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Sarcoma Classification by DNA-methylation profiling

ABSTRACT: Sarcoma Classification by DNA-methylation profiling

PROVIDER: PRJNA590525 | ENA |

REPOSITORIES: ENA

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Sarcoma Classification by DNA-methylation profiling

Project description:DNA methylation classification reference set (1077) and validation set (428) of 1505 sarcoma samples using Illumina HumanMethylation450 BeadChips or Illumina Infinium HumanMethylation850 BeadChips

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Sarcoma classification by DNA methylation profiling.

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DNA methylation analysis of Rhabdoid tumor of the kidney, Clear cell sarcoma of the kidney and Ewing's sarcoma family of tumors

Project description:Genome wide DNA methylation profiling of Rhabdoid tumor of the kidney, Clear cell sarcoma of the kidney, Ewing's sarcoma family of tumors and non-neoplastic kidney. The Illumina Infinium HumanMethylation 27 BeadChip was used to obtain DNA methylation profiles across approximately 27000 CpGs . Samples included 3 Rhabdoid tumor of the kidney, 3 Clear cell sarcoma of the kidney, 3 Ewing's sarcoma family of tumor and 3 non-neoplastic kidney. Bisulfite converted DNA from the 12 samples were hybridized to the Illumina Infinium HumanMethylation27 Beadchip.

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DNA methylation analysis of Rhabdoid tumor of the kidney, Clear cell sarcoma of the kidney and Ewing's sarcoma family of tumors

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Intra-Tumor DNA Methylation Heterogeneity in Glioblastoma; Implications for DNA Methylation-based Classification

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DNA methylation-based classification of hematolymphoid neoplasms

Project description:Accurate pathological diagnosis is crucial for optimal management of cancer patients. For a number of hematolymphoid tumor entities, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variability in the histopathological diagnosis of many tumor types. Genome-wide DNA methylation profiling has been shown to contribute to accurate and precise tumor classification and diagnosis in several tumor types, including central nervous system neoplasms. We herein present the development of a comprehensive approach for DNA methylation-based hematolymphoid tumor classification across most entities and age groups and demonstrate its application in a clinical setting, defining 44 methylation classes comprising a good proportion of recognized hematolymphoid tumor types. In several cases, methylation signatures separated recognized tumor types into subclasses that showed statistically significant and distinct patient outcomes. We validate the classifier in independent samples that were not utilized in classifier development and show that the reliability of this method is highly accurate (concordance 97%) with a substantial impact on diagnostic precision in addition to standard methods. We show a relationship of methylation class match scores with tumor purity, finding that high-tumor-purity samples are more likely to receive a high-confidence match with our classifier. Finally, we show the impact of the classifier in clinical practice, where classifier results resulted in a change in diagnosis in specific hematolymphoid neoplasms. For broader accessibility, a free and user-friendly online portal for access to the hematolymphoid tumor methylation classifier will be available for external users.

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