1
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He Q, Yang Z, Xue B, Song X, Zhang C, Yin C, Li Z, Deng Z, Sun S, Qiao H, Xie J, Hou Z. Epilepsy alters brain networks in patients with insular glioma. CNS Neurosci Ther 2024; 30:e14805. [PMID: 38887197 PMCID: PMC11183176 DOI: 10.1111/cns.14805] [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: 01/31/2024] [Revised: 05/13/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024] Open
Abstract
AIMS We intend to elucidate the alterations of cerebral networks in patients with insular glioma-related epilepsy (GRE) based on resting-state functional magnetic resonance images. METHODS We collected 62 insular glioma patients, who were subsequently categorized into glioma-related epilepsy (GRE) and glioma with no epilepsy (GnE) groups, and recruited 16 healthy individuals matched to the patient's age and gender to form the healthy control (HC) group. Graph theoretical analysis was applied to reveal differences in sensorimotor, default mode, visual, and executive networks among different subgroups. RESULTS No significant alterations in functional connectivity were found in either hemisphere insular glioma. Using graph theoretical analysis, differences were found in visual, sensorimotor, and default mode networks (p < 0.05). When the glioma located in the left hemisphere, the degree centrality was reduced in the GE group compared to the GnE group. When the glioma located in the right insula, the degree centrality, nodal efficiency, nodal local efficiency, and nodal clustering coefficient of the GE group were lower than those of the GnE group. CONCLUSION The impact of insular glioma itself and GRE on the brain network is widespread. The networks altered by insular GRE differ depending on the hemisphere location. GRE reduces the nodal properties of brain networks than that in insular glioma.
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Affiliation(s)
- Qifeng He
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zuocheng Yang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - BoWen Xue
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xinyu Song
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Chuanhao Zhang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - ChuanDong Yin
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhenye Li
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhenghai Deng
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Shengjun Sun
- Department of Neuroradiology, Beijing Neurosurgical Institute, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Department of Radiology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Hui Qiao
- Department of Neurophysiology, Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
| | - Jian Xie
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zonggang Hou
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
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2
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Drexler R, Khatri R, Sauvigny T, Mohme M, Maire CL, Ryba A, Zghaibeh Y, Dührsen L, Salviano-Silva A, Lamszus K, Westphal M, Gempt J, Wefers AK, Neumann JE, Bode H, Hausmann F, Huber TB, Bonn S, Jütten K, Delev D, Weber KJ, Harter PN, Onken J, Vajkoczy P, Capper D, Wiestler B, Weller M, Snijder B, Buck A, Weiss T, Göller PC, Sahm F, Menstel JA, Zimmer DN, Keough MB, Ni L, Monje M, Silverbush D, Hovestadt V, Suvà ML, Krishna S, Hervey-Jumper SL, Schüller U, Heiland DH, Hänzelmann S, Ricklefs FL. A prognostic neural epigenetic signature in high-grade glioma. Nat Med 2024; 30:1622-1635. [PMID: 38760585 PMCID: PMC11186787 DOI: 10.1038/s41591-024-02969-w] [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: 08/07/2023] [Accepted: 04/03/2024] [Indexed: 05/19/2024]
Abstract
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.
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Affiliation(s)
- Richard Drexler
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Robin Khatri
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thomas Sauvigny
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Malte Mohme
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Cecile L Maire
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alice Ryba
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Yahya Zghaibeh
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Lasse Dührsen
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Amanda Salviano-Silva
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katrin Lamszus
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Manfred Westphal
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Gempt
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Annika K Wefers
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Julia E Neumann
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Molecular Neurobiology Hamburg (ZMNH), University Hospital Hamburg Eppendorf, Hamburg, Germany
| | - Helena Bode
- Research Institute Children's Cancer Center Hamburg, Hamburg, Germany
| | - Fabian Hausmann
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias B Huber
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Bonn
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kerstin Jütten
- Department of Neurosurgery, University Hospital Aachen, Aachen, Germany
| | - Daniel Delev
- Department of Neurosurgery, University Hospital Aachen, Aachen, Germany
- Department of Neurosurgery, University Clinic Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Katharina J Weber
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Frankfurt am Main, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany
- University Cancer Center (UCT) Frankfurt, Frankfurt am Main, Germany
| | - Patrick N Harter
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Frankfurt am Main, Germany
- Institute of Neuropathology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Julia Onken
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - David Capper
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University Munich, Munich, Germany
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Neurology, University of Zürich, Zurich, Switzerland
| | - Berend Snijder
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Alicia Buck
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Neurology, University of Zürich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
- Department of Neurology, University of Zürich, Zurich, Switzerland
| | - Pauline C Göller
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany
| | - Felix Sahm
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany
| | - Joelle Aline Menstel
- Department of Neurosurgery, Medical Center University of Freiburg, Freiburg, Germany
| | - David Niklas Zimmer
- Department of Neurosurgery, Medical Center University of Freiburg, Freiburg, Germany
| | | | - Lijun Ni
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Michelle Monje
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Dana Silverbush
- Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Volker Hovestadt
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Mario L Suvà
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Saritha Krishna
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Shawn L Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
| | - Ulrich Schüller
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Research Institute Children's Cancer Center Hamburg, Hamburg, Germany
- Department of Pediatric Hematology and Oncology, Research Institute Children's Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dieter H Heiland
- Department of Neurosurgery, University Clinic Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Neurosurgery, Medical Center University of Freiburg, Freiburg, Germany
- Translational Neurosurgery, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Sonja Hänzelmann
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Franz L Ricklefs
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
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3
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Zhang S, Yang X, Tan Q, Sun H, Chen D, Chen Y, Zhang H, Yang Y, Gong Q, Yue Q. Cortical myelin and thickness mapping provide insights into whole-brain tumor burden in diffuse midline glioma. Cereb Cortex 2024; 34:bhad491. [PMID: 38112602 PMCID: PMC10793579 DOI: 10.1093/cercor/bhad491] [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: 10/30/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 12/21/2023] Open
Abstract
Systemic infiltration is a hallmark of diffuse midline glioma pathogenesis, which can trigger distant disturbances in cortical structure. However, the existence and effects of these changes have been underexamined. This study aimed to investigate whole-brain cortical myelin and thickness alternations induced by diffuse midline glioma. High-resolution T1- and T2-weighted images were acquired from 90 patients with diffuse midline glioma with H3 K27-altered and 64 patients with wild-type and 86 healthy controls. Cortical thickness and myelin content was calculated using Human Connectome Project pipeline. Significant differences in cortical thickness and myelin content were detected among groups. Short-term survival prediction model was constructed using automated machine learning. Compared with healthy controls, diffuse midline glioma with H3 K27-altered patients showed significantly reduced cortical myelin in bilateral precentral gyrus, postcentral gyrus, insular, parahippocampal gyrus, fusiform gyrus, and cingulate gyrus, whereas diffuse midline glioma with H3 K27 wild-type patients exhibited well-preserved myelin content. Furtherly, when comparing diffuse midline glioma with H3 K27-altered and diffuse midline glioma with H3 K27 wild-type, the decreased cortical thickness in parietal and occipital regions along with demyelination in medial orbitofrontal cortex was observed in diffuse midline glioma with H3 K27-altered. Notably, a combination of cortical features and tumor radiomics allowed short-term survival prediction with accuracy 0.80 and AUC 0.84. These findings may aid clinicians in tailoring therapeutic approaches based on cortical characteristics, potentially enhancing the efficacy of current and future treatment modalities.
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Affiliation(s)
- Simin Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Xibiao Yang
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiaoyue Tan
- Division of Radiation Physics, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Di Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Yinying Chen
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Hongjing Zhang
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Radiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610065, China
| | - Yuan Yang
- Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen 610041, China
| | - Qiang Yue
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu 610041, China
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4
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Luckett PH, Olufawo M, Lamichhane B, Park KY, Dierker D, Verastegui GT, Yang P, Kim AH, Chheda MG, Snyder AZ, Shimony JS, Leuthardt EC. Predicting survival in glioblastoma with multimodal neuroimaging and machine learning. J Neurooncol 2023; 164:309-320. [PMID: 37668941 PMCID: PMC10522528 DOI: 10.1007/s11060-023-04439-8] [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: 08/03/2023] [Accepted: 08/26/2023] [Indexed: 09/06/2023]
Abstract
PURPOSE Glioblastoma (GBM) is the most common and aggressive malignant glioma, with an overall median survival of less than two years. The ability to predict survival before treatment in GBM patients would lead to improved disease management, clinical trial enrollment, and patient care. METHODS GBM patients (N = 133, mean age 60.8 years, median survival 14.1 months, 57.9% male) were retrospectively recruited from the neurosurgery brain tumor service at Washington University Medical Center. All patients completed structural neuroimaging and resting state functional MRI (RS-fMRI) before surgery. Demographics, measures of cortical thickness (CT), and resting state functional network connectivity (FC) were used to train a deep neural network to classify patients based on survival (< 1y, 1-2y, >2y). Permutation feature importance identified the strongest predictors of survival based on the trained models. RESULTS The models achieved a combined cross-validation and hold out accuracy of 90.6% in classifying survival (< 1y, 1-2y, >2y). The strongest demographic predictors were age at diagnosis and sex. The strongest CT predictors of survival included the superior temporal sulcus, parahippocampal gyrus, pericalcarine, pars triangularis, and middle temporal regions. The strongest FC features primarily involved dorsal and inferior somatomotor, visual, and cingulo-opercular networks. CONCLUSION We demonstrate that machine learning can accurately classify survival in GBM patients based on multimodal neuroimaging before any surgical or medical intervention. These results were achieved without information regarding presentation symptoms, treatments, postsurgical outcomes, or tumor genomic information. Our results suggest GBMs have a global effect on the brain's structural and functional organization, which is predictive of survival.
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Affiliation(s)
- Patrick H Luckett
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA.
| | - Michael Olufawo
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Bidhan Lamichhane
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Center for Health Sciences, Oklahoma State University, Tulsa, OK, 74136, USA
| | - Ki Yun Park
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Peter Yang
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Albert H Kim
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Brain Tumor Center at Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Milan G Chheda
- Brain Tumor Center at Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Brain Tumor Center at Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Brain Tumor Center at Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University in Saint Louis, St. Louis, MO, 63130, USA
- Department of Mechanical Engineering and Materials Science, Washington University in Saint Louis, St. Louis, MO, 63130, USA
- Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Brain Laser Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- National Center for Adaptive Neurotechnologies, Albany, USA
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5
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Drexler R, Khatri R, Sauvigny T, Mohme M, Maire CL, Ryba A, Zghaibeh Y, Dührsen L, Salviano-Silva A, Lamszus K, Westphal M, Gempt J, Wefers AK, Neumann J, Bode H, Hausmann F, Huber TB, Bonn S, Jütten K, Delev D, Weber KJ, Harter PN, Onken J, Vajkoczy P, Capper D, Wiestler B, Weller M, Snijder B, Buck A, Weiss T, Keough MB, Ni L, Monje M, Silverbush D, Hovestadt V, Suvà ML, Krishna S, Hervey-Jumper SL, Schüller U, Heiland DH, Hänzelmann S, Ricklefs FL. Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.04.552017. [PMID: 37609137 PMCID: PMC10441357 DOI: 10.1101/2023.08.04.552017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.
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Affiliation(s)
- Richard Drexler
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurology, Stanford University, Stanford, CA, 94305, USA
| | - Robin Khatri
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thomas Sauvigny
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Malte Mohme
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Cecile L. Maire
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alice Ryba
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Yahya Zghaibeh
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Lasse Dührsen
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Amanda Salviano-Silva
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katrin Lamszus
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Manfred Westphal
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Gempt
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Annika K. Wefers
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Julia Neumann
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Pediatric Hematology and Oncology, Research Institute Children’s Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Research Institute Children’s Cancer Center Hamburg, Hamburg, Germany
| | - Helena Bode
- Research Institute Children’s Cancer Center Hamburg, Hamburg, Germany
| | - Fabian Hausmann
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias B. Huber
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Hamburg Center for Translational Immunology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Bonn
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kerstin Jütten
- Department of Neurosurgery, University Hospital Aachen, Aachen, Germany
| | - Daniel Delev
- Department of Neurosurgery, University Hospital Aachen, Aachen, Germany
| | - Katharina J. Weber
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Frankfurt am Main, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany
- University Cancer Center (UCT) Frankfurt, Frankfurt am Main, Germany
| | - Patrick N. Harter
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Frankfurt am Main, Germany
- Institute of Neuropathology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Julia Onken
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - David Capper
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Benedikt Wiestler
- Department of Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University Munich, Munich
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Switzerland. Department of Neurology, University of Zürich, Switzerland
| | - Berend Snijder
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Alicia Buck
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Switzerland. Department of Neurology, University of Zürich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Switzerland. Department of Neurology, University of Zürich, Switzerland
| | - Michael B. Keough
- Department of Neurology, Stanford University, Stanford, CA, 94305, USA
| | - Lijun Ni
- Department of Neurology, Stanford University, Stanford, CA, 94305, USA
| | - Michelle Monje
- Department of Neurology, Stanford University, Stanford, CA, 94305, USA
| | | | | | - Mario L. Suvà
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Saritha Krishna
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, 94143, USA
| | - Shawn L. Hervey-Jumper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, 94143, USA
| | - Ulrich Schüller
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Pediatric Hematology and Oncology, Research Institute Children’s Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Research Institute Children’s Cancer Center Hamburg, Hamburg, Germany
| | - Dieter H. Heiland
- Department of Neurosurgery, Medical Center University of Freiburg, Freiburg, Germany
| | - Sonja Hänzelmann
- Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Hamburg Center for Translational Immunology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Franz L. Ricklefs
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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6
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Moretto M, Silvestri E, Facchini S, Anglani M, Cecchin D, Corbetta M, Bertoldo A. The dynamic functional connectivity fingerprint of high-grade gliomas. Sci Rep 2023; 13:10389. [PMID: 37369744 DOI: 10.1038/s41598-023-37478-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 06/22/2023] [Indexed: 06/29/2023] Open
Abstract
Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients' cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.
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Affiliation(s)
- Manuela Moretto
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy
| | - Erica Silvestri
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy
| | - Silvia Facchini
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Neuroscience, University of Padova, 35121, Padova, Italy
| | | | - Diego Cecchin
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Unit of Nuclear Medicine, University of Padova, 35121, Padova, Italy
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
- Department of Neuroscience, University of Padova, 35121, Padova, Italy
- Venetian Institute of Molecular Medicine, 35131, Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, 35131, Padova, Italy.
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6/B, 35131, Padova, Italy.
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7
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Yang J, Zhang X, Gao X, Wu H, Li X, Yang L, Zhang N. Fiber Density and Structural Brain Connectome in Glioblastoma Are Correlated With Glioma Cell Infiltration. Neurosurgery 2023; 92:1234-1242. [PMID: 36744904 DOI: 10.1227/neu.0000000000002356] [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: 08/25/2022] [Accepted: 11/08/2022] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Glioblastoma (GBM) preferred to infiltrate into white matter (WM) beyond the recognizable tumor margin. OBJECTIVE To investigate whether fiber density (FD) and structural brain connectome can provide meaningful information about WM destruction and glioma cell infiltration. METHODS GBM cases were collected based on inclusion criteria, and baseline information and preoperative MRI results were obtained. GBM lesions were automatically segmented into necrosis, contrast-enhanced tumor, and edema areas. We obtained the FD map to compute the FD and lnFD values in each subarea and reconstructed the structural brain connectome to obtain the topological metrics in each subarea. We also divided the edema area into a nonenhanced tumor (NET) area and a normal WM area based on the contralesional lnFD value in the edema area, and computed the NET ratio. RESULTS Twenty-five GBM cases were included in this retrospective study. The FD/lnFD value and topological metrics (aCp, aLp, aEg, aEloc, and ar) were significantly correlated with GBM subareas, which represented the extent of WM destruction and glioma cell infiltration. The FD/lnFD values and topological parameters were correlated with the NET ratio. In particular, the lnFD value in the edema area was correlated with the NET ratio (coefficient, 0.92). Therefore, a larger lnFD value indicates more severe glioma infiltration in the edema area and suggests an extended resection for better clinical outcomes. CONCLUSION The FD and structural brain connectome in this study provide a new insight into glioma infiltration and a different consideration of their clinical application in neuro-oncology.
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Affiliation(s)
- Jia Yang
- Department of Neurosurgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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8
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Meyer-Baese A, Jütten K, Meyer-Baese U, Amani AM, Malberg H, Stadlbauer A, Kinfe T, Na CH. Controllability and Robustness of Functional and Structural Connectomic Networks in Glioma Patients. Cancers (Basel) 2023; 15:2714. [PMID: 37345051 DOI: 10.3390/cancers15102714] [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: 03/30/2023] [Revised: 04/24/2023] [Accepted: 04/28/2023] [Indexed: 06/23/2023] Open
Abstract
Previous studies suggest that the topological properties of structural and functional neural networks in glioma patients are altered beyond the tumor location. These alterations are due to the dynamic interactions with large-scale neural circuits. Understanding and describing these interactions may be an important step towards deciphering glioma disease evolution. In this study, we analyze structural and functional brain networks in terms of determining the correlation between network robustness and topological features regarding the default-mode network (DMN), comparing prognostically differing patient groups to healthy controls. We determine the driver nodes of these networks, which are receptive to outside signals, and the critical nodes as the most important elements for controllability since their removal will dramatically affect network controllability. Our results suggest that network controllability and robustness of the DMN is decreased in glioma patients. We found losses of driver and critical nodes in patients, especially in the prognostically less favorable IDH wildtype (IDHwt) patients, which might reflect lesion-induced network disintegration. On the other hand, topological shifts of driver and critical nodes, and even increases in the number of critical nodes, were observed mainly in IDH mutated (IDHmut) patients, which might relate to varying degrees of network plasticity accompanying the chronic disease course in some of the patients, depending on tumor growth dynamics. We hereby implement a novel approach for further exploring disease evolution in brain cancer under the aspects of neural network controllability and robustness in glioma patients.
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Affiliation(s)
- Anke Meyer-Baese
- Department of Scientific Computing, Florida State University, Tallahassee, FL 32306, USA
- Institute for Biomedical Engineering, Technical University of Dresden, 01069 Dresden, Germany
| | - Kerstin Jütten
- Department of Neurosurgery, RWTH Aachen University, 52074 Aachen, Germany
| | - Uwe Meyer-Baese
- Department of Electrical and Computer Engineering, Florida State University, Tallahassee, FL 32310, USA
| | - Ali Moradi Amani
- School of Engineering, RMIT University, Melbourne, Victoria 3001, Australia
| | - Hagen Malberg
- Institute for Biomedical Engineering, Technical University of Dresden, 01069 Dresden, Germany
| | - Andreas Stadlbauer
- Department of Neurosurgery, Friedrich-Alexander University of Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Thomas Kinfe
- Department of Neurosurgery, Friedrich-Alexander University of Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Chuh-Hyoun Na
- Department of Neurosurgery, RWTH Aachen University, 52074 Aachen, Germany
- Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), 52074 Aachen, Germany
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9
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Self-Referential Processing and Resting-State Functional MRI Connectivity of Cortical Midline Structures in Glioma Patients. Brain Sci 2022; 12:brainsci12111463. [DOI: 10.3390/brainsci12111463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 10/13/2022] [Accepted: 10/24/2022] [Indexed: 11/16/2022] Open
Abstract
Metacognition has only scarcely been investigated in brain tumor patients. It is unclear if and how the tumor-lesioned brain might be able to maintain an adequate sense-of-self. As cortical midline structures (CMS) are regarded as essential for self-referential mental activity, we investigated resting-state fMRI connectivity (FC) of CMS to the default-mode network (DMN) and to the whole brain, comparing glioma patients and matched controls. Subjects furthermore performed a trait judgement (TJ), a trait recall task (TR), and neuropsychological testing. In the TJ, adjectives had to be ascribed as self- or non-self-describing, assessing the self-serving effect (SSE), a normally observed bias for positive traits. In the TR, the mnemic neglect effect (MNE), a memory advantage for positive traits, was tested. The groups were compared and partial correlations between FC and test metrics were analyzed. Although patients were significantly impaired in terms of verbal memory, groups did not differ in the SSE or the MNE results, showing preserved metacognitive abilities in patients. FC of CMS to the DMN was maintained, but was significantly decreased to whole brain in the patients. FC of the dorsomedial prefrontal cortex (DMPFC) to whole brain was correlated with the MNE in patients. Preserving the DMPFC in therapeutic interventions might be relevant for maintaining self-related verbal information processing in the memory domain in glioma patients.
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Quantum dots: The cutting-edge nanotheranostics in brain cancer management. J Control Release 2022; 350:698-715. [PMID: 36057397 DOI: 10.1016/j.jconrel.2022.08.047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 12/14/2022]
Abstract
Quantum dots (QDs) are semiconductor nanocrystals possessing unique optoelectrical properties in that they can emit light energy of specific tunable wavelengths when excited by photons. They are gaining attention nowadays owing to their all-around ability to allow high-quality bio-imaging along with targeted drug delivery. The most lethal central nervous system (CNS) disorders are brain cancers or malignant brain tumors. CNS is guarded by the blood-brain barrier which poses a selective blockade toward drug delivery into the brain. QDs have displayed strong potential to deliver therapeutic agents into the brain successfully. Their bio-imaging capability due to photoluminescence and specific targeting ability through the attachment of ligand biomolecules make them preferable clinical tools for coming times. Biocompatible QDs are emerging as nanotheranostic tools to identify/diagnose and selectively kill cancer cells. The current review focuses on QDs and associated nanoformulations as potential futuristic clinical aids in the continuous battle against brain cancer.
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Ciavarro M, Grande E, Bevacqua G, Morace R, Ambrosini E, Pavone L, Grillea G, Vangelista T, Esposito V. Structural Brain Network Reorganization Following Anterior Callosotomy for Colloid Cysts: Connectometry and Graph Analysis Results. Front Neurol 2022; 13:894157. [PMID: 35923826 PMCID: PMC9340207 DOI: 10.3389/fneur.2022.894157] [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] [Received: 03/11/2022] [Accepted: 06/03/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction:The plasticity of the neural circuits after injuries has been extensively investigated over the last decades. Transcallosal microsurgery for lesions affecting the third ventricle offers an interesting opportunity to investigate the whole-brain white matter reorganization occurring after a selective resection of the genu of the corpus callosum (CC).MethodDiffusion MRI (dMRI) data and neuropsychological testing were collected pre- and postoperatively in six patients with colloid cysts, surgically treated with a transcallosal-transgenual approach. Longitudinal connectometry analysis on dMRI data and graph analysis on structural connectivity matrix were implemented to analyze how white matter pathways and structural network topology reorganize after surgery.ResultsAlthough a significant worsening in cognitive functions (e.g., executive and memory functioning) at early postoperative, a recovery to the preoperative status was observed at 6 months. Connectometry analysis, beyond the decrease of quantitative anisotropy (QA) near the resection cavity, showed an increase of QA in the body and forceps major CC subregions, as well as in the left intra-hemispheric corticocortical associative fibers. Accordingly, a reorganization of structural network topology was observed between centrality increasing in the left hemisphere nodes together with a rise in connectivity strength among mid and posterior CC subregions and cortical nodes.ConclusionA structural reorganization of intra- and inter-hemispheric connective fibers and structural network topology were observed following the resection of the genu of the CC. Beyond the postoperative transient cognitive impairment, it could be argued anterior CC resection does not preclude neural plasticity and may subserve the long-term postoperative cognitive recovery.
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Affiliation(s)
- Marco Ciavarro
- Mediterranean Neurological Institute Neuromed (IRCCS) Neuromed, Pozzilli, Italy
- *Correspondence: Marco Ciavarro
| | - Eleonora Grande
- Department of Neuroscience, Imaging and Clinical Sciences, Gabriele d'Annunzio University, Chieti, Italy
| | | | - Roberta Morace
- Mediterranean Neurological Institute Neuromed (IRCCS) Neuromed, Pozzilli, Italy
| | - Ettore Ambrosini
- Department of General Psychology, University of Padua, Padua, Italy
- Department of Neuroscience, University of Padua, Padua, Italy
- Padua Neuroscience Center, University of Padua, Padua, Italy
| | - Luigi Pavone
- Mediterranean Neurological Institute Neuromed (IRCCS) Neuromed, Pozzilli, Italy
| | - Giovanni Grillea
- Mediterranean Neurological Institute Neuromed (IRCCS) Neuromed, Pozzilli, Italy
| | - Tommaso Vangelista
- Mediterranean Neurological Institute Neuromed (IRCCS) Neuromed, Pozzilli, Italy
| | - Vincenzo Esposito
- Mediterranean Neurological Institute Neuromed (IRCCS) Neuromed, Pozzilli, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
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Chen Z, Ye N, Teng C, Li X. Alternations and Applications of the Structural and Functional Connectome in Gliomas: A Mini-Review. Front Neurosci 2022; 16:856808. [PMID: 35478847 PMCID: PMC9035851 DOI: 10.3389/fnins.2022.856808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 02/28/2022] [Indexed: 12/12/2022] Open
Abstract
In the central nervous system, gliomas are the most common, but complex primary tumors. Genome-based molecular and clinical studies have revealed different classifications and subtypes of gliomas. Neuroradiological approaches have non-invasively provided a macroscopic view for surgical resection and therapeutic effects. The connectome is a structural map of a physical object, the brain, which raises issues of spatial scale and definition, and it is calculated through diffusion magnetic resonance imaging (MRI) and functional MRI. In this study, we reviewed the basic principles and attributes of the structural and functional connectome, followed by the alternations of connectomes and their influences on glioma. To extend the applications of connectome, we demonstrated that a series of multi-center projects still need to be conducted to systemically investigate the connectome and the structural-functional coupling of glioma. Additionally, the brain-computer interface based on accurate connectome could provide more precise structural and functional data, which are significant for surgery and postoperative recovery. Besides, integrating the data from different sources, including connectome and other omics information, and their processing with artificial intelligence, together with validated biological and clinical findings will be significant for the development of a personalized surgical strategy.
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Affiliation(s)
- Ziyan Chen
- Department of Neurosurgery, Xiangya Hospital, Central South University, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, China
| | - Ningrong Ye
- Department of Neurosurgery, Xiangya Hospital, Central South University, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, China
| | - Chubei Teng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, China
- Department of Neurosurgery, The First Affiliated Hospital, University of South China, Hengyang, China
| | - Xuejun Li
- Department of Neurosurgery, Xiangya Hospital, Central South University, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, China
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Dadario NB, Sughrue ME. Should Neurosurgeons Try to Preserve Non-Traditional Brain Networks? A Systematic Review of the Neuroscientific Evidence. J Pers Med 2022; 12:jpm12040587. [PMID: 35455703 PMCID: PMC9029431 DOI: 10.3390/jpm12040587] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/30/2022] [Accepted: 04/03/2022] [Indexed: 12/25/2022] Open
Abstract
The importance of large-scale brain networks in higher-order human functioning is well established in neuroscience, but has yet to deeply penetrate neurosurgical thinking due to concerns of clinical relevance. Here, we conducted the first systematic review examining the clinical importance of non-traditional, large-scale brain networks, including the default mode (DMN), central executive (CEN), salience (SN), dorsal attention (DAN), and ventral attention (VAN) networks. Studies which reported evidence of neurologic, cognitive, or emotional deficits in relation to damage or dysfunction in these networks were included. We screened 22,697 articles on PubMed, and 551 full-text articles were included and examined. Cognitive deficits were the most common symptom of network disturbances in varying amounts (36–56%), most frequently related to disruption of the DMN (n = 213) or some combination of DMN, CEN, and SN networks (n = 182). An increased proportion of motor symptoms was seen with CEN disruption (12%), and emotional (35%) or language/speech deficits (24%) with SN disruption. Disruption of the attention networks (VAN/DAN) with each other or the other networks mostly led to cognitive deficits (56%). A large body of evidence is available demonstrating the clinical importance of non-traditional, large-scale brain networks and suggests the need to preserve these networks is relevant for neurosurgical patients.
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Affiliation(s)
- Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA;
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia
- Omniscient Neurotechnology, Sydney, NSW 2000, Australia
- Correspondence:
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What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients? Tomography 2022; 8:267-280. [PMID: 35202187 PMCID: PMC8878995 DOI: 10.3390/tomography8010021] [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] [Received: 12/20/2021] [Revised: 01/12/2022] [Accepted: 01/14/2022] [Indexed: 11/24/2022] Open
Abstract
Resting-state functional MRI has been increasingly implemented in imaging protocols for the study of functional connectivity in glioma patients as a sequence able to capture the activity of brain networks and to investigate their properties without requiring the patients’ cooperation. The present review aims at describing the most recent results obtained through the analysis of resting-state fMRI data in different contexts of interest for brain gliomas: the identification and localization of functional networks, the characterization of altered functional connectivity, and the evaluation of functional plasticity in relation to the resection of the glioma. An analysis of the literature showed that significant and promising results could be achieved through this technique in all the aspects under investigation. Nevertheless, there is room for improvement, especially in terms of stability and generalizability of the outcomes. Further research should be conducted on homogeneous samples of glioma patients and at fixed time points to reduce the considerable variability in the results obtained across and within studies. Future works should also aim at establishing robust metrics for the assessment of the disruption of functional connectivity and its recovery at the single-subject level.
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