Abstract
Aging is associated with highly reproducible DNA methylation (DNAm) changes, which may contribute to higher prevalence of malignant diseases in the elderly. In this study, we analyzed epigenetic aging signatures in 5,621 DNAm profiles of 25 cancer types from The Cancer Genome Atlas (TCGA). Overall, age-associated DNAm patterns hardly reflect chronological age of cancer patients, but they are coherently modified in a non-stochastic manner, particularly at CpGs that become hypermethylated upon aging in non-malignant tissues. This coordinated regulation in epigenetic aging signatures can therefore be used for aberrant epigenetic age-predictions, which facilitate disease stratification. For example, in acute myeloid leukemia (AML) higher epigenetic age-predictions are associated with increased incidence of mutations in RUNX1, WT1, and IDH2, whereas mutations in TET2, TP53, and PML-PARA translocation are more frequent in younger age-predictions. Furthermore, epigenetic aging signatures correlate with overall survival in several types of cancer (such as lower grade glioma, glioblastoma multiforme, esophageal carcinoma, chromophobe renal cell carcinoma, cutaneous melanoma, lung squamous cell carcinoma, and neuroendocrine neoplasms). In conclusion, age-associated DNAm patterns in cancer are not related to chronological age of the patient, but they are coordinately regulated, particularly at CpGs that become hypermethylated in normal aging. Furthermore, the apparent epigenetic age-predictions correlate with clinical parameters and overall survival in several types of cancer, indicating that regulation of DNAm patterns in age-associated CpGs is relevant for cancer development.
Highlights
Age is the strongest demographic risk factor for cancer, indicating that molecular changes upon aging trigger malignant transformation
Some epigenetic modifications accumulate throughout life in a highly reproducible manner–they may contribute to the aging process and facilitate reliable age-predictions
Advantages of choosing this tumor were that acute myeloid leukemia (AML) comprises relatively high percentages of malignant cells that can be estimated by blast counts and the availability of large DNA methylation (DNAm) datasets of whole blood derived from healthy controls that be used as a reference
Summary
Age is the strongest demographic risk factor for cancer, indicating that molecular changes upon aging trigger malignant transformation. Aging is accompanied by specific epigenetic modifications, which may contribute to aberrant chromatin conformation and stability [2,3] Such epigenetic modifications are observed in DNA methylation (DNAm) changes that resemble addition or removal of methyl groups to cytosines in a CpG dinucleotide context. Several CpGs acquire almost linear hypermethylation or hypomethylation upon aging and linear univariate or multivariate models can be used to estimate chronological age [4,5,6,7,8] Such epigenetic age-predictors provide strong biomarkers for biological aging and may support identification of relevant factors for the process of aging—including gender, genetic variants, and body mass index [7,9]. The recent explosion in our knowledge of how chromatin organization modulates gene transcription has further highlighted the importance of epigenetic mechanisms in aging and disease [12]
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