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Mishchenko TA, Turubanova VD, Gorshkova EN, Krysko O, Vedunova MV, Krysko DV. Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy. Front Immunol 2024; 14:1299064. [PMID: 38274827 PMCID: PMC10809268 DOI: 10.3389/fimmu.2023.1299064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/11/2023] [Indexed: 01/27/2024] Open
Abstract
Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.
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Affiliation(s)
- Tatiana A. Mishchenko
- Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Victoria D. Turubanova
- Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- Neuroscience Research Institute, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Ekaterina N. Gorshkova
- Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Olga Krysko
- Cell Death Investigation and Therapy Laboratory, Anatomy and Embryology Unit, Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Maria V. Vedunova
- Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- Faculty of Biology and Biotechnologies, National Research University Higher School of Economics, Moscow, Russia
| | - Dmitri V. Krysko
- Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- Cell Death Investigation and Therapy Laboratory, Anatomy and Embryology Unit, Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
- Department of Pathophysiology, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
- Cancer Research Institute Ghent, Ghent, Belgium
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152
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Weller M, Felsberg J, Hentschel B, Gramatzki D, Kubon N, Wolter M, Reusche M, Roth P, Krex D, Herrlinger U, Westphal M, Tonn JC, Regli L, Maurage CA, von Deimling A, Pietsch T, Le Rhun E, Reifenberger G. Improved prognostic stratification of patients with isocitrate dehydrogenase-mutant astrocytoma. Acta Neuropathol 2024; 147:11. [PMID: 38183430 PMCID: PMC10771615 DOI: 10.1007/s00401-023-02662-1] [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: 09/16/2023] [Revised: 11/19/2023] [Accepted: 11/20/2023] [Indexed: 01/08/2024]
Abstract
Prognostic factors and standards of care for astrocytoma, isocitrate dehydrogenase (IDH)-mutant, CNS WHO grade 4, remain poorly defined. Here we sought to explore disease characteristics, prognostic markers, and outcome in patients with this newly defined tumor type. We determined molecular biomarkers and assembled clinical and outcome data in patients with IDH-mutant astrocytomas confirmed by central pathology review. Patients were identified in the German Glioma Network cohort study; additional cohorts of patients with CNS WHO grade 4 tumors were identified retrospectively at two sites. In total, 258 patients with IDH-mutant astrocytomas (114 CNS WHO grade 2, 73 CNS WHO grade 3, 71 CNS WHO grade 4) were studied. The median age at diagnosis was similar for all grades. Karnofsky performance status at diagnosis inversely correlated with CNS WHO grade (p < 0.001). Despite more intensive treatment upfront with higher grade, CNS WHO grade was strongly prognostic: median overall survival was not reached for grade 2 (median follow-up 10.4 years), 8.1 years (95% CI 5.4-10.8) for grade 3, and 4.7 years (95% CI 3.4-6.0) for grade 4. Among patients with CNS WHO grade 4 astrocytoma, median overall survival was 5.5 years (95% CI 4.3-6.7) without (n = 58) versus 1.8 years (95% CI 0-4.1) with (n = 12) homozygous CDKN2A deletion. Lower levels of global DNA methylation as detected by LINE-1 methylation analysis were strongly associated with CNS WHO grade 4 (p < 0.001) and poor outcome. MGMT promoter methylation status was not prognostic for overall survival. Histomolecular stratification based on CNS WHO grade, LINE-1 methylation level, and CDKN2A status revealed four subgroups of patients with significantly different outcomes. In conclusion, CNS WHO grade, global DNA methylation status, and CDKN2A homozygous deletion are prognostic in patients with IDH-mutant astrocytoma. Combination of these parameters allows for improved prediction of outcome. These data aid in designing upcoming trials using IDH inhibitors.
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Affiliation(s)
- Michael Weller
- Department of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland.
- Department of Neurology, University of Zurich, Zurich, Switzerland.
| | - Jörg Felsberg
- Institute of Neuropathology, Heinrich Heine University, Medical Faculty, and University Hospital Düsseldorf, Düsseldorf, Germany
| | - Bettina Hentschel
- Institute for Medical Informatics, Statistics and Epidemiology, University Leipzig, Leipzig, Germany
| | - Dorothee Gramatzki
- Department of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Nadezhda Kubon
- Institute of Neuropathology, Heinrich Heine University, Medical Faculty, and University Hospital Düsseldorf, Düsseldorf, Germany
| | - Marietta Wolter
- Institute of Neuropathology, Heinrich Heine University, Medical Faculty, and University Hospital Düsseldorf, Düsseldorf, Germany
| | - Matthias Reusche
- Institute for Medical Informatics, Statistics and Epidemiology, University Leipzig, Leipzig, Germany
| | - Patrick Roth
- Department of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurology, University of Zurich, Zurich, Switzerland
| | - Dietmar Krex
- Faculty of Medicine, Department of Neurosurgery, Technische Universität Dresden, University Hospital Carl Gustav Carus, Dresden, Germany
| | | | - Manfred Westphal
- Department of Neurosurgery, University of Hamburg, Hamburg, Germany
| | - Joerg C Tonn
- Department of Neurosurgery, Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland
- Department of Neurosurgery, University of Zurich, Zurich, Switzerland
| | - Claude-Alain Maurage
- Department of Pathology, Centre Biologie Pathologie, Lille University Hospital, Hopital Nord, Lille, France
| | - Andreas von Deimling
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Neuropathology, German Cancer Center (DKFZ), and German Cancer Consortium (DKTK), Partner Site Heidelberg, Heidelberg, Germany
| | - Torsten Pietsch
- Department of Neuropathology, University of Bonn Medical Center, DGNN Brain Tumor Reference Center, Bonn, Germany
| | - Emilie Le Rhun
- Department of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurology, University of Zurich, Zurich, Switzerland
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland
- Department of Neurosurgery, University of Zurich, Zurich, Switzerland
- Department of Neurosurgery, Lille University Hospital, Lille, France
| | - Guido Reifenberger
- Institute of Neuropathology, Heinrich Heine University, Medical Faculty, and University Hospital Düsseldorf, Düsseldorf, Germany
- German Cancer Consortium (DKTK), Partner Site Essen/Düsseldorf, Düsseldorf, Germany
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153
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Hong B, Yang E, Su D, Ju J, Cui X, Wang Q, Tong F, Zhao J, Yang S, Cheng C, Xin L, Xiao M, Yi K, Zhan Q, Ding Y, Xu H, Cui L, Kang C. EPIC-1042 as a potent PTRF/Cavin1-caveolin-1 interaction inhibitor to induce PARP1 autophagic degradation and suppress temozolomide efflux for glioblastoma. Neuro Oncol 2024; 26:100-114. [PMID: 37651725 PMCID: PMC10768988 DOI: 10.1093/neuonc/noad159] [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: 04/24/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Temozolomide (TMZ) treatment efficacy in glioblastoma is determined by various mechanisms such as TMZ efflux, autophagy, base excision repair (BER) pathway, and the level of O6-methylguanine-DNA methyltransferase (MGMT). Here, we reported a novel small-molecular inhibitor (SMI) EPIC-1042 (C20H28N6) with the potential to decrease TMZ efflux and promote PARP1 degradation via autolysosomes in the early stage. METHODS EPIC-1042 was obtained from receptor-based virtual screening. Co-immunoprecipitation and pull-down assays were applied to verify the blocking effect of EPIC-1042. Western blotting, co-immunoprecipitation, and immunofluorescence were used to elucidate the underlying mechanisms of EPIC-1042. In vivo experiments were performed to verify the efficacy of EPIC-1042 in sensitizing glioblastoma cells to TMZ. RESULTS EPIC-1042 physically interrupted the interaction of PTRF/Cavin1 and caveolin-1, leading to reduced secretion of small extracellular vesicles (sEVs) to decrease TMZ efflux. It also induced PARP1 autophagic degradation via increased p62 expression that more p62 bound to PARP1 and specially promoted PARP1 translocation into autolysosomes for degradation in the early stage. Moreover, EPIC-1042 inhibited autophagy flux at last. The application of EPIC-1042 enhanced TMZ efficacy in glioblastoma in vivo. CONCLUSION EPIC-1042 reinforced the effect of TMZ by preventing TMZ efflux, inducing PARP1 degradation via autolysosomes to perturb the BER pathway and recruitment of MGMT, and inhibiting autophagy flux in the later stage. Therefore, this study provided a novel therapeutic strategy using the combination of TMZ with EPIC-1042 for glioblastoma treatment.
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Affiliation(s)
- Biao Hong
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Eryan Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Dongyuan Su
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Jiasheng Ju
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Xiaoteng Cui
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Qixue Wang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Fei Tong
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Jixing Zhao
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Shixue Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Chunchao Cheng
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Lei Xin
- Department of Neurosurgery, Affiliated Hospital of Hebei University, Baoding, China
| | - Menglin Xiao
- Department of Neurosurgery, Affiliated Hospital of Hebei University, Baoding, China
| | - Kaikai Yi
- Department of Neuro-Oncology and Neurosurgery, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin, China
| | - Qi Zhan
- Tianjin Key Laboratory of Composite and Functional Materials, School of Materials Science and Engineering, Tianjin University, Tianjin, China
| | - Yaqing Ding
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Hanyi Xu
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Longtao Cui
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
| | - Chunsheng Kang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin, China
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154
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Pinson H, Silversmit G, Vanhauwaert D, Vanschoenbeek K, Okito JPK, De Vleeschouwer S, Boterberg T, De Gendt C. Epidemiology and survival of adult-type diffuse glioma in Belgium during the molecular era. Neuro Oncol 2024; 26:191-202. [PMID: 37651614 PMCID: PMC10768998 DOI: 10.1093/neuonc/noad158] [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: 04/08/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Survival data of diffuse adult-type glioma is mostly based on prospective clinical trials or small retrospective cohort studies. Real-world data with large patient cohorts is currently lacking. METHODS Using the nationwide, population-based Belgian Cancer Registry, all known histological reports of patients diagnosed with an adult-type diffuse glioma in Belgium between 2017 and 2019 were reviewed. The ICD-O-3 morphology codes were matched with the histological diagnosis. The gathered data were transformed into the 2021 World Health Organization classification of CNS tumors using the IDH- and 1p/19q-mutation status. RESULTS Between 2017 and 2019, 2233 diffuse adult-type gliomas were diagnosed in Belgium. Full molecular status was available in 67.1% of identified cases. The age-standardized incidence rate of diffuse adult-type glioma in Belgium was estimated at 8.55 per 100 000 person-years and 6.72 per 100 000 person-years for grade 4 lesions. Median overall survival time in IDH-wild-type glioblastoma was 9.3 months, significantly shorter compared to grade 4 IDH-mutant astrocytoma (median survival time: 25.9 months). The 3-year survival probability was 86.0% and 75.7% for grades 2 and 3 IDH-mutated astrocytoma. IDH-wild-type astrocytoma has a worse prognosis with a 3-year survival probability of 31.6% for grade 2 and 5.7% for grade 3 lesions. CONCLUSIONS This registry-based study presents a large cohort of adult-type diffuse glioma with known molecular status and uses real-world survival data. It adds to the current literature which is mainly based on historical landmark trials and smaller retrospective cohort studies.
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Affiliation(s)
- Harry Pinson
- Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium
| | | | | | | | | | - Steven De Vleeschouwer
- Department of Neurosurgery, UZ Leuven, Leuven, Belgium
- Laboratory for experimental neurosurgery and neuroanatomy, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven, Leuven, Belgium
| | - Tom Boterberg
- Department of Radiation Oncology, Ghent University Hospital, Ghent, Belgium
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155
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Karschnia P, Dietrich J, Bruno F, Dono A, Juenger ST, Teske N, Young JS, Sciortino T, Häni L, van den Bent M, Weller M, Vogelbaum MA, Morshed RA, Haddad AF, Molinaro AM, Tandon N, Beck J, Schnell O, Bello L, Hervey-Jumper S, Thon N, Grau SJ, Esquenazi Y, Rudà R, Chang SM, Berger MS, Cahill DP, Tonn JC. Surgical management and outcome of newly diagnosed glioblastoma without contrast enhancement (low-grade appearance): a report of the RANO resect group. Neuro Oncol 2024; 26:166-177. [PMID: 37665776 PMCID: PMC10768992 DOI: 10.1093/neuonc/noad160] [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: 07/19/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Resection of the contrast-enhancing (CE) tumor represents the standard of care in newly diagnosed glioblastoma. However, some tumors ultimately diagnosed as glioblastoma lack contrast enhancement and have a 'low-grade appearance' on imaging (non-CE glioblastoma). We aimed to (a) volumetrically define the value of non-CE tumor resection in the absence of contrast enhancement, and to (b) delineate outcome differences between glioblastoma patients with and without contrast enhancement. METHODS The RANO resect group retrospectively compiled a global, eight-center cohort of patients with newly diagnosed glioblastoma per WHO 2021 classification. The associations between postoperative tumor volumes and outcome were analyzed. Propensity score-matched analyses were constructed to compare glioblastomas with and without contrast enhancement. RESULTS Among 1323 newly diagnosed IDH-wildtype glioblastomas, we identified 98 patients (7.4%) without contrast enhancement. In such patients, smaller postoperative tumor volumes were associated with more favorable outcome. There was an exponential increase in risk for death with larger residual non-CE tumor. Accordingly, extensive resection was associated with improved survival compared to lesion biopsy. These findings were retained on a multivariable analysis adjusting for demographic and clinical markers. Compared to CE glioblastoma, patients with non-CE glioblastoma had a more favorable clinical profile and superior outcome as confirmed in propensity score analyses by matching the patients with non-CE glioblastoma to patients with CE glioblastoma using a large set of clinical variables. CONCLUSIONS The absence of contrast enhancement characterizes a less aggressive clinical phenotype of IDH-wildtype glioblastomas. Maximal resection of non-CE tumors has prognostic implications and translates into favorable outcome.
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Affiliation(s)
- Philipp Karschnia
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Jorg Dietrich
- Department of Neurology, Division of Neuro-Oncology, Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Francesco Bruno
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin, Italy
| | - Antonio Dono
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, USA
| | | | - Nico Teske
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Jacob S Young
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Tommaso Sciortino
- Division of Neuro-Oncology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Levin Häni
- Department of Neurosurgery, Medical Center – University of Freiburg, Freiburg, Germany
| | - Martin van den Bent
- Department of Neurology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | | | - Ramin A Morshed
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Alexander F Haddad
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Annette M Molinaro
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Nitin Tandon
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, USA
| | - Juergen Beck
- Department of Neurosurgery, Medical Center – University of Freiburg, Freiburg, Germany
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center – University of Freiburg, Freiburg, Germany
| | - Lorenzo Bello
- Division of Neuro-Oncology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Shawn Hervey-Jumper
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Niklas Thon
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
| | - Stefan J Grau
- Department of Neurosurgery, University of Cologne, Cologne, Germany
| | - Yoshua Esquenazi
- Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX, USA
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin, Italy
| | - Susan M Chang
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Mitchel S Berger
- Department of Neurosurgery and Division of Neuro-Oncology, University of San Francisco, San Francisco, CA, USA
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Joerg-Christian Tonn
- Department of Neurosurgery, LMU University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Germany
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156
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Hayashi T, Tateishi K, Matsuyama S, Iwashita H, Miyake Y, Oshima A, Honma H, Sasame J, Takabayashi K, Sugino K, Hirata E, Udaka N, Matsushita Y, Kato I, Hayashi H, Nakamura T, Ikegaya N, Takayama Y, Sonoda M, Oka C, Sato M, Isoda M, Kato M, Uchiyama K, Tanaka T, Muramatsu T, Miyake S, Suzuki R, Takadera M, Tatezuki J, Ayabe J, Suenaga J, Matsunaga S, Miyahara K, Manaka H, Murata H, Yokoyama T, Tanaka Y, Shuto T, Ichimura K, Kato S, Yamanaka S, Cahill DP, Fujii S, Shankar GM, Yamamoto T. Intraoperative Integrated Diagnostic System for Malignant Central Nervous System Tumors. Clin Cancer Res 2024; 30:116-126. [PMID: 37851071 DOI: 10.1158/1078-0432.ccr-23-1660] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/19/2023] [Accepted: 10/16/2023] [Indexed: 10/19/2023]
Abstract
PURPOSE The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors uses an integrated approach involving histopathology and molecular profiling. Because majority of adult malignant brain tumors are gliomas and primary CNS lymphomas (PCNSL), rapid differentiation of these diseases is required for therapeutic decisions. In addition, diffuse gliomas require molecular information on single-nucleotide variants (SNV), such as IDH1/2. Here, we report an intraoperative integrated diagnostic (i-ID) system to classify CNS malignant tumors, which updates legacy frozen-section (FS) diagnosis through incorporation of a qPCR-based genotyping assay. EXPERIMENTAL DESIGN FS evaluation, including GFAP and CD20 rapid IHC, was performed on adult malignant CNS tumors. PCNSL was diagnosed through positive CD20 and negative GFAP immunostaining. For suspected glioma, genotyping for IDH1/2, TERT SNV, and CDKN2A copy-number alteration was routinely performed, whereas H3F3A and BRAF SNV were assessed for selected cases. i-ID was determined on the basis of the 2021 WHO classification and compared with the permanent integrated diagnosis (p-ID) to assess its reliability. RESULTS After retrospectively analyzing 153 cases, 101 cases were prospectively examined using the i-ID system. Assessment of IDH1/2, TERT, H3F3AK27M, BRAFV600E, and CDKN2A alterations with i-ID and permanent genomic analysis was concordant in 100%, 100%, 100%, 100%, and 96.4%, respectively. Combination with FS and intraoperative genotyping assay improved diagnostic accuracy in gliomas. Overall, i-ID matched with p-ID in 80/82 (97.6%) patients with glioma and 18/19 (94.7%) with PCNSL. CONCLUSIONS The i-ID system provides reliable integrated diagnosis of adult malignant CNS tumors.
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Affiliation(s)
- Takahiro Hayashi
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Kensuke Tateishi
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
- Laboratory of Biopharmaceutical and Regenerative Science, Graduate School of Medical Science, Yokohama City University, Yokohama, Japan
| | - Shinichiro Matsuyama
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Hiromichi Iwashita
- Department of Pathology, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Yohei Miyake
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Akito Oshima
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Hirokuni Honma
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Jo Sasame
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Katsuhiro Takabayashi
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Kyoka Sugino
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
- Laboratory of Biopharmaceutical and Regenerative Science, Graduate School of Medical Science, Yokohama City University, Yokohama, Japan
| | - Emi Hirata
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Naoko Udaka
- Department of Diagnostic Pathology, Yokohama City University Hospital, Yokohama, Japan
| | - Yuko Matsushita
- Department of Brain Disease Translational Research, Juntendo University Faculty of Medicine, Tokyo, Japan
| | - Ikuma Kato
- Department of Molecular Pathology, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Hiroaki Hayashi
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
- Department of Pediatrics, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Taishi Nakamura
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
- Department of Neurosurgery, Yokohama City University Medical Center, Yokohama, Japan
| | - Naoki Ikegaya
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Yutaro Takayama
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Masaki Sonoda
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Chihiro Oka
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Mitsuru Sato
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Masataka Isoda
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Miyui Kato
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
- Laboratory of Biopharmaceutical and Regenerative Science, Graduate School of Medical Science, Yokohama City University, Yokohama, Japan
| | - Kaho Uchiyama
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
- Laboratory of Biopharmaceutical and Regenerative Science, Graduate School of Medical Science, Yokohama City University, Yokohama, Japan
| | - Tamon Tanaka
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Toshiki Muramatsu
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Neurosurgical-Oncology Laboratory, Yokohama City University, Yokohama, Japan
| | - Shigeta Miyake
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Ryosuke Suzuki
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
- Department of Neurosurgery, Odawara Municipal Hospital, Odawara, Japan
| | - Mutsumi Takadera
- Department of Neurosurgery, Yokohama City Minato Red Cross Hospital, Yokohama, Japan
- Department of Neurosurgery, Yokosuka Kyosai Hospital, Yokosuka, Japan
| | - Junya Tatezuki
- Department of Neurosurgery, Yokohama City Minato Red Cross Hospital, Yokohama, Japan
| | - Junichi Ayabe
- Department of Neurosurgery, Yokosuka Kyosai Hospital, Yokosuka, Japan
| | - Jun Suenaga
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Shigeo Matsunaga
- Department of Neurosurgery, Yokohama Rosai Hospital, Yokohama, Japan
| | - Kosuke Miyahara
- Department of Neurosurgery, National Hospital Organization Yokohama Medical Center, Yokohama, Japan
| | - Hiroshi Manaka
- Department of Neurosurgery, Yokohama Minami Kyosai Hospital, Yokohama, Japan
| | - Hidetoshi Murata
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | | | - Yoshihide Tanaka
- Department of Neurosurgery, Yokosuka Kyosai Hospital, Yokosuka, Japan
| | - Takashi Shuto
- Department of Neurosurgery, Yokohama Rosai Hospital, Yokohama, Japan
| | - Koichi Ichimura
- Department of Brain Disease Translational Research, Juntendo University Faculty of Medicine, Tokyo, Japan
| | - Shingo Kato
- Department of Clinical Cancer Genomics, Yokohama City University, Yokohama, Japan
| | - Shoji Yamanaka
- Department of Diagnostic Pathology, Yokohama City University Hospital, Yokohama, Japan
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Satoshi Fujii
- Department of Diagnostic Pathology, Yokohama City University Hospital, Yokohama, Japan
- Department of Molecular Pathology, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
| | - Ganesh M Shankar
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Tetsuya Yamamoto
- Department of Neurosurgery, Yokohama City University, Graduate School of Medicine, Yokohama, Japan
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Liu Z, Xu X, Zhang W, Zhang L, Wen M, Gao J, Yang J, Kan Y, Yang X, Wen Z, Chen S, Cao X. A fusion model integrating magnetic resonance imaging radiomics and deep learning features for predicting alpha-thalassemia X-linked intellectual disability mutation status in isocitrate dehydrogenase-mutant high-grade astrocytoma: a multicenter study. Quant Imaging Med Surg 2024; 14:251-263. [PMID: 38223098 PMCID: PMC10784047 DOI: 10.21037/qims-23-807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/24/2023] [Indexed: 01/16/2024]
Abstract
Background The mutational status of alpha-thalassemia X-linked intellectual disability (ATRX) is an important indicator for the treatment and prognosis of high-grade gliomas, but reliable ATRX testing currently requires invasive procedures. The objective of this study was to develop a clinical trait-imaging fusion model that combines preoperative magnetic resonance imaging (MRI) radiomics and deep learning (DL) features with clinical variables to predict ATRX status in isocitrate dehydrogenase (IDH)-mutant high-grade astrocytoma. Methods A total of 234 patients with IDH-mutant high-grade astrocytoma (120 ATRX mutant type, 114 ATRX wild type) from 3 centers were retrospectively analyzed. Radiomics and DL features from different regions (edema, tumor, and the overall lesion) were extracted to construct multiple imaging models by combining different features in different regions for predicting ATRX status. An optimal imaging model was then selected, and its features and linear coefficients were used to calculate an imaging score. Finally, a fusion model was developed by combining the imaging score and clinical variables. The performance and application value of the fusion model were evaluated through the comparison of receiver operating characteristic curves, the construction of a nomogram, calibration curves, decision curves, and clinical application curves. Results The overall hybrid model constructed with radiomics and DL features from the overall lesion was identified as the optimal imaging model. The fusion model showed the best prediction performance with an area under curve of 0.969 in the training set, 0.956 in the validation set, and 0.949 in the test set as compared to the optimal imaging model (0.966, 0.916, and 0.936, respectively) and clinical model (0.677, 0.641, 0.772, respectively). Conclusions The clinical trait-imaging fusion model based on preoperative MRI could effectively predict the ATRX mutation status of individuals with IDH-mutant high-grade astrocytoma and has the potential to help patients through the development of a more effective treatment strategy before treatment.
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Affiliation(s)
- Zhi Liu
- Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Xinyi Xu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wang Zhang
- College of Computer & Information Science, Southwest University, Chongqing, China
| | - Liqiang Zhang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ming Wen
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jueni Gao
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jun Yang
- Department of Endocrinology, University-Town Hospital of Chongqing Medical University, Chongqing, China
| | - Yubo Kan
- School of Medical and Life Sciences Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xing Yang
- Department of Radiology, Chongqing United Medical Imaging Center, Chongqing, China
| | - Zhipeng Wen
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Shanxiong Chen
- College of Computer & Information Science, Southwest University, Chongqing, China
| | - Xu Cao
- School of Medical and Life Sciences Chengdu University of Traditional Chinese Medicine, Chengdu, China
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158
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Kling T, Ferreyra Vega S, Suman M, Dénes A, Lipatnikova A, Lagerström S, Olsson Bontell T, Jakola AS, Carén H. Refinement of prognostication for IDH-mutant astrocytomas using DNA methylation-based classification. Brain Pathol 2024:e13233. [PMID: 38168467 DOI: 10.1111/bpa.13233] [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: 08/05/2023] [Accepted: 12/18/2023] [Indexed: 01/05/2024] Open
Abstract
The 2021 World Health Organization (WHO) grading system of isocitrate dehydrogenase (IDH)-mutant astrocytomas relies on histological features and the presence of homozygous deletion of the cyclin-dependent kinase inhibitor 2A and 2B (CDKN2A/B). DNA methylation profiling has become highly relevant in the diagnosis of central nervous system (CNS) tumors including gliomas, and it has been incorporated into routine clinical diagnostics in some countries. In this study, we, therefore, examined the value of DNA methylation-based classification for prognostication of patients with IDH-mutant astrocytomas. We analyzed histopathological diagnoses, genome-wide DNA methylation array data, and chromosomal copy number alteration profiles from a cohort of 385 adult-type IDH-mutant astrocytomas, including a local cohort of 127 cases and 258 cases from public repositories. Prognosis based on WHO 2021 CNS criteria (histological grade and CDKN2A/B homozygous deletion status), other relevant chromosomal/gene alterations in IDH-mutant astrocytomas and DNA methylation-based subclassification according to the molecular neuropathology classifier were assessed. We demonstrate that DNA methylation-based classification of IDH-mutant astrocytomas can be used to predict outcome of the patients equally well as WHO 2021 CNS criteria. In addition, methylation-based subclassification enabled the identification of IDH-mutant astrocytoma patients with poor survival among patients with grade 3 tumors and patients with grade 4 tumors with a more favorable outcome. In conclusion, DNA methylation-based subclassification adds prognostic information for IDH-mutant astrocytomas that can further refine the current WHO 2021 grading scheme for these patients.
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Affiliation(s)
- Teresia Kling
- Sahlgrenska Center for Cancer Research, Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sandra Ferreyra Vega
- Sahlgrenska Center for Cancer Research, Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Medha Suman
- Sahlgrenska Center for Cancer Research, Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Dénes
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Lipatnikova
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Stina Lagerström
- Sahlgrenska Center for Cancer Research, Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Thomas Olsson Bontell
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Pathology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Asgeir Store Jakola
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Helena Carén
- Sahlgrenska Center for Cancer Research, Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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159
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Que T, Yuan X, Tan JE, Zheng H, Yi G, Li Z, Wang X, Liu J, Xu H, Wang Y, Zhang XA, Huang G, Qi S. Applying the en-bloc technique in corpus callosum glioblastoma surgery contributes to maximal resection and better prognosis: a retrospective study. BMC Surg 2024; 24:4. [PMID: 38166900 PMCID: PMC10763443 DOI: 10.1186/s12893-023-02264-4] [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: 01/14/2023] [Accepted: 11/10/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Corpus callosum glioblastoma (ccGBM) is a specific type of GBM and has worse outcomes than other non-ccGBMs. We sought to identify whether en-bloc resection of ccGBMs based on T2-FLAIR imaging contributes to clinical outcomes and can achieve a satisfactory balance between maximal resection and preservation of neurological function. METHODS A total of 106 adult ccGBM patients (including astrocytoma, WHO grade 4, IDH mutation, and glioblastoma) were obtained from the Department of Neurosurgery in Nanfang Hospital between January 2008 and December 2018. The clinical data, including gender, age, symptoms, location of tumor, involvement of eloquent areas, extent of resection (EOR), pre- and postoperative Karnofsky Performance Status (KPS) scales, and National Institute of Health stroke scale (NIHSS) scores were collected. Propensity score matching (PSM) analysis was applied to control the confounders for analyzing the relationship between the en-bloc technique and EOR, and the change in the postoperative KPS scales and NIHSS scores. RESULTS Applying the en-bloc technique did not negatively affect the postoperative KPS scales compared to no-en-bloc resection (P = 0.851 for PSM analysis) but had a positive effect on preserving or improving the postoperative NIHSS scores (P = 0.004 for PSM analysis). A positive correlation between EOR and the en-bloc technique was identified (r = 0.483, P < 0.001; r = 0.720, P < 0.001 for PSM analysis), indicating that applying the en-bloc technique could contribute to enlarged maximal resection. Further survival analysis confirmed that applying the en-bloc technique and achieving supramaximal resection could significantly prolong OS and PFS, and multivariate analysis suggested that tumor location, pathology, EOR and the en-bloc technique could be regarded as independent prognostic indicators for OS in patients with ccGBMs, and pathology, EOR and the en-bloc technique were independently correlated with patient's PFS. Interestingly, the en-bloc technique also provided a marked reduction in the risk of tumor recurrence compared with the no-en-bloc technique in tumors undergoing TR, indicating that the essential role of the en-bloc technique in ccGBM surgery (HR: 0.712; 95% CI: 0.535-0.947; P = 0.02). CONCLUSIONS The en-bloc technique could contribute to achieving an enlarged maximal resection and could significantly prolong overall survival and progression-free survival in patients with ccGBMs.
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Affiliation(s)
- Tianshi Que
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Xi Yuan
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Jian-Er Tan
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Haojie Zheng
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Guozhong Yi
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Zhiyong Li
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Xiaoyan Wang
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Junlu Liu
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Haiyan Xu
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Yajuan Wang
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Xi-An Zhang
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
| | - Guanglong Huang
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
| | - Songtao Qi
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
- The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
- Nanfang Glioma Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, People's Republic of China.
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160
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Chen L, Zhang J, Chi C, Che W, Dong G, Wang J, Du Y, Wang R, Zhu Z, Tian J, Ji N, Chen X, Li D. Lower-grade gliomas surgery guided by GRPR-targeting PET/NIR dual-modality image probe: a prospective and single-arm clinical trial. Theranostics 2024; 14:819-829. [PMID: 38169486 PMCID: PMC10758047 DOI: 10.7150/thno.91554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 12/08/2023] [Indexed: 01/05/2024] Open
Abstract
Purpose: Lower-grade gliomas (LGGs) are a group of infiltrative growing glial brain tumors characterized by intricate intratumoral heterogeneity and subtle visual appearance differences from non-tumor tissue, which can lead to errors in pathologic tissue sampling. Although 5-ALA fluorescence has been an essential method for visualizing gliomas during surgery, its effectiveness is limited in the case of LGGs due to low sensitivity. Therefore, we developed a novel PET/NIR dual-modality image probe targeting gastrin-releasing peptide receptor (GRPR) in glioma cells to enhance tumor visualization and improve the accuracy of sampling. Methods: A prospective, non-randomized, single-center feasibility clinical trial (NCT03407781) was conducted in the referral center from October 21, 2016, to August 17, 2018. Consecutive enrollment included patients suspected of having LGGs and considered suitable candidates for surgical removal. Group 1 comprised ten patients who underwent preoperative 68Ga-IRDye800CW-BBN PET/MRI assessment followed by intraoperative fluorescence-guided surgery. Group 2 included 42 patients who underwent IRDye800CW-BBN fluorescence-guided surgery. The primary endpoints were the predictive value of preoperative PET imaging for intraoperative fluorescence and the sensitivity and specificity of fluorescence-guided sampling. Results: Thirty-nine patients were included in the in-depth analysis of endpoints, with 25 (64.1%) exhibiting visible fluorescence, while 14 (35.9%) did not. The preoperative positive PET uptake exhibited a greater accuracy in predicting intraoperative fluorescence compared to MRI enhancement (100% [10/10] vs. 87.2% [34/39]). A total of 125 samples were harvested during surgery. Compared with pathology, subjective fluorescence intensity showed a sensitivity of 88.6% and a specificity of 88.2% in identifying WHO grade III samples. For WHO grade II samples, the sensitivity and specificity of fluorescence were 54.7% and 88.2%, respectively. Conclusion: This study has demonstrated the feasibility of the novel dual-modality imaging technique for integrated pre- and intraoperative targeted imaging via the same molecular receptor in surgeries for LGGs. The PET/NIR dual-modality probe exhibits promise for preoperative surgical planning in fluorescence-guided surgery and provides greater accuracy in guiding tumor sampling compared to 5-ALA in patients with LGGs.
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Affiliation(s)
- Liangpeng Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jingjing Zhang
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and Faculty of Engineering, National University of Singapore, Singapore
- Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Chongwei Chi
- Key Laboratory of Molecular Imaging, Chinese Academy of Science, Beijing, China
| | - Wenqiang Che
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Gehong Dong
- Department of Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Junmei Wang
- Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yanru Du
- Department of Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Rongxi Wang
- Department of Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China
| | - Zhaohui Zhu
- Department of Nuclear Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Chinese Academy of Science, Beijing, China
| | - Nan Ji
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Xiaoyuan Chen
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and Faculty of Engineering, National University of Singapore, Singapore
- Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Deling Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
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161
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Tan H, Nugent JG, Fecker A, Richie EA, Maanum KA, Nerison C, Bowden SG, Yaylali I, Han SJ, Colgan DD, Oken B, Raslan AM. Rapid Passive Gamma Mapping as an Adjunct to Electrical Stimulation Mapping for Functional Localization in Resection of Primary Brain Neoplasms. World Neurosurg 2024; 181:e483-e492. [PMID: 37871691 DOI: 10.1016/j.wneu.2023.10.085] [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: 07/05/2023] [Revised: 10/17/2023] [Accepted: 10/18/2023] [Indexed: 10/25/2023]
Abstract
OBJECTIVE We examined the utility of passive high gamma mapping (HGM) as an adjunct to conventional awake brain mapping during glioma resection. We compared functional and survival outcomes before and after implementing intraoperative HGM. METHODS This was a retrospective cohort study of 75 patients who underwent a first-time, awake craniotomy for glioma resection. Patients were stratified by whether their operation occurred before or after the implementation of a U.S. Food and Drug Administration-approved high-gamma mapping tool in July 2017. RESULTS The preimplementation and postimplementation cohorts included 28 and 47 patients, respectively. Median intraoperative time (261 vs. 261 minutes, P = 0.250) and extent of resection (97.14% vs. 98.19%, P = 0.481) were comparable between cohorts. Median Karnofsky performance status at initial follow-up was similar between cohorts (P = 0.650). Multivariable Cox regression models demonstrated an adjusted hazard ratio for overall survival of 0.10 (95% confidence interval: 0.02-0.43, P = 0.002) for the postimplementation cohort relative to the preimplementation cohort. Progression-free survival adjusted for insular involvement showed an adjusted hazard ratio of 1.00 (95% confidence interval: 0.49-2.06, P = 0.999) following HGM implementation. Falling short of statistical significance, prevalence of intraoperative seizures and/or afterdischarges decreased after HGM implementation as well (12.7% vs. 25%, P = 0.150). CONCLUSIONS Our results tentatively indicate that passive HGM is a safe and potentially useful adjunct to electrical stimulation mapping for awake cortical mapping, conferring at least comparable functional and survival outcomes with a nonsignificant lower rate of intraoperative epileptiform events. Considering the limitations of our study design and patient cohort, further investigation is needed to better identify optimal use cases for HGM.
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Affiliation(s)
- Hao Tan
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Joseph G Nugent
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Adeline Fecker
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Emma A Richie
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Kayla A Maanum
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Caleb Nerison
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Stephen G Bowden
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA
| | - Ilker Yaylali
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Seunggu J Han
- Department of Neurosurgery, Stanford Medicine, Palo Alto, California, USA
| | - Dana D Colgan
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Barry Oken
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Ahmed M Raslan
- Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA.
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Albert NL, Galldiks N, Ellingson BM, van den Bent MJ, Chang SM, Cicone F, de Groot J, Koh ES, Law I, Le Rhun E, Mair MJ, Minniti G, Rudà R, Scott AM, Short SC, Smits M, Suchorska B, Tolboom N, Traub-Weidinger T, Tonn JC, Verger A, Weller M, Wen PY, Preusser M. PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group. Lancet Oncol 2024; 25:e29-e41. [PMID: 38181810 DOI: 10.1016/s1470-2045(23)00525-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 01/07/2024]
Abstract
Response Assessment in Neuro-Oncology (RANO) response criteria have been established and were updated in 2023 for MRI-based response evaluation of diffuse gliomas in clinical trials. In addition, PET-based imaging with amino acid tracers is increasingly considered for disease monitoring in both clinical practice and clinical trials. So far, a standardised framework defining timepoints for baseline and follow-up investigations and response evaluation criteria for PET imaging of diffuse gliomas has not been established. Therefore, in this Policy Review, we propose a set of criteria for response assessment based on amino acid PET imaging in clinical trials enrolling participants with diffuse gliomas as defined in the 2021 WHO classification of tumours of the central nervous system. These proposed PET RANO criteria provide a conceptual framework that facilitates the structured implementation of PET imaging into clinical research and, ultimately, clinical routine. To this end, the PET RANO 1.0 criteria are intended to encourage specific investigations of amino acid PET imaging of gliomas.
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Affiliation(s)
- Nathalie L Albert
- Department of Nuclear Medicine, LMU Hospital, LMU Munich, Munich, Germany
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Institute of Neuroscience and Medicine (INM-3), Research Center Juelich, Juelich, Germany; Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Francesco Cicone
- Nuclear Medicine Unit, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - John de Groot
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Eng-Siew Koh
- Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centre, Liverpool, NSW, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Ian Law
- Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, Copenhagen, Denmark
| | - Emilie Le Rhun
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland; Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Maximilian J Mair
- Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
| | - Giuseppe Minniti
- Department of Radiological Sciences, Oncology and Anatomical Pathology, Sapienza University of Rome, Policlinico Umberto I, Rome, Italy; IRCCS Neuromed, Pozzilli IS, Italy
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin and City of Health and Science of Turin, Turin, Italy
| | - Andrew M Scott
- Department of Molecular Imaging and Therapy, Austin Health and University of Melbourne, Melbourne, VIC, Australia; Olivia Newton-John Cancer Research Institute and School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Susan C Short
- Leeds Institute of Medical Research at St James's, The University of Leeds, Leeds, UK
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, Netherlands; Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, Netherlands; Medical Delta, Delft, Netherlands
| | - Bogdana Suchorska
- Department of Neurosurgery, Heidelberg University Hospital, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, Netherlands
| | - Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | | | - Antoine Verger
- Department of Nuclear Medicine & Nancyclotep Imaging Platform, CHRU Nancy and IADI INSERM UMR 1254, Universitè de Lorraine, Nancy, France
| | - Michael Weller
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland; Department of Neurology, University of Zurich, Zurich, Switzerland
| | - Patrick Y Wen
- Center For Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Matthias Preusser
- Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria.
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163
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Christ SM, Youssef G, Tanguturi SK, Cagney D, Shi D, McFaline-Figueroa JR, Chukwueke U, Lee EQ, Hertler C, Andratschke N, Weller M, Reardon DA, Haas-Kogan D, Guckenberger M, Wen PY, Rahman R. Re-irradiation of recurrent IDH-wildtype glioblastoma in the bevacizumab and immunotherapy era: Target delineation, outcomes and patterns of recurrence. Clin Transl Radiat Oncol 2024; 44:100697. [PMID: 38046107 PMCID: PMC10689476 DOI: 10.1016/j.ctro.2023.100697] [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: 06/28/2023] [Revised: 10/12/2023] [Accepted: 10/28/2023] [Indexed: 12/05/2023] Open
Abstract
Introduction and background While recurrent glioblastoma patients are often treated with re-irradiation, there is limited data on the use of re-irradiation in the setting of bevacizumab (BEV), temozolomide (TMZ) re-challenge, or immune checkpoint inhibition (ICI). We describe target delineation in patients with prior anti-angiogenic therapy, assess safety and efficacy of re-irradiation, and evaluate patterns of recurrence. Materials and methods Patients with a histologically confirmed diagnosis of glioblastoma treated at a single institution between 2013 and 2021 with re-irradiation were included. Tumor, treatment and clinical data were collected. Logistic and Cox regression analysis were used for statistical analysis. Results One hundred and seventeen recurrent glioblastoma patients were identified, receiving 129 courses of re-irradiation. In 66 % (85/129) of cases, patients had prior BEV. In the 80 patients (62 %) with available re-irradiation plans, 20 (25 %) had all T2/FLAIR abnormality included in the gross tumor volume (GTV). Median overall survival (OS) for the cohort was 7.3 months, and median progression-free survival (PFS) was 3.6 months. Acute CTCAE grade ≥ 3 toxicity occurred in 8 % of cases. Concurrent use of TMZ or ICI was not associated with improved OS nor PFS. On multivariable analysis, higher KPS was significantly associated with longer OS (p < 0.01). On subgroup analysis, patients with prior BEV had significantly more marginal recurrences than those without (26 % vs. 13 %, p < 0.01). Conclusion Re-irradiation can be safely employed in recurrent glioblastoma patients. Marginal recurrence was more frequent in patients with prior BEV, suggesting a need to consider more inclusive treatment volumes incorporating T2/FLAIR abnormality.
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Affiliation(s)
- Sebastian M. Christ
- Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, USA
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Gilbert Youssef
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Shyam K. Tanguturi
- Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Daniel Cagney
- Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Diana Shi
- Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, USA
| | | | - Ugonma Chukwueke
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Eudocia Q. Lee
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Caroline Hertler
- Competence Center Palliative Care, University Hospital and University of Zurich, Zurich, Switzerland
| | - Nicolaus Andratschke
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - David A. Reardon
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Daphne Haas-Kogan
- Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Rifaquat Rahman
- Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, USA
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164
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Wongsurawat T, Jenjaroenpun P, Anekwiang P, Arigul T, Thongrattana W, Jamshidi‐Parsian A, Boysen G, Suriyaphol P, Suktitipat B, Srirabheebhat P, Cheunsuchon P, Tanboon J, Nookaew I, Sathornsumetee S. Exploiting nanopore sequencing for characterization and grading of IDH-mutant gliomas. Brain Pathol 2024; 34:e13203. [PMID: 37574201 PMCID: PMC10711254 DOI: 10.1111/bpa.13203] [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: 03/31/2023] [Accepted: 07/28/2023] [Indexed: 08/15/2023] Open
Abstract
The 2021 WHO Classification of Central Nervous System Tumors recommended evaluation of cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletion in addition to codeletion of 1p/19q to characterize IDH-mutant gliomas. Here, we demonstrated the use of a nanopore-based copy-number variation sequencing (nCNV-seq) approach to simultaneously identify deletions of CDKN2A/B and 1p/19q. The nCNV-seq approach was initially evaluated on three distinct glioma cell lines and then applied to 19 IDH-mutant gliomas (8 astrocytomas and 11 oligodendrogliomas) from patients. The whole-arm 1p/19q codeletion was detected in all oligodendrogliomas with high concordance among nCNV-seq, FISH, DNA methylation profiling, and whole-genome sequencing. For the CDKN2A/B deletion, nCNV-seq detected the loss in both astrocytoma and oligodendroglioma, with strong correlation with the CNV profiles derived from whole-genome sequencing (Pearson correlation (r) = 0.95, P < 2.2 × 10-16 to r = 0.99, P < 2.2 × 10-16 ) and methylome profiling. Furthermore, nCNV-seq can differentiate between homozygous and hemizygous deletions of CDKN2A/B. Taken together, nCNV-seq holds promise as a new, alternative approach for a rapid and simultaneous detection of the molecular signatures of IDH-mutant gliomas without capital expenditure for a sequencer.
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Affiliation(s)
- Thidathip Wongsurawat
- Division of Medical Bioinformatics, Department of Research and Development, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
- Department of Biomedical Informatics, College of MedicineUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Piroon Jenjaroenpun
- Division of Medical Bioinformatics, Department of Research and Development, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
- Department of Biomedical Informatics, College of MedicineUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Panatna Anekwiang
- Department of Medicine (Neurology), Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Tantip Arigul
- Division of Medical Bioinformatics, Department of Research and Development, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Wichayapat Thongrattana
- Division of Medical Bioinformatics, Department of Research and Development, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Azemat Jamshidi‐Parsian
- Department of Radiation OncologyUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Gunnar Boysen
- Department of Environmental and Occupational HealthUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Prapat Suriyaphol
- Division of Medical Bioinformatics, Department of Research and Development, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Bhoom Suktitipat
- Division of Medical Bioinformatics, Department of Research and Development, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
- Department of Biochemistry, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Prajak Srirabheebhat
- Department of Surgery (Neurosurgery), Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Pornsuk Cheunsuchon
- Department of Pathology, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Jantima Tanboon
- Department of Pathology, Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
| | - Intawat Nookaew
- Department of Biomedical Informatics, College of MedicineUniversity of Arkansas for Medical SciencesLittle RockArkansasUSA
| | - Sith Sathornsumetee
- Department of Medicine (Neurology), Faculty of Medicine Siriraj HospitalMahidol UniversityBangkokThailand
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165
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Parmar V, Haubold J, Salhöfer L, Meetschen M, Wrede K, Glas M, Guberina M, Blau T, Bos D, Kureishi A, Hosch R, Nensa F, Forsting M, Deuschl C, Umutlu L. Fully automated MR-based virtual biopsy of primary CNS lymphomas. Neurooncol Adv 2024; 6:vdae022. [PMID: 38516329 PMCID: PMC10956963 DOI: 10.1093/noajnl/vdae022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024] Open
Abstract
Background Primary central nervous system lymphomas (PCNSL) pose a challenge as they may mimic gliomas on magnetic resonance imaging (MRI) imaging, compelling precise differentiation for appropriate treatment. This study focuses on developing an automated MRI-based workflow to distinguish between PCNSL and gliomas. Methods MRI examinations of 240 therapy-naive patients (141 males and 99 females, mean age: 55.16 years) with cerebral gliomas and PCNSLs (216 gliomas and 24 PCNSLs), each comprising a non-contrast T1-weighted, fluid-attenuated inversion recovery (FLAIR), and contrast-enhanced T1-weighted sequence were included in the study. HD-GLIO, a pre-trained segmentation network, was used to generate segmentations automatically. To validate the segmentation efficiency, 237 manual segmentations were prepared (213 gliomas and 24 PCNSLs). Subsequently, radiomics features were extracted following feature selection and training of an XGBoost algorithm for classification. Results The segmentation models for gliomas and PCNSLs achieved a mean Sørensen-Dice coefficient of 0.82 and 0.80 for whole tumors, respectively. Three classification models were developed in this study to differentiate gliomas from PCNSLs. The first model differentiated PCNSLs from gliomas, with an area under the curve (AUC) of 0.99 (F1-score: 0.75). The second model discriminated between high-grade gliomas and PCNSLs with an AUC of 0.91 (F1-score: 0.6), and the third model differentiated between low-grade gliomas and PCNSLs with an AUC of 0.95 (F1-score: 0.89). Conclusions This study serves as a pilot investigation presenting an automated virtual biopsy workflow that distinguishes PCNSLs from cerebral gliomas. Prior to clinical use, it is necessary to validate the results in a prospective multicenter setting with a larger number of PCNSL patients.
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Affiliation(s)
- Vicky Parmar
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - Johannes Haubold
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - Luca Salhöfer
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - Mathias Meetschen
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - Karsten Wrede
- Department of Neurosurgery and Spine Surgery, University Hospital Essen, Essen, Germany
| | - Martin Glas
- Department of Neuropathology, University Hospital Essen, Essen, Germany
| | - Maja Guberina
- Department of Radiotherapy, University Hospital Essen, Essen, Germany
| | - Tobias Blau
- Department of Neurology and Neurooncology, University Hospital Essen, Essen, Germany
| | - Denise Bos
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Anisa Kureishi
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - René Hosch
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - Felix Nensa
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
- Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany
| | - Michael Forsting
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Cornelius Deuschl
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
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166
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Arora H, Mammi M, Patel NM, Zyfi D, Dasari HR, Yunusa I, Simjian T, Smith TR, Mekary RA. Dexamethasone and overall survival and progression free survival in patients with newly diagnosed glioblastoma: a meta-analysis. J Neurooncol 2024; 166:17-26. [PMID: 38151699 DOI: 10.1007/s11060-023-04549-3] [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: 11/29/2023] [Accepted: 12/16/2023] [Indexed: 12/29/2023]
Abstract
PURPOSE Glioblastomas, the most common primary malignant brain tumors in adults, still hold poor prognosis. Corticosteroids, such as dexamethasone, are usually prescribed to reduce peritumoral edema and limit neurological symptoms, although potential detrimental effects of these drugs have been described. The present meta-analysis aimed to explore the association of dexamethasone with overall survival (OS) and progression free survival (PFS) in patients with newly diagnosed glioblastoma. METHODS PubMed, Cochrane Library, Embase, and ClinicalTrials.gov were searched for pertinent studies following the Preferred Reporting Items of Systematic Review and Meta-Analysis checklist. Pooled multivariable-adjusted hazard ratios (HR) for OS and PFS and their associated 95% confidence intervals (CIs) were calculated using the random-effects model and the heterogeneity among studies was assessed using I2. The quality of evidence was assessed using the GRADE criteria. RESULTS Seven studies were included, pooling data of 1,257 patients, with age varying from 11 to 81 years. Glioblastoma patients on pre- or peri-operative dexamethasone were associated with a significantly poorer overall survival (HR: 1.33, 95% CI: 1.15, 1.55; 7 studies; I2: 59.9%) and progression free survival (HR: 1.77, 95% CI: 1.05, 2.97; 3 studies; I2: 71.1%) compared to patients not on dexamethasone. The quality of evidence was moderate for overall survival and low for progression free survival. CONCLUSION Dexamethasone appeared to be associated with poor survival outcomes of glioblastoma patients.
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Affiliation(s)
- Harshit Arora
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marco Mammi
- Neurosurgery Division, "M. Bufalini" Hospital, Cesena, Italy
| | - Naisargi Manishkumar Patel
- School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences (MCPHS) University, Boston, MA, USA
| | - Dea Zyfi
- School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences (MCPHS) University, Boston, MA, USA
| | - Hema Reddy Dasari
- School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences (MCPHS) University, Boston, MA, USA
| | - Ismael Yunusa
- School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences (MCPHS) University, Boston, MA, USA
- College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Thomas Simjian
- School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences (MCPHS) University, Boston, MA, USA
| | - Timothy R Smith
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rania A Mekary
- Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- School of Pharmacy, Massachusetts College of Pharmacy and Health Sciences (MCPHS) University, Boston, MA, USA.
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167
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Karlberg A, Pedersen LK, Vindstad BE, Skjulsvik AJ, Johansen H, Solheim O, Skogen K, Kvistad KA, Bogsrud TV, Myrmel KS, Giskeødegård GF, Ingebrigtsen T, Berntsen EM, Eikenes L. Diagnostic accuracy of anti-3-[ 18F]-FACBC PET/MRI in gliomas. Eur J Nucl Med Mol Imaging 2024; 51:496-509. [PMID: 37776502 PMCID: PMC10774221 DOI: 10.1007/s00259-023-06437-4] [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: 06/22/2023] [Accepted: 09/06/2023] [Indexed: 10/02/2023]
Abstract
PURPOSE The primary aim was to evaluate whether anti-3-[18F]FACBC PET combined with conventional MRI correlated better with histomolecular diagnosis (reference standard) than MRI alone in glioma diagnostics. The ability of anti-3-[18F]FACBC to differentiate between molecular and histopathological entities in gliomas was also evaluated. METHODS In this prospective study, patients with suspected primary or recurrent gliomas were recruited from two sites in Norway and examined with PET/MRI prior to surgery. Anti-3-[18F]FACBC uptake (TBRpeak) was compared to histomolecular features in 36 patients. PET results were then added to clinical MRI readings (performed by two neuroradiologists, blinded for histomolecular results and PET data) to assess the predicted tumor characteristics with and without PET. RESULTS Histomolecular analyses revealed two CNS WHO grade 1, nine grade 2, eight grade 3, and 17 grade 4 gliomas. All tumors were visible on MRI FLAIR. The sensitivity of contrast-enhanced MRI and anti-3-[18F]FACBC PET was 61% (95%CI [45, 77]) and 72% (95%CI [58, 87]), respectively, in the detection of gliomas. Median TBRpeak was 7.1 (range: 1.4-19.2) for PET positive tumors. All CNS WHO grade 1 pilocytic astrocytomas/gangliogliomas, grade 3 oligodendrogliomas, and grade 4 glioblastomas/astrocytomas were PET positive, while 25% of grade 2-3 astrocytomas and 56% of grade 2-3 oligodendrogliomas were PET positive. Generally, TBRpeak increased with malignancy grade for diffuse gliomas. A significant difference in PET uptake between CNS WHO grade 2 and 4 gliomas (p < 0.001) and between grade 3 and 4 gliomas (p = 0.002) was observed. Diffuse IDH wildtype gliomas had significantly higher TBRpeak compared to IDH1/2 mutated gliomas (p < 0.001). Adding anti-3-[18F]FACBC PET to MRI improved the accuracy of predicted glioma grades, types, and IDH status, and yielded 13.9 and 16.7 percentage point improvement in the overall diagnoses for both readers, respectively. CONCLUSION Anti-3-[18F]FACBC PET demonstrated high uptake in the majority of gliomas, especially in IDH wildtype gliomas, and improved the accuracy of preoperatively predicted glioma diagnoses. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov ID: NCT04111588, URL: https://clinicaltrials.gov/study/NCT04111588.
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Affiliation(s)
- Anna Karlberg
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway.
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
| | | | - Benedikte Emilie Vindstad
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Jarstein Skjulsvik
- Department of Pathology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Faculty of Medical and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Håkon Johansen
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway
| | - Ole Solheim
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Karoline Skogen
- Department of Radiology and Nuclear Medicine, Oslo University Hospitals, Oslo, Norway
| | - Kjell Arne Kvistad
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway
| | - Trond Velde Bogsrud
- PET-Centre, University Hospital of North Norway, Tromsø, Norway
- Department of Nuclear Medicine and PET-Centre, Aarhus University Hospital, Aarhus, Denmark
| | | | - Guro F Giskeødegård
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tor Ingebrigtsen
- Department of Neurosurgery, University Hospital of North Norway, Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway
| | - Erik Magnus Berntsen
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, N-7030, Trondheim, Norway
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Live Eikenes
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
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168
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Feucht D, Haas P, Skardelly M, Behling F, Rieger D, Bombach P, Paulsen F, Hoffmann E, Hauser TK, Bender B, Renovanz M, Niyazi M, Tabatabai G, Tatagiba M, Roder C. Preoperative growth dynamics of untreated glioblastoma: Description of an exponential growth type, correlating factors, and association with postoperative survival. Neurooncol Adv 2024; 6:vdae053. [PMID: 38680987 PMCID: PMC11046984 DOI: 10.1093/noajnl/vdae053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/01/2024] Open
Abstract
Background Little is known about the growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival. Methods We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1 mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined by multivariable. Results Out of 749 patients screened, 13 had ≥3 preoperative MRI, 70 had 2 MRI and met the inclusion criteria. A curve estimation regression model showed the best fit for exponential tumor growth. Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho = -0.59, P < .001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log-rank: P = .010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox regression model for patients after tumor resection. Conclusions Especially small lesions suggestive of glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.
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Affiliation(s)
- Daniel Feucht
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Patrick Haas
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Marco Skardelly
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, Klinikum am Steinenberg, Reutlingen, Germany
| | - Felix Behling
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
- Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
- Department of Radiation Oncology, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - David Rieger
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Paula Bombach
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Frank Paulsen
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
| | - Elgin Hoffmann
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Radiation Oncology, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Till-Karsten Hauser
- Department of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Benjamin Bender
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), DKFZ partner site Tübingen, Tübingen, Germany
| | - Mirjam Renovanz
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
- Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Maximilian Niyazi
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Radiation Oncology, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Ghazaleh Tabatabai
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), DKFZ partner site Tübingen, Tübingen, Germany
| | - Marcos Tatagiba
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Constantin Roder
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
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Ljungqvist J, Barchéus H, Abbas F, Ozanne A, Nilsson D, Corell A. Clinical experiences and learning curves from robot-assisted neurosurgical biopsies with Stealth Autoguide™. Neurooncol Adv 2024; 6:vdae079. [PMID: 38845693 PMCID: PMC11154144 DOI: 10.1093/noajnl/vdae079] [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: 06/09/2024] Open
Abstract
Background Biopsies of intracranial lesions are a cornerstone in the diagnosis of unresectable tumors to guide neurooncological treatment; however, the procedure is also associated with risks. The results from the cranial robot guidance system Stealth Autoguide™ were studied after introduction at a neurosurgical department. Primary aims include the presentation of clinical and radiological data, accuracy of radiological diagnosis, learning curves of the new technology, diagnostic yield, and precision. The secondary aim was to study complications. Methods Retrospective data inclusion was performed on patients ≥ 18 years undergoing biopsy with Stealth Autoguide™ due to suspected brain tumors in the first 3 years after the introduction of the technique. Data regarding clinical characteristics, intraoperative variables, pathological diagnosis, and complications were recorded. Analyses of learning curves were performed. Results A total of 79 procedures were performed on 78 patients with a mean age of 62 years (SD 12.7, range 23-82), 30.8% were female. Tumors were often multifocal (63.3%) and supratentorial (89.9%). The diagnostic yield was 87.3%. The first-hand radiological diagnosis was correct in 62.0%. A slight decrease in operation time was observed, although not significant. The surgeon contributed to 12% of the variability. Conclusions Robot-assisted biopsies with Stealth Autoguide™ seem to be comparable, with regards to complications, to frame-based and other frameless neurosurgical biopsies. Learning curves demonstrated no statistical differences in time of surgery and only 12% surgeon-related variation (ie, variation caused by the change of performing surgeon), suggesting a successful implementation of this technical adjunct.
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Affiliation(s)
- Johan Ljungqvist
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Hanna Barchéus
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Fatima Abbas
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
| | - Anneli Ozanne
- Institute of Health and Care Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Daniel Nilsson
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alba Corell
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, University of Gothenburg, Sahlgrenska Academy, Gothenburg, Sweden
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden
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170
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Kinslow CJ, Garton ALA, Rae AI, Kocakavuk E, McKhann GM, Cheng SK, Sisti MB, Bruce JN, Wang TJC. Extent of resection for low-grade gliomas - Prognostic or therapeutic? Clin Neurol Neurosurg 2024; 236:108117. [PMID: 38219356 DOI: 10.1016/j.clineuro.2024.108117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 01/06/2024] [Indexed: 01/16/2024]
Affiliation(s)
- Connor J Kinslow
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 622 West 168th Street, BNH B011, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 1130 St Nicholas Ave, New York, NY 10032, USA
| | - Andrew L A Garton
- Department of Neurosurgery, Weill Cornell Medical Center and NewYork-Presbyterian Hospital, New York City, NY, USA
| | - Ali I Rae
- Department of Neurological Surgery, Oregon Health & Sciences University, 3181 SW Sam Jackson Pkwy, Portland, OR 97239, USA
| | - Emre Kocakavuk
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA; Department of Hematology and Stem Cell Transplantation, West German Cancer Center (WTZ), National Center for Tumor Diseases (NCT) West, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Guy M McKhann
- Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 1130 St Nicholas Ave, New York, NY 10032, USA; Department of Neurological Surgery, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY 10032, USA
| | - Simon K Cheng
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 622 West 168th Street, BNH B011, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 1130 St Nicholas Ave, New York, NY 10032, USA
| | - Michael B Sisti
- Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 1130 St Nicholas Ave, New York, NY 10032, USA; Department of Neurological Surgery, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY 10032, USA
| | - Jeffrey N Bruce
- Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 1130 St Nicholas Ave, New York, NY 10032, USA; Department of Neurological Surgery, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, 710 West 168th Street, New York, NY 10032, USA
| | - Tony J C Wang
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 622 West 168th Street, BNH B011, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, 1130 St Nicholas Ave, New York, NY 10032, USA.
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171
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Álvarez-Torres MDM, Balaña C, Fuster-García E, Puig J, García-Gómez JM. Unlocking Bevacizumab's Potential: rCBV max as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients. Cancers (Basel) 2023; 16:161. [PMID: 38201588 PMCID: PMC10778147 DOI: 10.3390/cancers16010161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 12/27/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival. PURPOSES In this study, we aimed to analyze the influence of tumor vascularity on the benefit provided by BVZ and propose preoperative rCBVmax at the high angiogenic tumor habitat as a predictive biomarker to select patients who can benefit the most. METHODS Clinical and MRI data from 106 patients with glioblastoma IDH-wildtype have been analyzed. Thirty-nine of them received BVZ, and the remaining sixty-seven did not receive a second-line treatment. The ONCOhabitats method was used to automatically calculate rCBV. RESULTS We found a median survival from progression of 305 days longer for patients with moderate vascular tumors who received BVZ than those who did not receive any second-line treatment. This contrasts with patients with high-vascular tumors who only presented a median survival of 173 days longer when receiving BVZ. Furthermore, better responses to BVZ were found for the moderate-vascular group with a higher proportion of patients alive at 6, 12, 18, and 24 months after progression. CONCLUSIONS We propose rCBVmax as a potential biomarker to select patients who can benefit more from BVZ after tumor progression. In addition, we propose a threshold of 7.5 to stratify patients into moderate- and high-vascular groups to select the optimal second-line treatment.
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Affiliation(s)
- María del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Carmen Balaña
- Applied Research Group in Oncology (B-ARGO Group), Institut Catala d’Oncologia (ICO), Institut Investigació Germans Trias i Pujol (IGTP), 08916 Badalona, Spain;
| | - Elies Fuster-García
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Josep Puig
- Radiology Department CDI, Hospital Clinic of Barcelona, 08036 Barcelona, Spain;
| | - Juan Miguel García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valencia, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
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172
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Di Nunno V, Aprile M, Bartolini S, Gatto L, Tosoni A, Ranieri L, De Biase D, Asioli S, Franceschi E. The Biological and Clinical Role of the Telomerase Reverse Transcriptase Gene in Glioblastoma: A Potential Therapeutic Target? Cells 2023; 13:44. [PMID: 38201248 PMCID: PMC10778438 DOI: 10.3390/cells13010044] [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: 10/25/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
Abstract
Glioblastoma IDH-wildtype represents the most lethal and frequent primary tumor of the central nervous system. Thanks to important scientific efforts, we can now investigate its deep genomic assessment, elucidating mutated genes and altered biological mechanisms in addition to its clinical aggressiveness. The telomerase reverse transcriptase gene (TERT) is the most frequently altered gene in solid tumors, including brain tumors and GBM IDH-wildtype. In particular, it can be observed in approximately 80-90% of GBM IDH-wildtype cases. Its clonal distribution on almost all cancer cells makes this gene an optimal target. However, the research of effective TERT inhibitors is complicated by several biological and clinical obstacles which can be only partially surmounted. Very recently, novel immunological approaches leading to TERT inhibition have been investigated, offering the potential to develop an effective target for this altered protein. Here, we perform a narrative review investigating the biological role of TERT alterations on glioblastoma and the principal obstacles associated with TERT inhibitions in this population. Moreover, we discuss possible combination treatment strategies to overcome these limitations.
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Affiliation(s)
- Vincenzo Di Nunno
- Nervous System Medical Oncology Department, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy (E.F.)
| | - Marta Aprile
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40138 Bologna, Italy
| | - Stefania Bartolini
- Nervous System Medical Oncology Department, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy (E.F.)
| | - Lidia Gatto
- Department of Oncology, Azienda Unità Sanitaria Locale (AUSL) Bologna, 40139 Bologna, Italy
| | - Alicia Tosoni
- Nervous System Medical Oncology Department, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy (E.F.)
| | - Lucia Ranieri
- Nervous System Medical Oncology Department, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy (E.F.)
| | - Dario De Biase
- Solid Tumor Molecular Pathology Laboratory, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
- Department of Pharmacy and Biotechnology (FaBit), University of Bologna, 40126 Bologna, Italy
| | - Sofia Asioli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Surgical Pathology Section, Alma Mater Studiorum, University of Bologna, 40126 Bologna, Italy
| | - Enrico Franceschi
- Nervous System Medical Oncology Department, IRCCS Istituto delle Scienze Neurologiche di Bologna, 40139 Bologna, Italy (E.F.)
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Zeng S, Ma H, Xie D, Huang Y, Yang J, Lin F, Ma Z, Wang M, Yang Z, Zhao J, Chu J. Tumor Multiregional Mean Apparent Propagator (MAP) Features in Evaluating Gliomas-A Comparative Study With Diffusion Kurtosis Imaging (DKI). J Magn Reson Imaging 2023. [PMID: 38131220 DOI: 10.1002/jmri.29202] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/08/2023] [Accepted: 12/09/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Glioma classification affects treatment and prognosis. Reliable imaging methods for preoperatively evaluating gliomas are essential. PURPOSE To evaluate tumor multiregional mean apparent propagator (MAP) features in glioma diagnosis and to compare those with diffusion-kurtosis imaging (DKI). STUDY TYPE Retrospective study. SUBJECTS 70 untreated glioma patients (31 LGGs (low-grade gliomas), 34 women; mean age, 47 ± 12 years, training (60%, n = 42) and testing cohorts (40%, n = 28)). FIELD STRENGTH/SEQUENCE 3-T, diffusion-MRI using q-space Cartesian grid sampling with 11 different b-values. ASSESSMENT Tumor multiregional MAP (mean squared displacement (MSD); q-space inverse variance (QIV); non-Gaussianity (NG); axial/radial non-Gaussianity (NGAx, NGRad); return-to-origin/axis/plane probability (RTOP, RTAP, and RTPP)); and DKI metrics (axial/mean/radial kurtosis (AK, MK, and RK)) on tumor parenchyma (TP) and peritumoral areas (PT) in histopathologically gliomas grading and genotyping were assessed. STATISTICAL TESTS Mann-Whitney U; Kruskal-Wallis; Benjamini-Hochberg; Bonferroni-correction; receiver operating curve (ROC) and area under curve (AUC); DeLong's test; Random Forest (RF). P value<0.05 was considered statistically significant after multiple comparisons correction. RESULTS Compared with LGGs, MSD, and QIV were significantly lower in TP, whereas NG, NGAx, NGRad, RTOP, RTAP, RTPP, and DKI metrics were significantly higher in HGGs (high-grade gliomas) (P ≤ 0.007), as well as in isocitrate-dehydrogenase (IDH)-mutated than IDH-wildtype gliomas (P ≤ 0.039). These trends were reversed for PT (tumor grades, P ≤ 0.011; IDH-mutation status, P ≤ 0.012). ROC analysis showed that, in TP, DKI metrics performed best in TP (AUC 0.83), whereas in PT, RTPP performed best (AUC 0.77) in glioma grading. AK performed best in TP (AUC 0.77), whereas MSD and RTPP performed best in PT (AUC 0.73) in IDH genotyping. Further RF analysis with DKI and MAP demonstrated good performance in grading (AUC 0.91, Accuracy 82%) and IDH genotyping (AUC 0.87, Accuracy 79%). DATA CONCLUSION Tumor multiregional MAP features could effectively evaluate gliomas. The performance of MAP may be similar to DKI in TP, while in PT, MAP may outperform DKI. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Shanmei Zeng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Hui Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Dingxiang Xie
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Yingqian Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jia Yang
- Department of Neurosurgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Fangzeng Lin
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zuliwei Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Mengzhu Wang
- Department of MR Scientific Marketing, Siemens Healthineers, Guangzhou, Guangdong, China
| | - Zhiyun Yang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jing Zhao
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Jianping Chu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
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Tillmanns N, Lost J, Tabor J, Vasandani S, Vetsa S, Marianayagam N, Yalcin K, Erson-Omay EZ, von Reppert M, Jekel L, Merkaj S, Ramakrishnan D, Avesta A, de Oliveira Santo ID, Jin L, Huttner A, Bousabarah K, Ikuta I, Lin M, Aneja S, Turowski B, Aboian M, Moliterno J. Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas. Sci Rep 2023; 13:22942. [PMID: 38135704 PMCID: PMC10746716 DOI: 10.1038/s41598-023-48918-4] [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: 03/08/2023] [Accepted: 12/01/2023] [Indexed: 12/24/2023] Open
Abstract
Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithms incorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. GBMs without CDKN2A alterations were significantly larger (64 vs. 30%, p = 0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI 1.5-12.1; p < 0.001). We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status.
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Affiliation(s)
- Niklas Tillmanns
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, 40225, Dusseldorf, Germany
| | - Jan Lost
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Joanna Tabor
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Sagar Vasandani
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Shaurey Vetsa
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | | | - Kanat Yalcin
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | | | - Marc von Reppert
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Leon Jekel
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Sara Merkaj
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Divya Ramakrishnan
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Arman Avesta
- Department of Radiation Oncology, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Irene Dixe de Oliveira Santo
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
| | - Lan Jin
- R&D, Sema4, 333 Ludlow Street, North Tower, 8th Floor, Stamford, CT, 06902, USA
| | - Anita Huttner
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | - Ichiro Ikuta
- Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ, 85054, USA
| | - MingDe Lin
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA
- Visage Imaging, Inc., 12625 High Bluff Dr, Suite 205, San Diego, CA, 92130, USA
| | - Sanjay Aneja
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Bernd Turowski
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, 40225, Dusseldorf, Germany
| | - Mariam Aboian
- Brain Tumor Research Group, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, PO Box 208042, New Haven, CT, 06520, USA.
- , New Haven, USA.
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Kim N, Shin H, Lim DH, Nam DH, Lee JI, Seol HJ, Kong DS, Choi JW, Chong K, Lee WJ. Treatment Outcomes after Dose-Escalated Moderately Hypofractionated Radiotherapy for Frail Patients with High-Grade Glioma. Cancers (Basel) 2023; 16:64. [PMID: 38201492 PMCID: PMC10778244 DOI: 10.3390/cancers16010064] [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: 11/15/2023] [Revised: 12/13/2023] [Accepted: 12/19/2023] [Indexed: 01/12/2024] Open
Abstract
For high-grade glioma (HGG) patients with old age or poor performance status, hypofractionated radiotherapy (hypoRT) in 10-15 fractions is recommended. Also, limited data exist on the impact of salvage treatment after progression in frail patients. We retrospectively analyzed the outcomes of dose-escalated hypoRT in 40 frail HGG patients who were treated with hypoRT between 2013 and 2021. With a median biologically effective dose of 71.7 Gy, a total dose of 56 Gy in 20 fractions was the most frequently used regimen (53.7%). The median age and Karnofsky Performance Status of patients were 74 years and 70, respectively. Most patients (n = 31, 77.5%) were diagnosed with glioblastoma, IDH-wildtype, CNS WHO grade 4. Only 10 (25.0%) patients underwent surgical resection, and 28 (70.0%) patients received concurrent temozolomide during hypoRT. With a median follow-up of 9.7 months, the median overall survival (OS) was 12.2 months. Of the 30 (75.0%) patients with disease progression, only 12 patients received salvage treatment. The OS after progression differed significantly depending on salvage treatment (median OS, 9.6 vs. 4.6 months, p = 0.032). Dose-escalated hypoRT in 20 fractions produced survival outcomes outperforming historical data for frail patients.
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Affiliation(s)
- Nalee Kim
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (N.K.); (H.S.)
| | - Hyunju Shin
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (N.K.); (H.S.)
| | - Do Hoon Lim
- Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (N.K.); (H.S.)
| | - Do-Hyun Nam
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
| | - Jung-Il Lee
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
| | - Ho Jun Seol
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
| | - Doo-Sik Kong
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
| | - Jung Won Choi
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
| | - Kyuha Chong
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
| | - Won Jae Lee
- Department of Neurosurgery, Brain Tumor Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; (D.-H.N.); (J.-I.L.); (H.J.S.); (D.-S.K.); (J.W.C.); (K.C.); (W.J.L.)
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Pace A, Lombardi G, Villani V, Benincasa D, Abbruzzese C, Cestonaro I, Corrà M, Padovan M, Cerretti G, Caccese M, Silvani A, Gaviani P, Giannarelli D, Ciliberto G, Paggi MG. Efficacy and safety of chlorpromazine as an adjuvant therapy for glioblastoma in patients with unmethylated MGMT gene promoter: RACTAC, a phase II multicenter trial. Front Oncol 2023; 13:1320710. [PMID: 38162492 PMCID: PMC10755935 DOI: 10.3389/fonc.2023.1320710] [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: 10/12/2023] [Accepted: 11/20/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction Drug repurposing is a promising strategy to develop new treatments for glioblastoma. In this phase II clinical trial, we evaluated the addition of chlorpromazine to temozolomide in the adjuvant phase of the standard first-line therapeutic protocol in patients with unmethylated MGMT gene promoter. Methods This was a multicenter phase II single-arm clinical trial. The experimental procedure involved the combination of CPZ with standard treatment with TMZ in the adjuvant phase of the Stupp protocol in newly-diagnosed GBM patients carrying an unmethylated MGMT gene promoter. Progression-free survival was the primary endpoint. Secondary endpoints were overall survival and toxicity. Results Forty-one patients were evaluated. Twenty patients (48.7%) completed 6 cycles of treatment with TMZ+CPZ. At 6 months, 27 patients (65.8%) were without progression, achieving the primary endpoint. Median PFS was 8.0 months (95% CI: 7.0-9.0). Median OS was 15.0 months (95% CI: 13.1-16.9). Adverse events led to reduction or interruption of CPZ dosage in 4 patients (9.7%). Discussion The addition of CPZ to standard TMZ in the first-line treatment of GBM patients with unmethylated MGMT gene promoter was safe and led to a longer PFS than expected in this population of patients. These findings provide proof-of-concept for the potential of adding CPZ to standard TMZ treatment in GBM patients with unmethylated MGMT gene promoter. Clinical trial registration https://clinicaltrials.gov/study/NCT04224441, identifier NCT04224441.
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Affiliation(s)
- Andrea Pace
- IRCCS - Regina Elena National Cancer Institute, Rome, Italy
| | | | | | | | | | | | - Martina Corrà
- Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Marta Padovan
- Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | | | - Mario Caccese
- Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | | | | | | | | | - Marco G. Paggi
- IRCCS - Regina Elena National Cancer Institute, Rome, Italy
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Sanvito F, Kaufmann TJ, Cloughesy TF, Wen PY, Ellingson BM. Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration. FRONTIERS IN RADIOLOGY 2023; 3:1267615. [PMID: 38152383 PMCID: PMC10751345 DOI: 10.3389/fradi.2023.1267615] [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: 07/26/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, United States
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Zhou QQ, Guo J, Wang Z, Li J, Chen M, Xu Q, Zhu L, Xu Q, Wang Q, Pan H, Pan J, Zhu Y, Song M, Liu X, Wang J, Zhang Z, Zhang L, Wang Y, Cai H, Chen X, Lu G. Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology. J Adv Res 2023:S2090-1232(23)00377-6. [PMID: 38072311 DOI: 10.1016/j.jare.2023.12.002] [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: 08/04/2023] [Revised: 11/29/2023] [Accepted: 12/01/2023] [Indexed: 02/13/2024] Open
Abstract
INTRODUCTION Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. OBJECTIVE To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. METHODS We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. RESULTS The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm-1 showed a positive linear correlation with PD-L1 expression level. CONCLUSIONS This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.
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Affiliation(s)
- Qing-Qing Zhou
- Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing, China; Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Jingxing Guo
- School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan, China.
| | - Ziyang Wang
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China; Nanjing Nuoyuan Medical Devices Co. Ltd, Nanjing, China
| | - Jianrui Li
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Meng Chen
- Nanjing Nuoyuan Medical Devices Co. Ltd, Nanjing, China
| | - Qiang Xu
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Lijun Zhu
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Qing Xu
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Qiang Wang
- Department of Neurosurgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Hao Pan
- Department of Neurosurgery, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Jing Pan
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yong Zhu
- School of Science, China Pharmaceutical University, Nanjing, China
| | - Ming Song
- Department of Mathmatical Sciences, The University of Texas at Dallas, Richardson, USA
| | - Xiaoxue Liu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jiandong Wang
- Department of Pathology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zhiqiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Longjiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yiqing Wang
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China
| | - Huiming Cai
- Department of Biomedical Engineering, College of Engineering and Applied Sciences, State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, China; Nanjing Nuoyuan Medical Devices Co. Ltd, Nanjing, China
| | - Xiaoyuan Chen
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore; Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Guangming Lu
- Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing, China; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China; State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China.
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Deng L, Ren J, Li B, Wang Y, Jiang N, Wang Y, Cui H. Predictive value of CCL2 in the prognosis and immunotherapy response of glioblastoma multiforme. BMC Genomics 2023; 24:746. [PMID: 38057698 DOI: 10.1186/s12864-023-09674-x] [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: 03/03/2023] [Accepted: 09/12/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Glioblastoma multiforme (GBM) is the most common and lethal primary brain tumor with a poor prognosis. The C-C motif chemokine ligand 2 (CCL2) has shown abnormal expression associated with progression of multiple malignancies, however, its role in predicting the prognosis and immunotherapy response of GBM remains poorly understood. RESULTS CCL2 was highly expressed in GBM as analyzed by integrating CGGA, GEPIA and UALCAN online platforms, and further verified by histologic examinations, qRT-PCR analysis, and independent GEO datasets. CCL2 could serve as an independent prognostic factor for both the poor overall survival and progression-free survival of GBM patients based on TCGA data, univariate and multivariate cox analyses. Functional enrichment analysis revealed that CCL2 mainly participated in the regulation of chemokine signaling pathway and inflammatory response. Further, CCL2 expression was positively correlated with CD4 T cells, macrophages, neutrophils and myeloid dendritic cells infiltrating GBM as calculated by the TIMER2.0 algorithm. Importantly, the tumor immune dysfunction and exclusion (TIDE) algorithm showed that in CCL2-high GBM group, the expression of CD274, CTLA4, HAVCR2 and other immune checkpoints were significantly increased, and the immune checkpoint blockade (ICB) therapy was accordingly more responsive. CONCLUSIONS CCL2 can be used as a predictor of prognosis as well as immunotherapy response in GBM, offering potential clinical implications.
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Affiliation(s)
- Longfei Deng
- Cancer Center, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Jie Ren
- Cancer Center, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Benqin Li
- Cancer Center, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Yinggang Wang
- Cancer Center, Medical Research Institute, Southwest University, Chongqing, 400715, China
| | - Nianfen Jiang
- Health Management Center, Southwest University Hospital, Chongqing, 400715, China
| | - Yi Wang
- Department of Endocrinology, The Ninth People's Hospital of Chongqing, Chongqing, 400799, China.
| | - Hongjuan Cui
- Cancer Center, Medical Research Institute, Southwest University, Chongqing, 400715, China.
- State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing, 400715, China.
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Cabello-Aguilar S, Vendrell JA, Solassol J. A Bioinformatics Toolkit for Next-Generation Sequencing in Clinical Oncology. Curr Issues Mol Biol 2023; 45:9737-9752. [PMID: 38132454 PMCID: PMC10741970 DOI: 10.3390/cimb45120608] [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: 11/06/2023] [Revised: 11/28/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023] Open
Abstract
Next-generation sequencing (NGS) has taken on major importance in clinical oncology practice. With the advent of targeted therapies capable of effectively targeting specific genomic alterations in cancer patients, the development of bioinformatics processes has become crucial. Thus, bioinformatics pipelines play an essential role not only in the detection and in identification of molecular alterations obtained from NGS data but also in the analysis and interpretation of variants, making it possible to transform raw sequencing data into meaningful and clinically useful information. In this review, we aim to examine the multiple steps of a bioinformatics pipeline as used in current clinical practice, and we also provide an updated list of the necessary bioinformatics tools. This resource is intended to assist researchers and clinicians in their genetic data analyses, improving the precision and efficiency of these processes in clinical research and patient care.
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Affiliation(s)
- Simon Cabello-Aguilar
- Montpellier BioInformatics for Clinical Diagnosis (MOBIDIC), Molecular Medicine and Genomics Platform (PMMG), CHU Montpellier, 34295 Montpellier, France
- Laboratoire de Biologie des Tumeurs Solides, Département de Pathologie et Oncobiologie, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France; (J.A.V.); (J.S.)
| | - Julie A. Vendrell
- Laboratoire de Biologie des Tumeurs Solides, Département de Pathologie et Oncobiologie, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France; (J.A.V.); (J.S.)
| | - Jérôme Solassol
- Laboratoire de Biologie des Tumeurs Solides, Département de Pathologie et Oncobiologie, CHU Montpellier, Université de Montpellier, 34295 Montpellier, France; (J.A.V.); (J.S.)
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181
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Zhao B, Qi H, Ma W. MGMT Promoter Methylation and Chemotherapy Outcomes in Low-Grade and Anaplastic Gliomas. JAMA Oncol 2023; 9:1734-1735. [PMID: 37856142 DOI: 10.1001/jamaoncol.2023.4736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Affiliation(s)
- Binghao Zhao
- DKTK Clinical Cooperation Unit (CCU) Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
| | - Hao Qi
- DKTK Clinical Cooperation Unit (CCU) Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wenbin Ma
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, PR China
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182
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Felefly T, Roukoz C, Fares G, Achkar S, Yazbeck S, Meyer P, Kordahi M, Azoury F, Nasr DN, Nasr E, Noël G, Francis Z. An Explainable MRI-Radiomic Quantum Neural Network to Differentiate Between Large Brain Metastases and High-Grade Glioma Using Quantum Annealing for Feature Selection. J Digit Imaging 2023; 36:2335-2346. [PMID: 37507581 PMCID: PMC10584786 DOI: 10.1007/s10278-023-00886-x] [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: 04/19/2023] [Revised: 06/11/2023] [Accepted: 07/17/2023] [Indexed: 07/30/2023] Open
Abstract
Solitary large brain metastases (LBM) and high-grade gliomas (HGG) are sometimes hard to differentiate on MRI. The management differs significantly between these two entities, and non-invasive methods that help differentiate between them are eagerly needed to avoid potentially morbid biopsies and surgical procedures. We explore herein the performance and interpretability of an MRI-radiomics variational quantum neural network (QNN) using a quantum-annealing mutual-information (MI) feature selection approach. We retrospectively included 423 patients with HGG and LBM (> 2 cm) who had a contrast-enhanced T1-weighted (CE-T1) MRI between 2012 and 2019. After exclusion, 72 HGG and 129 LBM were kept. Tumors were manually segmented, and a 5-mm peri-tumoral ring was created. MRI images were pre-processed, and 1813 radiomic features were extracted. A set of best features based on MI was selected. MI and conditional-MI were embedded into a quadratic unconstrained binary optimization (QUBO) formulation that was mapped to an Ising-model and submitted to D'Wave's quantum annealer to solve for the best combination of 10 features. The 10 selected features were embedded into a 2-qubits QNN using PennyLane library. The model was evaluated for balanced-accuracy (bACC) and area under the receiver operating characteristic curve (ROC-AUC) on the test set. The model performance was benchmarked against two classical models: dense neural networks (DNN) and extreme gradient boosting (XGB). Shapley values were calculated to interpret sample-wise predictions on the test set. The best 10-feature combination included 6 tumor and 4 ring features. For QNN, DNN, and XGB, respectively, training ROC-AUC was 0.86, 0.95, and 0.94; test ROC-AUC was 0.76, 0.75, and 0.79; and test bACC was 0.74, 0.73, and 0.72. The two most influential features were tumor Laplacian-of-Gaussian-GLRLM-Entropy and sphericity. We developed an accurate interpretable QNN model with quantum-informed feature selection to differentiate between LBM and HGG on CE-T1 brain MRI. The model performance is comparable to state-of-the-art classical models.
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Affiliation(s)
- Tony Felefly
- Radiation Oncology Department, Hôtel-Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon.
- ICube Laboratory, University of Strasbourg, Strasbourg, France.
- Radiation Oncology Department, Hôtel-Dieu de Lévis, Lévis, QC, Canada.
| | - Camille Roukoz
- Radiation Oncology Department, Hôtel-Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon
| | - Georges Fares
- Radiation Oncology Department, Hôtel-Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon
- Physics Department, Saint Joseph University, Beirut, Lebanon
| | - Samir Achkar
- Radiation Oncology Department, Gustave Roussy Cancer Campus, 94805, Villejuif, France
| | - Sandrine Yazbeck
- Department of Radiology, University of Maryland School of Medicine, 655 W Baltimore St S, Baltimore, MD, 21201, USA
| | - Philippe Meyer
- Medical Physics Department, Institut de Cancérologie de Strasbourg (ICANS), 67200, Strasbourg, France
- IMAGeS Unit, IRIS Platform, ICube, University of Strasbourg, 67085, Strasbourg Cedex, France
| | | | - Fares Azoury
- Radiation Oncology Department, Hôtel-Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon
| | - Dolly Nehme Nasr
- Radiation Oncology Department, Hôtel-Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon
| | - Elie Nasr
- Radiation Oncology Department, Hôtel-Dieu de France Hospital, Saint Joseph University, Beirut, Lebanon
| | - Georges Noël
- Radiotherapy Department, Institut de Cancérologie de Strasbourg (ICANS), 67200, Strasbourg, France
- Radiobiology Department, IMIS Unit, IRIS Platform, ICube, University of Strasbourg, 67085, Strasbourg Cedex, France
- Faculty of Medicine, University of Strasbourg, 67000, Strasbourg, France
| | - Ziad Francis
- Physics Department, Saint Joseph University, Beirut, Lebanon
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Teske N, Tonn JC, Karschnia P. How to evaluate extent of resection in diffuse gliomas: from standards to new methods. Curr Opin Neurol 2023; 36:564-570. [PMID: 37865849 DOI: 10.1097/wco.0000000000001212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2023]
Abstract
PURPOSE OF REVIEW Maximal safe tumor resection represents the current standard of care for patients with newly diagnosed diffuse gliomas. Recent efforts have highlighted the prognostic value of extent of resection measured as residual tumor volume in patients with isocitrate dehydrogenase (IDH)-wildtype and -mutant gliomas. Accurate assessment of such information therefore appears essential in the context of clinical trials as well as patient management. RECENT FINDINGS Current recommendations for evaluation of extent of resection rest upon standardized postoperative MRI including contrast-enhanced T1-weighted sequences, T2-weighted/fluid-attenuated-inversion-recovery sequences, and diffusion-weighted imaging to differentiate postoperative tumor volumes from ischemia and nonspecific imaging findings. In this context, correct timing of postoperative imaging within the postoperative period is of utmost importance. Advanced MRI techniques including perfusion-weighted MRI and MR-spectroscopy may add further insight when evaluating residual tumor remnants. Positron emission tomography (PET) using amino acid tracers proves beneficial in identifying metabolically active tumor beyond anatomical findings on conventional MRI. SUMMARY Future efforts will have to refine recommendations on postoperative assessment of residual tumor burden in respect to differences between IDH-wildtype and -mutant gliomas, and incorporate the emerging role of advanced imaging modalities like amino acid PET.
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Affiliation(s)
- Nico Teske
- Department of Neurosurgery, LMU University Hospital, LMU Munich
- German Cancer Consortium (DKTK), Partner Site, Munich, Germany
| | - Joerg-Christian Tonn
- Department of Neurosurgery, LMU University Hospital, LMU Munich
- German Cancer Consortium (DKTK), Partner Site, Munich, Germany
| | - Philipp Karschnia
- Department of Neurosurgery, LMU University Hospital, LMU Munich
- German Cancer Consortium (DKTK), Partner Site, Munich, Germany
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Wang P, Xie S, Wu Q, Weng L, Hao Z, Yuan P, Zhang C, Gao W, Wang S, Zhang H, Song Y, He J, Gao Y. Model incorporating multiple diffusion MRI features: development and validation of a radiomics-based model to predict adult-type diffuse gliomas grade. Eur Radiol 2023; 33:8809-8820. [PMID: 37439936 PMCID: PMC10667393 DOI: 10.1007/s00330-023-09861-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 05/06/2023] [Accepted: 05/14/2023] [Indexed: 07/14/2023]
Abstract
OBJECTIVES To develop and validate a radiomics-based model (ADGGIP) for predicting adult-type diffuse gliomas (ADG) grade by combining multiple diffusion modalities and clinical and imaging morphologic features. METHODS In this prospective study, we recruited 103 participants diagnosed with ADG and collected their preoperative conventional MRI and multiple diffusion imaging (diffusion tensor imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging, and mean apparent propagator diffusion-MRI) data in our hospital, as well as clinical information. Radiomic features of the diffusion images and clinical information and morphological data from the radiological reports were extracted, and multiple pipelines were used to construct the optimal model. Model validation was performed through a time-independent validation cohort. ROC curves were used to evaluate model performance. The clinical benefit was determined by decision curve analysis. RESULTS From June 2018 to May 2021, 72 participants were recruited for the training cohort. Between June 2021 and February 2022, 31 participants were enrolled in the prospective validation cohort. In the training cohort (AUC 0.958), internal validation cohort (0.942), and prospective validation cohort (0.880), ADGGIP had good accuracy in predicting ADG grade. ADGGIP was also significantly better than the single-modality prediction model (AUC 0.860) and clinical imaging morphology model (0.841) (all p < .01) in the prospective validation cohort. When the threshold probability was greater than 5%, ADGGIP provided the greatest net benefit. CONCLUSION ADGGIP, which is based on advanced diffusion modalities, can predict the grade of ADG with high accuracy and robustness and can help improve clinical decision-making. CLINICAL RELEVANCE STATEMENT Integrated multi-modal predictive modeling is beneficial for early detection and treatment planning of adult-type diffuse gliomas, as well as for investigating the genuine clinical significance of biomarkers. KEY POINTS • Integrated model exhibits the highest performance and stability. • When the threshold is greater than 5%, the integrated model has the greatest net benefit. • The advanced diffusion models do not demonstrate better performance than the simple technology.
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Affiliation(s)
- Peng Wang
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
- Inner Mongolia Medical University, Hohhot, 010110, China
| | - Shenghui Xie
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Qiong Wu
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Lixin Weng
- Inner Mongolia Medical University, Hohhot, 010110, China
- Department of Pathology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Zhiyue Hao
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Pengxuan Yuan
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Chi Zhang
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Weilin Gao
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Huapeng Zhang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Yang Song
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Jinlong He
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China.
| | - Yang Gao
- Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010059, China.
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185
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Taskiran E, Yilmaz B, Akgun MY, Kemerdere R, Uzan M, Isler C. Neurophysiologic cut off values for safe resection of patients with supratentorial gliomas. Acta Neurochir (Wien) 2023; 165:4227-4234. [PMID: 37917380 DOI: 10.1007/s00701-023-05865-3] [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: 07/24/2023] [Accepted: 10/21/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND Gliomas have infiltrative nature and tumor volume has direct prognostic value. Optimal resection limits delineated by high-frequency monopolar stimulation with multipulse short train technique is still a matter of debate for safe surgery without (or with acceptable) neurological deficits. It is also an enigma whether the same cut-off values are valid for high and low grades. We aimed to analyze the value of motor mapping/monitoring findings on postoperative motor outcome in diffuse glioma surgery. METHODS Patients who were operated on due to glioma with intraoperative neuromonitorization at our institution between 2017 and 2021 were analyzed. Demographic information, pre- and post-operative neurological deficit, magnetic resonance images, resection rates, and motor evoked potential (MEP) findings were analyzed. RESULTS Eighty-seven patients of whom 55 had high-grade tumors were included in the study. Total/near-total resection was achieved in 85%. Subcortical motor threshold (ScMTh) from resection cavity to the corticospinal tract was ≤ 2mA in 17; 3 mA in 14; 4 mA in 6; 5 mA in 7, and ≥5mA in 50 patients. On the 6th month examination, six patients (5 with high-grade tumor) had motor deficits. These patients had changes in MEP that exceeded critical threshold during monitoring. Receiver operating characteristic analysis revealed 2.5 mA ScMTh as the cut-off point for limb paresis after awakening and 6 months for the groups. CONCLUSIONS Subcortical mapping with MEP monitoring helps to achieve safe wider resection. The optimal safe limit for SCMTh was determined as 2.5 mA. Provided that safe threshold values are maintained in MEP, surgeon may force the functional limits by lowering the SCMTh to 1 mA, especially in low-grade gliomas.
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Affiliation(s)
- E Taskiran
- Department of Neurology, Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Istanbul, Turkey
| | - B Yilmaz
- Department of Neurology, Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Istanbul, Turkey
| | - M Y Akgun
- Department of Neurosurgery, Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Istanbul, Turkey
| | - R Kemerdere
- Department of Neurosurgery, Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Istanbul, Turkey
| | - M Uzan
- Department of Neurosurgery, Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Istanbul, Turkey
| | - C Isler
- Department of Neurosurgery, Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Istanbul, Turkey.
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186
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Baumgarten P, Prange G, Kamp MA, Monden D, Neef V, Schwarzer F, Dubinski D, Dinc N, Weber KJ, Czabanka M, Hattingen E, Ronellenfitsch MW, Steinbach JP, Senft C. Treatment of very elderly glioblastoma patients ≥ 75 years of age: whom to treat. J Neurooncol 2023; 165:509-515. [PMID: 38032426 PMCID: PMC10752837 DOI: 10.1007/s11060-023-04518-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: 10/09/2023] [Accepted: 11/20/2023] [Indexed: 12/01/2023]
Abstract
PURPOSE The prognosis of patients ≥ 75 years suffering from glioblastoma is poor. Novel therapies are usually reserved for patients ≤ 70 years. In an aging population, treatment of very elderly patients remains a challenge. METHODS Between 2010 and 2018, a total of 977 glioblastoma patients were treated at our institution. Of these, 143 patients were ≥ 75 years at diagnosis. Primary procedure was surgical resection or biopsy followed by adjuvant treatment, whenever possible. We retrospectively investigated overall survival (OS) and potential prognostic factors influencing survival, including Karnofsky Performance Status (KPS), surgical therapy, adjuvant therapy as well as MGMT promotor status. RESULTS In very elderly patients, median age was 79 years (range: 75-110). Biopsy only was performed in 104 patients; resection was performed in 39 patients. Median OS for the entire cohort was 5.9 months. Univariate analysis showed that KPS at presentation (≥ 70 vs. ≤60), surgery vs. biopsy, adjuvant chemotherapy and adjuvant radiotherapy were significantly associated with OS (6 vs. 3, p < 0.0111; 12 vs. 4, p = 0.0011; 11 vs. 4, p = 0.0003 and 10 vs. 1.5 months, p < 0.0001, respectively). Multivariate analysis confirmed adjuvant radiotherapy (p < 0.0001) and chemotherapy (p = 0.0002) as independent factors influencing OS. CONCLUSION For very elderly patients, the natural course of disease without treatment is devastating. These patients benefit from multimodal treatment including adjuvant radiotherapy and chemotherapy. A beneficial effect of resection has not been demonstrated. Treatment options and outcomes should be thoughtfully discussed before treatment decisions are made.
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Affiliation(s)
- Peter Baumgarten
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.
- Department of Neurosurgery, University Hospital Jena, Friedrich Schiller University, Am Klinikum 1, D-07747, Jena, Germany.
| | - Georg Prange
- Department of Neurosurgery, University Hospital Jena, Friedrich Schiller University, Jena, Germany
| | - Marcel A Kamp
- Department of Neurosurgery, University Hospital Jena, Friedrich Schiller University, Jena, Germany
- Centre for Palliative and Neuro-palliative Care, Brandenburg Medical School Theodor Fontane and Faculty of Health Sciences Brandenburg, Campus Rüdersdorf, Rüdersdorf bei Berlin, Germany
| | - Daniel Monden
- Department of Neurosurgery, University Hospital Jena, Friedrich Schiller University, Jena, Germany
- Department of Neurosurgery, Hannover Medical School, Hannover, Germany
| | - Vanessa Neef
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Franziska Schwarzer
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Daniel Dubinski
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
- Department of Neurosurgery, University Medicine Rostock, Rostock, Germany
| | - Nazife Dinc
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
- Department of Neurosurgery, University Hospital Jena, Friedrich Schiller University, Jena, Germany
| | - Katharina J Weber
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt, Germany
- German Cancer Consortium (DKTK), partner site Frankfurt/Mainz, Frankfurt, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), Goethe University, Frankfurt, Germany
- University Cancer Center (UCT), Goethe University Hospital, Frankfurt, Germany
| | - Markus Czabanka
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Michael W Ronellenfitsch
- Department of Neuro-Oncology, University Hospital Frankfurt - Goethe-University, Frankfurt, Germany
| | - Joachim P Steinbach
- Department of Neuro-Oncology, University Hospital Frankfurt - Goethe-University, Frankfurt, Germany
| | - Christian Senft
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
- Department of Neurosurgery, University Hospital Jena, Friedrich Schiller University, Am Klinikum 1, D-07747, Jena, Germany
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187
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Biswas I, Precilla DS, Kuduvalli SS, Ramachandran MA, Akshaya S, Raman V, Prabhu D, Anitha TS. Unveiling the anti-glioma potential of a marine derivative, Fucoidan: its synergistic cytotoxicity with Temozolomide-an in vitro and in silico experimental study. 3 Biotech 2023; 13:397. [PMID: 37974928 PMCID: PMC10645720 DOI: 10.1007/s13205-023-03814-6] [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] [Accepted: 10/16/2023] [Indexed: 11/19/2023] Open
Abstract
Glioma coined as a "butterfly" tumor associated with a dismal prognosis. Marine algal compounds with the richest sources of bioactive components act as significant anti-tumor therapeutics. However, there is a paucity of studies conducted on Fucoidan to enhance the anti-glioma efficacy of Temozolomide. Therefore, the present study aimed to evaluate the synergistic anti-proliferative, anti-inflammatory and pro-apoptotic effects of Fucoidan with Temozolomide in in vitro and in silico experimental setup. The anti-proliferative effects of Temozolomide and Fucoidan were evaluated on C6 glioma cells by MTT and migration assay. Modulation of inflammatory markers and apoptosis induction was affirmed at the morphological and transcriptional level by dual staining and gene expression. Molecular docking (MD) and molecular dynamics simulation (MDS) studies were performed against the targets to rationalize the inhibitory effect. The dual-drug combination significantly reduced the cell viability and migration of glioma cells in a synergistic dose-dependent manner. At the molecular level, the dual-drug combination significantly down-regulated inflammatory genes with a concomitant upregulation of pro-apoptotic marker. In consensus with our in vitro findings, molecular docking and simulation studies revealed that the anti-tumor ligands: Temozolomide, Fucoidan with 5-(3-Methy1-trizeno)-imidazole-4-carboxamide (MTIC), and 4-amino-5-imidazole-carboxamide (AIC) had the potency to bind to the inflammatory proteins at their active sites, mediated by H-bonds and other non-covalent interactions. The dual-drug combinatorial treatment synergistically inhibited the proliferation, migration of glioma cells and promoted apoptosis; conversely with the down-regulation of inflammatory genes. However, pre-clinical experimental evidence is warranted for the possible translation of this combination. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03814-6.
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Affiliation(s)
- Indrani Biswas
- Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed to-be University), Puducherry, 607402 India
| | - Daisy S. Precilla
- Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed to-be University), Puducherry, 607402 India
| | - Shreyas S. Kuduvalli
- Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed to-be University), Puducherry, 607402 India
| | | | - S. Akshaya
- Jeppiaar College of Engineering, Chennai, Tamil Nadu 600119 India
| | - Venkat Raman
- Thiruvalluvar University, Vellore, Tamil Nadu 632115 India
| | - Dhamodharan Prabhu
- Centre for Drug Discovery, Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, 641021 India
| | - T. S. Anitha
- Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed to-be University), Puducherry, 607402 India
- Present Address: Department of Biochemistry and Molecular Biology, Pondicherry University, Puducherry, 605014 India
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188
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Chen Q, Wang K, Ren X, Zhao X, Chen Q, Fan D, Zhang S, Li X, Ai L. Individualized discrimination of tumor progression from treatment-related changes in different types of adult-type diffuse gliomas using [ 11C]methionine PET. J Neurooncol 2023; 165:547-559. [PMID: 38095773 DOI: 10.1007/s11060-023-04529-7] [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: 11/07/2023] [Accepted: 12/04/2023] [Indexed: 12/29/2023]
Abstract
PURPOSE This study aimed to assess the ability of [11C]methionine (MET) PET in distinguishing between tumor progression (TP) and treatment-related changes (TRCs) among different types of adult-type diffuse gliomas according to the 2021 World Health Organization classification and predict overall survival (OS). METHODS We retrospectively selected 113 patients with adult-type diffuse gliomas with suspected TP who underwent MET PET imaging. Maximum and mean tumor-to-background ratios (TBRmax, TBRmean) and metabolic tumor volume (MTV) were calculated. Diagnoses were verified by histopathology (n = 50) or by clinical/radiological follow-up (n = 63). The diagnostic performance of MET PET parameters was evaluated through receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculation. Survival analysis employed the Kaplan-Meier method and Cox proportional-hazards regression. RESULTS TP and TRCs were diagnosed in 76 (67%) and 37 (33%) patients, respectively. ROC analysis revealed TBRmax had the best performance in differentiating TP from TRCs with a cut-off of 1.96 in IDH-mutant astrocytoma (AUC, 0.87; sensitivity, 93%; specificity 69%), 1.80 in IDH-mutant and 1p/19q-codeleted oligodendroglioma (AUC, 0.96; sensitivity, 100%; specificity, 89%), and 2.13 in IDH wild-type glioblastoma (AUC, 0.89; sensitivity, 89%; specificity, 78%), respectively. On multivariate analysis, higher TBRmean and MTV were significantly correlated with shorter OS in all IDH-mutant gliomas, as well as in IDH-mutant astrocytoma subgroup. CONCLUSION This work confirms that MET PET has varying diagnostic performances in distinguishing TP from TRCs within three types of adult-type diffuse gliomas, and highlights its high diagnostic accuracy in IDH-mutant and 1p/19q-codeleted oligodendroglioma and potential prognostic value for IDH-mutant gliomas, particularly IDH-mutant astrocytoma.
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Affiliation(s)
- Qiang Chen
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Kai Wang
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Xiaohui Ren
- Department of Neurosurgical Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xiaobin Zhao
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Qian Chen
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Di Fan
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Shu Zhang
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Xiaotong Li
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China
| | - Lin Ai
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, 119 West Road of South 4th Ring, Fengtai District, Beijing, China.
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189
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Gregucci F, Di Guglielmo FC, Surgo A, Carbonara R, Laera L, Ciliberti MP, Gentile MA, Calbi R, Caliandro M, Sasso N, Davi' V, Bonaparte I, Fanelli V, Giraldi D, Tortora R, Internò V, Giuliani F, Surico G, Signorelli F, Lombardi G, Fiorentino A. Reirradiation with radiosurgery or stereotactic fractionated radiotherapy in association with regorafenib in recurrent glioblastoma. Strahlenther Onkol 2023:10.1007/s00066-023-02172-9. [PMID: 37987802 DOI: 10.1007/s00066-023-02172-9] [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: 06/27/2023] [Accepted: 10/01/2023] [Indexed: 11/22/2023]
Abstract
PURPOSE No standard treatment has yet been established for recurrent glioblastoma (GBM). In this context, the aim of the current study was to evaluate safety and efficacy of reirradiation (re-RT) by radiosurgery or fractionated stereotactic radiotherapy (SRS/FSRT) in association with regorafenib. METHODS Patients with a histological or radiological diagnosis of recurrent GBM who received re-RT by SRS/FSRT and regorafenib as second-line systemic therapy were included in the analysis. RESULTS From January 2020 to December 2022, 21 patients were evaluated. The median time between primary/adjuvant RT and disease recurrence was 8 months (range 5-20). Median re-RT dose was 24 Gy (range 18-36 Gy) for a median number of 5 fractions (range 1-6). Median regorafenib treatment duration was 12 weeks (range 3-26). Re-RT was administered before starting regorafenib or in the week off regorafenib during the course of chemotherapy. The median and the 6‑month overall survival (OS) from recurrence were 8.4 months (95% confidence interval [CI] 6.9-12.7 months) and 75% (95% CI 50.9-89.1%), respectively. The median progression-free survival (PFS) from recurrence was 6 months (95% CI 3.7-8.5 months). The most frequent side effects were asthenia that occurred in 10 patients (8 cases of grade 2 and 2 cases of grade 3), and hand-foot skin reaction (2 patients grade 3, 3 patients grade 2). Adverse events led to permanent regorafenib discontinuation in 2 cases, while in 5/21 cases (23.8%), a dose reduction was administered. One patient experienced dehiscence of the surgical wound after reintervention and during regorafenib treatment, while another patient reported intestinal perforation that required hospitalization. CONCLUSION For recurrent GBM, re-RT with SRT/FSRT plus regorafenib is a safe treatment. Prospective trials are necessary.
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Affiliation(s)
- Fabiana Gregucci
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy.
| | | | - Alessia Surgo
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Roberta Carbonara
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Letizia Laera
- Department of Medical Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Maria Paola Ciliberti
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | | | - Roberto Calbi
- Department of Radiology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Morena Caliandro
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Nicola Sasso
- Department of Medical Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Valerio Davi'
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Ilaria Bonaparte
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Vincenzo Fanelli
- Department of Neurosurgery, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - David Giraldi
- Department of Neurosurgery, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Romina Tortora
- Centro Orientamento Oncologico (COrO), Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Valeria Internò
- Department of Medical Oncology, Ospedale San Paolo, Bari, Italy
| | | | - Giammarco Surico
- Department of Medical Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
| | - Francesco Signorelli
- Division of Neurosurgery, Department of Translational Biomedicine and Neurosciences (DiBraiN), University "Aldo Moro" of Bari, Bari, Italy
| | - Giuseppe Lombardi
- Department of Medical Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy
| | - Alba Fiorentino
- Department of Radiation Oncology, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Italy
- Department of Medicine and Surgery, LUM University, Casamassima-Bari, Italy
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190
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Wen PY, van den Bent M, Youssef G, Cloughesy TF, Ellingson BM, Weller M, Galanis E, Barboriak DP, de Groot J, Gilbert MR, Huang R, Lassman AB, Mehta M, Molinaro AM, Preusser M, Rahman R, Shankar LK, Stupp R, Villanueva-Meyer JE, Wick W, Macdonald DR, Reardon DA, Vogelbaum MA, Chang SM. RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults. J Clin Oncol 2023; 41:5187-5199. [PMID: 37774317 PMCID: PMC10860967 DOI: 10.1200/jco.23.01059] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/12/2023] [Accepted: 08/10/2023] [Indexed: 10/01/2023] Open
Abstract
PURPOSE The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION The revised RANO 2.0 criteria refine response assessment in gliomas.
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Affiliation(s)
- Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - Martin van den Bent
- Department Neuro-Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Gilbert Youssef
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - Timothy F. Cloughesy
- UCLA Brain Tumor Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | | | | | - John de Groot
- Division of Neuro-Oncology, Department of Neurosurgery, University of California, San Francisco, CA
| | - Mark R. Gilbert
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Raymond Huang
- Division of Neuro-radiology, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Andrew B. Lassman
- Division of Neuro-Oncology, Department of Neurology, Herbert Irving Comprehensive Cancer Center and Irving Institute for Clinical and Translational Research, Columbia University Vagelos College of Physicians and Surgeons and New York-Presbyterian Hospital, New York, NY
| | | | - Annette M. Molinaro
- Division of Biomedical Statistics and Informatics, Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA
| | - Matthias Preusser
- Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria
| | - Rifaquat Rahman
- Department of Radiation Oncology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Lalitha K. Shankar
- Clinical Trials Branch, Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Roger Stupp
- Malnati Brain Tumor Institute, Lurie Comprehensive Cancer Center and Departments of Neurological Surgery, Neurology and Division of Hematology/Oncology, Northwestern University, Chicago, IL
| | | | - Wolfgang Wick
- Department of Neurology Heidelberg University Hospital & Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David R. Macdonald
- Departments of Clinical Neurological Sciences and Oncology (Emeritus), Western University, London, Ontario, Canada
| | - David A. Reardon
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA
| | - Michael A. Vogelbaum
- Departments of Neuro-Oncology and Neurosurgery, Moffitt Cancer Center, Tampa, FL
| | - Susan M. Chang
- Division of Neuro-Oncology, Department of Neurosurgery, University of California, San Francisco, CA
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191
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Begagić E, Pugonja R, Bečulić H, Čeliković A, Tandir Lihić L, Kadić Vukas S, Čejvan L, Skomorac R, Selimović E, Jaganjac B, Juković-Bihorac F, Jusić A, Pojskić M. Molecular Targeted Therapies in Glioblastoma Multiforme: A Systematic Overview of Global Trends and Findings. Brain Sci 2023; 13:1602. [PMID: 38002561 PMCID: PMC10669565 DOI: 10.3390/brainsci13111602] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 11/10/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
This systematic review assesses current molecular targeted therapies for glioblastoma multiforme (GBM), a challenging condition with limited treatment options. Using PRISMA methodology, 166 eligible studies, involving 2526 patients (61.49% male, 38.51% female, with a male-to-female ratio of 1.59/1), were analyzed. In laboratory studies, 52.52% primarily used human glioblastoma cell cultures (HCC), and 43.17% employed animal samples (mainly mice). Clinical participants ranged from 18 to 100 years, with 60.2% using combined therapies and 39.8% monotherapies. Mechanistic categories included Protein Kinase Phosphorylation (41.6%), Cell Cycle-Related Mechanisms (18.1%), Microenvironmental Targets (19.9%), Immunological Targets (4.2%), and Other Mechanisms (16.3%). Key molecular targets included Epidermal Growth Factor Receptor (EGFR) (10.8%), Mammalian Target of Rapamycin (mTOR) (7.2%), Vascular Endothelial Growth Factor (VEGF) (6.6%), and Mitogen-Activated Protein Kinase (MEK) (5.4%). This review provides a comprehensive assessment of molecular therapies for GBM, highlighting their varied efficacy in clinical and laboratory settings, ultimately impacting overall and progression-free survival in GBM management.
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Affiliation(s)
- Emir Begagić
- Department of General Medicine, School of Medicine, Unversity of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina; (E.B.)
| | - Ragib Pugonja
- Department of Anatomy, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
- Department of General Medicine, Primary Health Care Center, Nikole Šubića Zrinjskog bb., 72260 Busovača, Bosnia and Herzegovina
| | - Hakija Bečulić
- Department of General Medicine, Primary Health Care Center, Nikole Šubića Zrinjskog bb., 72260 Busovača, Bosnia and Herzegovina
- Department of Neurosurgery, Cantonal Hospital Zenica, Crkvice 76, 72000 Zenica, Bosnia and Herzegovina
| | - Amila Čeliković
- Department of General Medicine, School of Medicine, Unversity of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina; (E.B.)
| | - Lejla Tandir Lihić
- Department of Neurology, Cantonal Hospital Zenica, Crkvice 76, 72000 Zenica, Bosnia and Herzegovina
| | - Samra Kadić Vukas
- Department of Neurology, Cantonal Hospital Zenica, Crkvice 76, 72000 Zenica, Bosnia and Herzegovina
| | - Lejla Čejvan
- Department of General Medicine, School of Medicine, Unversity of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina; (E.B.)
| | - Rasim Skomorac
- Department of Neurosurgery, Cantonal Hospital Zenica, Crkvice 76, 72000 Zenica, Bosnia and Herzegovina
- Department of Surgery, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
| | - Edin Selimović
- Department of Surgery, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
| | - Belma Jaganjac
- Department of Histology, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina; (B.J.)
| | - Fatima Juković-Bihorac
- Department of Histology, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina; (B.J.)
- Department of Pathology, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina
- Department of Pathology, Cantonal Hospital Zenica, Crkvice 76, 72000 Zenica, Bosnia and Herzegovina
| | - Aldin Jusić
- Department of Neurosurgery, Cantonal Hospital Zenica, Crkvice 76, 72000 Zenica, Bosnia and Herzegovina
| | - Mirza Pojskić
- Department of Neurosurgery, University Hospital Marburg, Baldingerstr., 35033 Marburg, Germany
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192
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Molica C, Gili A, Nardelli C, Pierini T, Arniani S, Beacci D, Mavridou E, Mandarano M, Corinaldesi R, Metro G, Gorello P, Giovenali P, Cenci N, Castrioto C, Lupattelli M, Roila F, Mecucci C, La Starza R. Optimizing the risk stratification of astrocytic tumors by applying the cIMPACT-NOW Update 3 signature: real-word single center experience. Sci Rep 2023; 13:20101. [PMID: 37973912 PMCID: PMC10654668 DOI: 10.1038/s41598-023-46701-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023] Open
Abstract
Our work reports implementation of a useful genetic diagnosis for the clinical managment of patients with astrocytic tumors. We investigated 313 prospectively recruited diffuse astrocytic tumours by applying the cIMPACT-NOW Update 3 signature. The cIMPACT-NOW Update 3 (cIMPACT-NOW 3) markers, i.e., alterations of TERT promoter, EGFR, and/or chromosome 7 and 10, characterized 96.4% of IDHwt cases. Interestingly, it was also found in 48,5% of IDHmut cases. According to the genomic profile, four genetic subgroups could be distinguished: (1) IDwt/cIMPACT-NOW 3 (n = 270); (2) IDHwt/cIMPACT-NOW 3 negative (= 10); (3) IDHmut/cIMPACT-NOW 3 (n = 16); and 4) IDHmut/cIMPACT-NOW 3 negative (n = 17). Multivariate analysis confirmed that IDH1/2 mutations confer a favorable prognosis (IDHwt, HR 2.91 95% CI 1.39-6.06), and validated the prognostic value of the cIMPACT-NOW 3 signature (cIMPACT-NOW 3, HR 2.15 95% CI 1.15-4.03). To accurately identify relevant prognostic categories, overcoming the limitations of histopathology and immunohistochemistry, molecular-cytogenetic analyses must be fully integrated into the diagnostic work-up of astrocytic tumors.
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Affiliation(s)
- Carmen Molica
- Medical Oncology, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Alessio Gili
- Public Health Section, Department of Experimental Medicine, University of Perugia, Perugia, Italy
| | - Carlotta Nardelli
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy
| | - Tiziana Pierini
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy
| | - Silvia Arniani
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy
| | - Donatella Beacci
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy
| | - Elena Mavridou
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy
| | - Martina Mandarano
- Diagnostic Cytology and Histology Unit, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Rodolfo Corinaldesi
- Division of Neurosurgery, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Giulio Metro
- Medical Oncology, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Paolo Gorello
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100, Perugia, Italy
| | - Paolo Giovenali
- Diagnostic Cytology and Histology Unit, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Nunzia Cenci
- Division of Neurosurgery, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Corrado Castrioto
- Division of Neurosurgery, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Marco Lupattelli
- Division of Radiotherapy, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Fausto Roila
- Medical Oncology, S. Maria Della Misericordia Hospital, Piazzale Giorgio Menghini 8/9, 06132, Perugia, Italy
| | - Cristina Mecucci
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy
| | - Roberta La Starza
- Molecular Medicine Laboratory, Centro di Ricerche Emato-Oncologiche (C.R.E.O.), S. Maria Della Misericordia Hospital, University of Perugia, Piazzale Menghini 9, 06132, Perugia, Italy.
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193
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Ioannidis GS, Pigott LE, Iv M, Surlan-Popovic K, Wintermark M, Bisdas S, Marias K. Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas. Front Neurol 2023; 14:1249452. [PMID: 38046592 PMCID: PMC10690367 DOI: 10.3389/fneur.2023.1249452] [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: 06/28/2023] [Accepted: 10/31/2023] [Indexed: 12/05/2023] Open
Abstract
Objective This study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2-4) from 3 different centers. Methods To quantify the DSC perfusion signal two different mathematical modeling methods were used (Gamma fitting, leakage correction algorithms) considering the assumptions about the compartments contributing in the blood flow between the extra- and intra vascular space. Results The Mean slope of increase (MSI) and the K1 parameter of the bidirectional exchange model exhibited the highest performance with (ACC 74.3% AUROC 74.2%) and (ACC 75% AUROC 70.5%) respectively. Conclusion The proposed framework on DSC-MRI radiogenomics in gliomas has the potential of becoming a reliable diagnostic support tool exploiting the mathematical modeling of the DSC signal to characterize IDH mutation status through a more reproducible and standardized signal analysis scheme for facilitating clinical translation.
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Affiliation(s)
- Georgios S. Ioannidis
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science, Foundation for Research and Technology—Hellas (FORTH), Heraklion, Greece
| | - Laura Elin Pigott
- Institute of Health and Social Care, London South Bank University, London, United Kingdom
- Faculty of Brain Science, Queen Square Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery University College London, London, United Kingdom
| | - Michael Iv
- Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, CA, United States
| | - Katarina Surlan-Popovic
- Department of Radiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Department of Neuroradiology, University Medical Centre, Ljubljana, Slovenia
| | - Max Wintermark
- Department of Radiology, Division of Neuroimaging and Neurointervention, Stanford University, Stanford, CA, United States
| | - Sotirios Bisdas
- Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology, UCL, London, United Kingdom
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London, United Kingdom
| | - Kostas Marias
- Computational BioMedicine Laboratory (CBML), Institute of Computer Science, Foundation for Research and Technology—Hellas (FORTH), Heraklion, Greece
- Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Heraklion, Greece
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194
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Zhang Y, Zhang H, Zhang H, Ouyang Y, Su R, Yang W, Huang B. Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures. J Magn Reson Imaging 2023. [PMID: 37955154 DOI: 10.1002/jmri.29123] [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: 07/19/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/14/2023] Open
Abstract
BACKGROUND Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM remains uncertain. PURPOSE To construct and validate a demographic-MRI deep-learning radiomics nomogram (DDLRN) integrating demographic-MRI and DLR signatures to differentiate GBM from SBM preoperatively. STUDY TYPE Retrospective. POPULATION Two hundred and thirty-five patients with GBM (N = 115) or SBM (N = 120), randomly divided into a training cohort (90 GBM and 98 SBM) and a validation cohort (25 GBM and 22 SBM). FIELD STRENGTH/SEQUENCE Axial T2-weighted fast spin-echo sequence (T2WI), T2-weighted fluid-attenuated inversion recovery sequence (T2-FLAIR), and contrast-enhanced T1-weighted spin-echo sequence (CE-T1WI) using 1.5-T and 3.0-T scanners. ASSESSMENT The demographic-MRI signature was constructed with seven imaging features ("pool sign," "irregular ring sign," "regular ring sign," "intratumoral vessel sign," the ratio of the area of peritumoral edema to the enhanced tumor, the ratio of the lesion area on T2-FLAIR to CE-T1WI, and the tumor location) and demographic factors (age and sex). Based on multiparametric MRI, radiomics and deep-learning (DL) models, DLR signature, and DDLRN were developed and validated. STATISTICAL TESTS The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and support vector machine algorithm were applied for feature selection and construction of radiomics and DL models. RESULTS DDLRN showed the best performance in differentiating GBM from SBM with area under the curves (AUCs) of 0.999 and 0.947 in the training and validation cohorts, respectively. Additionally, the DLR signature (AUC = 0.938) outperformed the radiomics and DL models, and the demographic-MRI signature (AUC = 0.775) was comparable to the T2-FLAIR radiomics and DL models in the validation cohort (AUC = 0.762 and 0.749, respectively). DATA CONCLUSION DDLRN integrating demographic-MRI and DLR signatures showed excellent performance in differentiating GBM from SBM. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yuze Zhang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Hongbo Zhang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Hanwen Zhang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ying Ouyang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ruru Su
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Wanqun Yang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Biao Huang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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195
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Pour ME, Moghadam SG, Shirkhani P, Sahebkar A, Mosaffa F. Therapeutic cell-based vaccines for glioblastoma multiforme. Med Oncol 2023; 40:354. [PMID: 37952224 DOI: 10.1007/s12032-023-02220-5] [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: 07/08/2023] [Accepted: 10/12/2023] [Indexed: 11/14/2023]
Abstract
Glioblastoma multiforme (GBM), a highly aggressive tumor, poses significant challenges in achieving successful treatment outcomes. Conventional therapeutic modalities including surgery, radiation, and chemotherapy have demonstrated limited efficacy, primarily attributed to the complexities associated with drug delivery to the tumor site and tumor heterogeneity. To address this critical need for innovative therapies, the potential of cancer vaccines utilizing tumor cells and dendritic cells has been explored for GBM treatment. This article provides a comprehensive review of therapeutic vaccinations employing cell-based vaccine strategies for the management of GBM. A meticulous evaluation of 45 clinical trials involving more than 1500 participants revealed that cell-based vaccinations have exhibited favorable safety profiles with minimal toxicity. Moreover, these vaccines have demonstrated modest improvements in overall survival and progression-free survival among patients. However, certain limitations still persist. Notably, there is a need for advancements in the development of potent antigens to evoke immune responses, as well as the optimization of dosage regimens. Consequently, while cell-based vaccinations show promise as a potential therapeutic approach for GBM, further research is imperative to overcome the current limitations. The ultimate objective is to surmount these obstacles and establish cell-based vaccinations as a standard therapeutic modality for GBM.
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Affiliation(s)
- Mehrshad Ebrahim Pour
- School of Pharmacy, Department of Pharmaceutical Biotechnology, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Samin Ghorbani Moghadam
- School of Pharmacy, Department of Pharmaceutical Biotechnology, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Parian Shirkhani
- School of Pharmacy, Department of Pharmaceutical Biotechnology, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Amirhossein Sahebkar
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fatemeh Mosaffa
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
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196
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Hänsch L, Peipp M, Mastall M, Villars D, Myburgh R, Silginer M, Weiss T, Gramatzki D, Vasella F, Manz MG, Weller M, Roth P. Chimeric antigen receptor T cell-based targeting of CD317 as a novel immunotherapeutic strategy against glioblastoma. Neuro Oncol 2023; 25:2001-2014. [PMID: 37335916 PMCID: PMC10628943 DOI: 10.1093/neuonc/noad108] [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: 10/03/2022] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Chimeric antigen receptor (CAR) T cell therapy has proven to be successful against hematological malignancies. However, exploiting CAR T cells to treat solid tumors is more challenging for various reasons including the lack of suitable target antigens. Here, we identify the transmembrane protein CD317 as a novel target antigen for CAR T cell therapy against glioblastoma, one of the most aggressive solid tumors. METHODS CD317-targeting CAR T cells were generated by lentivirally transducing human T cells from healthy donors. The anti-glioma activity of CD317-CAR T cells toward various glioma cells was assessed in vitro in cell lysis assays. Subsequently, we determined the efficacy of CD317-CAR T cells to control tumor growth in vivo in clinically relevant mouse glioma models. RESULTS We generated CD317-specific CAR T cells and demonstrate strong anti-tumor activity against several glioma cell lines as well as primary patient-derived cells with varying CD317 expression levels in vitro. A CRISPR/Cas9-mediated knockout of CD317 protected glioma cells from CAR T cell lysis, demonstrating the target specificity of the approach. Silencing of CD317 expression in T cells by RNA interference reduced fratricide of engineered T cells and further improved their effector function. Using orthotopic glioma mouse models, we demonstrate the antigen-specific anti-tumor activity of CD317-CAR T cells, which resulted in prolonged survival and cure of a fraction of CAR T cell-treated animals. CONCLUSIONS These data reveal a promising role of CD317-CAR T cell therapy against glioblastoma, which warrants further evaluation to translate this immunotherapeutic strategy into clinical neuro-oncology.
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Affiliation(s)
- Lena Hänsch
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Matthias Peipp
- Division of Antibody-Based Immunotherapy, Department of Internal Medicine II, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
- Division of Antibody-based Immunotherapy, Christian-Albrechts-University, Kiel, Germany
| | - Maximilian Mastall
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Danielle Villars
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Renier Myburgh
- Department of Medical Oncology and Hematology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Manuela Silginer
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Dorothee Gramatzki
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Flavio Vasella
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
- Department of Neurosurgery, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Markus G Manz
- Department of Medical Oncology and Hematology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Patrick Roth
- Department of Neurology and Brain Tumor Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
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197
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McCord M, Jamshidi P, Thirunavu V, Santana-Santos L, Vormittag-Nocito E, Dittman D, Parker S, Baczkowski J, Jennings L, Walshon J, McCortney K, Galbraith K, Zhang H, Lukas RV, Stupp R, Dixit K, Kumthekar P, Heimberger AB, Snuderl M, Horbinski C. Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results. Acta Neuropathol Commun 2023; 11:175. [PMID: 37919784 PMCID: PMC10623846 DOI: 10.1186/s40478-023-01680-0] [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: 08/21/2023] [Accepted: 10/25/2023] [Indexed: 11/04/2023] Open
Abstract
MGMT promoter methylation testing is required for prognosis and predicting temozolomide response in gliomas. Accurate results depend on sufficient tumor cellularity, but histologic estimates of cellularity are subjective. We sought to determine whether driver mutation variant allelic frequency (VAF) could serve as a more objective metric for cellularity and identify possible false-negative MGMT samples. Among 691 adult-type diffuse gliomas, MGMT promoter methylation was assessed by pyrosequencing (N = 445) or DNA methylation array (N = 246); VAFs of TERT and IDH driver mutations were assessed by next generation sequencing. MGMT results were analyzed in relation to VAF. By pyrosequencing, 56% of all gliomas with driver mutation VAF ≥ 0.325 had MGMT promoter methylation, versus only 37% with VAF < 0.325 (p < 0.0001). The mean MGMT promoter pyrosequencing score was 19.3% for samples with VAF VAF ≥ 0.325, versus 12.7% for samples with VAF < 0.325 (p < 0.0001). Optimal VAF cutoffs differed among glioma subtypes (IDH wildtype glioblastoma: 0.12-0.18, IDH mutant astrocytoma: ~0.33, IDH mutant and 1p/19q co-deleted oligodendroglioma: 0.3-0.4). Methylation array was more sensitive for MGMT promoter methylation at lower VAFs than pyrosequencing. Microscopic examination tended to overestimate tumor cellularity when VAF was low. Re-testing low-VAF cases with methylation array and droplet digital PCR (ddPCR) confirmed that a subset of them had originally been false-negative. We conclude that driver mutation VAF is a useful quality assurance metric when evaluating MGMT promoter methylation tests, as it can help identify possible false-negative cases.
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Affiliation(s)
- Matthew McCord
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Pouya Jamshidi
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Vineeth Thirunavu
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Lucas Santana-Santos
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Erica Vormittag-Nocito
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - David Dittman
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Stephanie Parker
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Joseph Baczkowski
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Lawrence Jennings
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Jordain Walshon
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Kathleen McCortney
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Kristyn Galbraith
- Department of Pathology, New York University Langone Health, New York, USA
| | - Hui Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, USA
| | - Rimas V Lukas
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, USA
- Lou and Jean Malnati Brain Tumor Institute of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, USA
| | - Roger Stupp
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, USA
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, USA
- Lou and Jean Malnati Brain Tumor Institute of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, USA
| | - Karan Dixit
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, USA
- Lou and Jean Malnati Brain Tumor Institute of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, USA
| | - Priya Kumthekar
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, USA
- Lou and Jean Malnati Brain Tumor Institute of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, USA
| | - Amy B Heimberger
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, USA
- Lou and Jean Malnati Brain Tumor Institute of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, USA
| | - Matija Snuderl
- Department of Pathology, New York University Langone Health, New York, USA
| | - Craig Horbinski
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, USA.
- Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, USA.
- Lou and Jean Malnati Brain Tumor Institute of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, USA.
- Feinberg School of Medicine, Northwestern University, 303 E Superior Street, 6-518, Chicago, IL, 60611, USA.
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198
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Kneepkens E, Wolfs C, Wanders RG, Traneus E, Eekers D, Verhaegen F. Shoot-through proton FLASH irradiation lowers linear energy transfer in organs at risk for neurological tumors and is robust against density variations. Phys Med Biol 2023; 68:215020. [PMID: 37820687 DOI: 10.1088/1361-6560/ad0280] [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: 04/17/2023] [Accepted: 10/11/2023] [Indexed: 10/13/2023]
Abstract
Objective. The goal of the study was to test the hypothesis that shoot-through FLASH proton beams would lead to lower dose-averaged LET (LETD) values in critical organs, while providing at least equal normal tissue sparing as clinical proton therapy plans.Approach. For five neurological tumor patients, pencil beam scanning (PBS) shoot-through plans were made, using the maximum energy of 227 MeV and assuming a hypothetical FLASH protective factor (FPF) of 1.5. The effect of different FPF ranging from 1.2 to 1.8 on the clinical goals were also considered. LETDwas calculated for the clinical plan and the shoot-through plan, applying a 2 Gy total dose threshold (RayStation 8 A/9B and 9A-IonRPG). Robust evaluation was performed considering density uncertainty (±3% throughout entire volume).Main results.Clinical plans showed large LETDvariations compared to shoot-through plans and the maximum LETDin OAR is 1.2-8 times lower for the latter. Although less conformal, shoot-through plans met the same clinical goals as the clinical plans, for FLASH protection factors above 1.4. The FLASH shoot-through plans were more robust to density uncertainties with a maximum OAR D2%increase of 0.6 Gy versus 5.7 Gy in the clinical plans.Significance.Shoot-through proton FLASH beams avoid uncertainties in LETDdistributions and proton range, provide adequate target coverage, meet planning constraints and are robust to density variations.
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Affiliation(s)
- Esther Kneepkens
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Cecile Wolfs
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Roel-Germ Wanders
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Erik Traneus
- RaySearch Laboratories AB, SE-103 65, Stockholm, Sweden
| | - Danielle Eekers
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Frank Verhaegen
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
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199
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Islam S, Inglese M, Grech-Sollars M, Aravind P, Dubash S, Barwick TD, O'Neill K, Wang J, Saleem A, O'Callaghan J, Anchini G, Williams M, Waldman A, Aboagye EO. Feasibility of [ 18F]fluoropivalate hybrid PET/MRI for imaging lower and higher grade glioma: a prospective first-in-patient pilot study. Eur J Nucl Med Mol Imaging 2023; 50:3982-3995. [PMID: 37490079 PMCID: PMC10611885 DOI: 10.1007/s00259-023-06330-0] [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: 03/20/2023] [Accepted: 07/04/2023] [Indexed: 07/26/2023]
Abstract
PURPOSE MRI and PET are used in neuro-oncology for the detection and characterisation of lesions for malignancy to target surgical biopsy and to plan surgical resections or stereotactic radiosurgery. The critical role of short-chain fatty acids (SCFAs) in brain tumour biology has come to the forefront. The non-metabolised SCFA radiotracer, [18F]fluoropivalate (FPIA), shows low background signal in most tissues except eliminating organs and has appropriate human dosimetry. Tumour uptake of the radiotracer is, however, unknown. We investigated the uptake characteristics of FPIA in this pilot PET/MRI study. METHODS Ten adult glioma subjects were identified based on radiological features using standard-of-care MRI prior to any surgical intervention, with subsequent histopathological confirmation of glioma subtype and grade (lower-grade - LGG - and higher-grade - HGG - patients). FPIA was injected as an intravenous bolus injection (range 342-368 MBq), and dynamic PET and MRI data were acquired simultaneously over 66 min. RESULTS All patients tolerated the PET/MRI protocol. Three patients were reclassified following resection and histology. Tumour maximum standardised uptake value (SUVmax,60) increased in the order LGG (WHO grade 2) < HGG (WHO grade 3) < HGG (WHO grade 4). The net irreversible solute transfer, Ki, and influx rate constant, K1, were significantly higher in HGG (p < 0.05). Of the MRI variables studied, DCE-MRI-derived extravascular-and-extracellular volume fraction (ve) was high in tumours of WHO grade 4 compared with other grades (p < 0.05). SLC25A20 protein expression was higher in HGG compared with LGG. CONCLUSION Tumoural FPIA PET uptake is higher in HGG compared to LGG. This study supports further investigation of FPIA PET/MRI for brain tumour imaging in a larger patient population. CLINICAL TRIAL REGISTRATION Clinicaltrials.gov, NCT04097535.
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Affiliation(s)
- Shahriar Islam
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Marianna Inglese
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Matthew Grech-Sollars
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Preetha Aravind
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Suraiya Dubash
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Tara D Barwick
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Kevin O'Neill
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - James Wang
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Azeem Saleem
- Invicro Limited, Burlington Danes Building, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
- Hull York Medical School, University of Hull, Cottingham Road, Hull, HU6 7RX, UK
| | - James O'Callaghan
- Invicro Limited, Burlington Danes Building, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Giulio Anchini
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Matthew Williams
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Adam Waldman
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Eric O Aboagye
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
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200
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Kamp MA, von Sass C, Januzi D, Dibué M, Libourius K, Lawson McLean AC, Baumgarten P, Lawson McLean A, Dinc N, Senft CA. Frequency of social burden and underage children in neuro-oncological patients. J Cancer Res Clin Oncol 2023; 149:15911-15922. [PMID: 37679652 PMCID: PMC10620259 DOI: 10.1007/s00432-023-05338-1] [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: 06/29/2023] [Accepted: 08/24/2023] [Indexed: 09/09/2023]
Abstract
OBJECTIVE Brain tumours can cause significant burden for patients and their families, including physical, psychological, and social challenges. This burden can be particularly difficult for patients with malignant brain tumours and those with underage children. However, the frequency of social burden among neuro-oncological patients and the proportion of patients with underaged children is currently unknown. The aim of this retrospective study is to determine the frequency of social and family dysfunction among neuro-oncological patients, the percentage of such patients who have underage children, and to assess their associated burden. METHODS During a 22-month period, all brain tumour patients were asked to complete a short questionnaire that included epidemiological data, the EORTC-qlq-C30 and -BN20 questionnaire, and the distress thermometer. Data were collected and analysed using Prism 9 for macOS (version 9, GraphPad Prism). RESULTS Our analysis included 881 brain tumour patients, of which 540 were female. Median age was 61 years (ranging from 16 to 88 years). Of all patients, 228 suffered from malignant intracranial tumours. More than half of all patients and more than 65% of patients with malignant tumours reported that their illness or medical treatment interfered with their social activities and family life. Almost 30% of patients reported moderate or severe complaints. About 27% of all patients (and 31% of patients with malignancies) expressed moderate or major concerns that their family life could be disrupted. Among the patients with malignancies, 83.5% of patients had a total of 318 children at the time of tumour diagnosis, with a mean age of 33 ± 0.9. Of these patients with malignancies, 38 (17.9%) had a total of 56 underage children at the time of tumour diagnosis, and currently have 53 underage children. Patients with minor children had more financial worries but less interference of their disease with social activities, less psycho-oncological distress, and a more positive outlook into the future (each, p < 0.0001). They evaluated their general health status and quality of life in the week prior to their current appointment significantly better (each p < 0.0001). CONCLUSION Our study found that 17.9% of patients with malignant brain tumours have underage children. However, having underage children may actually be a positive resource for these patients, as they show lower distress values and better quality of life.
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Affiliation(s)
- Marcel A Kamp
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany.
| | - Christiane von Sass
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Donjetë Januzi
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Maxine Dibué
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Katharina Libourius
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Anna C Lawson McLean
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Peter Baumgarten
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Aaron Lawson McLean
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Nazife Dinc
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
| | - Christian A Senft
- Centre of Neuro-Oncology, Department of Neurosurgery, Jena University Hospital, Friedrich-Schiller-University Jena, Jena, Germany
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