scholarly journals Dysregulated Expression and Methylation Analysis Identified TLX1NB as a Novel Recurrence Marker in Low-Grade Gliomas

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Hongzhou Duan ◽  
Zuozhen Yang ◽  
Chen Li ◽  
Jiayong Zhang ◽  
Shengli Shen ◽  
...  
Keyword(s):  
Low Grade ◽  
Methylation Data ◽  
Methylation Analysis ◽  
Gene Methylation ◽  
Poor Survival ◽  
Curative Effect ◽  
Low Grade Gliomas ◽  
Complete Surgical Resection ◽  
Early Biomarker ◽  
Low Expression

Low-grade gliomas (LGGs) are the most common CNS tumors, and the main therapy for LGGs is complete surgical resection, due to its curative effect. However, LGG recurrence occurs frequently. Biomarkers play a crucial role in evaluating the recurrence and prognosis of LGGs. Numerous studies have focused on LGG prognosis. However, the multiomics research investigating the roles played by gene methylation and expression in LGG recurrence remains limited. In this study, we integrated the TCGA and GEO datasets, analyzing RNA and methylation data for recurrence (R) and nonrecurrence (NR) groups. We found a low expression of TLX1NB and high methylation in recurrence patients. Low expression of TLX1NB is associated with poor survival (OS: p = 0.04 ). The expression of TLX1NB is likely to play a role in the prognosis of LGG. Therefore, TLX1NB may represent an alternative early biomarker for the recurrence of low-grade gliomas.

scholarly journals High Expression of H2BC12 Predicts Poor Survival Outcome of Low-Grade Gliomas: A Study Based on TCGA Data

2021 ◽  
Author(s):  
Yilei Xiao ◽  
Zhaoquan Xing ◽  
Mengyou Li ◽  
Xin Li ◽  
Ding Wang ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Survival Outcomes ◽  
Low Grade ◽  
Primary Therapy ◽  
Poor Survival ◽  
Gene Set Enrichment ◽  
Data Set ◽  
Gene Set ◽  
Low Grade Gliomas

Abstract Purpose Low-grade gliomas (LGG) have highly variable clinical behaviors, with a high incidence of disease progression as 70% within ten years. Regardless of treatment combining surgery and radiotherapy or chemotherapy, LGG is still associated with adverse survival outcomes. Therefore, our study was performed to satisfy the increasing demand of novel sensitive biomarkers and therapeutic targets in treatment and diagnosis of LGG. Methods The TCGA data set was used to examine the relationship between H2BC12 expression and clinical pathologic characteristics. The significance of H2BC12 expression in prognosis was also investigated. In addition, H2BC12 expression-related pathways were enriched by gene set enrichment analysis (GSEA). Association analysis of H2BC12 gene expression and immune infiltration was performed by single sample gene set enrichment analysis (ssGSEA). Results Significantly up-regulated expression of H2BC12 mRNA was found in LGG tissue when compared to normal tissue and was proven to be diagnostic (have diagnostic significance) for LGG. In the meantime, high H2BC12 levels were associated with WHO grade, IDH status, 1p/19q codeletion, primary therapy outcome and histological type of LGG, and additionally, prognostic for adverse survival outcomes. In the multivariate analysis, high H2BC12 levels were identified to be an independent predictor for poor survival outcomes of LGG patients. Pathways in cancer, signaling by Wnt or PI3K-AKT signaling pathway, DNA repair, cellular senescence and DNA double strand break repair were differentially activated in the phenotype that positively associated with H2BC12. Conclusion H2BC12 is a promising biomarker for the diagnosis and prognosis of LGG.

Gene Methylation Data – a New Challenge for Bioinformaticians?

2005 ◽  
Vol 44 (04) ◽  
pp. 516-519 ◽  
Author(s):  
H. M. Müller ◽  
H. Fiegl ◽  
M. Widschwendter ◽  
G. Goebel
Keyword(s):  
Dna Methylation ◽  
Study Design ◽  
Marker Genes ◽  
Methylation Data ◽  
Methylation Analysis ◽  
Gene Methylation ◽  
Research Activity ◽  
Molecular Alterations ◽  
Research Questions ◽  
Dna Methylation Analysis

Summary Objectives: Changes in the status of DNA methylation, known as epigenetic alterations, are among the most common molecular alterations in human neoplasia. For the first time, we reported on the analysis of fecal DNA from patients with CRC to determine the feasibility, sensitivity and specificity of this approach. We want to present basic information about DNA methylation analysis in the context of bioinformatics, the study design and several statistical experiences with gene methylation data. Additionally we outline chances and new research questions in the field of DNA methylation. Methods: We present current approaches to DNA methylation analysis based on one reference study. Its study design and the statistical analysis is reflected in the context of biomarker development. Finally we outline perspectives and research questions for statisticians and bioinformaticians. Results: Identification of at least three genes as potential DNA methylation-based tumor marker genes (SFRP2, SFRP5, PGR). Conclusions: DNA methylation analysis is a rising topic in molecular genetics. Gene methylation will push the extension of biobanks to include new types of genetic data. Study design and statistical methods for the detection of methylation biomarkers must be improved. For the purpose of establishing methylation analysis as a new diagnostic/prognostic tool the adaptation of several approaches has become a challenging field of research activity.

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.

Prognostic histopathologic features of canine glial tumors

2021 ◽  
pp. 030098582110257
Author(s):  
Joshua L. Merickel ◽  
G. Elizabeth Pluhar ◽  
Aaron Rendahl ◽  
M. Gerard O’Sullivan
Keyword(s):  
Brain Tumor ◽  
Median Survival ◽  
Low Grade ◽  
Astrocytic Tumors ◽  
Translational Model ◽  
Poor Survival ◽  
Whole Brain ◽  
Tumor Types ◽  
Tumor Biopsies ◽  
Prognostic Data

Gliomas are relatively common tumors in aged dogs (especially brachycephalic breeds), and the dog is proving to be useful as a translational model for humans with brain tumors. Hitherto, there is relatively little prognostic data for canine gliomas and none on outcome related to specific histological features. Histologic sections of tumor biopsies from 33 dogs with glioma treated with surgical resection and immunotherapy and 21 whole brains obtained postmortem were reviewed. Tumors were diagnosed as astrocytic, oligodendroglial, or undefined glioma using Comparative Brain Tumor Consortium criteria. Putative features of malignancy were evaluated, namely, mitotic counts, glomeruloid vascularization, and necrosis. For biopsies, dogs with astrocytic tumors lived longer than those with oligodendroglial or undefined tumor types (median survival 743, 205, and 144 days, respectively). Dogs with low-grade gliomas lived longer than those with high-grade gliomas (median survival 734 and 194 days, respectively). Based on analysis of tumor biopsies, low mitotic counts, absence of glomeruloid vascularization, and absence of necrosis correlated with increased survival (median 293, 223, and 220 days, respectively), whereas high mitotic counts, glomeruloid vascularization, and necrosis correlated with poor survival (median 190, 170, and 154 days, respectively). Mitotic count was the only histological feature in biopsy samples that significantly correlated with survival ( P < .05). Whole-brain analyses for those same histologic features had similar and more robust correlations, and were statistically significant for all features ( P < .05). The small size of biopsy samples may explain differences between biopsy and whole-brain tumor data. These findings will allow more accurate prognosis for gliomas.

scholarly journals LGG-18. EVEROLIMUS TREATMENT IN PEDIATRIC PATIENTS AFFECTED BY LOW-GRADE GLIOMAS (pLGG) NON-TSC, BRAF v600-WT

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii369-iii369
Author(s):  
Antonella Cacchione ◽  
Evelina Miele ◽  
Maria Chiara Lodi ◽  
Andrea Carai ◽  
Giovanna Stefania Colafati ◽  
...  
Keyword(s):  
Adverse Event ◽  
Disease Progression ◽  
Mapk Pathway ◽  
Brain Mri ◽  
Mammalian Target Of Rapamycin ◽  
Low Grade ◽  
Duration Of Treatment ◽  
Tumor Biopsy ◽  
Low Grade Gliomas ◽  
Personalized Approach

Abstract BACKGROUND MAPK pathway is the hallmark of pediatric low grade gliomas (pLGGs); hyperactivation of mTOR (mammalian target of rapamycin) might be a suitable biomarker for therapeutic response. We investigated the feasibility of Everolimus, mTOR inhibitor, in patients affected by pLGGs. METHODS Patients 1 to 18 years old, diagnosed with pLGG, with a positive tumor biopsy for mTOR/phospho-mTOR and radiological and / or clinical disease progression, treated at Bambino Gesù Children’s Hospital in Rome were evaluated. Tumor DNA methylation analysis was performed in 10 cases. Exclusion criteria included: Tuberous Sclerosis patients, Sub Ependymal Giant Astrocytoma. Everolimus was administered orally at a dose of 2.5 mg or 5 mg daily based on body weight. Patients were evaluated with brain MRI every 4, 8 and 12 months after treatment start and every six months thereafter. RESULTS 16 patients were enrolled from September 2014 and 2019. The median age was 7.5 years old. All patients had at least one adverse event. Events rated as severe (grade 3/4) were reported in 6 patients. Stomatitis was the most frequent adverse event. One patient discontinued treatment due to grade 4 toxicity (ulcerative stomatitis and fatigue). The median duration of treatment was 21 months (4–57 months). Brain MRI evaluations have showed disease stability in 11 patients, partial response in 2 patients and disease progression in 3 patients. CONCLUSIONS Everolimus has proven to be well tolerated and effective treatment in terms of disease stability in patients with pLGGs. It’s also an excellent example of chemo-free personalized approach.

scholarly journals Hemispheric low-grade gliomas

2016 ◽  
Vol 32 (10) ◽  
pp. 1787-1787
Author(s):  
Gianpiero Tamburrini ◽  
Jose Hinojosa
Keyword(s):  
Low Grade ◽  
Low Grade Gliomas
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