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10. Characteristics of IDH-mutant gliomas with non-canonical IDH mutation.

Author

Poetsch, L., Bronnimann, C., Loiseau, H., Frénel, J. S., Siegfried, A., Seizeur, R., Gauchotte, G., Cappellen, D., Carpentier, C., Figarella-Branger, D., Eimer, S., Meyronet, D., Ducray, F., POLA network, Desenclos, C., Sevestre, H, Menei, P, Rousseau, A, Cruel, T, and Lopez, S

Abstract

Background: Approximately 10% of IDH-mutant gliomas harbour non-canonical IDH mutations (non-p.R132H IDH1 and IDH2 mutations). Objective: The aim of this study was to analyse the characteristics of non-canonical IDH-mutant gliomas. Materials and methods: We retrospectively analysed the characteristics of 166 patients with non-canonical IDH mutant gliomas and compared them to those of 155 consecutive patients with IDH1 p.R132H mutant gliomas. Results: The median age at diagnosis was 38 years in patients with non-canonical IDH mutant gliomas and 43 years in glioma patients with IDH1 p.R132H-mutant tumours. Family history of cancer was more frequent among glioma patients harbouring non-canonical IDH mutations than in patients with IDH1 p.R132H mutations (22.2% vs 5.1%; P < 0.05). Tumours were predominantly localised in the frontal lobe regardless of the type of IDH mutation. Compared to IDH1 p.R132H-mutant gliomas, tumours with non-canonical IDH mutations were more frequently found in the infratentorial region (5.5% vs 0%; P < 0.05) and were often multicentric (4.8% vs 0.9%; P < 0.05). Compared to IDH1 P.R132H-mutant gliomas, tumours with non-canonical IDH1 mutations were more frequently astrocytomas (65.6% vs 43%, P < 0.05), while those with IDH2 mutations were more frequently oligodendrogliomas (85% vs 48.3%; P < 0.05). The median overall survival was similar in patients with IDH1 p.R132H-mutant gliomas and patients with non-canonical IDH-mutant gliomas. Conclusion: Gliomas with non-canonical IDH mutations have distinct radiological and histological characteristics. The presence of such tumours seems to be associated with genetic predisposition to cancer development. [ABSTRACT FROM AUTHOR]

Published
2021
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13. Intérêt des séquences avancées en IRM dans l’évaluation à la réponse au Bevacizumab. Suivi multimodal de 20 glioblastomes

Author

Seloi, O., primary, Heintz, A., additional, Hanafi, R., additional, Laborde, R., additional, Dou, W., additional, Ruan, S., additional, Prades, J., additional, Le Gars, D., additional, Deramond, H., additional, Lefranc, M., additional, Coutte, A., additional, Toussaint, P., additional, Desenclos, C., additional, Chauffert, B., additional, Boone, M., additional, and Constans, J.M., additional

Published
2017
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14. Importance des variations spectrales durant 36 mois de suivi longitudinal IRM et SRM de 80 patients atteints de glioblastomes traités

Author

Constans, J.-M., primary, Heintz, A., additional, Seloi, O., additional, Deleval, N., additional, Beauvois, M., additional, Hanafi, R., additional, Dallery, F., additional, Dou, W., additional, Ruan, S., additional, Prades, J., additional, Le Gars, D., additional, Baledent, O., additional, Deramond, H., additional, Houessinon, A., additional, Fichten, A., additional, Lefranc, M., additional, Coutte, A., additional, Toussaint, P., additional, Desenclos, C., additional, Chauffert, B., additional, and Boone, M., additional

Published
2017
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17. Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma.

Author

Rosenberg, Shai, Ducray, Francois, Alentorn, Agusti, Dehais, Caroline, Elarouci, Nabila, Kamoun, Aurelie, Marie, Yannick, Tanguy, Marie‐Laure, De Reynies, Aurélien, Mokhtari, Karima, Figarella‐Branger, Dominique, Delattre, Jean‐Yves, Idbaih, Ahmed, Desenclos, C., Sevestre, H., Menei, P., Rousseau, A., Cruel, T., Lopez, S., and Mihai, M‐I

Subjects
CANCER relapse, GLIOMAS, GENETIC polymorphisms, GENOMES, LONGITUDINAL method, MACHINE learning, MULTIVARIATE analysis, GENETIC mutation, RISK assessment, TRANSFERASES, MICRORNA, PROGNOSIS, GENETICS
Abstract

Background: 1p/19q‐codeleted anaplastic gliomas have variable clinical behavior. We have recently shown that the common 9p21.3 allelic loss is an independent prognostic factor in this tumor type. The aim of this study is to identify less frequent genomic copy number variations (CNVs) with clinical importance that may shed light on molecular oncogenesis of this tumor type. Materials and Methods: A cohort of 197 patients with anaplastic oligodendroglioma was collected as part of the French POLA network. Clinical, pathological, and molecular information was recorded. CNV analysis was performed using single‐nucleotide polymorphism arrays. Computational biology and feature selection based on the random forests method were used to identify CNV events associated with overall survival and other clinical‐pathological variables. Results: Recurrent chromosomal events were identified in chromosomes 4, 9, and 11. Forty‐six focal amplification events and 22 focal deletion events were identified. Twenty‐four focal CNV areas were associated with survival, and five of them were significantly associated with survival after multivariable analysis. Nine out of 24 CNV events were validated using an external cohort of The Cancer Genome Atlas. Five of the validated events contain a cancer‐related gene or microRNA: CDKN2A deletion, SS18L1 amplification, RHOA/MIR191 copy‐neutral loss of heterozygosity, FGFR3 amplification, and ARNT amplification. The CNV profile contributes to better survival prediction compared with clinical‐based risk assessment. Conclusion: Several recurrent CNV events, detected in anaplastic oligodendroglioma, enable better survival prediction. More importantly, they help in identifying potential genes for understanding oncogenesis and for personalized therapy. Implications for Practice: Genomic analysis of 197 anaplastic oligodendroglioma tumors reveals recurrent somatic copy number variation areas that may help in understanding oncogenesis and target identification for precision medicine. A machine learning multivariable model built using this genomic information enables better survival prediction. This article discusses genomic copy number variations (CNV) with clinical importance in the setting anaplastic oligodendroglioma. Analysis was based on a grade III glioma patient cohort established by the French POLA network, which allowed for the identification of correlations between CNV events with clinical‐pathological variables and prognosis. [ABSTRACT FROM AUTHOR]

Published
2018
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21. Melanocytic schwannomas. Report of three cases

Author

Peltier J, Cyril Page, Toussaint P, Bruniau A, Desenclos C, and Le Gars D

Subjects
Adult, Aged, 80 and over, Fatal Outcome, Lumbar Vertebrae, Treatment Outcome, Humans, Female, Neuroma, Acoustic, Spinal Cord Neoplasms, Magnetic Resonance Imaging, Thoracic Vertebrae
Abstract

Melanocytic tumors are rare. The literature reports less than 40 cases and suggests that they behave aggressively, can recur and progress to malignancy.We report three patients with melanocytic schwannomas located in the cervical spine, in the thoracic spine and in the lumbar spine. In the two first cases, these symptoms were a spinal cord compression whereas the last patient presented symptoms of cruralgy.MRI always showed an extramedullary intradural tumor arising from the root destroying the intervertebral foramen.The patients underwent laminectomy and the excision was complete. Immunohistochemical stains were positive to S100 and HMB45 antibodies. The evolution was unfavourable for two patients with local recurrence and leptomeningeal metastasis.These three cases demonstrate that melanocytic schwannomas have a guarded prognosis because of their metastatic potential, especially for young people.

Published
2006

44. Melanocytic schwannomas

Author

Peltier, J., primary, Page, C., additional, Toussaint, P., additional, Bruniau, A., additional, Desenclos, C., additional, and Le Gars, D., additional

Published
2005
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50. Correction to: The French glioblastoma biobank (FGB): a national clinicobiological database.

Author

Clavreul, Anne, Soulard, Gwénaëlle, Lemée, Jean-Michel, Rigot, Marion, Fabbro-Peray, Pascale, Bauchet, Luc, Figarella-Branger, Dominique, Menei, Philippe, FGB network, Boone, M., Chauffert, B., Desenclos, C., Herpe, Y-E., Sevestre, H., Tebbakha, R., Blanchet, O., Rousseau, A., Bouillot-Eimer, S., Dubus, P., and Loiseau, H.

Subjects
DATABASES
Abstract

An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

Published
2020
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