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Niu H, Cao H, Liu X, Chen Y, Cheng Z, Long J, Li F, Sun C, Zuo P. The Significance of the Redox Gene in the Prognosis and Therapeutic Response of Glioma. Am J Clin Oncol 2024; 47:259-270. [PMID: 38318849 DOI: 10.1097/coc.0000000000001086] [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: 02/07/2024]
Abstract
OBJECTIVES Glioblastoma (GBM) is a fatal adult central nervous system tumor. Due to its high heterogeneity, the survival rate and prognosis of patients are poor. Thousands of people die of this disease every year all over the world. At present, the treatment of GBM is mainly through surgical resection and the combination of later drugs, radiotherapy, and chemotherapy. An abnormal redox system is involved in the malignant progression and treatment tolerance of glioma, which is the main reason for poor survival and prognosis. The construction of a GBM redox-related prognostic model may be helpful in improving the redox immunotherapy and prognosis of GBM. METHODS Based on glioma transcriptome data and clinical data from The Cancer Genome Atlas, databases, a risk model of redox genes was constructed by univariate and multivariate Cox analysis. The good prediction performance of the model was verified by the internal validation set of The Cancer Genome Atlas, and the external data of Chinese Glioma Genome Atlas. RESULTS The results confirmed that the higher the risk score, the worse the survival of patients. Age and isocitrate dehydrogenase status were significantly correlated with risk scores. The analysis of immune infiltration and immunotherapy found that there were significant differences in the immune score, matrix score, and ESTIMATE score between high and low-risk groups. reverse transcription polymerase chain reaction and immunohistochemical staining of glioma samples confirmed the expression of the hub gene. CONCLUSION Our study suggests that the 5 oxidative-related genes nitricoxidesynthase3 , NCF2 , VASN , FKBP1B , and TXNDC2 are hub genes, which may provide a reliable prognostic tool for glioma clinical treatment.
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Affiliation(s)
| | | | - Xin Liu
- Department of Molecular Diagnosis Center, The Third Affiliated Hospital of Kunming Medical University/Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming
| | | | | | - Jinyong Long
- Department of Surgery, Jinping County People's Hospital, Jinping
| | - Fuhua Li
- Department of Surgery, Jinping County People's Hospital, Jinping
| | - Chaoyan Sun
- Department of Emergency, Zhoukou Central Hospital, Zhoukou, China
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Hajri R, Nicod-Lalonde M, Hottinger AF, Prior JO, Dunet V. Prediction of Glioma Grade and IDH Status Using 18F-FET PET/CT Dynamic and Multiparametric Texture Analysis. Diagnostics (Basel) 2023; 13:2604. [PMID: 37568967 PMCID: PMC10417545 DOI: 10.3390/diagnostics13152604] [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: 06/21/2023] [Revised: 08/01/2023] [Accepted: 08/03/2023] [Indexed: 08/13/2023] Open
Abstract
Mutations in isocitrate dehydrogenase (IDH) represent an independent predictor of better survival in patients with gliomas. We aimed to assess grade and IDH mutation status in patients with untreated gliomas, by evaluating the respective value of 18F-FET PET/CT via dynamic and texture analyses. A total of 73 patients (male: 48, median age: 47) who underwent an 18F-FET PET/CT for initial glioma evaluation were retrospectively included. IDH status was available in 61 patients (20 patients with WHO grade 2 gliomas, 41 with grade 3-4 gliomas). Time-activity curve type and 20 parameters obtained from static analysis using LIFEx© v6.30 software were recorded. Respective performance was assessed using receiver operating characteristic curve analysis and stepwise multivariate regression analysis adjusted for patients' age and sex. The time-activity curve type and texture parameters derived from the static parameters showed satisfactory-to-good performance in predicting glioma grade and IDH status. Both time-activity curve type (stepwise OR: 101.6 (95% CI: 5.76-1791), p = 0.002) and NGLDM coarseness (stepwise OR: 2.08 × 1043 (95% CI: 2.76 × 1012-1.57 × 1074), p = 0.006) were independent predictors of glioma grade. No independent predictor of IDH status was found. Dynamic and texture analyses of 18F-FET PET/CT have limited predictive value for IDH status when adjusted for confounding factors. However, they both help predict glioma grade.
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Affiliation(s)
- Rami Hajri
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland;
| | - Marie Nicod-Lalonde
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland; (M.N.-L.); (J.O.P.)
| | - Andreas F. Hottinger
- Department of Neurology, Lausanne University Hospital, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland;
- Lukas Lundin & Family Brain Tumor Research Center, Lausanne University Hospital, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland
| | - John O. Prior
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland; (M.N.-L.); (J.O.P.)
| | - Vincent Dunet
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland;
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Qing Z, Xiaoai K, Caiqiang X, Shenglin L, Xiaoyu H, Bin Z, Junlin Z. Nomogram for predicting early recurrence in patients with high-grade gliomas. World Neurosurg 2022; 164:e619-e628. [PMID: 35589036 DOI: 10.1016/j.wneu.2022.05.039] [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: 02/19/2022] [Revised: 05/06/2022] [Accepted: 05/07/2022] [Indexed: 10/18/2022]
Abstract
OBJECTIVE To develop a nomogram to predict early recurrence of high-grade glioma (HGG) based on clinical pathology, genetic factors and MRI parameters. METHODS 154 patients with HGG were classified into recurrence and non-recurrence groups based on the pathological diagnosis and RANO criteria. Clinical pathology information included age, sex, preoperative Karnofsky performance status (KPS) scores,grade, and cell proliferation index (Ki-67). Gene information included P53, IDH1, MGMT, and TERT expression status. All patients underwent baseline MRIs before treatment, including T1WI, T2WI, T1C, Flair, and DWI examinations. Tumor location, single/multiple tumors, tumor diameter, peritumoral edema, necrotic cyst, hemorrhage, average apparent diffusion coefficient(ADC) value, and minimum ADC values were evaluated. Univariate and multivariate logistic regression analyses were used to determine the predictors of early recurrence and build nomogram. RESULTS Univariate analysis showed that the number of tumors (OR, 0.258; 95% CI: 0.104, 0.639; P = 0.003) and peritumoral edema (OR, 0.965; 95% CI 0.942, 0.988; P = 0.003; mean in the recurrence group 22.04±17.21 mm; mean in the non-recurrence group 14.22±12.84 mm) were statistically significantly different in patients with early recurrence. Genetic factors associated with early recurrence included IDH1 (OR, 4.405; 95% CI 1.874, 10.353; P= 0.001), and MGMT (OR, 2.389; 95% CI 1.234, 4.628; P= 0.010). Multivariate logistic regression analysis revealed that the number of tumors (OR, 0.227; 95% CI 0.084, 0.616; P = 0.004), peritumoral edema (OR, 0.969; 95% CI 0.945, 0.993; P = 0.013), and IDH1 (OR, 4.200; 95% CI 1.602, 10.013; P= 0.004) were independent risk factors for early recurrence. The nomogram showed the highest net benefit when the threshold probability was less than 60%. CONCLUSION A nomogram prediction model can effectively aid in clinical treatment decisions for patients with newly diagnosed HGG .
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Affiliation(s)
- Zhou Qing
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Second Clinical School,Lanzhou University, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China
| | - Ke Xiaoai
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China
| | - Xue Caiqiang
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Second Clinical School,Lanzhou University, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China
| | - Li Shenglin
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Second Clinical School,Lanzhou University, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China
| | - Huang Xiaoyu
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Second Clinical School,Lanzhou University, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China
| | - Zhang Bin
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Second Clinical School,Lanzhou University, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China
| | - Zhou Junlin
- Department of Radiology, Lanzhou University Second Hospital, Gansu, China; Key Laboratory of Medical Imaging of Gansu Province, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence,China.
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Hasanau T, Pisarev E, Kisil O, Nonoguchi N, Le Calvez-Kelm F, Zvereva M. Detection of TERT Promoter Mutations as a Prognostic Biomarker in Gliomas: Methodology, Prospects, and Advances. Biomedicines 2022; 10:728. [PMID: 35327529 PMCID: PMC8945783 DOI: 10.3390/biomedicines10030728] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/13/2022] [Accepted: 03/17/2022] [Indexed: 11/16/2022] Open
Abstract
This article reviews the existing approaches to determining the TERT promoter mutational status in patients with various tumoral diseases of the central nervous system. The operational characteristics of the most common methods and their transferability in medical practice for the selection or monitoring of personalized treatments based on the TERT status and other related molecular biomarkers in patients with the most common tumors, such as glioblastoma, oligodendroglioma, and astrocytoma, are compared. The inclusion of new molecular markers in the course of CNS clinical management requires their rapid and reliable assessment. Availability of molecular evaluation of gliomas facilitates timely decisions regarding patient follow-up with the selection of the most appropriate treatment protocols. Significant progress in the inclusion of molecular biomarkers for their subsequent clinical application has been made since 2016 when the WHO CNS classification first used molecular markers to classify gliomas. In this review, we consider the methodological approaches used to determine mutations in the promoter region of the TERT gene in tumors of the central nervous system. In addition to classical molecular genetical methods, other methods for determining TERT mutations based on mass spectrometry, magnetic resonance imaging, next-generation sequencing, and nanopore sequencing are reviewed with an assessment of advantages and disadvantages. Beyond that, noninvasive diagnostic methods based on the determination of the mutational status of the TERT promoter are discussed.
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Affiliation(s)
- Tsimur Hasanau
- Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia;
| | - Eduard Pisarev
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119234 Moscow, Russia;
- Chair of Chemistry of Natural Compounds, Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Olga Kisil
- Gause Institute of New Antibiotics, 119021 Moscow, Russia;
| | - Naosuke Nonoguchi
- Department of Neurosurgery, Osaka Medical and Pharmaceutical University, Takatsuki 569-8686, Japan;
| | - Florence Le Calvez-Kelm
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), 69372 Lyon, France;
| | - Maria Zvereva
- Chair of Chemistry of Natural Compounds, Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia
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Qu CX, Ji HM, Shi XC, Bi H, Zhai LQ, Han DW. Characteristics of the isocitrate dehydrogenase gene and telomerase reverse transcriptase promoter mutations in gliomas in Chinese patients. Brain Behav 2020; 10:e01583. [PMID: 32146731 PMCID: PMC7177565 DOI: 10.1002/brb3.1583] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/10/2020] [Accepted: 02/13/2020] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVES To explore the characteristics of IDH and TERT promoter mutations in gliomas in Chinese patients. METHODS A total of 124 Chinese patients with gliomas were enrolled to study the frequencies of mutations in isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp). Among the 124 patients, 59 patients were enrolled to study the classification of gliomas based on mutations in IDH and TERTp. RESULTS Isocitrate dehydrogenase mutations are positively correlated with a good prognosis but mutations in TERTp cannot predict prognoses independently. The combined analysis of the mutations of IDH and TERTp can predict the prognosis more accurately. Patients with IDH and TERTp glioma mutations have the best prognosis, followed by only IDH mutation patients and only TERTp mutation patients, which have the worst prognosis. IDH and TERTp mutations occur frequently in males, younger patients or lower-grade patients. In contrast, only TERTp mutations occur frequently in females, older patients or higher-grade patients. CONCLUSIONS Patients with IDH and TERTp glioma mutations have the best prognosis, and only IDH mutation patients and only TERTp mutation patients have the worst prognosis. Moreover, the molecular classification of gliomas by mutations of IDH and TERTp is not suitable for pediatric patients.
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Affiliation(s)
- Chong-Xiao Qu
- Department of Pathology, Shanxi Provincial People's Hospital, Taiyuan, China.,Department of Pathophysiology, Basic Medical Science, Shanxi Medical University, Taiyuan, China
| | - Hong-Ming Ji
- Department of Neurosurgery, Shanxi Provincial People's Hospital, Taiyuan, China
| | - Xiang-Cheng Shi
- Department of Pathology, Shanxi Provincial People's Hospital, Taiyuan, China
| | - Hong Bi
- Department of Pathology, Shanxi Provincial People's Hospital, Taiyuan, China
| | - Li-Qin Zhai
- Department of Pathology, Shanxi Provincial People's Hospital, Taiyuan, China
| | - De-Wu Han
- Department of Pathophysiology, Basic Medical Science, Shanxi Medical University, Taiyuan, China
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