BI-27 * ANALYSIS OF THE BIOCHEMICAL PROFILE OF LOW GRADE GLIOMA WITH DIFFERENT IDH1 MUTATION STATUS USING VIBRATIONAL SPECTROSCOPY

Abstract BACKGROUND Tumour Protein 53 (TP53) is a tumour suppressor gene that is mutated in at least 50% of human malignancies. The prevalence of TP53 mutation is much higher in astrocytomas with reports of up to 75% TP53 mutant cases. Rare cases of TP53 mutation also exist in oligodendroglial tumours (10–13%). P53 pathway is therefore an important factor in low-grade glioma tumorigenesis. Although the prognostic impact of TP53 mutations has been studied previously, no concrete concordance were reached between the studies. In this study, we investigated the prognostic effects of TP53 mutation in astrocytoma and oligodendroglioma. MATERIAL AND METHODS A cohort of 65 matched primary and recurrent fresh frozen tumours were sequenced to identify hotspot exons of TP53 mutation. Exons 1 to 10 were sequenced and pathogenic mutations were mostly predominant between Exons 4 and 8. The cohort was further expanded with 78 low grade glioma fresh frozen tissues and hotspot exons were sequenced. Selecting only the primary tumour from 65 matched tumours, a total of 50 Astrocytoma cases and 51 oligodendroglioma cases were analysed for prognostic effects of TP53. Only pathogenic TP53 mutations confirmed through COSMIC and NCBI databases were included in the over survival and progression-free survival analysis. RESULTS 62% (31/50) of astrocytomas and 16% (8/51) of oligodendrogliomas harboured pathogenic TP53 mutations. Pathogenic hotspot mutations in codon 273 (c.817 C>T and c.818 G>A) was prevalent in astrocytoma with 58% (18/31) of tumours with these mutations. TP53 mutation status was maintained between primary and recurrent tumours in 93% of cases. In astrocytoma, overall survival of TP53 mutant patients was longer compared to TP53 wild-type patients (p<0.01) but was not significant after adjusting for age, gender, grade and IDH1 mutation status. In contrast, astrocytoma patients with specific TP53 mutation in codon 273 showed significantly better survival compared to other TP53 mutant and TP53 wild-type patients combined (p<0.01) in our multivariate analysis. Time to first recurrence (progression-free survival) of TP53 mutant patients was significantly longer than TP53 wild-type patients (p<0.01) after adjustments were made, while TP53 mutation in codon 273 was not prognostic for progression-free survival. In oligodendroglioma patients, TP53 mutations did not significantly affect overall survival and progression-free survival. CONCLUSION In agreement with others, TP53 mutation is more prevalent in Astrocytoma and mutations in codon 273 are significantly associated with longer survival.

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IDH1 mutation is associated with a higher preoperative seizure incidence in low-grade glioma: A systematic review and meta-analysis

Seizure ◽

10.1016/j.seizure.2018.01.011 ◽

2018 ◽

Vol 55 ◽

pp. 76-82 ◽

Cited By ~ 7

Author(s):

Yucai Li ◽

Xia Shan ◽

Zhifeng Wu ◽

Yinyan Wang ◽

Miao Ling ◽

...

Keyword(s):

Systematic Review ◽

Meta Analysis ◽

Idh1 Mutation ◽

Low Grade Glioma ◽

Low Grade

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Use of DNA copy number analysis of grade 2-4 gliomas to reveal differences in molecular ontogeny associated with IDH mutation status.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.2026 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 2026-2026

Author(s):

Mariko Sato ◽

Kenneth D. Aldape ◽

Clinton C Mason ◽

Kristin Diefes ◽

Lindsey Heathcock ◽

...

Keyword(s):

Copy Number ◽

Genetic Alterations ◽

Idh1 Mutation ◽

Low Grade ◽

Copy Number Alterations ◽

Copy Number Analysis ◽

Mutation Status ◽

Younger Age ◽

Ffpe Samples ◽

Molecular Inversion Probes

2026 Background: The genetic alterations of glioma have been studied extensively. IDH1 mutation is associated with younger age and better survival. However, differences in molecular ontogeny within glioma related to IDH1 mutation remain unknown. Here we describe a detailed analysis of copy number alterations (CNA) between IDH1mut vs IDH1wt gliomas of grade 2-3 and 4. Methods: CNA were detected by molecular inversion probes (Affymetrix) and analyzed with Nexus Copy Number Software (BioDiscovery). DNA was extracted from 94 patient FFPE samples including grade 2-3: IDH1wt (n = 17) and IDH1mut (n = 28), and grade IV: IDH1wt ( n = 25) and IDH1mut(n = 24). Chromothripsis was detected using a stringent criteria of at least ten switches of CNA in individual chromosomes. Results: We validated prior findings that IDH1wt GBM have higher frequency of Chr7 amplification (including EGFR) and loss of Chr10 (including PTEN). Other CNA across all grades were: gain of 19q12 and loss of 14q11 in IDH1wt, and gain of 11q21, 10p11, 8q21 and loss of 11p15, 19q13 in IDH1mut. Within grade 2-3 samples, few CNA were associated with mutation status: 2-3wt demonstrated higher frequencies of gain of 7q and loss of 10q, 14q11, and 22q13, while 2-3mut demonstrated higher frequencies of 11q21 gain and 19q13 loss. Grade 4 tumors demonstrated more CNA that differed by mutation status, with 4wt tumors demonstrating gain of 7 and loss of 10 and 14q11, while 4mut demonstrated gains of 8q, 10p, 12p13, 1q23, and loss of 11p15, 3p, 19q13, among others. Comparison of grade 2-3mut vs grade 4mut tumors demonstrated larger number of CNA in the grade 4mut tumors including gain of 1p, 14q, 13q33, 9p, 8q and loss of 22q, 11p15, 10q, and 3p, among others. A significantly higher incidence of chromothripsis events was observed in grade 4mut compared to grade 4wt (p = 0.0374). Conclusions: CNA analysis showed significant differences in molecular ontogeny between IDH1wt and IDH1mut, some of which may further elucidate pathogenesis. Significant CNA increases and increased chromthripsis in grade 4mut support malignant transformation of low grade gliomas through accumulation of genomic instability and genomic catastrophe.

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Deep Convolutional Neural Network to predict 1p19q co-deletion and IDH1 mutation status from MRI in Low Grade Gliomas

10th International Conference on Pattern Recognition Systems (ICPRS-2019) ◽

10.1049/cp.2019.0240 ◽

2019 ◽

Author(s):

S.R. González ◽

I. Zemmoura ◽

C. Tauber

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Idh1 Mutation ◽

Deep Convolutional Neural Network ◽

Low Grade ◽

Mutation Status ◽

Low Grade Gliomas

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NI-40 * MR IMAGING AND SPECTROSCOPY PROVIDES INSIGHT INTO MALIGNANT TRANSFORMATION AND IDH-MUTATION STATUS IN DIFFUSE LOW-GRADE GLIOMA

Neuro-Oncology ◽

10.1093/neuonc/nou264.38 ◽

2014 ◽

Vol 16 (suppl 5) ◽

pp. v146-v147

Author(s):

L. Jalbert ◽

J. Phillips ◽

A. Molinaro ◽

S. Chang ◽

S. Nelson

Keyword(s):

Mr Imaging ◽

Malignant Transformation ◽

Low Grade Glioma ◽

Low Grade ◽

Idh Mutation ◽

Mutation Status ◽

Imaging And Spectroscopy ◽

Insight Into

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Combined IDH1 mutation and MGMT methylation status on long-term survival of patients with cerebral low-grade glioma

Clinical Neurology and Neurosurgery ◽

10.1016/j.clineuro.2015.07.019 ◽

2015 ◽

Vol 138 ◽

pp. 37-44 ◽

Cited By ~ 19

Author(s):

Kazuhiro Tanaka ◽

Takashi Sasayama ◽

Katsu Mizukawa ◽

Kumi Takata ◽

Nor Shazrina Sulaiman ◽

...

Keyword(s):

Methylation Status ◽

Idh1 Mutation ◽

Low Grade Glioma ◽

Low Grade ◽

Mgmt Methylation ◽

Term Survival ◽

Long Term Survival

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Establishment of an Endocytosis-Related Prognostic Signature for Patients With Low-Grade Glioma

Frontiers in Genetics ◽

10.3389/fgene.2021.709666 ◽

2021 ◽

Vol 12 ◽

Author(s):

Dawei Wang ◽

Shiguang Liu ◽

Guangxin Wang

Keyword(s):

Functional Analysis ◽

Expression Profiles ◽

Gene Signature ◽

Low Grade Glioma ◽

Gene Set Enrichment Analysis ◽

Low Grade ◽

Normal Brain ◽

Ppi Network ◽

Prognostic Signature ◽

Mutation Status

BackgroundLow-grade glioma (LGG) is a heterogeneous tumor that might develop into high-grade malignant glioma, which markedly reduces patient survival time. Endocytosis is a cellular process responsible for the internalization of cell surface proteins or external materials into the cytosol. Dysregulated endocytic pathways have been linked to all steps of oncogenesis, from initial transformation to late invasion and metastasis. However, endocytosis-related gene (ERG) signatures have not been used to study the correlations between endocytosis and prognosis in cancer. Therefore, it is essential to develop a prognostic model for LGG based on the expression profiles of ERGs.MethodsThe Cancer Genome Atlas and the Genotype-Tissue Expression database were used to identify differentially expressed ERGs in LGG patients. Gene ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene set enrichment analysis methodologies were adopted for functional analysis. A protein-protein interaction (PPI) network was constructed and hub genes were identified based on the Search Tool for the Retrieval of Interacting Proteins database. Univariate and multivariate Cox regression analyses were used to develop an ERG signature to predict the overall survival (OS) of LGG patients. Finally, the association between the ERG signature and gene mutation status was further analyzed.ResultsSixty-two ERGs showed distinct mRNA expression patterns between normal brain tissues and LGG tissues. Functional analysis indicated that these ERGs were strikingly enriched in endosomal trafficking pathways. The PPI network indicated that EGFR was the most central protein. We then built a 29-gene signature, dividing patients into high-risk and low-risk groups with significantly different OS times. The prognostic performance of the 29-gene signature was validated in another LGG cohort. Additionally, we found that the mutation scores calculated based on the TTN, PIK3CA, NF1, and IDH1 mutation status were significantly correlated with the endocytosis-related prognostic signature. Finally, a clinical nomogram with a concordance index of 0.881 predicted the survival probability of LGG patients by integrating clinicopathologic features and ERG signatures.ConclusionOur ERG-based prediction models could serve as an independent prognostic tool to accurately predict the outcomes of LGG.

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