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Updating TCGA glioma classification through integration of molecular profiling data following the 2016 and 2021 WHO guidelines

Medonca, M. L.; Coletti, R.; Goncalves, C. S.; Martins, E. P.; Costa, B. M.; Vinga, S.; Lopes, M. B.

2023-02-21 bioinformatics
10.1101/2023.02.19.529134 bioRxiv
Show abstract

The understanding of glioma disease has been evolving drastically with dedicated research into the genetic and molecular profiling of glioma tumour tissue. Molecular biomarkers have gained progressive and substantial importance in providing diagnostic information, leading to groundbreaking changes in the tumour classification system, criteria and taxonomy standardised by the 2016 and 2021 editions of the World Health Organization Classification of Tumours of the Central Nervous Systems guidelines (WHO-2016 and WHO-2021, respectively). Some of the insights into glioma disease derived from extensive research on open-source multi-omics databases, such as the Cancer Genome Atlas (TCGA). However, given the substantial changes in glioma classification, retrospective databases may harbour outdated diagnostic annotations, suboptimal for further research. Here we propose two methods for updating the tumour classification of TCGA glioma samples in accordance with WHO-2016 and WHO-2021 guidelines through the integration of curated molecular profiling information. Our methods allowed for the diagnostic update of 98% and 87% of evaluated TCGA glioma cases according to WHO-2016 and -2021, respectively, and highlighted changes in patient-specific diagnosis across both guidelines editions. Our reclassification pipelines are provided in software R, facilitating direct reproduction or tailoring upon new releases of WHO guidelines.

Published in Scientific Data (predicted rank #18) · training set

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