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Seminars in Cancer Biology
Article . 2022 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Seminars in Cancer Biology
Article
License: CC BY NC ND
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Epigenomic technologies for precision oncology

Authors: Dieter Weichenhan; Daniel B. Lipka; Pavlo Lutsik; Ashish Goyal; Christoph Plass;

Epigenomic technologies for precision oncology

Abstract

Epigenetic patterns in a cell control the expression of genes and consequently determine the phenotype of a cell. Cancer cells possess altered epigenomes which include aberrant patterns of DNA methylation, histone tail modifications, nucleosome positioning and of the three-dimensional chromatin organization within a nucleus. These altered epigenetic patterns are potential useful biomarkers to detect cancer cells and to classify tumor types. In addition, the cancer epigenome dictates the response of a cancer cell to therapeutic intervention and, therefore its knowledge, will allow to predict response to different therapeutic approaches. Here we review the current state-of-the-art technologies that have been developed to decipher epigenetic patterns on the genomic level and discuss how these methods are potentially useful for precision oncology.

Keywords

Epigenomics, Neoplasms, Humans, DNA Methylation, Precision Medicine, Chromatin Assembly and Disassembly

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    10
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
hybrid
Related to Research communities
Cancer Research