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Li Z, Zhang H, Wang X, Yang Y, Zhang Y, Zhuang Y, Wei Z, Yang Q, Gao E, Zhang Y, Cai S, Chen Z, Cai C, Bao J, Cheng J. Preoperative Subtyping of WHO Grade 1 Meningiomas Using a Single-Shot Ultrafast MR T2 Mapping. J Magn Reson Imaging 2024; 60:964-976. [PMID: 38112331 DOI: 10.1002/jmri.29183] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Meningioma subtype is crucial in treatment planning and prognosis delineation, for grade 1 meningiomas. T2 relaxometry could provide detailed microscopic information but is often limited by long scanning times. PURPOSE To investigate the potential of T2 maps derived from multiple overlapping-echo detachment imaging (MOLED) for predicting meningioma subtypes and Ki-67 index, and to compare the diagnostic efficiency of two different region-of-interest (ROI) placements (whole-tumor and contrast-enhanced, respectively). STUDY TYPE Prospective. PHANTOM/SUBJECTS A phantom containing 11 tubes of MnCl2 at different concentrations, eight healthy volunteers, and 75 patients with grade 1 meningioma. FIELD STRENGTH/SEQUENCE 3 T scanner. MOLED, T2-weighted spin-echo sequence, T2-dark-fluid sequence, and postcontrast T1-weighted gradient echo sequence. ASSESSMENT Two ROIs were delineated: the whole-tumor area (ROI1) and contrast-enhanced area (ROI2). Histogram parameters were extracted from T2 maps. Meningioma subtypes and Ki-67 index were reviewed by a neuropathologist according to the 2021 classification criteria. STATISTICAL TESTS Linear regression, Bland-Altman analysis, Pearson's correlation analysis, independent t test, Mann-Whitney U test, Kruskal-Wallis test with Bonferroni correction, and multivariate logistic regression analysis with the P-value significance level of 0.05. RESULTS The MOLED T2 sequence demonstrated excellent accuracy for phantoms and volunteers (Meandiff = -1.29%, SDdiff = 1.25% and Meandiff = 0.36%, SDdiff = 2.70%, respectively), and good repeatability for volunteers (average coefficient of variance = 1.13%; intraclass correlation coefficient = 0.877). For both ROI1 and ROI2, T2 variance had the highest area under the curves (area under the ROC curve = 0.768 and 0.761, respectively) for meningioma subtyping. There was no significant difference between the two ROIs (P = 0.875). Significant correlations were observed between T2 parameters and Ki-67 index (r = 0.237-0.374). DATA CONCLUSION MOLED T2 maps can effectively differentiate between meningothelial, fibrous, and transitional meningiomas. Moreover, T2 histogram parameters were significantly correlated with the Ki-67 index. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zongye Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hongyan Zhang
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yijie Yang
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Yue Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuchuan Zhuang
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA
| | - Zhiliang Wei
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Qinqin Yang
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Eryuan Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuhui Cai
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Zhong Chen
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Congbo Cai
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Jianfeng Bao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Inetas-Yengin G, Bayrak OF. Related mechanisms, current treatments, and new perspectives in meningioma. Genes Chromosomes Cancer 2024; 63:e23248. [PMID: 38801095 DOI: 10.1002/gcc.23248] [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] [Received: 04/04/2024] [Revised: 04/18/2024] [Accepted: 05/02/2024] [Indexed: 05/29/2024] Open
Abstract
Meningiomas are non-glial tumors that are the most common primary brain tumors in adults. Although meningioma can possibly be cured with surgical excision, variations in atypical/anaplastic meningioma have a high recurrence rate and a poor prognosis. As a result, it is critical to develop novel therapeutic options for high-grade meningiomas. This review highlights the current histology of meningiomas, prevalent genetic and molecular changes, and the most extensively researched signaling pathways and therapies in meningiomas. It also reviews current clinical studies and novel meningioma treatments, including immunotherapy, microRNAs, cancer stem cell methods, and targeted interventions within the glycolysis pathway. Through the examination of the complex landscape of meningioma biology and the highlighting of promising therapeutic pathways, this review opens the way for future research efforts aimed at improving patient outcomes in this prevalent intracranial tumor entity.
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Affiliation(s)
- Gizem Inetas-Yengin
- Department of Medical Genetics, Yeditepe University, Medical School, Istanbul, Turkey
- Department of Genetics and Bioengineering, Yeditepe University, Istanbul, Turkey
| | - Omer Faruk Bayrak
- Department of Medical Genetics, Yeditepe University, Medical School, Istanbul, Turkey
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Wang J, Shou J, Gao H, Wang B, Ding P, Yang P. Analysis of risk factors affecting wound healing and wound infection after meningioma resection. Int Wound J 2024; 21:e14870. [PMID: 38629599 PMCID: PMC11022305 DOI: 10.1111/iwj.14870] [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] [Received: 03/07/2024] [Revised: 03/19/2024] [Accepted: 03/21/2024] [Indexed: 04/19/2024] Open
Abstract
To analyse the risk factors affecting wound healing and infection after spinal meningioma resection surgery. The surgical incision healing of 137 patients who underwent spinal meningioma resection at our hospital from January 2021 to January 2024 was analysed. The data collected included physical examination findings, haematological and biochemical measurements, and various scales assessed upon admission and after surgery. These data were then analysed. The surgical wound healing, infection and postoperative complications were statistically analysed. Multiple logistic regression analysis method was used to conduct risk factor analysis on corresponding indicators; the odds ratio and p value of 95% confidence interval were calculated. Factors such as age and smoking history were significantly negatively correlated with wound healing after meningioma resection (odds ratio < 1.000, p < 0.05), while preoperative albumin and platelet count were significantly positively correlated with wound healing (odds ratio > 1.000, p < 0.05). Age, WHO Meningioma Grading, preoperative albumin and preoperative platelet were significantly negatively correlated with wound infection after meningioma resection (odds ratio < 1.000, p < 0.05). The history of virus infection and history of neurological disorders were significantly positively correlated with wound infection (odds ratio > 1.000, p < 0.05). The influence of each factor is different. Age, smoking history, WHO Meningioma Grading, preoperative albumin, preoperative platelets, history of virus infection and history of neurological disorders had the greatest influence on wound healing and infection after meningioma resection.
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Affiliation(s)
- Jianye Wang
- Department of NeurosurgeryThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Jixin Shou
- Department of NeurosurgeryThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Haidong Gao
- Department of NeurosurgeryThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Bingbing Wang
- Department of NeurosurgeryThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Panfeng Ding
- Department of NeurosurgeryThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Peng Yang
- Department of NeurosurgeryThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
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Galli R, Lehner F, Richter S, Kirsche K, Meinhardt M, Juratli TA, Temme A, Kirsch M, Warta R, Herold-Mende C, Ricklefs FL, Lamszus K, Sievers P, Sahm F, Eyüpoglu IY, Uckermann O. Prediction of WHO grade and methylation class of aggressive meningiomas: Extraction of diagnostic information from infrared spectroscopic data. Neurooncol Adv 2024; 6:vdae082. [PMID: 39006162 PMCID: PMC11245706 DOI: 10.1093/noajnl/vdae082] [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] [Indexed: 07/16/2024] Open
Abstract
Background Infrared (IR) spectroscopy allows intraoperative, optical brain tumor diagnosis. Here, we explored it as a translational technology for the identification of aggressive meningioma types according to both, the WHO CNS grading system and the methylation classes (MC). Methods Frozen sections of 47 meningioma were examined by IR spectroscopic imaging and different classification approaches were compared to discern samples according to WHO grade or MC. Results IR spectroscopic differences were more pronounced between WHO grade 2 and 3 than between MC intermediate and MC malignant, although similar spectral ranges were affected. Aggressive types of meningioma exhibited reduced bands of carbohydrates (at 1024 cm-1) and nucleic acids (at 1080 cm-1), along with increased bands of phospholipids (at 1240 and 1450 cm-1). While linear discriminant analysis was able to discern spectra of WHO grade 2 and 3 meningiomas (AUC 0.89), it failed for MC (AUC 0.66). However, neural network classifiers were effective for classification according to both WHO grade (AUC 0.91) and MC (AUC 0.83), resulting in the correct classification of 20/23 meningiomas of the test set. Conclusions IR spectroscopy proved capable of extracting information about the malignancy of meningiomas, not only according to the WHO grade, but also for a diagnostic system based on molecular tumor characteristics. In future clinical use, physicians could assess the goodness of the classification by considering classification probabilities and cross-measurement validation. This might enhance the overall accuracy and clinical utility, reinforcing the potential of IR spectroscopy in advancing precision medicine for meningioma characterization.
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Affiliation(s)
- Roberta Galli
- Faculty of Medicine, Medical Physics and Biomedical Engineering, Technische Universität Dresden, Dresden, Germany
| | - Franz Lehner
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Sven Richter
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Else Kroener Fresenius Center for Digital Health, Technische Universität Dresden, Dresden, Germany
| | - Katrin Kirsche
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Matthias Meinhardt
- Faculty of Medicine, Department of Pathology, Technische Universität Dresden, Dresden, Germany
| | - Tareq A Juratli
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | | | - Matthias Kirsch
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Rolf Warta
- Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
| | - Christel Herold-Mende
- Division of Experimental Neurosurgery, Department of Neurosurgery, Heidelberg University, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
| | - Franz L Ricklefs
- Laboratory for Brain Tumor Research, Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katrin Lamszus
- Laboratory for Brain Tumor Research, Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Philipp Sievers
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany
- CCU Neuropathology, German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Sahm
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany
- CCU Neuropathology, German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ilker Y Eyüpoglu
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Ortrud Uckermann
- Department of Neurosurgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Else Kroener Fresenius Center for Digital Health, Technische Universität Dresden, Dresden, Germany
- Department of Psychiatry and Psychotherapy, Division of Medical Biology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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Hanna C, Willman M, Cole D, Mehkri Y, Liu S, Willman J, Lucke-Wold B. Review of meningioma diagnosis and management. EGYPTIAN JOURNAL OF NEUROSURGERY 2023; 38:16. [PMID: 37124311 PMCID: PMC10138329 DOI: 10.1186/s41984-023-00195-z] [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: 04/18/2022] [Accepted: 06/14/2022] [Indexed: 05/02/2023] Open
Abstract
Meningiomas are the most common intracranial tumors in adult patients. Although the majority of meningiomas are diagnosed as benign, approximately 20% of cases are high-grade tumors that require significant clinical treatment. The gold standard for grading central nervous system tumors comes from the World Health Organization Classification of Tumors of the central nervous system. Treatment options also depend on the location, imaging, and histopathological features of the tumor. This review will cover diagnostic strategies for meningiomas, including 2021 updates to the World Health Organization's grading of meningiomas. Meningioma treatment plans are variable and highly dependent on tumor grading. This review will also update the reader on developments in the treatment of meningiomas, including surgery, radiation therapy and monoclonal antibody treatment.
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Affiliation(s)
- Chadwin Hanna
- Department of Neurosurgery, University of Florida, Gainesville, FL, USA
| | - Matthew Willman
- Department of Neurosurgery, University of Florida, Gainesville, FL, USA
| | - Dwayne Cole
- Department of Neurosurgery, University of Florida, Gainesville, FL, USA
| | - Yusuf Mehkri
- Department of Neurosurgery, University of Florida, Gainesville, FL, USA
| | - Sophie Liu
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | - Jonathan Willman
- Department of Neurosurgery, University of Florida, Gainesville, FL, USA
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Ijad N, Dahal A, Kim AE, Wakimoto H, Juratli TA, Brastianos PK. Novel Systemic Approaches for the Management of Meningiomas. Neurosurg Clin N Am 2023; 34:447-454. [DOI: 10.1016/j.nec.2023.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
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Amadasu E, Panther E, Lucke-Wold B. Characterization and Treatment of Spinal Tumors. INTENSIVE CARE RESEARCH 2022; 2:76-95. [PMID: 36741203 PMCID: PMC9893847 DOI: 10.1007/s44231-022-00014-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 09/03/2022] [Indexed: 02/07/2023]
Abstract
The prevalence of spinal tumors is rare in comparison to brain tumors which encompass most central nervous system tumors. Tumors of the spine can be divided into primary and metastatic tumors with the latter being the most common presentation. Primary tumors are subdivided based on their location on the spinal column and in the spinal cord into intramedullary, intradural extramedullary, and primary bone tumors. Back pain is a common presentation in spine cancer patients; however, other radicular pain may be present. Magnetic resonance imaging (MRI) is the imaging modality of choice for intradural extramedullary and intramedullary tumors. Plain radiographs are used in the initial diagnosis of primary bone tumors while Computed tomography (CT) and MRI may often be necessary for further characterization. Complete surgical resection is the treatment of choice for spinal tumors and may be curative for well circumscribed lesions. However, intralesional resection along with adjuvant radiation and chemotherapy can be indicated for patients that would experience increased morbidity from damage to nearby neurological structures caused by resection with wide margins. Even with the current treatment options, the prognosis for aggressive spinal cancer remains poor. Advances in novel treatments including molecular targeting, immunotherapy and stem cell therapy provide the potential for greater control of malignant and metastatic tumors of the spine.
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Affiliation(s)
- Efosa Amadasu
- School of Medicine, University of South Florida, Tampa, USA
| | - Eric Panther
- Department of Neurosurgery, University of Florida, Gainesville, USA
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Deng J, Hua L, Bian L, Chen H, Chen L, Cheng H, Dou C, Geng D, Hong T, Ji H, Jiang Y, Lan Q, Li G, Liu Z, Qi S, Qu Y, Shi S, Sun X, Wang H, You Y, Yu H, Yue S, Zhang J, Zhang X, Wang S, Mao Y, Zhong P, Gong Y. Molecular diagnosis and treatment of meningiomas: an expert consensus (2022). Chin Med J (Engl) 2022; 135:1894-1912. [PMID: 36179152 PMCID: PMC9746788 DOI: 10.1097/cm9.0000000000002391] [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] [Received: 05/19/2022] [Indexed: 11/27/2022] Open
Abstract
ABSTRACT Meningiomas are the most common primary intracranial neoplasm with diverse pathological types and complicated clinical manifestations. The fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), published in 2021, introduces major changes that advance the role of molecular diagnostics in meningiomas. To follow the revision of WHO CNS5, this expert consensus statement was formed jointly by the Group of Neuro-Oncology, Society of Neurosurgery, Chinese Medical Association together with neuropathologists and evidence-based experts. The consensus provides reference points to integrate key biomarkers into stratification and clinical decision making for meningioma patients. REGISTRATION Practice guideline REgistration for transPAREncy (PREPARE), IPGRP-2022CN234.
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Affiliation(s)
- Jiaojiao Deng
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Lingyang Hua
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- Neurosurgical Institute of Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Liuguan Bian
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Hong Chen
- Department of Pathology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Ligang Chen
- Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China
| | - Hongwei Cheng
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Changwu Dou
- Department of Neurosurgery, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia 750306, China
| | - Dangmurenjiapu Geng
- Department of Neurosurgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang 830011, China
| | - Tao Hong
- Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, China
| | - Hongming Ji
- Department of Neurosurgery, Shanxi Medical University Shanxi Provincial People's Hospital, Taiyuan, Shanxi 030012, China
| | - Yugang Jiang
- Department of Neurosurgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
| | - Qing Lan
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Soochow, Jiangsu 215004, China
| | - Gang Li
- Department of Neurosurgery, Qilu Hospital, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250063, China
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Songtao Qi
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Yan Qu
- Department of Neurosurgery, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi 710038, China
| | - Songsheng Shi
- Department of Neurosurgery, Fujian Medical University Affiliated Union Hospital, Fuzhou, Fujian 350001, China
| | - Xiaochuan Sun
- Department of Neurosurgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400042, China
| | - Haijun Wang
- Department of Neurosurgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong 510080, China
| | - Yongping You
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Hualin Yu
- Department of Neurosurgery, Kunming Medical University First Affiliated Hospital, Kunming, Yunnan 650032, China
| | - Shuyuan Yue
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jianming Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310003, China
| | - Xiaohua Zhang
- Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Shuo Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Ping Zhong
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200040, China
- Neurosurgical Institute of Fudan University, Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai 200040, China
| | - Ye Gong
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai 200040, China
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Deng J, Sun S, Chen J, Wang D, Cheng H, Chen H, Xie Q, Hua L, Gong Y. TERT Alterations Predict Tumor Progression in De Novo High-Grade Meningiomas Following Adjuvant Radiotherapy. Front Oncol 2021; 11:747592. [PMID: 34778063 PMCID: PMC8586415 DOI: 10.3389/fonc.2021.747592] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 09/30/2021] [Indexed: 01/02/2023] Open
Abstract
Background Adjuvant radiotherapy (RT) is one of the most commonly used treatments for de novo high-grade meningiomas (HGMs) after surgery, but genetic determinants of clinical benefit are poorly characterized. Objective We describe efforts to integrate clinical genomics to discover predictive biomarkers that would inform adjuvant treatment decisions in de novo HGMs. Methods We undertook a retrospective analysis of 37 patients with de novo HGMs following RT. Clinical hybrid capture-based sequencing assay covering 184 genes was performed in all cases. Associations between tumor clinical/genomic characteristics and RT response were assessed. Overall survival (OS) and progression-free survival (PFS) curves were plotted using the Kaplan–Meier method. Results Among the 172 HGMs from a single institution, 42 cases (37 WHO grade 2 meningiomas and five WHO grade 3 meningiomas) were identified as de novo HGMs following RT. Only TERT mutations [62.5% C228T; 25% C250T; 12.5% copy number amplification (CN amp.)] were significantly associated with tumor progression after postoperative RT (adjusted p = 0.003). Potential different somatic interactions between TERT and other tested genes were not identified. Furthermore, TERT alterations (TERT-alt) were the predictor of tumor progression (Fisher’s exact tests, p = 0.003) and were associated with decreased PFS (log-rank test, p = 0.0114) in de novo HGMs after RT. Conclusion Our findings suggest that TERT-alt is associated with tumor progression and poor outcome of newly diagnosed HGM patients after postoperative RT.
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Affiliation(s)
- Jiaojiao Deng
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China
| | - Shuchen Sun
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China
| | - Jiawei Chen
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China
| | - Daijun Wang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China
| | - Haixia Cheng
- Department of Neuropathology, Huashan Hospital, Fudan University, Shanghai, China
| | - Hong Chen
- Department of Neuropathology, Huashan Hospital, Fudan University, Shanghai, China
| | - Qing Xie
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China
| | - Lingyang Hua
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China
| | - Ye Gong
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Neurosurgery, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Fudan University, Shanghai, China.,Department of Critical Care Medicine, Huashan Hospital, Fudan University, Shanghai, China
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