Molecular tumor classification using DNA methylome analysis
Tumor classifiers based on molecular patterns promise to define and reliably classify tumor entities. The high tissue- and cell type-specificity of DNA methylation, as well as its high stability, makes DNA methylation an ideal choice for the development of tumor classifiers. Herein, we review existi...
Gespeichert in:
| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
3 July 2020
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| In: |
Human molecular genetics
Year: 2020, Jahrgang: 29, Heft: R2, Pages: R205-R213 |
| ISSN: | 1460-2083 |
| DOI: | 10.1093/hmg/ddaa147 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1093/hmg/ddaa147
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| Verfasserangaben: | Martin Sill, Christoph Plass, Stefan M. Pfister and Daniel B. Lipka |
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| 520 | |a Tumor classifiers based on molecular patterns promise to define and reliably classify tumor entities. The high tissue- and cell type-specificity of DNA methylation, as well as its high stability, makes DNA methylation an ideal choice for the development of tumor classifiers. Herein, we review existing tumor classifiers using DNA methylome analysis and will provide an overview on their emerging impact on cancer classification, the detection of novel cancer subentities and patient stratification with a focus on brain tumors, sarcomas and hematopoietic malignancies. Furthermore, we provide an outlook on the enormous potential of DNA methylome analysis to complement classical histopathological and genetic diagnostics, including the emerging field of epigenomic analysis in liquid biopsies. | ||
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