Table_3_CancerClock: A DNA Methylation Age Predictor to Identify and Characterize Aging Clock in Pan-Cancer.XLSX
Many biological indicators related to chronological age have been proposed. Recent studies found that epigenetic clock or DNA methylation age is highly correlated with chronological age. In particular, a significant difference between DNA methylation age (m-age) and chronological age was observed in cancers. However, the prediction and characterization of m-age in pan-cancer remains an explored area. In this study, 1,631 age-related methylation sites in normal tissues were discovered and analyzed. A comprehensive computational model named CancerClock was constructed to predict the m-age for normal samples based on methylation levels of the extracted methylation sites. LASSO linear regression model was used to screen and train the CancerClock model in normal tissues. The accuracy of CancerClock has proved to be 81%, and the correlation value between chronological age and m-age was 0.939 (P < 0.01). Next, CancerClock was used to evaluate the difference between m-age and chronological age for 33 cancer types from TCGA. There were significant differences between predicted m-age and chronological age in large number of cancer samples. These cancer samples were defined as “age-related cancer samples” and they have some differential methylation sites. The differences between predicted m-age and chronological age may contribute to cancer development. Some of these differential methylation sites were associated with cancer survival. CancerClock provided assistance in estimating the m-age in normal and cancer samples. The changes between m-age and chronological age may improve the diagnosis and prognosis of cancers.
History
References
- https://doi.org//10.1152/physrev.00026.2007
- https://doi.org//10.1093/bib/bbz118
- https://doi.org//10.1007/s40572-018-0203-2
- https://doi.org//10.1038/nature14192
- https://doi.org//10.3978/j.issn.2078-6891.2015.070
- https://doi.org//10.1093/nar/gky955
- https://doi.org//10.18637/jss.v033.i01
- https://doi.org//10.3748/wjg.v22.i47.10325
- https://doi.org//10.1177/1471082X14565526
- https://doi.org//10.2217/epi-2017-0019
- https://doi.org//10.3414/ME16-01-0033
- https://doi.org//10.1186/gb-2013-14-10-r115
- https://doi.org//10.1016/j.cell.2018.03.042
- https://doi.org//10.1186/s13058-017-0873-y
- https://doi.org//10.3892/ijo.2016.3473
- https://doi.org//10.1093/jnci/djz020
- https://doi.org//10.1186/s13148-015-0125-x
- https://doi.org//10.1093/nar/gkw377
- https://doi.org//10.1093/nar/gky1027
- https://doi.org//10.3390/cancers7020815
- https://doi.org//10.1016/j.arr.2018.04.005
- https://doi.org//10.1073/pnas.1714478115
- https://doi.org//10.1186/s13148-016-0228-z
- https://doi.org//10.1007/s00414-017-1636-0
- https://doi.org//10.1186/s13059-017-1203-5
- https://doi.org//10.1111/jcmm.14403
- https://doi.org//10.1007/s12160-016-9845-1
- https://doi.org//10.3390/cancers11101515
- https://doi.org//10.1038/ncomms6659
- https://doi.org//10.1002/humu.22444
- https://doi.org//10.1038/srep22722
- https://doi.org//10.1186/gb-2014-15-2-r24
- https://doi.org//10.1002/ijc.29537
- https://doi.org//10.1186/s13059-019-1818-9
- https://doi.org//10.1158/1055-9965.EPI-19-0208
- https://doi.org//10.18632/oncotarget.10891
- https://doi.org//10.1186/s12967-015-0556-3
- https://doi.org//10.1016/j.omtn.2018.06.007
- https://doi.org//10.1093/bib/bby021
- https://doi.org//10.1186/s13046-015-0219-5
- https://doi.org//10.1186/s12943-017-0580-4
- https://doi.org//10.14336/AD.2016.1230
- https://doi.org//10.1016/j.fsigen.2016.05.014
Usage metrics
Read the peer-reviewed publication
Categories
- Bioprocessing, Bioproduction and Bioproducts
- Industrial Biotechnology Diagnostics (incl. Biosensors)
- Industrial Microbiology (incl. Biofeedstocks)
- Industrial Molecular Engineering of Nucleic Acids and Proteins
- Industrial Biotechnology not elsewhere classified
- Medical Biotechnology Diagnostics (incl. Biosensors)
- Biological Engineering
- Regenerative Medicine (incl. Stem Cells and Tissue Engineering)
- Medical Biotechnology not elsewhere classified
- Agricultural Marine Biotechnology
- Biomaterials
- Biomechanical Engineering
- Biotechnology
- Biomarkers
- Biomedical Engineering not elsewhere classified
- Genetic Engineering
- Synthetic Biology
- Bioremediation
- Medical Molecular Engineering of Nucleic Acids and Proteins