| Title |
Evolution of DNA Methylation Is Linked to Genetic Aberrations in Chronic Lymphocytic Leukemia
|
|---|---|
| Published in |
Cancer Discovery, March 2014
|
| DOI | 10.1158/2159-8290.cd-13-0349 |
| Pubmed ID | |
| Authors |
Christopher C. Oakes, Rainer Claus, Lei Gu, Yassen Assenov, Jennifer Hüllein, Manuela Zucknick, Matthias Bieg, David Brocks, Olga Bogatyrova, Christopher R. Schmidt, Laura Rassenti, Thomas J. Kipps, Daniel Mertens, Peter Lichter, Hartmut Döhner, Stephan Stilgenbauer, John C. Byrd, Thorsten Zenz, Christoph Plass |
| Abstract |
Although clonal selection by genetic driver aberrations in cancer is well documented, the ability of epigenetic alterations to promote tumor evolution is undefined. We used 450k arrays and next-generation sequencing to evaluate intratumor heterogeneity and evolution of DNA methylation and genetic aberrations in chronic lymphocytic leukemia (CLL). CLL cases exhibit vast interpatient differences in intratumor methylation heterogeneity, with genetically clonal cases maintaining low methylation heterogeneity and up to 10% of total CpGs in a monoallelically methylated state. Increasing methylation heterogeneity correlates with advanced genetic subclonal complexity. Selection of novel DNA methylation patterns is observed only in cases that undergo genetic evolution, and independent genetic evolution is uncommon and is restricted to low-risk alterations. These results reveal that although evolution of DNA methylation occurs in high-risk, clinically progressive cases, positive selection of novel methylation patterns entails coevolution of genetic alteration(s) in CLL. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Germany | 3 | 2% |
| Portugal | 1 | <1% |
| Belgium | 1 | <1% |
| Austria | 1 | <1% |
| Unknown | 179 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 42 | 22% |
| Student > Ph. D. Student | 40 | 21% |
| Student > Doctoral Student | 15 | 8% |
| Student > Master | 13 | 7% |
| Student > Bachelor | 12 | 6% |
| Other | 31 | 16% |
| Unknown | 35 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 53 | 28% |
| Biochemistry, Genetics and Molecular Biology | 49 | 26% |
| Medicine and Dentistry | 25 | 13% |
| Immunology and Microbiology | 6 | 3% |
| Computer Science | 4 | 2% |
| Other | 12 | 6% |
| Unknown | 39 | 21% |