The 2016 World Health Organization Classification of Tumors of the Central Nervous System is both a conceptual and practical advance over its 2007 predecessor. For the first time, the WHO classification of CNS tumors uses molecular parameters in addition to histology to define many tumor entities, thus formulating a concept for how CNS tumor diagnoses should be structured in the molecular era. As such, the 2016 CNS WHO presents major restructuring of the diffuse gliomas, medulloblastomas and other embryonal tumors, and incorporates new entities that are defined by both histology and molecular features, including glioblastoma, IDH-wildtype and glioblastoma, IDH-mutant; diffuse midline glioma, H3 K27M-mutant; RELA fusion-positive ependymoma; medulloblastoma, WNT-activated and medulloblastoma, SHH-activated; and embryonal tumour with multilayered rosettes, C19MC-altered. The 2016 edition has added newly recognized neoplasms, and has deleted some entities, variants and patterns that no longer have diagnostic and/or biological relevance. Other notable changes include the addition of brain invasion as a criterion for atypical meningioma and the introduction of a soft tissue-type grading system for the now combined entity of solitary fibrous tumor / hemangiopericytoma-a departure from the manner by which other CNS tumors are graded. Overall, it is hoped that the 2016 CNS WHO will facilitate clinical, experimental and epidemiological studies that will lead to improvements in the lives of patients with brain tumors.

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The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Chemokines constitute a family of chemoattractant cytokines and are subdivided into four families on the basis of the number and spacing of the conserved cysteine residues in the N-terminus of the protein. Chemokines play a major role in selectively recruiting monocytes, neutrophils, and lymphocytes, as well as in inducing chemotaxis through the activation of G-protein-coupled receptors. Monocyte chemoattractant protein-1 (MCP-1/CCL2) is one of the key chemokines that regulate migration and infiltration of monocytes/macrophages. Both CCL2 and its receptor CCR2 have been demonstrated to be induced and involved in various diseases. Migration of monocytes from the blood stream across the vascular endothelium is required for routine immunological surveillance of tissues, as well as in response to inflammation. This review will discuss these biological processes and the structure and function of CCL2.

Monocyte chemoattractant protein-1 (MCP-1): an overview.

The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS), published in 2021, is the sixth version of the international standard for the classification of brain and spinal cord tumors. Building on the 2016 updated fourth edition and the work of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy, the 2021 fifth edition introduces major changes that advance the role of molecular diagnostics in CNS tumor classification. At the same time, it remains wedded to other established approaches to tumor diagnosis such as histology and immunohistochemistry. In doing so, the fifth edition establishes some different approaches to both CNS tumor nomenclature and grading and it emphasizes the importance of integrated diagnoses and layered reports. New tumor types and subtypes are introduced, some based on novel diagnostic technologies such as DNA methylome profiling. The present review summarizes the major general changes in the 2021 fifth edition classification and the specific changes in each taxonomic category. It is hoped that this summary provides an overview to facilitate more in-depth exploration of the entire fifth edition of the WHO Classification of Tumors of the Central Nervous System.

The 2021 WHO Classification of Tumors of the Central Nervous System: a summary.

AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

La tumeur rhabdoide et teratoide atypique est une tumeur cerebrale rare de l'enfant, de mauvais pronostic. Nous en rapportons un cas congenital, revele par une paralysie faciale peripherique. Cette tumeur polymorphe etait composee de cellules rhabdoides associees a des zones typiques de tumeur neuroectodermique primitive. La detection en immunohistochimie des 3 molecules vimentine, antigene epithelial de membrane et actine musculaire lisse etait evocatrice de tumeur rhabdoide. L'analyse genetique de notre patient a montre une mutation homozygote du gene hSFN5/INII (22q11) dans l'ADN tumoral et heterozygote dans l'ADN constitutionnel, comme cela a ete demontre dans les tumeurs rhabdoides et teratoides atypiques et les tumeurs rhabdoides renales et extra-renales.

Atypical teratoid and rhabdoid tumor. Report of a congenital case

Severe mesangiolysis in a patient exposed to glycol ether solvents.

Meningeal solitary fibrous tumors-hemangiopericytomas (SFT-HPC) and a meningiomas can be difficult to distinguish on histologic examination. a STAT6 immunohistochemistry (IHC) is a reliable diagnostic marker of a SFT-HPCs. Recently, GRIA2 has also been reported to be a diagnostic a marker of SFT-HPC, although no extensive data are available for a meningeal SFT-HPCs yet. The aim of this study was to test their a diagnostic performance in a large cohort of SFT-HPCs and meningiomas. a IHC analyses for GRIA2 and STAT6 were performed on tissue microarrays a containing 76 SFT-HPCs and 181 meningiomas. Results were compared with a previous data with ALDH1 and CD34. Two different anti-STAT6 antibodies a were tested: SC-20 polyclonal and YE361 monoclonal antibody. Ninety-six a percent of meningeal SFT-HPCs but no meningioma displayed nuclear STAT6 a positivity. With SC-20 antibody, concomitant cytoplasmic staining for a STAT6 was observed in > 50% of all cases, including meningiomas. a However, using YE361 antibody, cytoplasmic staining was absent, and a nuclear signal intensity was stronger leading to better interpretation a of STAT6 IHC. GRIA2 was positive in 84% of SFT-HPCs and in 16% of a meningiomas. STAT6 had excellent sensitivity (96%) and specificity a (100%), ALDH1 and GRIA2 had same sensitivity (84%), but ALDH1 and CD34 a had better specificity than GRIA2 (97% and 96% vs. 84%, a respectively). For the differential diagnosis of SFT-HPCs versus a meningiomas, the best diagnostic approach is to perform STAT6, followed a by ALDH1 and CD34 in the case of uncommon STAT6-negative cases. Because a of meningioma positivity, GRIA2 seems less useful in this indication.

Dominique Figarella-Branger

Papers

Atypical teratoid and rhabdoid tumor. Report of a congenital case

Severe mesangiolysis in a patient exposed to glycol ether solvents.

Differential Diagnosis of Meningeal SFT-HPC and Meningioma Which ă Immunohistochemical Markers Should Be Used?

Intérêt de la mesure du volume sanguin régional cérébral relatif par IRM de perfusion dans la prise en charge des gliomes

Histopathological grading of intracranial pediatric ependymomas