Practical implications of integrated glioma classification according to the World Health Organization classification of tumors of the central nervous system 2016

Malzkorn, Bastian; Reifenberger, Guido

doi:10.1097/cco.0000000000000327

Cited by 65 publications

(45 citation statements)

References 46 publications

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“…Malzkorn and Reifenberger15 put forth the practical implications concerning increased costs, quality control of newer techniques and increased turnaround time of diagnosis.…”

Section: Discussionmentioning

confidence: 99%

A simple algorithmic approach using histology and immunohistochemistry for the current classification of adult diffuse glioma in a resource-limited set-up

et al. 2017

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In a resource-limited set-up, histology with IHC (IDH1(R132H) and ATRX) form the baseline to reasonably derive four histomolecular subgroups of diffuse glioma. Of these, we recommend, OA,NOS and IDH1(R132H)-non-mt ODG,NOS to be our priority for performing 1p/19q co-deletion studies in comparison to IDH-mt ODG,NOS, and it would not be mandatory for astrocytoma. Sequencing for rare IDH mutations is advised for A,NOS and OA,NOS groups, but not for the IDH1(R132H)-non-mutant diffuse gliomas with 1p/19q co-deletion.

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“…Malzkorn and Reifenberger15 put forth the practical implications concerning increased costs, quality control of newer techniques and increased turnaround time of diagnosis.…”

Section: Discussionmentioning

confidence: 99%

A simple algorithmic approach using histology and immunohistochemistry for the current classification of adult diffuse glioma in a resource-limited set-up

et al. 2017

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“…IDH1 or IDH2 mutations are found in both astrocytic and oligodendroglial tumors since they act as a starting point for gliomagenesis. Therefore, the 2016 World Health Organization (WHO) classification guidelines combined astrocytic tumors and oligodendroglial tumors into one category [7-10]. Furthermore, each tumor has a typical genetic signature.…”

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confidence: 99%

Molecular Testing of Brain Tumor

Park

Won

Kim

et al. 2017

J Pathol Transl Med

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The World Health Organization (WHO) classification of central nervous system (CNS) tumors was revised in 2016 with a basis on the integrated diagnosis of molecular genetics. We herein provide the guidelines for using molecular genetic tests in routine pathological practice for an accurate diagnosis and appropriate management. While astrocytomas and IDH-mutant (secondary) glioblastomas are characterized by the mutational status of IDH, TP53, and ATRX, oligodendrogliomas have a 1p/19q codeletion and mutations in IDH, CIC, FUBP1, and the promoter region of telomerase reverse transcriptase (TERTp). IDH-wildtype (primary) glioblastomas typically lack mutations in IDH, but are characterized by copy number variations of EGFR, PTEN, CDKN2A/B, PDGFRA, and NF1 as well as mutations of TERTp. High-grade pediatric gliomas differ from those of adult gliomas, consisting of mutations in H3F3A, ATRX, and DAXX, but not in IDH genes. In contrast, well-circumscribed low-grade neuroepithelial tumors in children, such as pilocytic astrocytoma, pleomorphic xanthoastrocytoma, and ganglioglioma, often have mutations or activating rearrangements in the BRAF, FGFR1, and MYB genes. Other CNS tumors, such as ependymomas, neuronal and glioneuronal tumors, embryonal tumors, meningothelial, and other mesenchymal tumors have important genetic alterations, many of which are diagnostic, prognostic, and predictive markers and therapeutic targets. Therefore, the neuropathological evaluation of brain tumors is increasingly dependent on molecular genetic tests for proper classification, prediction of biological behavior and patient management. Identifying these gene abnormalities requires cost-effective and high-throughput testing, such as next-generation sequencing. Overall, this paper reviews the global guidelines and diagnostic algorithms for molecular genetic testing of brain tumors.

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“…It is not known yet whether and how heterozygosity or homozygosity for IDH mutations influences biological behavior. The vast majority of diffuse gliomas presenting as glioblastoma at first diagnosis are IDH wild type (‘primary glioblastomas’) [90, 91, 93, 105]. …”

Section: Introductionmentioning

confidence: 99%

Glioma: experimental models and reality

et al. 2017

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In theory, in vitro and in vivo models for human gliomas have great potential to not only enhance our understanding of glioma biology, but also to facilitate the development of novel treatment strategies for these tumors. For reliable prediction and validation of the effects of different therapeutic modalities, however, glioma models need to comply with specific and more strict demands than other models of cancer, and these demands are directly related to the combination of genetic aberrations and the specific brain micro-environment gliomas grow in. This review starts with a brief introduction on the pathological and molecular characteristics of gliomas, followed by an overview of the models that have been used in the last decades in glioma research. Next, we will discuss how these models may play a role in better understanding glioma development and especially in how they can aid in the design and optimization of novel therapies. The strengths and weaknesses of the different models will be discussed in light of genotypic, phenotypic and metabolic characteristics of human gliomas. The last part of this review provides some examples of how therapy experiments using glioma models can lead to deceptive results when such characteristics are not properly taken into account.

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Practical implications of integrated glioma classification according to the World Health Organization classification of tumors of the central nervous system 2016

Abstract: We summarize the relevant changes in the revised WHO classification of gliomas, outline the integrated approach, and discuss its practical implications and potential challenges.

Cited by 65 publications

References 46 publications

A simple algorithmic approach using histology and immunohistochemistry for the current classification of adult diffuse glioma in a resource-limited set-up

A simple algorithmic approach using histology and immunohistochemistry for the current classification of adult diffuse glioma in a resource-limited set-up

Molecular Testing of Brain Tumor

Glioma: experimental models and reality

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