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@ARTICLE{Sill:157103,
author = {M. Sill$^*$ and C. Plass$^*$ and S. M. Pfister$^*$ and D.
Lipka$^*$},
title = {{M}olecular tumor classification using {DNA} methylome
analysis.},
journal = {Human molecular genetics},
volume = {29},
number = {R2},
issn = {1460-2083},
address = {Oxford},
publisher = {Oxford Univ. Press},
reportid = {DKFZ-2020-01394},
pages = {R205-R213},
year = {2020},
note = {2020 Oct 20;29(R2):R205-R213#EA:B062#LA:B340#},
abstract = {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.},
subtyp = {Review Article},
cin = {B062 / HD01 / B370 / B340},
ddc = {570},
cid = {I:(DE-He78)B062-20160331 / I:(DE-He78)HD01-20160331 /
I:(DE-He78)B370-20160331 / I:(DE-He78)B340-20160331},
pnm = {312 - Functional and structural genomics (POF3-312)},
pid = {G:(DE-HGF)POF3-312},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:32657331},
doi = {10.1093/hmg/ddaa147},
url = {https://inrepo02.dkfz.de/record/157103},
}