Review: Challenges in the histopathological classification of ganglioglioma and DNT: microscopic agreement studies and a preliminary genotype‐phenotype analysis

Blümcke, Ingmar; Coras, Roland; Wefers, Annika K.; Capper, David; Aronica, Eleonora; Becker, Albert; Honavar, Mrinalini; Stone, T. J.; Jacques, Thomas S.; Miyata, Hajime; Mühlebner, Angelika; Pimentel, José; Söylemezoğlu, Figen; Thom, Maria

doi:10.1111/nan.12522

Cited by 54 publications

(74 citation statements)

References 45 publications

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“…Among paediatric low‐grade gliomas and glioneuronal tumours, at least nine main DNA methylation classes have so far been established and seem sufficiently distinct for tumour classification . The molecular classes are clearly related to the established histological tumour classes although there is typically some degree of reallocation when molecular classes are overlaid on histological series . Figure lists the main molecular classes.…”

Section: Methylation Profiling Of Established Paediatric Brain Tumourmentioning

confidence: 99%

Invited Review: DNA methylation‐based classification of paediatric brain tumours

Perez

Capper

2020

Neuropathology Appl Neurobio

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2020) Neuropathology and Applied Neurobiology 46, 28-47 DNA methylation-based classification of paediatric brain tumours DNA methylation-based machine learning algorithms represent powerful diagnostic tools that are currently emerging for several fields of tumour classification. For various reasons, paediatric brain tumours have been the main driving forces behind this rapid development and brain tumour classification tools are likely further advanced than in any other field of cancer diagnostics. In this review, we will discuss the main characteristics that were important for this rapid advance, namely the high clinical need for improvement of paediatric brain tumour diagnostics, the robustness of methylated DNA and the consequential possibility to generate high-quality molecular data from archival formalin-fixed paraffin-embedded pathology specimens, the implementation of a single array platform by most laboratories allowing data exchange and data pooling to an unprecedented extent, as well as the high suitability of the data format for machine learning. We will further discuss the four most central output qualities of DNA methylation profiling in a diagnostic setting (tumour classification, tumour sub-classification, copy number analysis and guidance for additional molecular testing) individually for the most frequent types of paediatric brain tumours. Lastly, we will discuss DNA methylation profiling as a tool for the detection of new paediatric brain tumour classes and will give an overview of the rapidly growing family of new tumours identified with the aid of this technique.

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Section: Methylation Profiling Of Established Paediatric Brain Tumourmentioning

confidence: 99%

Invited Review: DNA methylation‐based classification of paediatric brain tumours

Perez

Capper

2020

Neuropathology Appl Neurobio

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“…It requires long experience with many surgical specimens, which is difficult to accomplish by most centers across the globe. International histopathology agreement studies support the notion of difficult‐to‐classify and ‐agree histopathology patterns in focal epilepsies . The authors of this current feature article promote the strategy, therefore, to integrate genetic analysis with histopathology patterns to reach a more reliable diagnosis and consensus classification system.…”

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confidence: 83%

“…Increasing availability of surgical human brain tissue specimens obtained from anatomically and functionally well‐characterized areas fostered neuropathology analysis to better classify the etiology and pathogenesis of human MCD. Hence, the overly large spectrum of morphological variants make any current histopathology‐based disease classification system difficult to apply . It requires long experience with many surgical specimens, which is difficult to accomplish by most centers across the globe.…”

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confidence: 99%

“…In 2016, the implementation of the 4th revised edition of the WHO classification system of tumors of the nervous system achieved a successful translation of genetics and histopathology into an integrated genotype‐phenotype diagnostic scheme . Notwithstanding, this applies foremost to gliomas and embryonal brain tumors whereas less frequent tumor entities still await this transition, including those low‐grade glioneuronal epilepsy‐associated tumors often encountered in epilepsy surgery . It will take, therefore, concerted efforts from the entire community TO MOVE ON.…”

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confidence: 99%

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It is time to move on

Blümcke

2019

Brain Pathology

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“…It was identi ed in 3.3% of DNT [32] . For DNT-like tumors with BRAF mutations, we should be wary of whether they were indeed GG or DNT-GG mixed tumors due to the challenges in the histopathological classi cation of GG and DNT [33] . Frequently observed genetic change in Pilocytic astrocytomas was BRAF mutation, particularly, KIAA1549-BRAF fusion that was identi ed in > 70% of all PAs, while BRAF V600E mutation only existed in 5% of the supratentorial PA [34] .…”

Section: Histopathological Features and Immunoreactivity Pattern Of Bmentioning

confidence: 99%

The Immunoreactivity Patterns of BRAF VE1 and Its Diagnostic Value in Brain Tumors

Fan

Chen³

et al. 2020

Preprint

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Background: BRAF mutations have been detected in a high proportion of melanoma, papillary thyroid carcinoma, and various primary brain tumors. But the sensitivity and specificity of immunohistochemical detection of BRAF-V600E mutant protein were not evaluated in brain tumors. The aim of this study was to assess the utlity of BRAF-V600E IHC compared to molecular biology on a large series of brain tumors, in order to provide a useful reference for the use of BRAF-V600E IHC in clinical practice.Methods and results: We analyzed the BRAF-V600E immunoreactivity pattern and its expression profile by immunohistochemistry (IHC) in 122 patients diagnosed with different tumors of brain including gangliocytoma/ganglioma(GC/GG), pleomorphic xanthoastrocytomas(PXA), epithelioid glioblastoma(E-GBM), dysembryoplastic neuroepithelial tumour(DNT), pilocytic astrocytoma(PA), and papillary craniopharyngioma(p-CPG). VE1 immunostaining of 52 cases showed clear cytoplasmic diffuse positive pattern in majority tumor cells. 14 cases were presented with clear granular cytoplasmic positive pattern in single tumor cell or tumor cell cluster. 22 cases displayed equivocal positive with undefined location. 34 cases were negative. Including 81 immunopositive cases and 29 immunonegative cases were further confirmed by Real-time PCR. And 63 of 81 immunopositive cases were confirmed with BRAF-V600E mutation (77.8%), and all of 29 negative cases were confirmed to have wild-type BRAF (100%). Interestingly, only the cases showing clear immunoreactivity patterns (e.g cytoplasmic) with clean background had immunostaining results consistent with the molecular detection results, regardless of the number of positive cells (61/61,100%). However, samples with indeterminate immunoreactivity patterns were most likely to have false positive results (18/20, 90%). Conclusions: VE1 immunostaining could replace molecular detection to some extent, on the premise of mastering the key points in the interpretation of BRAF VE1 immunostaining: 1) As long as the positive signal was accurately located in the cytoplasm of tumor cells, the sample was considered to have BRAF V600E mutation, disregarding the number of positive cells; 2) Tissue samples that had no signal of BRAF VE1 expression with clear background could be confirmed with wild-type BRAF-V600E; 3) Some equivocal positive with uniform “coating” or nucleus positive cases were often considered as false-positive and usually required further molecular detection.

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Review: Challenges in the histopathological classification of ganglioglioma and DNT: microscopic agreement studies and a preliminary genotype‐phenotype analysis

Cited by 54 publications

References 45 publications

Invited Review: DNA methylation‐based classification of paediatric brain tumours

Invited Review: DNA methylation‐based classification of paediatric brain tumours

It is time to move on

The Immunoreactivity Patterns of BRAF VE1 and Its Diagnostic Value in Brain Tumors

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