Clinical, histopathological, and molecular analyses of IDH-wild-type WHO grade II–III gliomas to establish genetic predictors of poor prognosis

Kuwahara, Kiyonori; Ohba, Shigeo; Nakae, Shunsuke; Hattori, Naoko; Pareira, Eriel Sandika; Yamada, Seiji; Sasaki, Hidenao; Abe, Masato; Hasegawa, Mitsuhiro; Hirose, Yuichi

doi:10.1007/s10014-019-00348-9

Cited by 19 publications

(13 citation statements)

References 29 publications

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“…Studies have shown that epidermal growth factor receptor ( EGFR ) amplification, telomerase reverse transcriptase ( TERT ) promoter mutation, the gain of chromosome 7, and the loss of chromosome 10q are all associated with the prognosis of these tumors. 19 , 20 As more knowledge is gained about the molecular types with poor prognosis among IDH1/2- wildtype tumors, the cIMPACT-NOW (Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy) has suggested diagnostic criteria to classify them as “diffuse astrocytic glioma, IDH -wildtype, with molecular features of glioblastoma, WHO grade IV.” 21 Our results support the need for a new molecular classification of IDH1/2 -wildtype gliomas, and especially anaplastic astrocytomas, and suggests that there may be more of these tumors than the known prevalence, depending on the population.…”

Section: Discussionmentioning

confidence: 99%

Estimation of the occurrence rates of IDH1 and IDH2 mutations in gliomas and the reconsideration of IDH-wildtype anaplastic astrocytomas: an institutional experience

2021

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Objectives Most diffuse gliomas are reported to harbor isocitrate dehydrogenase ( IDH) mutations. However, when these mutations are tested in clinical practice, the results are often negative. Methods This study examined the frequency of IDH1 and IDH2 mutations in gliomas classified according to the revised 2016 World Health Organization classification, and investigated their prognostic relevance. We tested 87 gliomas for IDH1 and IDH2 mutations using the peptide nucleic acid clamp method. Results IDH1 mutations were observed in 42% of diffuse astrocytomas, 23% of anaplastic astrocytomas, all oligodendrogliomas and anaplastic oligodendrogliomas, and 17% of glioblastomas. An IDH2 mutation was identified in one case of diffuse astrocytoma. In the survival analysis of diffuse astrocytic tumors, patients with IDH1/2-wildtype anaplastic astrocytomas tended to have a poor prognosis, similar to that of glioblastomas. Conclusions IDH2 mutations were infrequent in gliomas. In anaplastic astrocytomas, the frequency of IDH1/2-wildtype was relatively high, and the prognosis of patients with this type of tumor was very similar to that of those with glioblastomas. It may therefore be necessary to reconsider the classification and treatment strategies for IDH1/2-wildtype anaplastic astrocytomas.

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Section: Discussionmentioning

confidence: 99%

Estimation of the occurrence rates of IDH1 and IDH2 mutations in gliomas and the reconsideration of IDH-wildtype anaplastic astrocytomas: an institutional experience

2021

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“…Histological prediction of patient survival based on WHO classi cation has been challenged with the improvement of accurate molecular strati cation of gliomas [20]. Numerous studies demonstrate that IDH mutations induce aberrant DNA histone and methylation thus lead to glioma CpG-island methylator phenotype (G-CIMP), which is considered to be correlated with distinct biological and clinical characters in LGGs [21,22].…”

Section: Discussionmentioning

confidence: 99%

FABP5 enhances malignancies of lower-grade gliomas via canonical activation of NF-κB signaling

Wang

Alafate

Wang

et al. 2020

Preprint

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Abstract Background Lower-grade gliomas (LGGs) are grade II/III gliomas based on the WHO classification with significant genetic heterogeneity and clinical properties. Traditional histological classification of gliomas has been challenged by the improvement of molecular stratification, however, the reproducibility and diagnostic accuracy of LGGs classification remain poor. Methods In this study, we derived all relevant data of LGGs including TCGA and CGGA databases from official websites. Bioinformatic analyses unveiled the clinical significance of FABP5 and its potential downstream targets. IHC, qRT-PCR and western blot assays were further conducted to validate those bioinformatic findings. Moreover, lentiviral transduction assays were performed to evaluate the function of FABP5 in patient-derived cell lines. Results We identified fatty acid binding protein 5 (FABP5) as one of the most enriched genes in malignant LGGs and elevated FABP5 revealed severe outcomes in LGGs. Functionally, lentiviral suppression of FABP5 reduced malignant characters including proliferation, cloning formation, migration, invasion and TMZ resistance, contrarily, the malignancies of LGGs were enhanced by exogenous overexpression of FABP5. Mechanistically, epithelial-mesenchymal transition (EMT) was correlated to FABP5 expression in LGGs and tumor necrosis factor α (TNFα)-dependent NF-κB signaling was involved in this process. Furthermore, FABP5 induced phosphorylation of inhibitor of nuclear factor kappa-B kinase α (IKKα) thus activated nuclear factor kappa-B (NF-κB) signaling. Conclusion Taken together, our study indicated that FABP5 enhances malignancies of LGGs through canonical activation of NF-κB signaling, which could be used as individualized prognostic biomarker and potential therapeutic target of LGGs.

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“…Grade-II tumor is a low-grade Astrocytoma; Grade-III tumor is called Anaplastic Astrocytoma. Grade-IV tumor, the most aggressive type, is called Glioblastoma [18][19].…”

Section: Introductionmentioning

confidence: 99%

Detection and Classification of Brain Tumor in MRI Images Using Wavelet Transform and Convolutional Neural Network

Sarhan

2020

JAMMR

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A brain tumor is a mass of abnormal cells in the brain. Brain tumors can be benign or malignant. Conventional diagnosis of a brain tumor by the radiologist, is done by examining a set of images produced by magnetic resonance imaging (MRI). Many computer-aided detection (CAD) systems have been developed in order to help the radiologist reach his goal of correctly classifying the MRI image. Convolutional neural networks (CNNs) have been widely used in the classification of medical images. This paper presents a novel CAD technique for the classification of brain tumors in MRI images The proposed system extracts features from the brain MRI images by utilizing the strong energy compactness property exhibited by the Discrete Wavelet transform (DWT). The Wavelet features are then applied to a CNN to classify the input MRI image. Experimental results indicate that the proposed approach outperforms other commonly used methods and gives an overall accuracy of 98.5%.

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Clinical, histopathological, and molecular analyses of IDH-wild-type WHO grade II–III gliomas to establish genetic predictors of poor prognosis

Cited by 19 publications

References 29 publications

Estimation of the occurrence rates of IDH1 and IDH2 mutations in gliomas and the reconsideration of IDH-wildtype anaplastic astrocytomas: an institutional experience

Estimation of the occurrence rates of IDH1 and IDH2 mutations in gliomas and the reconsideration of IDH-wildtype anaplastic astrocytomas: an institutional experience

FABP5 enhances malignancies of lower-grade gliomas via canonical activation of NF-κB signaling

Detection and Classification of Brain Tumor in MRI Images Using Wavelet Transform and Convolutional Neural Network

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