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  • 1
    In: Klinische Pädiatrie, 2018, Vol.230(06)
    In: Klinische Pädiatrie, 2018, Vol.230(06), pp.305-313
    Description: Central nervous system (CNS) tumors account for the highest mortality among pediatric malignancies. Accurate diagnosis is essential for optimal clinical management. The increasing use of molecular diagnostics has opened up novel possibilities for more precise classification of CNS tumors. We here report a single-institutional collection of pediatric CNS tumor cases that underwent a refinement or a change of diagnosis after completion of molecular analysis that affected clinical decision-making including the application of molecularly informed targeted therapies. 13 pediatric CNS tumors were analyzed by conventional histology, immunohistochemistry, and molecular diagnostics including DNA methylation profiling in 12 cases, DNA sequencing in 8 cases and RNA sequencing in 3 cases. 3 tumors had a refinement of diagnosis upon molecular testing, and 6 tumors underwent a change of diagnosis. Targeted therapy was initiated in 5 cases. An underlying cancer predisposition syndrome was detected in 5 cases. Although this case series, retrospective and not population based, has its limitations, insight can be gained regarding precision of diagnosis and clinical management of the patients in selected cases. Accuracy of diagnosis was improved in the cases presented here by the addition of molecular diagnostics, impacting clinical management of affected patients, both in the first-line as well as in the follow-up setting. This additional information may support the clinical decision making in the treatment of challenging pediatric CNS tumors. Prospective testing of the clinical value of molecular diagnostics is currently underway.
    Keywords: Brain tumor ; Molecular diagnostics ; Targeted therapy ; Cancer predisposition syndromes
    ISSN: 0300-8630
    E-ISSN: 1439-3824
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  • 2
    In: Nature, 2018
    Description: Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
    Keywords: DNA Methylation ; Central Nervous System Neoplasms -- Diagnosis;
    ISSN: 0028-0836
    E-ISSN: 1476-4687
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