales 2065, Australia
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Gamboa NT, Karsy M, Gamboa JT, Yoon NK, Driscoll MJ, Sonnen JA, Salzman KL, Jensen RL. Preoperative and intraoperative perfusion magnetic resonance imaging in a RELA fusion-positive anaplastic ependymoma: A case report. Surg Neurol Int 2018; 9:144. [PMID: 30105138 PMCID: PMC6069373 DOI: 10.4103/sni.sni_116_18] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 05/07/2018] [Indexed: 01/07/2023] Open
Abstract
Background Ependymomas are rare neuroepithelial tumors thought to arise from radial glial precursor cells lining the walls of the ventricles and central canal of the brain and spinal cord, respectively. Histopathological classification, according to World Health Organization criteria, has only recently defined the RELA-fusion positive ependymoma. These tumors may account for 70% of supratentorial ependymomas in children and represent an aggressive entity distinct from other ependymomas. Case Description Here we present the case of a patient with RELA-fusion positive ependymoma of the frontal lobe in whom we used preoperative and intraoperative magnetic resonance (MR) perfusion imaging. In this first demonstrated intraoperative evaluation of MR perfusion in ependymoma, increased peripheral perfusion of the lesion in a ring-like manner with a discrete cutoff around the surgical margin correlated with intraoperative findings of a clear border between the tumor and brain, as well as pathological findings of increased MIB index and hypercellularity-specifically within solid tumor components. An abnormal perfusion pattern also suggested an aggressive lesion, which was later confirmed on pathological analysis. In addition, intraoperative MR perfusion improved detection of tumor tissue in combination with traditional T1-weighted contrast-enhanced methods, which increased extent of resection. Conclusions MR perfusion imaging may be a useful method for delineating tumor aggressiveness and borders, which can be prognostic.
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Affiliation(s)
- Nicholas T Gamboa
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - Michael Karsy
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - Joseph T Gamboa
- Department of Radiology, Texas Tech University Health Sciences Center, El Paso, Texas, USA
| | - Nam K Yoon
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - Meghan J Driscoll
- Department of Pathology, Division of Anatomic Pathology, University of Utah, Salt Lake City, Utah, USA
| | - Joshua A Sonnen
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA.,Department of Pathology, Division of Anatomic Pathology, University of Utah, Salt Lake City, Utah, USA
| | - Karen L Salzman
- Department of Neuroradiology, University of Utah, Salt Lake City, Utah, USA
| | - Randy L Jensen
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA.,Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
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Ly KI, Gerstner ER. The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies. Curr Treat Options Oncol 2018; 19:40. [PMID: 29931476 DOI: 10.1007/s11864-018-0558-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OPINION STATEMENT T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.
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Affiliation(s)
- K Ina Ly
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, Yawkey 9E, Boston, MA, 02114, USA
| | - Elizabeth R Gerstner
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, Yawkey 9E, Boston, MA, 02114, USA.
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