scholarly journals GE-01 * MOLECULAR AND PATHOLOGIC SUBSETS OF LOW GRADE GLIOMAS AND GLIONEURONAL TUMORS IDENTIFIED BY microRNA PROFILING

2014 ◽  
Vol 16 (suppl 5) ◽  
pp. v96-v96
Author(s):  
H. Ames ◽  
M. A. Vizcaino ◽  
F. Rodriguez
Keyword(s):  
Low Grade ◽  
Low Grade Gliomas ◽  
Microrna Profiling ◽  
Glioneuronal Tumors

scholarly journals LGG-06. COMPREHENSIVE GENOMIC CHARACTERIZATION AND INTEGRATED CLINICAL ANALYSIS OF LOW-GRADE GLIOMAS IN CHILDREN WITH NEUROFIBROMATOSIS TYPE 1

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i32-i32
Author(s):  
Michael Fisher ◽  
David Jones ◽  
Yimei Li ◽  
Xiaofan Guo ◽  
Poonam Sonawane ◽  
...  
Keyword(s):  
Neurofibromatosis Type 1 ◽  
Pik3ca Mutation ◽  
Neurofibromatosis Type ◽  
Clinical Analysis ◽  
Genetic Alterations ◽  
Low Grade ◽  
Low Grade Gliomas ◽  
Fgfr1 Mutation ◽  
Glioneuronal Tumors

Abstract Background Low-grade gliomas (LGGs) arising in children with neurofibromatosis type 1 (NF1) are usually not biopsied. To identify secondary genetic alterations or molecular features that may contribute to pathogenesis and correlate with clinical behavior, we initiated a comprehensive molecular and clinical analysis of pediatric NF1-LGGs. Methods NF1-LGGs were analysed by whole-genome sequencing (31), targeted gene panel sequencing (9), RNAseq transcriptomal profiling (33) and genome-wide DNA methylation analysis (67). Clinical annotation was available for 48 subjects. Results Most LGGs harbored bi-allelic NF1 inactivation as the sole genetic abnormality, but 11% had additional alterations (FGFR1 mutation, n=3; PIK3CA mutation, n=2; homozygous 9p21 deletion, n=2; MYB:QKI fusion, n=1; SETD2 mutation, n=1; EGFR amplification, n=1). FGFR1 mutation conferred additional growth advantage in multiple complementary murine Nf1 models. 88% of NF1-LGGs resembled sporadic pilocytic astrocytoma (PA) by methylation, higher than that based on histology. Non-PA methylation patterns included low-grade glial/glioneuronal tumors, rosette-forming glioneuronal tumors, MYB/MYBL1-altered glioma, and high-grade astrocytoma with piloid features (2 tumors histologically diagnosed as LGG). In total, 18% of samples were classified as non-PA and/or harbored an additional non-NF1 mutation. Non-PA methylation class tumors were more likely to harbor an additional non-NF1 mutation (p=0.005). 7.7% of optic pathway hypothalamic gliomas (OPHGs) had other mutations or were not classified by methylation as PA, compared with 20.6% of NF1-LGGs arising elsewhere. There was no difference based on age for the presence of an additional non-NF1 mutation or non-PA methylation class. Conclusions Given the overall low occurrence of non-NF1 mutations or non-PA methylation class tumors in this series, routine clinical biopsy of typically-appearing NF1-LGG may not be indicated, particularly for children with OPHG. Biopsy should be considered for non-OPHG tumors refractory to conventional treatment. As additional agents are developed and treatment strategies evolve, the rationale for biopsy of NF1-LGG may become stronger.

scholarly journals MicroRNA profiling of low-grade glial and glioneuronal tumors shows an independent role for cluster 14q32.31 member miR-487b

2016 ◽  
Vol 30 (2) ◽  
pp. 204-216 ◽  
Author(s):  
Heather Marion Ames ◽  
Ming Yuan ◽  
Maria Adelita Vizcaíno ◽  
Wayne Yu ◽  
Fausto J Rodriguez
Keyword(s):  
Low Grade ◽  
Microrna Profiling ◽  
Glioneuronal Tumors

MicroRNA profiling of pediatric low-grade gliomas (pLGGs)

2016 ◽  
Vol 61 ◽  
pp. S28
Author(s):  
G. Catanzaro ◽  
Z.M. Besharat ◽  
A. Mastronuzzi ◽  
A. Carai ◽  
E. Miele ◽  
...  
Keyword(s):  
Low Grade ◽  
Low Grade Gliomas ◽  
Microrna Profiling

scholarly journals Treatment burden and long‐term health deficits of patients with low‐grade gliomas or glioneuronal tumors diagnosed during the first year of life

Cancer ◽  
2019 ◽  
Vol 125 (7) ◽  
pp. 1163-1175 ◽  
Author(s):  
Anthony P. Y. Liu ◽  
Camden Hastings ◽  
Shengjie Wu ◽  
Johnnie K. Bass ◽  
Andrew M. Heitzer ◽  
...  
Keyword(s):  
First Year ◽  
Low Grade ◽  
Treatment Burden ◽  
Low Grade Gliomas ◽  
Glioneuronal Tumors ◽  
First Year Of Life

scholarly journals OP17 * MICRORNA PROFILING USING SMALL RNA-SEQ IN PAEDIATRIC LOW GRADE GLIOMAS

2014 ◽  
Vol 16 (suppl 6) ◽  
pp. vi19-vi19
Author(s):  
J. N. Jeyapalan ◽  
T. A. Jones ◽  
R. G. Tatevossian ◽  
I. Qaddoumi ◽  
D. W. Ellison ◽  
...  
Keyword(s):  
Small Rna ◽  
Low Grade ◽  
Rna Seq ◽  
Low Grade Gliomas ◽  
Microrna Profiling

scholarly journals Are low-grade gliomas of mesial temporal area alone?

2019 ◽  
Vol 10 ◽  
pp. 170
Author(s):  
Mehmet Yigit Akgun ◽  
Semih Can Cetintas ◽  
Rahsan Kemerdere ◽  
Seher Naz Yeni ◽  
Taner Tanriverdi
Keyword(s):  
Focal Cortical Dysplasia ◽  
Temporal Cortex ◽  
Oncological Outcome ◽  
Histopathological Diagnosis ◽  
Low Grade ◽  
Temporal Area ◽  
Low Grade Gliomas ◽  
Magnetic Resonance Imaging Mri ◽  
Glioneuronal Tumors ◽  
Temporal Neocortex

Background: Temporal neocortex which appears normal on magnetic resonance imaging (MRI) may have pathological tissues in low-grade gliomas (LGG) of pure mesial temporal area. Resection of the cortex may be required together with mesial temporal glioma for satisfactory seizure and oncological outcome. The aim of this study was to explore the presence of any pathological tissue on the temporal cortex that appeared normal on preoperative MRI in patients with pure mesial temporal LGGs. Methods: This prospective study included 10 patients who underwent surgical resection of temporal lobe for LGG of mesial temporal area. The temporal neocortex with normal appearance on MRI and mesial temporal area were resected separately, and histopathological diagnosis was performed. Results: LGGs of the mesial temporal area were diagnosed with glioneuronal tumors in 7 (70%) and low-grade astrocytoma in 2 (20%) patients. Regarding the temporal cortex, gliosis and focal cortical dysplasia were found in 7 (70%) and 2 (20%) patients. In one patient temporal cortex did not contain any pathological tissue. All were seizure-free and no tumor recurrence was noted at the last follow-up. Conclusion: Mesial temporal LGGs are not alone and a high proportion of temporal neocortex appeared normal on preoperative MRI, may contain dual pathology. Thus, anterior temporal resection should be performed to have satisfactory seizure and oncological outcomes.

scholarly journals Domain Mapping and Deep Learning from Multiple MRI Clinical Datasets for Prediction of Molecular Subtypes in Low Grade Gliomas

2020 ◽  
Vol 10 (7) ◽  
pp. 463 ◽  
Author(s):  
Muhaddisa Barat Ali ◽  
Irene Yu-Hua Gu ◽  
Mitchel S. Berger ◽  
Johan Pallud ◽  
Derek Southwell ◽  
...  
Keyword(s):  
Molecular Subtypes ◽  
Negative Impact ◽  
Molecular Classification ◽  
Tumor Segmentation ◽  
Test Accuracy ◽  
Low Grade ◽  
Idh Mutation ◽  
Molecular Type ◽  
Low Grade Gliomas ◽  
Domain Mapping

Brain tumors, such as low grade gliomas (LGG), are molecularly classified which require the surgical collection of tissue samples. The pre-surgical or non-operative identification of LGG molecular type could improve patient counseling and treatment decisions. However, radiographic approaches to LGG molecular classification are currently lacking, as clinicians are unable to reliably predict LGG molecular type using magnetic resonance imaging (MRI) studies. Machine learning approaches may improve the prediction of LGG molecular classification through MRI, however, the development of these techniques requires large annotated data sets. Merging clinical data from different hospitals to increase case numbers is needed, but the use of different scanners and settings can affect the results and simply combining them into a large dataset often have a significant negative impact on performance. This calls for efficient domain adaption methods. Despite some previous studies on domain adaptations, mapping MR images from different datasets to a common domain without affecting subtitle molecular-biomarker information has not been reported yet. In this paper, we propose an effective domain adaptation method based on Cycle Generative Adversarial Network (CycleGAN). The dataset is further enlarged by augmenting more MRIs using another GAN approach. Further, to tackle the issue of brain tumor segmentation that requires time and anatomical expertise to put exact boundary around the tumor, we have used a tight bounding box as a strategy. Finally, an efficient deep feature learning method, multi-stream convolutional autoencoder (CAE) and feature fusion, is proposed for the prediction of molecular subtypes (1p/19q-codeletion and IDH mutation). The experiments were conducted on a total of 161 patients consisting of FLAIR and T1 weighted with contrast enhanced (T1ce) MRIs from two different institutions in the USA and France. The proposed scheme is shown to achieve the test accuracy of 74 . 81 % on 1p/19q codeletion and 81 . 19 % on IDH mutation, with marked improvement over the results obtained without domain mapping. This approach is also shown to have comparable performance to several state-of-the-art methods.

Neurodevelopmental outcomes of children with low-grade gliomas

2008 ◽  
Vol 14 (3) ◽  
pp. 196-202 ◽  
Author(s):  
M. Douglas Ris ◽  
Dean W. Beebe
Keyword(s):  
Low Grade ◽  
Neurodevelopmental Outcomes ◽  
Low Grade Gliomas
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