Estimating breast tissue-specific DNA methylation age using next-generation sequencing data

被引:14
作者
Castle, James R. [1 ]
Lin, Nan [1 ]
Liu, Jinpeng [1 ]
Storniolo, Anna Maria V. [3 ]
Shendre, Aditi [4 ]
Hou, Lifang [5 ,6 ]
Horvath, Steve [7 ]
Liu, Yunlong [8 ]
Wang, Chi [1 ]
He, Chunyan [1 ,2 ]
机构
[1] Univ Kentucky, Markey Canc Ctr, 800 Rose St, Lexington, KY 40536 USA
[2] Univ Kentucky, Coll Med, Dept Internal Med, Div Med Oncol, Lexington, KY 40506 USA
[3] Indiana Univ, Simon Canc Ctr, Susan G Komen Tissue Bank, Indianapolis, IN 46204 USA
[4] Ohio State Univ, Dept Biomed Informat, Columbus, OH 43210 USA
[5] Northwestern Univ, Feinberg Sch Med, Robert H Lurie Comprehens Canc Ctr, Ctr Populat Epigenet, Chicago, IL 60611 USA
[6] Northwestern Univ, Feinberg Sch Med, Dept Prevent Med, Chicago, IL 60611 USA
[7] Univ Calif Los Angeles, Sch Publ Hlth, Dept Biostat, Los Angeles, CA 90024 USA
[8] Indiana Univ Sch Med, Dept Mol & Med Genet, Indianapolis, IN 46202 USA
关键词
DNA methylation; Aging; Epigenetic age; Breast; Next-generation sequencing; EPIGENETIC AGE; STEM-CELLS; CANCER; REGULARIZATION; MORTALITY; SELECTION; SUBTYPES; MODELS;
D O I
10.1186/s13148-020-00834-4
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background DNA methylation (DNAm) age has been widely accepted as an epigenetic biomarker for biological aging. Emerging evidence suggests that DNAm age can be tissue-specific and female breast tissue ages faster than other parts of the body. The Horvath clock, which estimates DNAm age across multiple tissues, has been shown to be poorly calibrated in breast issue. We aim to develop a model to estimate breast tissue-specific DNAm age. Methods Genome-wide DNA methylation sequencing data were generated for 459 normal, 107 tumor, and 45 paired adjacent-normal breast tissue samples. We determined a novel set of 286 breast tissue-specific clock CpGs using penalized linear regression and developed a model to estimate breast tissue-specific DNAm age. The model was applied to estimate breast tissue-specific DNAm age in different breast tissue types and in tumors with distinct clinical characteristics to investigate cancer-related aging effects. Results Our estimated breast tissue-specific DNAm age was highly correlated with chronological age (r = 0.88; p = 2.9 x 10(-31)) in normal breast tissue. Breast tumor tissue samples exhibited a positive epigenetic age acceleration, where DNAm age was on average 7 years older than respective chronological age (p = 1.8 x 10(-8)). In age-matched analyses, tumor breast tissue appeared 12 and 13 years older in DNAm age than adjacent-normal and normal breast tissue (p = 4.0 x 10(-6) and 1.0 x 10(-6), respectively). Both HER2+ and hormone-receptor positive subtypes demonstrated significant acceleration in DNAm ages (p = 0.04 and 3.8 x 10(-6), respectively), while no apparent DNAm age acceleration was observed for triple-negative breast tumors. We observed a non-linear pattern of epigenetic age acceleration with breast tumor grade. In addition, early-staged tumors showed a positive epigenetic age acceleration (p = 0.003) while late-staged tumors exhibited a non-significant negative epigenetic age acceleration (p = 0.10). Conclusions The intended applications for this model are wide-spread and have been shown to provide biologically meaningful results for cancer-related aging effects in breast tumor tissue. Future studies are warranted to explore whether breast tissue-specific epigenetic age acceleration is predictive of breast cancer development, treatment response, and survival as well as the clinical utility of whether this model can be extended to blood samples.
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页数:14
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