Molecular classification of brain tumor types
Method for molecular distinction of tumor species using standard techniques like Illumina's HumanMethylation450 (450k) BeadChip.
There are more than 100 brain tumor entities listed in the World Health Organisation classification. Many of these show complex patterns of potentially overlapping histological features. Moreover, even histologically identical tumors can belong to different molecular groups with very different treatment requirements and prognosis.
In order to tackle those challenges DKFZ and Heidelberg University Hospital researchers developed a method for classifying tumorous diseases based on their specific genomic DNA methylation profile.
The method is ready to use and reduced to practice at DKFZ and Heidelberg University Hospital. By using Illumina's HumanMethylation450 (450k) BeadChip over 2,000 tumor samples from all over the world have been successfully analyzed. Additionally, those samples helped further improving the classification rule algorithm and make this method – up to now – the most reliable molecular approach for the distinction of brain tumor entities.
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The method enables classification of a tumor sample by analyzing the methylation pattern of genome wide CpG positions. The acquired data are compared to a self-learning classification rule derived from a worldwide unique and highly sophisticated set of methylation data acquired from pre-classified tumor species. The method is especially useful for classifying brain tumors due to the fact that brain tumor sub-types comprise distinct and extremely stable methylation patterns, thus enabling discrimination of histologically indistinguishable tumor species (see figure). Furthermore, the method allows generating copy number profiles of the individual tumor entities.
Due to the sublime performance and consistency of the classification rule algorithm the presented technology has the potential to become the standard diagnostic tool for the differentiation of brain tumors and other tumor species.