Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, 300 George Street, Suite 120, New Haven, CT, 06511, USA.
Department of Big Data in Health Science, School of Public Health and Center for Clinical Big Data and Analytics, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Clin Epigenetics. 2022 Feb 24;14(1):30. doi: 10.1186/s13148-022-01249-z.
Age is one of the strongest risk factors for the development of breast cancer, however, the underlying etiology linking age and breast cancer remains unclear. We have previously observed links between epigenetic aging signatures in breast/tumor tissue and breast cancer risk/prevalence. However, these DNA methylation-based aging biomarkers capture diverse epigenetic phenomena and it is not known to what degree they relate to breast cancer risk, and/or progression.
Using six epigenetic clocks, we analyzed whether they distinguish normal breast tissue adjacent to tumor (cases) vs normal breast tissue from healthy controls (controls).
The Levine (p = 0.0037) and Yang clocks (p = 0.023) showed significant epigenetic age acceleration in cases vs controls in breast tissue. We observed that much of the difference between cases and controls is driven by CpGs associated with polycomb-related genes. Thus, we developed a new score utilizing only CpGs associated with polycomb-related genes and demonstrated that it robustly captured epigenetic age acceleration in cases vs controls (p = 0.00012). Finally, we tested whether this same signal could be seen in peripheral blood. We observed no difference in cases vs. controls and no correlation between matched tissue/blood samples, suggesting that peripheral blood is not a good surrogate marker for epigenetic age acceleration.
Moving forward, it will be critical for studies to elucidate whether epigenetic age acceleration in breast tissue precedes breast cancer diagnosis and whether methylation changes at CpGs associated with polycomb-related genes can be used to assess the risk of developing breast cancer among unaffected individuals.
年龄是乳腺癌发展的最强危险因素之一,然而,将年龄与乳腺癌联系起来的潜在病因尚不清楚。我们之前观察到乳腺/肿瘤组织中的表观遗传衰老特征与乳腺癌风险/患病率之间存在联系。然而,这些基于 DNA 甲基化的衰老生物标志物捕捉到了不同的表观遗传现象,尚不清楚它们与乳腺癌风险的关联程度,以及/或与乳腺癌的进展程度的关联程度。
使用六个表观遗传时钟,我们分析了它们是否能够区分肿瘤旁的正常乳腺组织(病例)与来自健康对照者的正常乳腺组织(对照)。
在乳腺组织中,Levine 时钟(p=0.0037)和 Yang 时钟(p=0.023)显示病例与对照之间存在明显的表观遗传年龄加速。我们观察到,病例与对照之间的大部分差异是由与多梳相关基因相关的 CpG 驱动的。因此,我们开发了一种仅利用与多梳相关基因相关的 CpG 的新评分,并证明它能够稳健地捕捉病例与对照之间的表观遗传年龄加速(p=0.00012)。最后,我们测试了这种相同的信号是否可以在外周血中看到。我们在病例与对照之间没有观察到差异,也没有观察到匹配的组织/血液样本之间的相关性,这表明外周血不是表观遗传年龄加速的良好替代标志物。
未来,阐明乳腺组织中的表观遗传年龄加速是否先于乳腺癌诊断,以及与多梳相关基因相关的 CpG 上的甲基化变化是否可用于评估未受影响个体发生乳腺癌的风险,将是至关重要的。