Journal articles on the topic 'Classification des gliomes'
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Taillibert, Sophie, Marta Pedretti, and Marc Sanson. "Classification actuelle des gliomes." La Presse Médicale 33, no. 18 (October 2004): 1274–77. http://dx.doi.org/10.1016/s0755-4982(04)98906-3.
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Figarella-Branger, D., C. Colin, B. Coulibaly, B. Quilichini, A. Maues De Paula, C. Fernandez, and C. Bouvier. "Classification histologique et moléculaire des gliomes." Revue Neurologique 164, no. 6-7 (June 2008): 505–15. http://dx.doi.org/10.1016/j.neurol.2008.03.011.
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Idbaih, A., Y. Marie, C. Lucchesi, G. Pierron, E. Manié, V. Raynal, K. Hoang-Xuan, et al. "Vers une classification moléculaire pronostique des gliomes." Revue Neurologique 163, no. 1 (January 2007): 21–23. http://dx.doi.org/10.1016/s0035-3787(07)90373-2.
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Taillibert, Sophie, Marta Pedretti, and Marc Sanson. "Génétique des gliomes, vers une classification moléculaire." La Presse Médicale 33, no. 18 (October 2004): 1268–73. http://dx.doi.org/10.1016/s0755-4982(04)98905-1.
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Brouland, Jean Philippe, and Andreas F. Hottinger. "Nouvelle classification OMS 2016 des gliomes : quels changements ?" Revue Médicale Suisse 13, no. 579 (2017): 1805–9. http://dx.doi.org/10.53738/revmed.2017.13.579.1805.
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Stella, I., M. Helleringer, A. Joud, P. Chastagner, and O. Klein. "Gliomes des voies optiques et hypothalamo-chiasmatiques de l’enfant : proposition d’une classification à usage neurochirurgical." Neurochirurgie 65, no. 2-3 (April 2019): 112. http://dx.doi.org/10.1016/j.neuchi.2019.03.024.
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Lubrano, V., E. Uro-Coste, P. Bousquet, C. Pierroux, M. B. Delisle, and J. Lagarrigue. "Étude histo-moléculaire de 26 gliomes de haut grade : impact sur la classification et le pronostic." Neurochirurgie 52, no. 5 (November 2006): 478. http://dx.doi.org/10.1016/s0028-3770(06)71277-2.
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Nioche, C., M. Soret, E. Gontier, I. Buvat, and G. Bonardel. "Évaluation de la classification des gliomes en TEP 18F-FDOPA obtenue à partir d’un critère quantitatif pour des acquisitions statiques ou dynamiques." Médecine Nucléaire 37, no. 5 (May 2013): 166–67. http://dx.doi.org/10.1016/j.mednuc.2013.03.122.
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Faraji-Rad, Mohammad. "Epidemiological Study of Molecular and Genetic Classification in Adult Diffuse Glioma." International Journal of Surgery & Surgical Techniques 6, no. 2 (2022): 1–5. http://dx.doi.org/10.23880/ijsst-16000171.
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Background: Mutations in isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) are frequent in lowgrade and high-grade gliomas. However, the diagnostic criteria, in particular for gliomas, are highly various. The aim of our study was to establish genetic profiles for mutation and calcification of diffuse gliomas and to evaluate their predictive factors. Methods: We estimate the different clinical and molecular characterization between IDH1, IDH2 mutant gliomas, p53, ATRX and 1p19q. In addition, whole-transcriptome sequencing and DNA extraction data were used to evaluate the distribution of genetic changes in IDH1 and IDH2 mutant gliomas in a Iranian high grade glioma. Results: Between 2016-2019, among 53 gliomas in our study, 29 cases (54.7% %) harbored an IDH1,2 mutation, 21 cases (39.6 %) harbored an p53 mutation and 19 cases (35.8 %) harbored an ATRX. In addition, 1p19q co-deletion mutation was found in 7 cases (12.2%). We found that IDH1 and IDH2 are mutually entirely in gliomas. There was no significant relation between histopathology, tumor location and clinical finding with diagnosed mutations. Conclusion: Our study discloses an associated distinction between IDH1 and IDH2 mutant gliomas nearly in half of patients, followed by p53. These mutations should be reviewed separately because their differences could have indication for the diagnosis and treatment of IDH1/2 mutant gliomas.
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Zhang, W., J. Zhao, D. Guo, W. Zhong, J. Shu, and Y. Luo. "Rôle de l’IRM de susceptibilité magnétique dans la mise en évidence de produits de dégradation de l’hémoglobine intratumoraux et dans la classification des gliomes." Journal de Radiologie 91, no. 4 (April 2010): 485–90. http://dx.doi.org/10.1016/s0221-0363(10)70063-9.
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Zaragori, T., M. Ginet, V. Roch, R. Grignon, Z. Lamiral, G. Gauchotte, L. Taillandier, P. Y. Marie, L. Imbert, and A. Verger. "L’intégration des paramètres dynamiques dans l’analyse des examens TEP à la 18F-FDOPA permet d’améliorer la prédiction de la classification WHO 2016 des gliomes." Médecine Nucléaire 43, no. 2 (March 2019): 181–82. http://dx.doi.org/10.1016/j.mednuc.2019.01.022.
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Kwikima, Ugumba. "GLIOMA-04 BRIDGING THE GAP ON ADULT GLIOMA IMAGING, DIAGNOSIS AND FOLLOW UP IN SUB-SAHARAN AFRICA." Neuro-Oncology Advances 5, Supplement_4 (October 31, 2023): iv1. http://dx.doi.org/10.1093/noajnl/vdad121.003.
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Abstract Cerebral Gliomas are the most common and devastating primary brain tumors. Prior to 2016 WHO CNS tumor classification update, the grading of gliomas, mainly relied on histological features, including cellularity, nuclear atypia, mitotic activity, vascularity, and necrosis, observed on light microscopy with the aid of immunohistochemistry. A number of studies confirmed that diffuse gliomas demonstrates different growth pattern, clinical behavior, and prognostication based on their genomic alterations, these findings necessitated incorporation of molecular subtypes in glioma classification, and leads to 2016 WHO CNS tumors Classification update. Introduction of molecular criteria into the classification of gliomas has given rise to interesting, wide-ranging implications regarding glioma management. In the current classification, all diffuse gliomas have been grouped based on their growth pattern, clinical behavior, and specifically sharing of the mutational state of the gene that codes for isocitrate dehydrogenase (IDH) in its isoforms (IDH1 and IDH2). Regardless of grade, the first phase in glioma molecular characterization is IDH testing. Mutations in IDH1 and IDH2 are associated with significant increase in progression free survival and overall survival. Immunohistochemistry, Molecular subtyping, Both FISH and genetic sequencing have significant implications in gliomas management and clinical outcome, yet they are not available in our low resource settings. Advanced MRI techniques (DTI, MR Perfussion, MR Spectroscopy, and Functional MRI) have a significant impact in presurgical planning and follow up of glioma patients after surgery and chemo radiation treatment. Radiographic findings can bridge the gap on accurate glioma diagnosis in sub-Saharan Africa through predicting Glioma Molecular subtypes based on clinical presentation and utilizing conventional MRI as a radio genomic tool. Also to emphasis in the utilization of available advanced MRI techniques (DTI, MR Perfussion, and MR spectroscopy) for presurgical planning and follow up of patients after Glioma treatment.
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Cinarer, Gokalp, and Bulent Gursel Emiroglu. "Classification of brain tumours using radiomic features on MRI." New Trends and Issues Proceedings on Advances in Pure and Applied Sciences, no. 12 (April 30, 2020): 80–90. http://dx.doi.org/10.18844/gjpaas.v0i12.4989.
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Glioma is one of the most common brain tumours among the diagnoses of existing brain tumours. Glioma grades are important factors that should be known in the treatment of brain tumours. In this study, the radiomic features of gliomas were analysed and glioma grades were classified by Gaussian Naive Bayes algorithm. Glioma tumours of 121 patients of Grade II and Grade III were examined. The glioma tumours were segmented with the Grow Cut Algorithm and the 3D feature of tumour magnetic resonance imaging images were obtained with the 3D Slicer programme. The obtained quantitative values were statistically analysed with Spearman and Mann–Whitney U tests and 21 features with statistically significant properties were selected from 107 features. The results showed that the best performing among the algorithms was Gaussian Naive Bayes algorithm with 80% accuracy. Machine learning and feature selection techniques can be used in the analysis of gliomas as well as pathological evaluations in glioma grading processes.
Keywords: Radiomics, glioma, naive bayes.
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Pitarch, Carla, Vicent Ribas, and Alfredo Vellido. "AI-Based Glioma Grading for a Trustworthy Diagnosis: An Analytical Pipeline for Improved Reliability." Cancers 15, no. 13 (June 27, 2023): 3369. http://dx.doi.org/10.3390/cancers15133369.
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Glioma is the most common type of tumor in humans originating in the brain. According to the World Health Organization, gliomas can be graded on a four-stage scale, ranging from the most benign to the most malignant. The grading of these tumors from image information is a far from trivial task for radiologists and one in which they could be assisted by machine-learning-based decision support. However, the machine learning analytical pipeline is also fraught with perils stemming from different sources, such as inadvertent data leakage, adequacy of 2D image sampling, or classifier assessment biases. In this paper, we analyze a glioma database sourced from multiple datasets using a simple classifier, aiming to obtain a reliable tumor grading and, on the way, we provide a few guidelines to ensure such reliability. Our results reveal that by focusing on the tumor region of interest and using data augmentation techniques we significantly enhanced the accuracy and confidence in tumor classifications. Evaluation on an independent test set resulted in an AUC-ROC of 0.932 in the discrimination of low-grade gliomas from high-grade gliomas, and an AUC-ROC of 0.893 in the classification of grades 2, 3, and 4. The study also highlights the importance of providing, beyond generic classification performance, measures of how reliable and trustworthy the model’s output is, thus assessing the model’s certainty and robustness.
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Kalidindi, Navya, Rosemarylin Or, Sam Babak, and Warren Mason. "Molecular Classification of Diffuse Gliomas." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 47, no. 4 (January 10, 2020): 464–73. http://dx.doi.org/10.1017/cjn.2020.10.
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ABSTRACT:Technological advances in the field of molecular genetics have improved the ability to classify brain tumors into subgroups with distinct clinical features and important therapeutic implications. The World Health Organization’s newest update on classification of gliomas (2016) incorporated isocitrate dehydrogenase 1 and 2 mutations, ATRX loss, 1p/19q codeletion status, and TP53 mutations to allow for improved classification of glioblastomas, low-grade and anaplastic gliomas. This paper reviews current advances in the understanding of diffuse glioma classification and the impact of molecular markers and DNA methylation studies on survival of patients with these tumors. We also discuss whether the classification and grading of diffuse gliomas should be based on histological findings, molecular markers, or DNA methylation subgroups in future iterations of the classification system.
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Hervey-Jumper, Shawn L., Jing Li, Joseph A. Osorio, Darryl Lau, Annette M. Molinaro, Arnau Benet, and Mitchel S. Berger. "Surgical assessment of the insula. Part 2: validation of the Berger-Sanai zone classification system for predicting extent of glioma resection." Journal of Neurosurgery 124, no. 2 (February 2016): 482–88. http://dx.doi.org/10.3171/2015.4.jns1521.
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OBJECT Though challenging, maximal safe resection of insular gliomas enhances overall and progression-free survival and deters malignant transformation. Previously published reports have shown that surgery can be performed with low morbidity. The authors previously described a Berger-Sanai zone classification system for insular gliomas. Using a subsequent dataset, they undertook this study to validate this zone classification system for predictability of extent of resection (EOR) in patients with insular gliomas. METHODS The study population included adults who had undergone resection of WHO Grade II, III, or IV insular gliomas. In accordance with our prior published report, tumor location was classified according to the Berger-Sanai quadrant-style classification system into Zones I through IV. Interobserver variability was analyzed using a cohort of newly diagnosed insular gliomas and independent classification scores given by 3 neurosurgeons at various career stages. Glioma volumes were analyzed using FLAIR and T1-weighted contrast-enhanced MR images. RESULTS One hundred twenty-nine procedures involving 114 consecutive patients were identified. The study population from the authors’ previously published experience included 115 procedures involving 104 patients. Thus, the total experience included 244 procedures involving 218 patients with insular gliomas treated at the authors’ institution. The most common presenting symptoms were seizure (68.2%) and asymptomatic recurrence (17.8%). WHO Grade II glioma histology was the most common (54.3%), followed by Grades III (34.1%) and IV (11.6%). The median tumor volume was 48.5 cm3. The majority of insular gliomas were located in the anterior portion of the insula with 31.0% in Zone I, 10.9% in Zone IV, and 16.3% in Zones I+IV. The Berger-Sanai zone classification system was highly reliable, with a kappa coefficient of 0.857. The median EOR for all zones was 85%. Comparison of EOR between the current and prior series showed no change and Zone I gliomas continue to have the highest median EOR. Short- and long-term neurological complications remain low, and zone classification correlated with short-term complications, which were highest in Zone I and in Giant insular gliomas. CONCLUSIONS The previously proposed Berger-Sanai classification system is highly reliable and predictive of insular glioma EOR and morbidity.
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Hauser, Peter. "Classification and Treatment of Pediatric Gliomas in the Molecular Era." Children 8, no. 9 (August 27, 2021): 739. http://dx.doi.org/10.3390/children8090739.
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The overall survival of pediatric gliomas varies over a wide spectrum depending on the tumor grade. Low-grade gliomas have an excellent long-term survival, with a possible burden of surgery, irradiation, and chemotherapy; in contrast, high-grade gliomas generally have a short-term, devastating lethal outcome. Recent advances in understanding their molecular background will transform the classification and therapeutic approaches of pediatric gliomas. Molecularly targeted treatments may acquire a leading role in the primary treatment of low-grade gliomas and may provide alternative therapeutic strategies for high-grade glioma cases in the attempt to avoid the highly unsuccessful conventional therapeutic approaches. This review aims to overview this progress.
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Mohamed, Ali Ahmed, Rakan Alshaibi, Steven Faragalla, Youssef Mohamed, and Brandon Lucke-Wold. "Updates on management of gliomas in the molecular age." World Journal of Clinical Oncology 15, no. 2 (February 24, 2024): 178–94. http://dx.doi.org/10.5306/wjco.v15.i2.178.
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Gliomas are primary brain tumors derived from glial cells of the central nervous system, afflicting both adults and children with distinct characteristics and therapeutic challenges. Recent developments have ushered in novel clinical and molecular prognostic factors, reshaping treatment paradigms based on classification and grading, determined by histological attributes and cellular lineage. This review article delves into the diverse treatment modalities tailored to the specific grades and molecular classifications of gliomas that are currently being discussed and used clinically in the year 2023. For adults, the therapeutic triad typically consists of surgical resection, chemotherapy, and radiotherapy. In contrast, pediatric gliomas, due to their diversity, require a more tailored approach. Although complete tumor excision can be curative based on the location and grade of the glioma, certain non-resectable cases demand a chemotherapy approach usually involving, vincristine and carboplatin. Additionally, if surgery or chemotherapy strategies are unsuccessful, Vinblastine can be used. Despite recent advancements in treatment methodologies, there remains a need of exploration in the literature, particularly concerning the efficacy of treatment regimens for isocitrate dehydrogenase type mutant astrocytomas and fine-tuned therapeutic approaches tailored for pediatric cohorts. This review article explores into the therapeutic modalities employed for both adult and pediatric gliomas in the context of their molecular classification.
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Billard, P., C. Guerriau, C. Carpentier, F. Juillard, N. Grandin, P. Lomonte, P. Kantapareddy, et al. "OS02.6.A The TeloDIAG: How telomeric parameters can help in glioma rapid diagnosis and liquid biopsies approaches." Neuro-Oncology 23, Supplement_2 (September 1, 2021): ii5—ii6. http://dx.doi.org/10.1093/neuonc/noab180.015.
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Abstract BACKGROUND The integration of molecular markers into the WHO 2016 classification has clarified the complex diagnosis of gliomas. Among these biomarkers, the TERT promoter mutation and the loss of ATRX (ATRX loss) are mutually exclusive alterations associated with re-activation of telomerase or alternative lengthening of telomeres (ALT), respectively. Strangely, 25% of gliomas display neither or both these alterations, a situation referred to as abnormal telomere maintenance mechanism (aTMM). MATERIAL AND METHODS To investigate the TMM actually involved in gliomas, the C-circle (CC) assay was adapted to tumor (FFPE and frozen) samples. RESULTS We constructed a CC-based algorithm able to identify the TMM of 284 gliomas with either TERT or ATRX alteration, with a sensitivity of 100% and a specificity of 97.3%, and succeeded in deciphering the TMM involved in 122 aTMM gliomas. Additionally, the combination of the TMM, the mutational status of the Isocitrate dehydrogenase 1/2 (IDH) gene, and the histological grading was used as base for a new classification: TeloDIAG. Six subtypes are defined in this classification: tOD, tLGA, tGBM_IDHmt, tGBM, and tAIV, corresponding to oligodendroglioma, IDHmt low grade astrocytoma, IDHmt glioblastoma, and IDHwt glioblastoma, respectively, the last class gathers ALT+ IDHwt glioma. The TeloDIAG diagnosis is 99% concordant with the WHO classification for glioma displaying typical molecular characteristics (N=312). It modified the classification of 38% (N=156) discordant tumors, such as IDHwt Astrocytoma, aTMM tumors, or gliomas with unexpected TMM (e.g. TERTwt oligodendroglioma, ATRX loss GBM). Interestingly, 20% (N=69) of TERTwt, ATRXwt, or IDHwt GBM were actually tAIV, which is remarkable as tAIV-glioma patients’ survival tended to be longer (21.2 months) than tGBM patients’ survival (16.5 months). Importantly, CC in blood sampled from IDHmt astrocytoma patients was detected with a sensitivity of 56% and a specificity of 95% (N = 206). CONCLUSION In sum, the TeloDIAG is a new, simple, and efficient tool helping in glioma diagnosis and a promising option for liquid biopsy
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Im, Sanghyuk, Jonghwan Hyeon, Eunyoung Rha, Janghyeon Lee, Ho-Jin Choi, Yuchae Jung, and Tae-Jung Kim. "Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning." Sensors 21, no. 10 (May 17, 2021): 3500. http://dx.doi.org/10.3390/s21103500.
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Diffuse gliomas are the most common primary brain tumors and they vary considerably in their morphology, location, genetic alterations, and response to therapy. In 2016, the World Health Organization (WHO) provided new guidelines for making an integrated diagnosis that incorporates both morphologic and molecular features to diffuse gliomas. In this study, we demonstrate how deep learning approaches can be used for an automatic classification of glioma subtypes and grading using whole-slide images that were obtained from routine clinical practice. A deep transfer learning method using the ResNet50V2 model was trained to classify subtypes and grades of diffuse gliomas according to the WHO’s new 2016 classification. The balanced accuracy of the diffuse glioma subtype classification model with majority voting was 0.8727. These results highlight an emerging role of deep learning in the future practice of pathologic diagnosis.
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Pisapia, David J. "The Updated World Health Organization Glioma Classification: Cellular and Molecular Origins of Adult Infiltrating Gliomas." Archives of Pathology & Laboratory Medicine 141, no. 12 (December 1, 2017): 1633–45. http://dx.doi.org/10.5858/arpa.2016-0493-ra.
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Context.— In the recently updated World Health Organization (WHO) classification of central nervous system tumors, our concept of infiltrating gliomas as a molecular dichotomy between oligodendroglial and astrocytic tumors has been codified. Advances in animal models of glioma and a wealth of sophisticated molecular analyses of human glioma tissue have led to a greater understanding of some of the biologic underpinnings of gliomagenesis. Objective.— To review our understanding of gliomagenesis in the setting of the recently updated WHO classification of central nervous system tumors. Topics addressed include a summary of an updated diagnostic schema for infiltrating gliomas, the crucial importance of isocitrate dehydrogenase mutations, candidate cells of origin for gliomas, environmental and other posited contributing factors to gliomagenesis, and the possible role of chromatin topology in setting the stage for gliomagenesis. Data Sources.— We conducted a primary literature search using PubMed. Conclusions.— With multidimensional molecular data sets spanning increasingly larger numbers of patients with infiltrating gliomas, our understanding of the disease at the point of surgical resection has improved dramatically and this understanding is reflected in the updated WHO classification. Animal models have demonstrated a diversity of candidates for glioma cells of origin, but crucial questions remain, including the role of neural stem cells, more differentiated progenitor cells, and glioma stem cells. At this stage the increase in data generated from human samples will hopefully inform the creation of newer animal models that will recapitulate more accurately the diversity of gliomas and provide novel insights into the biologic mechanisms underlying tumor initiation and progression.
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Tom, Martin C., Daniel P. Cahill, Jan C. Buckner, Jörg Dietrich, Michael W. Parsons, and Jennifer S. Yu. "Management for Different Glioma Subtypes: Are All Low-Grade Gliomas Created Equal?" American Society of Clinical Oncology Educational Book, no. 39 (May 2019): 133–45. http://dx.doi.org/10.1200/edbk_238353.
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Following the identification of key molecular alterations that provided superior prognostication and led to the updated 2016 World Health Organization (WHO) Central Nervous System (CNS) Tumor Classification, the understanding of glioma behavior has rapidly evolved. Mutations in isocitrate dehydrogenase (IDH) 1 and 2 are present in the majority of adult grade 2 and 3 gliomas, and when used in conjunction with 1p/19q codeletion for classification, the prognostic distinction between grade 2 versus grade 3 is diminished. As such, the previously often used term of “low-grade glioma,” which referred to grade 2 gliomas, has now been replaced by the phrase “lower-grade glioma” to encompass both grade 2 and 3 tumors. Additional molecular characterization is ongoing to even further classify this heterogeneous group of tumors. With such a colossal shift in the understanding of lower-grade gliomas, management of disease is being redefined in the setting of emerging molecular-genetic biomarkers. In this article, we review recent progress and future directions regarding the surgical, radiotherapeutic, chemotherapeutic, and long-term management of adult lower-grade gliomas.
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Tran, Paul Minh Huy, Lynn Kim Hoang Tran, Khaled bin Satter, Sharad Purohit, John Nechtman, Diane I. Hopkins, Bruno dos Santos, et al. "Retrospective Validation of a 168-Gene Expression Signature for Glioma Classification on a Single Molecule Counting Platform." Cancers 13, no. 3 (January 25, 2021): 439. http://dx.doi.org/10.3390/cancers13030439.
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Gene expression profiling has been shown to be comparable to other molecular methods for glioma classification. We sought to validate a gene-expression based glioma classification method. Formalin-fixed paraffin embedded tissue and flash frozen tissue collected at the Augusta University (AU) Pathology Department between 2000–2019 were identified and 2 mm cores were taken. The RNA was extracted from these cores after deparaffinization and bead homogenization. One hundred sixty-eight genes were evaluated in the RNA samples on the nCounter instrument. Forty-eight gliomas were classified using a supervised learning algorithm trained by using data from The Cancer Genome Atlas. An ensemble of 1000 linear support vector models classified 30 glioma samples into TP1 with classification confidence of 0.99. Glioma patients in TP1 group have a poorer survival (HR (95% CI) = 4.5 (1.3–15.4), p = 0.005) with median survival time of 12.1 months, compared to non-TP1 groups. Network analysis revealed that cell cycle genes play an important role in distinguishing TP1 from non-TP1 cases and that these genes may play an important role in glioma survival. This could be a good clinical pipeline for molecular classification of gliomas.
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Gisina, Alisa, Irina Kholodenko, Yan Kim, Maxim Abakumov, Alexey Lupatov, and Konstantin Yarygin. "Glioma Stem Cells: Novel Data Obtained by Single-Cell Sequencing." International Journal of Molecular Sciences 23, no. 22 (November 17, 2022): 14224. http://dx.doi.org/10.3390/ijms232214224.
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Glioma is the most common type of primary CNS tumor, composed of cells that resemble normal glial cells. Recent genetic studies have provided insight into the inter-tumoral heterogeneity of gliomas, resulting in the updated 2021 WHO classification of gliomas. Thorough understanding of inter-tumoral heterogeneity has already improved the prognosis and treatment outcomes of some types of gliomas. Currently, the challenge for researchers is to study the intratumoral cell heterogeneity of newly defined glioma subtypes. Cancer stem cells (CSCs) present in gliomas and many other tumors are an example of intratumoral heterogeneity of great importance. In this review, we discuss the modern concept of glioma stem cells and recent single-cell sequencing-driven progress in the research of intratumoral glioma cell heterogeneity. The particular emphasis was placed on the recently revealed variations of the cell composition of the subtypes of the adult-type diffuse gliomas, including astrocytoma, oligodendroglioma and glioblastoma. The novel data explain the inconsistencies in earlier glioma stem cell research and also provide insight into the development of more effective targeted therapy and the cell-based immunotherapy of gliomas. Separate sections are devoted to the description of single-cell sequencing approach and its role in the development of cell-based immunotherapies for glioma.
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Takei, H., J. Shinoda, S. Ikuta, T. Maruyama, Y. Muragaki, T. Kawasaki, Y. Ikegame, et al. "P14.01 Differential diagnosis of IDH mutant/IDH wildtype of glioma by using 11C-methionine, 11C-choline, and18F-fluorodeoxyglucose positron emission tomography." Neuro-Oncology 21, Supplement_3 (August 2019): iii66. http://dx.doi.org/10.1093/neuonc/noz126.237.
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Abstract BACKGROUND Positron emission tomography (PET) is important in noninvasive diagnostic imaging of gliomas. There are many PET studies on glioma diagnosis based on the 2007 World Health Organization (WHO) classification; however, there are no studies on glioma diagnosis using the new classification (the 2016 WHO classification).Here we investigated the relationship between PET imaging using 11C-methionine (MET), 11C-choline (CHO), and 18F-fluorodeoxyglucose (FDG) and wildtype isocitrate dehydrogenase (IDH) (IDH-wt)/mutant IDH (IDH-mut) in astrocytic and oligodendroglial tumors according to the 2016 WHO classification. MATERIAL AND METHODS In total, 105 patients with newly diagnosed cerebral gliomas (six diffuse astrocytomas [DAs] with IDH-wt, six DAs with IDH-mut, seven anaplastic astrocytomas [AAs] with IDH-wt, 24 AAs with IDH-mut, 26 glioblastomas [GBMs] with IDH-wt, five GBMs with IDH-mut, 19 oligodendrogliomas [ODs], and 12 anaplastic oligodendrogliomas [AOs]) were included. All OD and AO patients had both IDH-mut and 1p/19q codeletion. The maximum standardized uptake values (SUVs) of the tumor/normal cortex mean SUV ratios (T/N ratios) for MET, CHO, and FDG were calculated; the mean T/N ratios of DA, AA, and GBM with IDH-wt/IDH-mut were compared. The diagnostic accuracy for distinguishing gliomas with IDH-wt from those with IDH-mut was assessed using receiver operating characteristic (ROC) curve analysis of the mean T/N ratios for the three PET tracers. RESULTS There were significant differences in the mean T/N ratios for all three PET tracers between the IDH-wt and IDH-mut groups including all histological classifications (p<0.001). Among the 27 gliomas with mean T/N ratios higher than the cutoff values for all three PET tracers, 23 (85.2%) were classified into the IDH-wt group using ROC analysis. In DA, there were no significant differences in the T/N ratios for MET, CHO, and FDG between the IDH-wt and IDH-mut groups. In AA, the mean T/N ratios of all three PET tracers in the IDH-wt group were significantly higher than those in the IDH-mut group (p<0.001). In GBM, the mean T/N ratio in the IDH-wt group was significantly higher than that of the IDH-mut group for both MET (p=0.034) and CHO (p=0.01). However, there was no significant difference in the ratio for FDG. CONCLUSIONS PET imaging using MET, CHO, and FDG was confirmed to be informative for preoperatively differentiating gliomas according to the 2016 WHO classification, particularly for differentiating IDH-wt and IDH-mut tumors.
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Arcella, Antonietta, Fiona Limanaqi, Rosangela Ferese, Francesca Biagioni, Maria Antonietta Oliva, Marianna Storto, Mirco Fanelli, Stefano Gambardella, and Francesco Fornai. "Dissecting Molecular Features of Gliomas: Genetic Loci and Validated Biomarkers." International Journal of Molecular Sciences 21, no. 2 (January 20, 2020): 685. http://dx.doi.org/10.3390/ijms21020685.
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Recently, several studies focused on the genetics of gliomas. This allowed identifying several germline loci that contribute to individual risk for tumor development, as well as various somatic mutations that are key for disease classification. Unfortunately, none of the germline loci clearly confers increased risk per se. Contrariwise, somatic mutations identified within the glioma tissue define tumor genotype, thus representing valid diagnostic and prognostic markers. Thus, genetic features can be used in glioma classification and guided therapy. Such copious genomic variabilities are screened routinely in glioma diagnosis. In detail, Sanger sequencing or pyrosequencing, fluorescence in-situ hybridization, and microsatellite analyses were added to immunohistochemistry as diagnostic markers. Recently, Next Generation Sequencing was set-up as an all-in-one diagnostic tool aimed at detecting both DNA copy number variations and mutations in gliomas. This approach is widely used also to detect circulating tumor DNA within cerebrospinal fluid from patients affected by primary brain tumors. Such an approach is providing an alternative cost-effective strategy to genotype all gliomas, which allows avoiding surgical tissue collection and repeated tumor biopsies. This review summarizes available molecular features that represent solid tools for the genetic diagnosis of gliomas at present or in the next future.
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Seyve, Antoine, Caroline Dehais, Delphine Larrieu-Ciron, Charlotte Bronnimann, Carole Ramirez, Dominique Figarella-Branger, and François Ducray. "Fréquence et valeur pronostique de la prise de contraste au sein des gliomes de haut grade IDH-mutés diagnostiqués selon la classification OMS 2021 – une étude du réseau POLA." Revue Neurologique 179 (April 2023): S49—S50. http://dx.doi.org/10.1016/j.neurol.2023.01.372.
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Sanai, Nader, Juan Martino, and Mitchel S. Berger. "Morbidity profile following aggressive resection of parietal lobe gliomas." Journal of Neurosurgery 116, no. 6 (June 2012): 1182–86. http://dx.doi.org/10.3171/2012.2.jns111228.
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Object The impact of parietal lobe gliomas is typically studied in the context of parietal lobe syndromes. However, critical language pathways traverse the parietal lobe and are susceptible during tumor resection. The authors of this study reviewed their experience with parietal gliomas to characterize the impact of resection and the morbidity associated with language. Methods The study population included adults who had undergone resection of parietal gliomas of all grades. Tumor location was identified according to a proposed classification system for parietal region gliomas. Low- and high-grade tumors were volumetrically analyzed using FLAIR and T1-weighted contrast-enhanced MR imaging. Results One hundred nineteen patients with parietal gliomas were identified—34 with low-grade gliomas and 85 with high-grade gliomas. The median patient age was 45 years, and most patients (53) presented with seizures, whereas only 4 patients had an appreciable parietal lobe syndrome. The median preoperative tumor volume was 31.3 cm3, the median extent of resection was 96%, and the median postoperative tumor volume was 0.9 cm3. Surprisingly, the most common early postoperative neurological deficit was dysphasia (16 patients), not weakness (12 patients), sensory deficits (14 patients), or parietal lobe syndrome (10 patients). A proposed parietal glioma classification system, based on surgical anatomy, was predictive of language deficits. Conclusions This is the largest reported experience with parietal lobe gliomas. The findings suggested that parietal language pathways are compromised at a surprisingly high rate. The proposed parietal glioma classification system is predictive of postoperative morbidity associated with language and can assist with preoperative planning. Taken together, these data emphasize the value of identifying language pathways when operating within the parietal lobe.
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Nguyen, Anthony V., Jose M. Soto, Sarah-Marie Gonzalez, Jennifer Murillo, Eric R. Trumble, Frank Y. Shan, and Jason H. Huang. "H3G34-Mutant Gliomas—A Review of Molecular Pathogenesis and Therapeutic Options." Biomedicines 11, no. 7 (July 15, 2023): 2002. http://dx.doi.org/10.3390/biomedicines11072002.
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The 2021 World Health Organization Classification of Tumors of the Central Nervous System reflected advances in understanding of the roles of oncohistones in gliomagenesis with the introduction of the H3.3-G34R/V mutant glioma to the already recognized H3-K27M altered glioma, which represent the diagnoses of pediatric-type diffuse hemispheric glioma and diffuse midline glioma, respectively. Despite advances in research regarding these disease entities, the prognosis remains poor. While many studies and clinical trials focus on H3-K27M-altered-glioma patients, those with H3.3-G34R/V mutant gliomas represent a particularly understudied population. Thus, we sought to review the current knowledge regarding the molecular mechanisms underpinning the gliomagenesis of H3.3-G34R/V mutant gliomas and the diagnosis, treatment, long-term outcomes, and possible future therapeutics.
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Saluja, Sonam, Munesh Chandra Trivedi, and Shiv S. Sarangdevot. "Advancing glioma diagnosis: Integrating custom U-Net and VGG-16 for improved grading in MR imaging." Mathematical Biosciences and Engineering 21, no. 3 (2024): 4328–50. http://dx.doi.org/10.3934/mbe.2024191.
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<abstract> <p>In the realm of medical imaging, the precise segmentation and classification of gliomas represent fundamental challenges with profound clinical implications. Leveraging the BraTS 2018 dataset as a standard benchmark, this study delves into the potential of advanced deep learning models for addressing these challenges. We propose a novel approach that integrates a customized U-Net for segmentation and VGG-16 for classification. The U-Net, with its tailored encoder-decoder pathways, accurately identifies glioma regions, thus improving tumor localization. The fine-tuned VGG-16, featuring a customized output layer, precisely differentiates between low-grade and high-grade gliomas. To ensure consistency in data pre-processing, a standardized methodology involving gamma correction, data augmentation, and normalization is introduced. This novel integration surpasses existing methods, offering significantly improved glioma diagnosis, validated by high segmentation dice scores (WT: 0.96, TC: 0.92, ET: 0.89), and a remarkable overall classification accuracy of 97.89%. The experimental findings underscore the potential of integrating deep learning-based methodologies for tumor segmentation and classification in enhancing glioma diagnosis and formulating subsequent treatment strategies.</p> </abstract>
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Chen, Daiwen, Ziqian Chen, Shanwen Xu, and Hui Li. "Classification of Benign and Malignant Features of Glioma and Prediction of Early Metastasis and Recurrence Based on Enhanced MRI Imaging." Scientific Programming 2022 (March 4, 2022): 1–8. http://dx.doi.org/10.1155/2022/1955512.
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This work was aimed to establish a feature model for glioma grading and early metastasis and recurrence risk prediction based on contrast-enhanced magnetic resonance imaging (MRI). A total of 145 patients diagnosed with glioma by pathological examination were selected as the research subjects (training cohort: nasty 80; validation cohort: nasty 65). The imaging parameters T1-weighted (CET1WI), axial T2-weighted (T2WI), and apparent diffusion coefficient (ADC) were selected for the extraction of size and shape, intensity, histogram, and texture features. Image dimensionality reduction, feature selection, and model building were performed using the LASSO regression method. Using imaging features as potential predictors and evaluation indicators, the accuracy, sensitivity, and specificity of all prediction models and the area under the curve (AUC) of the receiver operating characteristic curve were calculated. Moreover, a predictive model for glioma grading and early metastasis risk was constructed. The results showed that under a single imaging parameter (T1-CE, DDC, T2WI-FLAIR, ADCslow, Alpha, ADC, CBF, and ADCfast), the diagnostic accuracy, sensitivity, specificity, AUC, and 95% confidence interval (CI) of low-grade gliomas (LGG), high-grade gliomas (HGG), and recurrent and nonrecurrent gliomas were significantly different (P < 0.05). The texture features, histogram features, and mean AUC of distinguishing low-grade and high-grade gliomas were 0.958, 0.945, and 0.954, respectively. The texture features, histogram features, and mean AUC for distinguishing recurrent and nonrecurrent gliomas were 0.949, 0.876, and 0.900, respectively. In short, the use of enhanced MRI imaging features can realize the prediction of early grading and recurrence of glioma and is of great significance for the early classification of benign and malignant characteristics of tumors.
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Skvortsova, T. Yu, Zh I. Savintseva, A. F. Gurchin, and A. I. Kholyavin. "Can the metabolic characteristics of diffuse glioma on <sup>11</sup>C-methionine PET/CT serve as a marker of its IDH status? Cross sectional study." Diagnostic radiology and radiotherapy 15, no. 1 (April 9, 2024): 35–45. http://dx.doi.org/10.22328/2079-5343-2024-15-1-35-45.
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INTRODUCTION: Since 2016, molecular markers, in particular, mutations in isocitrate dehydrogenase (IDH) 1 and 2, have been introduced as a classifying feature of cerebral gliomas that provided superior prognostication. The search for non-invasive biomarkers of the molecular profile of gliomas is necessary to improve the quality of preoperative diagnostics, identify patients with good and poor prognosis and determine treatment tactics.OBJECTIVE: Was to study the relationship between the IDH genotype of diffuse cerebral gliomas and metabolic biomarkers according to the results of PET/CT with [11C]methionine.MATERIALS AND METHOD: The results of PET/CT with 11C-methionine were identified to a retrospective analysis of 260 patients aged 18 to 75 years (median 40 years) with untreated cerebral glioma. Based on histological and molecular genetic studies of the surgical material including the determination of a mutation in the isocitrate dehydrogenase 1 (IDH1132H) gene, diffuse gliomas were classified according to the 2016 WHO classification of CNS tumors. Metabolic biomarkers included the calculation of tumor-to-brain ratio of 11С-methionine (TBRmax, TBRpeak and TBRmean) as well as the metabolic tumor volume (MTV). Statistics. Non-parametric tests were performed to compare the differences among patient groups. ROC curve analysis was performed to screen the optimal parameter and its best cutoff value for the discrimination of glioma genotype. All data analyses were performed using “Statistica 10,0” and “MedCalc” ststistical software. p-values less than 0.05 were considered statistically significant.RESULTS: According to the 2016 WHO classification astrocytic and oligodendroglial tumors of the adult type were divided into three groups: astrocytic gliomas with a mutation in the IDH1 gene (IDH1 mut) (n=95), astrocytic gliomas without a mutation in the IDH1 gene (IDH1 wild type — IDH1 wt) (n=103), and IDH1-mutant oligodendrogliomas (n=62). Significant differences in all ratios between the three molecular groups of gliomas were established. TBRmax cutoff of 2.27 differentiated between IDH1 wt and IDH1 mut gliomas with a sensitivity of 61% and a specificity of 77% (area under curve — AUC 0.752). When considering subgroups of gliomas that are homogeneous in terms of the IDH1 status or Grade, the dependence of TBR on the glioma histotype and grading was additionally established. In IDH1 mut oligodendrogliomas, TBR was significantly higher than in mutant astrocytomas, and in IDH1 wt astrocytomas, significant differences in TBR were established between Grade 2 and Grade 3–4. TBRmax was not a predictor of glioma type according to the WHO 2016 classification due to significant overlap of individual of TBR values. But TBRmax allowed diagnosing a cluster of malignant gliomas, including glioblastoma and astrocytoma Grade 3 IDH wt, as well as oligodendroglioma Grade 3 IDH1 mut, with a sensitivity of 65% and a specificity of 89% (AUC 0.848) at a cutoff of TBR=2.7. A strong correlation between the three tumor-to-brain ratios allows any ratio to be used in diagnostics. There were no significant differences in MTV between molecular types of gliomas.DISCUSSION: Distinguishing glioma types based on the 2016 WHO classification of the CNS tumors on the basis of 11Cmethionine uptake seems to be not reliable due to many factors that affect its uptake. In astrocytomas high TBR is associated with malignant grade and wild type IDH1 gene. However, the lack of differences in TBR between these astrocytomas and Grade 3 IDH1-mutant oligodendrogliomas does not allow one to predict the IDH1 status of the tumor in the absence of other radiological signs of the glioma histotype. The absence of differences in TBR between Grade 2 and Grade 3 astrocytomas IDH1 mut supports the view that they are considered as a single subgroup of lower grade gliomas. CONCLUSION: PET/CT with 11C-methionine has limited potential to assess the IDH status of diffuse gliomas. High TBR is associated with malignant glioma with wild-type IDH1 gene or oligodendroglial structure.
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Takei, Hiroaki, Jun Shinoda, Soko Ikuta, Takashi Maruyama, Yoshihiro Muragaki, Tomohiro Kawasaki, Yuka Ikegame, et al. "Usefulness of positron emission tomography for differentiating gliomas according to the 2016 World Health Organization classification of tumors of the central nervous system." Journal of Neurosurgery 133, no. 4 (October 2020): 1010–19. http://dx.doi.org/10.3171/2019.5.jns19780.
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OBJECTIVEPositron emission tomography (PET) is important in the noninvasive diagnostic imaging of gliomas. There are many PET studies on glioma diagnosis based on the 2007 WHO classification; however, there are no studies on glioma diagnosis using the new classification (the 2016 WHO classification). Here, the authors investigated the relationship between uptake of 11C-methionine (MET), 11C-choline (CHO), and 18F-fluorodeoxyglucose (FDG) on PET imaging and isocitrate dehydrogenase (IDH) status (wild-type [IDH-wt] or mutant [IDH-mut]) in astrocytic and oligodendroglial tumors according to the 2016 WHO classification.METHODSIn total, 105 patients with newly diagnosed cerebral gliomas (6 diffuse astrocytomas [DAs] with IDH-wt, 6 DAs with IDH-mut, 7 anaplastic astrocytomas [AAs] with IDH-wt, 24 AAs with IDH-mut, 26 glioblastomas [GBMs] with IDH-wt, 5 GBMs with IDH-mut, 19 oligodendrogliomas [ODs], and 12 anaplastic oligodendrogliomas [AOs]) were included. All OD and AO patients had both IDH-mut and 1p/19q codeletion. The maximum standardized uptake value (SUV) of the tumor/mean SUV of normal cortex (T/N) ratios for MET, CHO, and FDG were calculated, and the mean T/N ratios of DA, AA, and GBM with IDH-wt and IDH-mut were compared. The diagnostic accuracy for distinguishing gliomas with IDH-wt from those with IDH-mut was assessed using receiver operating characteristic (ROC) curve analysis of the mean T/N ratios for the 3 PET tracers.RESULTSThere were significant differences in the mean T/N ratios for all 3 PET tracers between the IDH-wt and IDH-mut groups of all histological classifications (p < 0.001). Among the 27 gliomas with mean T/N ratios higher than the cutoff values for all 3 PET tracers, 23 (85.2%) were classified into the IDH-wt group using ROC analysis. In DA, there were no significant differences in the T/N ratios for MET, CHO, and FDG between the IDH-wt and IDH-mut groups. In AA, the mean T/N ratios of all 3 PET tracers in the IDH-wt group were significantly higher than those in the IDH-mut group (p < 0.01). In GBM, the mean T/N ratio in the IDH-wt group was significantly higher than that in the IDH-mut group for both MET (p = 0.034) and CHO (p = 0.01). However, there was no significant difference in the ratio for FDG.CONCLUSIONSPET imaging using MET, CHO, and FDG was suggested to be informative for preoperatively differentiating gliomas according to the 2016 WHO classification, particularly for differentiating IDH-wt and IDH-mut tumors.
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Zhang, Lu, Sabrina Fritah, Petr V. Nazarov, Tony Kaoma, and Eric Van Dyck. "Impact of IDH Mutations, the 1p/19q Co-Deletion and the G-CIMP Status on Alternative Splicing in Diffuse Gliomas." International Journal of Molecular Sciences 24, no. 12 (June 6, 2023): 9825. http://dx.doi.org/10.3390/ijms24129825.
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By generating protein diversity, alternative splicing provides an important oncogenic pathway. Isocitrate dehydrogenase (IDH) 1 and 2 mutations and 1p/19q co-deletion have become crucial for the novel molecular classification of diffuse gliomas, which also incorporates DNA methylation profiling. In this study, we have carried out a bioinformatics analysis to examine the impact of the IDH mutation, as well as the 1p/19q co-deletion and the glioma CpG island methylator phenotype (G-CIMP) status on alternative splicing in a cohort of 662 diffuse gliomas from The Cancer Genome Atlas (TCGA). We identify the biological processes and molecular functions affected by alternative splicing in the various glioma subgroups and provide evidence supporting the important contribution of alternative splicing in modulating epigenetic regulation in diffuse gliomas. Targeting the genes and pathways affected by alternative splicing might provide novel therapeutic opportunities against gliomas.
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Brito, C., A. Azevedo, S. Esteves, C. Martins, M. Mafra, L. Roque, and M. Pojo. "P03.13 Evaluation of PIK3CA mutational status in glioma molecular subgroups." Neuro-Oncology 21, Supplement_3 (August 2019): iii27—iii28. http://dx.doi.org/10.1093/neuonc/noz126.094.
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Abstract BACKGROUND Gliomas are the most common and lethal malignant tumors of central nervous system. In 2016, World Health Organization (WHO) classification included IDH mutations and 1p/19q codeletion as diagnostic criteria to define glioma entities. However, new biomarkers for diagnosis, prognosis and response to therapy are needed. In this context, PIK3CA mutations have been described as constitutive mutations, which highlights their relevance in gliomas. Here we clarified the clinical relevance of PIK3CA mutations according to the 2016 WHO classification, the potential impact on diagnosis, prognosis, response to therapy, as well as their correlation with EGFR amplification and PTEN deletion. MATERIAL AND METHODS A cohort of 444 adult diffuse glioma samples from Instituto Português de Oncologia Lisboa Francisco Gentil (IPOLFG) was classified according to the 2016 WHO Classification. The mutational status of exon 9 and 20 of PIK3CA was evaluated in molecular subgroups of gliomas by Sanger sequencing. PTEN deletion and EGFR amplification were identified by Fluorescent in situ hybridization (FISH). RESULTS PIK3CA mutations showed a higher frequency in the subgroup of gliomas with IDH mutations and 1p/19q codeletion - oligodendrogliomas (10%). In Glioblastoma (GBM) IDH-mutant and IDH-wildtype these oncogenic mutations were observed in 9% and 3% of cases, respectively. Similar results were obtained using The Cancer Genome Atlas (TCGA) data, which was 8% and 2%, respectively. H1047R and E542K were the most frequent mutations identified in the glioma molecular subgroups. Importantly, we found 3 unreported pathogenic variants in exon 20 of PIK3CA (c.3112T>C, c.2988T>C, c.3040C>T) and one polymorphic variant (c.3210A>G). In addition, PIK3CA mutations, PTEN deletion and EGFR amplification were not mutually exclusive alterations in glioma molecular subgroups. For the first time in gliomas, it was identified the rs45455192 polymorphism at a frequency of 16% in astrocytomas IDH-mutant, 24% in oligodendrogliomas and 18% in both molecular subgroups of GBM, although this polymorphism did not have prognostic value. The analysis of PIK3CA mutations in glioma recurrences showed that these mutations are maintained during glioma progression. CONCLUSION In two independent cohorts (IPOLFG and TCGA), it was obtained similar frequencies of PIK3CA mutations in GBM molecular subgroups. In addition, these mutations are more relevant in less aggressive gliomas (IDH-mutated and 1p/19q codeleted). These alterations seem to be important in tumor maintenance and progression, which makes this gene a potential therapeutic target. In the future, we will investigate the effect of the in vitro pharmacological inhibition of PIK3CA in GBM mutant cell lines.
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Wang, Lei, Zhengtao Yu, Shaiqi Sun, Jun Peng, Rongjun Xiao, Shengpan Chen, Xiaokun Zuo, Quan Cheng, and Ying Xia. "Long non-coding RNAs: potential molecular biomarkers for gliomas diagnosis and prognosis." Reviews in the Neurosciences 28, no. 4 (May 24, 2017): 375–80. http://dx.doi.org/10.1515/revneuro-2016-0066.
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AbstractThe current grade classification system of gliomas is based on the histopathological features of these tumors and has great significance in defining groups of patients for clinical assessment. However, this classification system is also associated with a number of limitations, and as such, additional clinical assessment criteria are required. Long non-coding RNAs (lncRNAs) play a critical role in cellular functions and are currently regarded as potential biomarkers for glioma diagnosis and prognosis. Therefore, the molecular classification of glioma based on lncRNA expression may provide additional information to assist in the systematic identification of glioma. In the present paper, we review the emerging evidence indicating that specific lncRNAs may have the potential for use as key novel biomarkers and thus provide a powerful tool for the systematic diagnosis of glioma.
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Fernandes, Renata Tarraf, Gustavo Ramos Teixeira, Esther Cecin Mamere, Gabriela Alencar Bandeira, and Augusto Elias Mamere. "The 2021 World Health Organization classification of gliomas: an imaging approach." Radiologia Brasileira 56, no. 3 (June 2023): 157–61. http://dx.doi.org/10.1590/0100-3984.2022.0089-en.
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Abstract The purpose of this pictorial essay is to describe the recommendations of the 2021 World Health Organization classification for adult-type and pediatric-type gliomas and to discuss the main modifications in relation to the previous (2016) classification, exemplified by imaging, histological, and molecular findings in nine patients followed at our institutions. In recent years, molecular biomarkers have gained importance in the diagnosis and classification of gliomas, mainly because they have been shown to correlate with the biological behavior and prognosis of such tumors. It is important for neuroradiologists to familiarize themselves with this new classification of central nervous system tumors, so that they can use this knowledge in evaluating and reporting the imaging examinations of patients with glioma.
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Choi, Seonah, In-Ho Jung, Jaejoon Lim, Ju Hyung Moon, Eui Hyun Kim, Se Hoon Kim, Seok-Gu Kang, and Jong Hee Chang. "PATH-06. SURVIVAL ANALYSIS FOR ADULT MIDLINE GLIOMA: DO ADULT MIDLINE GLIOMAS WITH THE H3 K27M MUTATION REALLY HAVE POOR PROGNOSIS?" Neuro-Oncology 24, Supplement_7 (November 1, 2022): vii150—vii151. http://dx.doi.org/10.1093/neuonc/noac209.579.
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Abstract PURPOSE Since it is known that midline located glioma with H3K27 mutation in children has a disastrous prognosis, in 2016 WHO classification, these tumors were defined as diffuse midline glioma (DMG) and classified as grade IV. A lot of papers about pediatric DMG have been published, but there are not many papers about adult DMG. In this study, we aimed to identify factors affecting the prognosis of adult midline glioma. This is the first paper to study the prognosis of adult DMG according to histological grade and is the largest study to investigate the survival of adult DMG. METHODS We reviewed the chart of adult patients diagnosed with midline glioma with H3K27M mutation after undergoing resection or biopsy among patients who visited our institution between January 2010 and December 2020. Survival analysis was performed according to tumor location, histological grading, Karnofsky Performance Scale (KPS), and age. RESULTS Among the 125 adult midline gliomas we identified, 45 (36.0%) had the H3K27M mutation. As a result of survival analysis performed on 125 adult midline gliomas, low histological grade, KPS ≥ 80, and age ≤ 60 showed significantly better survival. After adjusting for age, the difference in survival between H3K27M mutation and wildtype group was not significant. As a result of survival analysis performed on 45 DMG, low histological grade, KPS ≥ 80, total resection, and concurrent chemoradiation therapy group showed significantly better survival. CONCLUSION In adult midline glioma, disastrous prognosis due to H3K27M mutation was not observed as in children. The prognosis of adult midline gliomas is determined by histological grade, age, KPS, and extent of tumor resection. Therefore, the current WHO classification, which classifies all H3K27M mutant midline gliomas as grade IV regardless of histological diagnoses, is not suitable for adults.
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Cheng, Chuandong, Ying Ji, Tiantian Han, Xiaomin Li, Yahui Huang, Weijie Sun, Guanghua Lu, Wanglong Deng, Ran Ding, and Fanfeng Bu. "MAPK pathway alteration may be a new integrated diagnosis term." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): e14022-e14022. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e14022.
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e14022 Background: The 2016 CNS WHO classification is the first to include molecular factors to classify in glioma. We are in the age of glioma subgroups, in which the category depended on the histological and molecular composition, providing more clinical behavior, prognosis, and therapeutic targets hints. The most well-known molecular modifications are IDH1/2 mutation, ATRX variant, TP53 variant, BRAF mutation or fusion, 1p/19q co-deletions. However, there is a diagnostic term“NOS” in the 2016 CNS WHO classification，which indicates that a tumor could not be placed into a more specific WHO category. Here, our analysis of the MAPK pathway may suggest a new subtype. Methods: Targeted next-generation DNA sequence of the 131-genes panel was performed on gliomas in 119 patients. We measured the somatic variations in the MAPK pathway after filtering known driver mutations. The analysis of genomic alterations was performed using a two-sided Fisher exact test. Results: 90/119（75.6%）were excluded due to known driver mutations. 29/119(24.4%) were classified in NOS with a typical “single MAPK pathway alteration” and different histological characteristics and WHO grade. The median age at diagnosis was 35 years (4-79) in our gliomas. The most frequent mutations were NF1(10/29), FGFR1(7/29), KRAS (6/29), BRAF (3/29), PTPN11(2/29), although there are other gene mutations like FGFR2, FGFR3, AKT1, MAP2K1. According to cIMPACT-NOW update 4, our pediatric gliomas ( < 30 years, n = 14) could be identified as “diffuse glioma, other MAPK pathway alteration.” Our adult gliomas have a higher frequency of NF1 mutations（8/15 vs. 2/14, p = 0.05), a lower KRAS (1/15 vs. 5/14) and FGFR1 (2/15 vs. 5/14) mutations than children. Conclusions: Our result suggests that MAPK pathway alteration may be a new integrated diagnosis term in all ages of glioma. Moreover, KRAS and FGFR1 may be associated with pediatric gliomas. NF1 is more common in adult gliomas.
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Fritah, S., A. Cano-Galiano, R. Toth, A. Hau, E. Martinez-Garcia, M. Allega, D. Sumpton, et al. "P02.18.B INTEGRATIVE OMICS ANALYSIS OF IDH1 MUTANT GLIOMA PATIENTS REVEALS ALTERATIONS IN BUTYRATE METABOLISM." Neuro-Oncology 25, Supplement_2 (September 1, 2023): ii33—ii34. http://dx.doi.org/10.1093/neuonc/noad137.103.
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Abstract BACKGROUND Mutations in isocitrate dehydrogenase (IDH) 1 or 2 define glioma classification and determine the biology of these tumors. Although IDH is an essential enzyme in the cellular metabolism, powerful genome-wide analyses focus mostly at the genetic and epigenetic levels, while differences between distinct glioma entities at the proteomics, metabolomics, and functional levels are still poorly understood. Here, we provide an integrative multi-omics analysis of glioma patients to reveal metabolomic vulnerabilities of gliomas stratified by IDH mutation. MATERIAL AND METHODS We performed a multi-omics analysis of two cohorts of glioma patients (n=28) stratified based on IDH mutation status. Molecular assessment included LC-MS analysis, EPIC DNA methylation arrays, RNA-seq/HTA array-based transcriptomics and label-free quantitative proteomics. In 13 patients 13C-glucose was injected prior to surgery and tumor and adjacent brain tissue was collected. Gut microbial profiling using 16S ribosomal RNA (rRNA) sequencing was performed in a separate cohort of 128 glioma patients and 24 healthy individuals. Additional validation was performed in isogenic glioma stem-like cultures with CRISPR knock-in of IDH mutation. RESULTS We show that several molecular layers collectively contribute to biological differences between IDH mutant and wild-type gliomas, with strongest differences observed at the DNA methylation level. IDH mutant gliomas present specific molecular features linked to tumor metabolism. We confirm previous findings on 2-HG, cysteine and de novo glutathione synthesis pathways, which are specifically altered in IDH mutant gliomas. We further identify butyrate metabolism as a novel pathway highly active in IDH mutant gliomas. Butyrate is a bacterial metabolite with multiple systemic effects that is normally synthesized in the gut. This is supported by our gut microbiota metagenomics analysis of glioma patients. Yet the detection of enzymes associated with butyrate metabolism in tumor tissue and cell lines suggests a differential/enhanced metabolic rewiring of the butyrate signaling in IDH mutant gliomas CONCLUSION Our data shows the importance of multiple molecular layers in shaping specific features of IDH mutant gliomas. We unravel an activated butyrate metabolism in IDH mutant gliomas that may underly a novel gut-brain axis in glioma patients.
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Pallud, J., B. Devaux, F. Nataf, P. Varlet, M. Koziak, J. F. Meder, C. Daumas-Duport, and F. X. Roux. "Délimitation spatiale des gliomes de bas grade. Mise en évidence de cellules tumorales au-delà de l’image IRM T2 dans les oligodendrogliomes de grade « A » (Classification Sainte-Anne) à limites nettes." Neurochirurgie 50, no. 5 (November 2004): 574. http://dx.doi.org/10.1016/s0028-3770(04)98355-5.
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Cho, Hwan-ho, Seung-hak Lee, Jonghoon Kim, and Hyunjin Park. "Classification of the glioma grading using radiomics analysis." PeerJ 6 (November 22, 2018): e5982. http://dx.doi.org/10.7717/peerj.5982.
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Background Grading of gliomas is critical information related to prognosis and survival. We aimed to apply a radiomics approach using various machine learning classifiers to determine the glioma grading. Methods We considered 285 (high grade n = 210, low grade n = 75) cases obtained from the Brain Tumor Segmentation 2017 Challenge. Manual annotations of enhancing tumors, non-enhancing tumors, necrosis, and edema were provided by the database. Each case was multi-modal with T1-weighted, T1-contrast enhanced, T2-weighted, and FLAIR images. A five-fold cross validation was adopted to separate the training and test data. A total of 468 radiomics features were calculated for three types of regions of interest. The minimum redundancy maximum relevance algorithm was used to select features useful for classifying glioma grades in the training cohort. The selected features were used to build three classifier models of logistics, support vector machines, and random forest classifiers. The classification performance of the models was measured in the training cohort using accuracy, sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic curve. The trained classifier models were applied to the test cohort. Results Five significant features were selected for the machine learning classifiers and the three classifiers showed an average AUC of 0.9400 for training cohorts and 0.9030 (logistic regression 0.9010, support vector machine 0.8866, and random forest 0.9213) for test cohorts. Discussion Glioma grading could be accurately determined using machine learning and feature selection techniques in conjunction with a radiomics approach. The results of our study might contribute to high-throughput computer aided diagnosis system for gliomas.
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Rahmat, Romi Fadillah, Mhd Faris Pratama, Sarah Purnamawati, Sharfina Faza, Arif Ridho Lubis, Al-Khowarizmi Al-Khowarizmi, and Muharman Lubis. "Astrocytoma, ependymoma, and oligodendroglioma classification with deep convolutional neural network." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (December 1, 2022): 1306. http://dx.doi.org/10.11591/ijai.v11.i4.pp1306-1313.
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Glioma as one of the most common types of brain tumor in the world has three different classes based on its cell types. They are astrocytoma, ependymoma, oligodendroglioma, each has different characteristics depending on the location and malignance level. Radiological examination by medical personnel is still carried out manually using magnetic resonance imaging (MRI) medical imaging. Brain structure, size, and various forms of tumors increase the level of difficulty in classifying gliomas. It is advisable to apply a method that can conduct gliomas classification through medical images. The proposed methods were proposed for this study using deep convolutional neural network (DCNN) for classification with k-means segmentation and contrast enhancement. The results show the effectiveness of the proposed methods with an accuracy of 95.5%.
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Hölzl, Dorothee, Georg Hutarew, Barbara Zellinger, Beate Alinger-Scharinger, Hans U. Schlicker, Christoph Schwartz, Karl Sotlar, and Theo F. J. Kraus. "EGFR Amplification Is a Phenomenon of IDH Wildtype and TERT Mutated High-Grade Glioma: An Integrated Analysis Using Fluorescence In Situ Hybridization and DNA Methylome Profiling." Biomedicines 10, no. 4 (March 29, 2022): 794. http://dx.doi.org/10.3390/biomedicines10040794.
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Gliomas are the most common intrinsic brain tumors in adults, and in accordance with their clinical behavior and patients’ outcome, they are graded by the World Health Organization (WHO) classification of brain tumors. One very interesting candidate for targeted tumor therapy may be epidermal growth factor receptor (EGFR) amplification. Here, we performed an integrated comparative analysis of EGFR amplification in 34 glioma samples using standard fluorescence in situ hybridization (FISH) and Illumina EPIC Infinium Methylation Bead Chip and correlated results with molecular glioma hallmarks. We found that the EPIC analysis showed the same power of detecting EGFR amplification compared with FISH. EGFR amplification was detectable in high-grade gliomas (25%). Moreover, EGFR amplification was found to be present solely in IDH wildtype gliomas (26%) and TERT mutated gliomas (27%), occurring independently of MGMT promoter methylation status and being mutually exclusive with 1p/19q codeletion (LOH). In summary, EPIC Bead Chip analysis is a reliable tool for detecting EGFR amplification and is comparable with the standard method FISH. EGFR amplification is a phenomenon of IDH wildtype TERT mutated high-grade gliomas.
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Ogawa, Tomoya, Keisuke Miyake, Takeshi Fujimori, Daisuke Ogawa, Masaki Okada, Tetsuhiro Hatakeyama, Masanobu Okauchi, Atsushi Shindo, Masahiko Kawanishi, and Takashi Tamiya. "NI-15 THE USEFULNESS OF PET IMAGING IN MOLECULAR DIAGNOSIS OF GLIOMA." Neuro-Oncology Advances 1, Supplement_2 (December 2019): ii28. http://dx.doi.org/10.1093/noajnl/vdz039.127.
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Abstract OBJECTIVE After WHO 2016 Classification of Tumors of the Central Nervous System have published, molecular diagnosis became part of the diagnostic criteria. In this study, we investigated the correlation between PET images and molecular diagnosis of glioma. METHODS We performed retrospective review of newly diagnosed supratentorial glioma patients who preoperatively underwent all four PET examinations (18F-FDG, 11C-MET, 18F-FLT and 18F-FMISO) from April 2009 to March 2019. The standardized uptake value (SUV) from the accumulation of each PET tracers, TNR (tumor to contralateral normal tissue ratio) of 18F-FDG,11C-MET and 18F-FLT, TBR (tumor to blood values ratio) of 18F-FMISO were measured. We investigated the correlation between these PET images and molecular diagnosis of glioma. RESULTS Data from total of 79 patients which were 42 cases of IDH wild type glioblastoma, 2 cases of IDH mutated glioblastoma, 9 cases of IDH wild type astrocytoma, 13 cases of IDH mutated astrocytoma and 13 cases of IDH mutated and 1p/19q co-deleted oligodendroglioma were included in this study. Both TNR of 11C-MET(p<0.01) and 18F-FLT(p<0.01), and also TBR of 18F-FMISO(p<0.01) in IDH wild type gliomas showed significantly higher than IDH mutated gliomas. In WHO Gr2-3 gliomas, only TNR of 18F-FLT showed a significant difference between IDH wild type gliomas and IDH mutated gliomas(p<0.01). TNR of 18F-FLT(p<0.01) and TBR of 18F-FMISO(p<0.01) in 1p/19q co-deleted gliomas were significantly lower than gliomas without 1p/19q co-deletion, but there were no significant differences in WHO Gr2-3 gliomas. Among IDH mutated gliomas, TNR of 11C-MET in 1p/19q co-deleted gliomas showed significantly higher uptake than gliomas without 1p/19q co-deletion(p<0.05). CONCLUSION Preoperative PET evaluation of each PET tracers may be useful for the molecular diagnosis of glioma.
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Wang, Yongheng, Yinyan Wang, Xing Fan, Shaowu Li, Xing Liu, Jiangfei Wang, and Tao Jiang. "Putamen involvement and survival outcomes in patients with insular low-grade gliomas." Journal of Neurosurgery 126, no. 6 (August 2016): 1788–94. http://dx.doi.org/10.3171/2016.5.jns1685.
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OBJECTIVEInsular glioma has a unique origin and biological behavior; however, the associations between its anatomical features and prognosis have not been well established. The object of this study was to propose a classification system of insular low-grade gliomas based on preoperative MRI findings and to assess the system's association with survival outcome.METHODSA total of 211 consecutively collected patients diagnosed with low-grade insular gliomas was analyzed. All patients were classified according to whether tumor involved the putamen on MR images. The prognostic role of this novel putaminal classification, as well as that of Yaşargil's classification, was examined using multivariate analyses.RESULTSNinety-nine cases (46.9%) of insular gliomas involved the putamen. Those tumors involving the putamen, as compared with nonputaminal tumors, were larger (p < 0.001), less likely to be associated with a history of seizures (p = 0.04), more likely to have wild-type IDH1 (p = 0.003), and less likely to be totally removed (p = 0.02). Significant favorable predictors of overall survival on univariate analysis included a high preoperative Karnofsky Performance Scale score (p = 0.02), a history of seizures (p = 0.04), gross-total resection (p = 0.006), nonputaminal tumors (p < 0.001), and an IDH1 mutation (p < 0.001). On multivariate analysis, extent of resection (p = 0.035), putamen classification (p = 0.014), and IDH1 mutation (p = 0.026) were independent predictors of overall survival. No prognostic role was found for Yaşargil's classification.CONCLUSIONSThe current study's findings suggest that the putamen classification is an independent predictor of survival outcome in patients with insular low-grade gliomas. This newly proposed classification allows preoperative survival prediction for patients with insular gliomas.
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Wang, Daoying, Haiyang Li, and Jingjing Niu. "Study on the Diagnostic Value of Magnetic Resonance Imaging in Patients with Malignant Glioma." Journal of Medical Imaging and Health Informatics 11, no. 1 (January 1, 2021): 186–91. http://dx.doi.org/10.1166/jmihi.2021.3442.
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Objective: To explore the value of multi-voxel-based monomer 1H-MRS (magnetic resonance imaging) in the classification of gliomas. Methods: 26 gliomas confirmed by surgery and pathology were examined by conventional MRI, multi-voxel 2D, and monomer 1H-MRS before surgery. Three types of regions of interest (ROI) were used to measure Cho/NAA (Choline hydroxide solution/N-acetyl aspartic acid) values in the tumor. Methods: In the multi-voxel 2D hydrogen proton spectrum, the solid part of the tumor or the most intensive region of the tumor was selected to determine the Cho/NAA value. At the same time, in the multi-voxel 2D hydrogen proton spectrum, the Fun/tool spectra's copy-2DBmin analysis software was used to obtain the Cho/NAA value distribution. Anatomically superimposed the pseudo-color image, and measure the Cho/NAA value in its largest Cho/NAA value region. In addition, based on the level set algorithm, it uses the Otsu algorithm to initially locate the edema area and provide the initial contour. Results: The Cho/NAA values measured by the ROI selection method were statistically significant, and the sensitivity and specificity of judging the benign and malignant gliomas indicated that Method 3 had the highest diagnostic value. Conclusion: Multi-voxel-based monomeric 1H-MRS magnetic resonance imaging has the highest value in guiding glioma classification and can improve the accuracy of glioma classification.
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Dozic, Slobodan, Dubravka Cvetkovic-Dozic, Milica Skender-Gazibara, and Branko Dozic. "Review of the World Health Organization classification of tumors of the nervous system." Archive of Oncology 10, no. 3 (2002): 175–77. http://dx.doi.org/10.2298/aoo0203175d.
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(Conclusion) Classifications of the nervous system tumors should be neither static nor definitive. The most recent, third, current WHO classification of nervous system tumors was published in 2000. Many substantial changes were introduced. New entities include the chordoid glioma of the third ventricle, the atypical teratoid/rhabdoid tumor, cerebellar liponeurocytoma (the former lipomatous medulloblstoma of the cerebellum), solitary fibrous tumor and perineurioma. The new tumor variants include the large cell medulloblastoma, tanacytic ependymoma and rhabdoid meningioma. Several essential changes were introduced in the meningiomas regarding histological subtypes, grading and proliferation index. In addition to new entities described in the 2000 WHO classification there are newly brain tumor entities and tumor variants, which are not included in the current classification due to the insufficient number of reporeted cases, for example papillary glioneuronal tumor, rosetted glioneuronal tumor, lipoastrocytoma and lipomatous meningioma. They will be probably accepted in the next WHO classificaton. In the current WHO classification the importance of cytogenetic and molecular biologic investigation in the understanding and further classifications of these tumors has been emphasized.
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Mischkulnig, M., B. Kiesel, T. Rötzer-Pejrimovsky, M. Borkovec, A. Lang, M. Millesi, L. I. Wadiura, et al. "P11.44.A The impact of heme biosynthesis regulation on glioma aggressiveness: correlations with most recent diagnostic molecular markers." Neuro-Oncology 24, Supplement_2 (September 1, 2022): ii67—ii68. http://dx.doi.org/10.1093/neuonc/noac174.233.
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Abstract Background The prognosis of patients with diffusely infiltrating gliomas is dismal but varies greatly between individuals. While characterization of gliomas was primarily relied on typical histopathological features, specific molecular markers increasingly gained importance and play a key role in the recently published 5th edition of the World Health Organization (WHO) classification. Heme biosynthesis represents a crucial pathway due to its key role in oxygen transport, energy production or drug metabolism. Recently, we described a “heme biosynthesis mRNA expression signature” that correlates with histopathological glioma grades and patient survival. The aim of the current study was to correlate the heme biosynthesis mRNA expression signature with the most recent diagnostic molecular markers for glioma stratification. Material and Methods In this study, patient data were derived from the “The Cancer Genome Atlas” (TCGA) lower-grade glioma and glioblastoma cohorts. We identified diffusely infiltrating gliomas correlating molecular tumor diagnosis according to the most recent WHO classification with heme biosynthesis mRNA expression. The following molecular markers were analyzed: EGFR amplification, TERT promoter mutation, CDKN2A/B homozygous loss, concurrent chromosome 7 gain/10 loss, MGMT methylation, IDH mutation, ATRX loss, p53 mutation and 1p19q co-deletion. Subsequently, we calculated the heme biosynthesis mRNA expression signature and correlated this signature with distinct molecular glioma markers as well as the resulting molecular subgroups. Results A total of 649 patients with available data on up-to-date molecular markers and heme biosynthesis mRNA expression were included. According to analysis of individual molecular markers, we found a significantly higher heme biosynthesis mRNA expression signature in gliomas with IDH wildtype (p<0.0005), without 1p19q co-deletion (p<0.0005), with homozygous CDKN2A/B loss (p<0.0005) and with EGFR amplification (p=0.001). Furthermore, we observed that the heme biosynthesis mRNA expression signature increased with the aggressiveness of the molecular subgroups (p<0.0005), being lowest in WHO grade 2 oligodendrogliomas and highest in WHO grade 4 glioblastomas. Conclusion Our data demonstrate a significant correlation between diagnostic molecular markers and heme biosynthesis regulation in diffusely infiltrating gliomas. Consequently, heme biosynthesis expression is a promising biomarker for glioma aggressiveness and might constitute a potential target for novel therapeutic approaches.
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Ajisebutu, Andrew, Farshad Nassiri, Justin Z. Wang, Yasin Mamatjan, Romina Nejad, Vikas Patil, Jeff Liu, et al. "METABOLOGENOMIC CHARACTERIZATION UNCOVERS HETEROGENEITY AMONG IDH MUTANT GLIOMAS." Neuro-Oncology Advances 5, Supplement_2 (July 1, 2023): i1. http://dx.doi.org/10.1093/noajnl/vdad071.001.
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Abstract Mutations in isocitrate dehydrogenase (IDH) enzymes are recognised to drive the molecular footprint of diffuse gliomas, and patients with IDH-mutant gliomas have overall favorable outcomes compared to patients with IDH wildtype tumors. Nonetheless, survival can vary widely even amongst patients with IDH-mutant tumors. A comprehensive metabologenomic characterization of IDH-mutant gliomas has not been performed to date. METHOD: Glioma samples from a cohort of 154 patients that underwent surgery at the UHN in Toronto, ON, underwent multiplatform molecular analysis, including metabolomic studies, genome- wide DNA methylation profiling and bulk RNA sequencing. A comprehensive, integrative analysis was performed, and validated through the use of an independent cohort derived from The Cancer Genome Atlas. RESULTS: We discovered a group of IDH-mutant gliomas with globally altered metabolism that highly resembled IDH wildtype tumors. Notably, these IDH-mutant gliomas with dysregulated metabolism were distinguished from their IDH-mutant counterparts by significantly shorter overall survival. The prognostic relevance of dysregulated metabolism complements, but was not wholly explained by canonically recognized prognostic classifications in IDH-mutant gliomas including 1p/19q codeletion, glioma CpG Island Hypermethylator (GCIMP) status and CDKN2A homozygous deletion. IDH-mutant tumors with dysregulated metabolism harbored distinct epigenetic alterations that converged to drive proliferative and stem-like transcriptional profiles. CONCLUSION: Utilizing a cross-platform analysis we have uncovered a novel subtyping of IDH-mutant gliomas with dysregulated cellular metabolism with similar survival to IDH-wildtype tumors. The metabolic profile provides unique information on glioma phenotypes, which may can facilitate a more comprehensive understanding of glioma biology, and provide a window to target novel dependencies.