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Tsuchiya T, Kawauchi D, Ohno M, Miyakita Y, Takahashi M, Yanagisawa S, Osawa S, Fujita S, Omura T, Narita Y. Risk Factors of Distant Recurrence and Dissemination of IDH Wild-Type Glioblastoma: A Single-Center Study and Meta-Analysis. Cancers (Basel) 2024; 16:2873. [PMID: 39199644 PMCID: PMC11352485 DOI: 10.3390/cancers16162873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Revised: 08/16/2024] [Accepted: 08/17/2024] [Indexed: 09/01/2024] Open
Abstract
Isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) is a highly aggressive brain tumor with a high recurrence rate despite adjuvant treatment. This study aimed to evaluate the risk factors for non-local recurrence of GBM. In the present study, we analyzed 104 GBMs with a single lesion (non-multifocal or multicentric). Univariate analysis revealed that subventricular zone (SVZ) involvement was significantly associated with non-local recurrence (hazard ratio [HR]: 2.09 [1.08-4.05]). Tumors in contact with the trigone of the lateral ventricle tended to develop subependymal dissemination (p = 0.008). Ventricular opening via surgery did not increase the risk of non-local recurrence in patients with SVZ involvement (p = 0.190). A systematic review was performed to investigate the risk of non-local recurrence, and 21 studies were identified. A meta-analysis of previous studies confirmed SVZ involvement (odds ratio [OR]: 1.30 [1.01-1.67]) and O-6-methylguanine DNA methyltransferase promoter methylation (OR: 1.55 [1.09-2.20]) as significant risk factors for local recurrence. A time-dependent meta-analysis revealed a significant association between SVZ involvement and dissemination (HR: 1.69 [1.09-2.63]), while no significant association was found for distant recurrence (HR: 1.29 [0.74-2.27]). Understanding SVZ involvement and specific tumor locations associated with non-local recurrence provides critical insights for the management of GBM.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Yoshitaka Narita
- Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, Tokyo 104-0045, Japan; (T.T.); (D.K.); (M.O.); (Y.M.); (M.T.); (S.Y.); (S.O.); (S.F.); (T.O.)
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Xiao M, Cui X, Xu C, Xin L, Zhao J, Yang S, Hong B, Tan Y, Zhang J, Li X, Li J, Kang C, Fang C. Deep-targeted gene sequencing reveals ARID1A mutation as an important driver of glioblastoma. CNS Neurosci Ther 2024; 30:e14698. [PMID: 38600891 PMCID: PMC11007544 DOI: 10.1111/cns.14698] [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: 08/29/2023] [Revised: 03/04/2024] [Accepted: 03/11/2024] [Indexed: 04/12/2024] Open
Abstract
AIMS To investigate the key factors influencing glioma progression and the emergence of treatment resistance by examining the intrinsic connection between mutations in DNA damage and repair-related genes and the development of chemoresistance in gliomas. METHODS We conducted a comprehensive analysis of deep-targeted gene sequencing data from 228 glioma samples. This involved identifying differentially mutated genes across various glioma grades, assessing their functions, and employing I-TASSER for homology modeling. We elucidated the functional changes induced by high-frequency site mutations in these genes and investigated their impact on glioma progression. RESULTS The analysis of sequencing mutation results of deep targeted genes in integration revealed that ARID1A gene mutation occurs frequently in glioblastoma and alteration of ARID1A could affect the tolerance of glioma cells to temozolomide treatment. The deletion of proline at position 16 in the ARID1A protein affected the stability of binding of the SWI/SNF core subunit BRG1, which in turn affected the stability of the SWI/SNF complex and led to altered histone modifications in the CDKN1A promoter region, thereby affecting the biological activity of glioma cells, as inferred from modeling and protein interaction analysis. CONCLUSION The ARID1A gene is a critical predictive biomarker for glioma. Mutations at the ARID1A locus alter the stability of the SWI/SNF complex, leading to changes in transcriptional regulation in glioma cells. This contributes to an increased malignant phenotype of GBM and plays a pivotal role in mediating chemoresistance.
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Affiliation(s)
- Menglin Xiao
- Department of NeurosurgeryAffiliated Hospital of Hebei UniversityBaodingChina
- Hebei Key Laboratory of Precise Diagnosis and Treatment of GliomaBaodingChina
| | - Xiaoteng Cui
- Laboratory of Neuro‐oncologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Can Xu
- Department of NeurosurgeryAffiliated Hospital of Hebei UniversityBaodingChina
- Hebei Key Laboratory of Precise Diagnosis and Treatment of GliomaBaodingChina
| | - Lei Xin
- Department of NeurosurgeryAffiliated Hospital of Hebei UniversityBaodingChina
- Hebei Key Laboratory of Precise Diagnosis and Treatment of GliomaBaodingChina
| | - Jixing Zhao
- Laboratory of Neuro‐oncologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Shixue Yang
- Laboratory of Neuro‐oncologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Biao Hong
- Laboratory of Neuro‐oncologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Yanli Tan
- Department of PathologyAffiliated Hospital of Hebei UniversityBaodingChina
- Department of PathologyHebei University School of Basic Medical SciencesBaodingChina
| | - Jie Zhang
- Department of PathologyHebei University School of Basic Medical SciencesBaodingChina
| | - Xiang Li
- Department of PathologyHebei University School of Basic Medical SciencesBaodingChina
| | - Jie Li
- Department of ProteomicsTianjin Enterprise Key Laboratory of Clinical Multi‐omicsTianjinChina
| | - Chunsheng Kang
- Laboratory of Neuro‐oncologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Chuan Fang
- Department of NeurosurgeryAffiliated Hospital of Hebei UniversityBaodingChina
- Hebei Key Laboratory of Precise Diagnosis and Treatment of GliomaBaodingChina
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Ehret F, Zühlke O, Schweizer L, Kahn J, Csapo-Schmidt C, Roohani S, Zips D, Capper D, Adeberg S, Abdollahi A, Knoll M, Kaul D. Validation of a methylation-based signature for subventricular zone involvement in glioblastoma. J Neurooncol 2024; 167:89-97. [PMID: 38376766 PMCID: PMC10978677 DOI: 10.1007/s11060-024-04570-0] [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: 12/12/2023] [Accepted: 01/11/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE Glioblastomas (GBM) with subventricular zone (SVZ) contact have previously been associated with a specific epigenetic fingerprint. We aim to validate a reported bulk methylation signature to determine SVZ contact. METHODS Methylation array analysis was performed on IDHwt GBM patients treated at our institution. The v11b4 classifier was used to ensure the inclusion of only receptor tyrosine kinase (RTK) I, II, and mesenchymal (MES) subtypes. Methylation-based assignment (SVZM ±) was performed using hierarchical cluster analysis. Magnetic resonance imaging (MRI) (T1ce) was independently reviewed for SVZ contact by three experienced readers. RESULTS Sixty-five of 70 samples were classified as RTK I, II, and MES. Full T1ce MRI-based rater consensus was observed in 54 cases, which were retained for further analysis. Epigenetic SVZM classification and SVZ were strongly associated (OR: 15.0, p = 0.003). Thirteen of fourteen differential CpGs were located in the previously described differentially methylated LRBA/MAB21L2 locus. SVZ + tumors were linked to shorter OS (hazard ratio (HR): 3.80, p = 0.02) than SVZM + at earlier time points (time-dependency of SVZM, p < 0.05). Considering the SVZ consensus as the ground truth, SVZM classification yields a sensitivity of 96.6%, specificity of 36.0%, positive predictive value (PPV) of 63.6%, and negative predictive value (NPV) of 90.0%. CONCLUSION Herein, we validated the specific epigenetic signature in GBM in the vicinity of the SVZ and highlighted the importance of methylation of a part of the LRBA/MAB21L2 gene locus. Whether SVZM can replace MRI-based SVZ assignment as a prognostic and diagnostic tool will require prospective studies of large, homogeneous cohorts.
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Affiliation(s)
- Felix Ehret
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Oliver Zühlke
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Leonille Schweizer
- Institute of Neurology (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Johannes Kahn
- Department of Radiology, Health and Medical University, Potsdam, Germany
| | - Christoph Csapo-Schmidt
- Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Siyer Roohani
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Junior Clinician Scientist Program, Berlin, Germany
| | - Daniel Zips
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David Capper
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Sebastian Adeberg
- Department of Radiation Oncology, University Hospital Marburg/Gießen, Marburg, Germany
| | - Amir Abdollahi
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Knoll
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - David Kaul
- Department of Radiation Oncology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany.
- Charité - Universitätsmedizin Berlin, Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Zhang W, Yan Z, Peng J, Zhao S, Ran L, Yin H, Zhong D, Yang J, Ye J, Xu S. Magnetic resonance imaging and deoxyribonucleic acid methylation-based radiogenomic models for survival risk stratification of glioblastoma. Med Biol Eng Comput 2024; 62:853-864. [PMID: 38057447 DOI: 10.1007/s11517-023-02971-3] [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: 02/10/2023] [Accepted: 11/14/2023] [Indexed: 12/08/2023]
Abstract
Glioblastoma multiforme (GBM) is one of the deadliest tumours. This study aimed to construct radiogenomic prognostic models of glioblastoma overall survival (OS) based on magnetic resonance imaging (MRI) Gd-T1WI images and deoxyribonucleic acid (DNA) methylation-seq and to understand the related biological pathways. The ResNet3D-18 model was used to extract radiomic features, and Lasso-Cox regression analysis was utilized to establish the prognostic models. A nomogram was constructed by combining the radiogenomic features and clinicopathological variables. The DeLong test was performed to compare the area under the curve (AUC) of the models. We screened differentially expressed genes (DEGs) with original ribonucleic acid (RNA)-seq in risk stratification and used Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotations for functional enrichment analysis. For the 1-year OS models, the AUCs of the radiogenomic set, methylation set and deep learning set in the training cohort were 0.864, 0.804 and 0.787, and those in the validation cohort were 0.835, 0.768 and 0.651, respectively. The AUCs of the 0.5-, 1- and 2-year nomograms in the training cohort were 0.943, 0.861 and 0.871, and those in the validation cohort were 0.864, 0.885 and 0.805, respectively. A total of 245 DEGs were screened; functional enrichment analysis showed that these DEGs were associated with cell immunity. The survival risk-stratifying radiogenomic models for glioblastoma OS had high predictability and were associated with biological pathways related to cell immunity.
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Affiliation(s)
- Wentao Zhang
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zikang Yan
- Department of Bioinformatics, the Basic Medical School of Chongqing Medical University, Chongqing, 400016, China
| | - Jian Peng
- The Center for Clinical Molecular Medical Detection, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Shan Zhao
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Longke Ran
- Department of Bioinformatics, the Basic Medical School of Chongqing Medical University, Chongqing, 400016, China
| | - Haoyang Yin
- Department of Neurosurgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Dong Zhong
- Department of Neurosurgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Junjun Yang
- Key Laboratory of Optoelectronic Technologyand, Systems of the Ministry of Education, Chongqing University, Chongqing, 400044, China
| | - Junyong Ye
- Key Laboratory of Optoelectronic Technologyand, Systems of the Ministry of Education, Chongqing University, Chongqing, 400044, China.
| | - Shengsheng Xu
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Nuechterlein N, Shelbourn A, Cimino PJ. Whole gain of chromosome 19, not co-gain of chromosomes 19 and 20, characterizes a class of glioblastomas with more favorable outcomes. J Neuropathol Exp Neurol 2023; 83:53-57. [PMID: 37964704 PMCID: PMC10746695 DOI: 10.1093/jnen/nlad092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023] Open
Affiliation(s)
- Nicholas Nuechterlein
- Neuropathology Unit, Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Allison Shelbourn
- Neuropathology Unit, Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Patrick J Cimino
- Neuropathology Unit, Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
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Xu D, Cao M, Wang B, Bi X, Zhang H, Wu D, Zhang C, Xu J, Xu Z, Zheng D, Chen L, Li P, Wang H, Liu Y, Jiang H, Li K. Epigenetically regulated lncRNAs dissect the intratumoural heterogeneity and facilitate immune evasion of glioblastomas. Theranostics 2023; 13:1490-1505. [PMID: 37056564 PMCID: PMC10086206 DOI: 10.7150/thno.79874] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 02/25/2023] [Indexed: 03/14/2023] Open
Abstract
Background: Glioblastomas are the most common and malignant central nervous system (CNS) tumors that occupied a highly heterogeneous tumor microenvironment (TIME). Long noncoding RNAs (lncRNAs), whose expression can be modified by DNA methylation, are emerging as critical regulators in the immune system. However, knowledge about the epigenetic changes in lncRNAs and their contribution to the immune heterogeneity of glioma is still lacking. Methods: In this study, we integrated paired methylome and transcriptome datasets of glioblastomas and identified 2 robust immune subtypes based on lncRNA methylation features. The immune characteristics of glioma subtypes were compared. Furthermore, immune-related lncRNAs were identified and their relationships with immune evasion were evaluated. Results: Glioma immunophenotypes exhibited distinct immune-related characteristics as well as clinical and epigenetic features. 149 epigenetically regulated (ER) lncRNAs were recognized that possessed inverse variation in epigenetic and transcriptional levels between glioma subtypes. Immune-related lncRNAs were further identified through the investigation of their correlation with immune cell infiltrations and immune-related pathways. In particular, the 'Hot' glioma subtype with higher immunoactivity while a worse survival outcome was found to character immune evasion features. We finally prioritized candidate ER lncRNAs associated with immune evasion markers and response to glioma immunotherapy. Among them, CD109-AS1 and LINC02447 were validated as novel immunoevasive biomarkers for glioma through in vitro experiments. Conclusion: In summary, our study systematically reveals the crosstalk among DNA methylation, lncRNA, and immune regulation in glioblastomas, and will facilitate the development of epigenetic immunotherapy approaches.
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Affiliation(s)
- Dahua Xu
- Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, 570311, China
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Meng Cao
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Bo Wang
- Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, 570311, China
| | - Xiaoman Bi
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Haiying Zhang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Pharmaceutical, Hainan Medical University, Haikou, 571199, China
| | - Deng Wu
- School of Life Sciences, Faculty of Science, The Chinese University of Hong Kong, 999077, Hong Kong
| | - Chunrui Zhang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100020, China
| | - Jiankai Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Zhizhou Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Dehua Zheng
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Liyang Chen
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Peihu Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Hong Wang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
| | - Yan Liu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Pharmaceutical, Hainan Medical University, Haikou, 571199, China
| | - Hongyan Jiang
- Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, 570311, China
| | - Kongning Li
- Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, 570311, China
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, 571199, China
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