Zhou Jiaqi, Li Miao, Chen Yu, Wang Shangzi, Wang Danke, Suo Chen, Chen Xingdong
State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China.
Key Laboratory of Genetic Evolution & Animal Models, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
Biol Sex Differ. 2024 Dec 23;15(1):106. doi: 10.1186/s13293-024-00682-4.
DNA methylation (DNAm) influences both sex differences and cancer development, yet the mechanisms connecting these factors remain unclear.
Utilizing data from The Cancer Genome Atlas, we conducted a comprehensive analysis of sex-related DNAm effects in nine non-reproductive cancers, compared to paired normal adjacent tissues (NATs), and validated the results using independent datasets. First, we assessed the extent of sex differential DNAm between cancers and NATs to explore how sex-related DNAm differences change in cancerous tissues. Next, we employed a multivariate adaptive shrinkage approach to model the covariance of cancer-related DNAm effects between sexes, aiming to elucidate how sex impacts aberrant DNAm patterns in cancers. Finally, we investigated correlations between the methylome and transcriptome to identify key signals driving sex-biased DNAm regulation in cancers.
Our analysis revealed a significant attenuation of sex differences in DNAm within cancerous tissues compared to baseline differences in normal tissues. We identified 3,452 CpGs (P < 0.05) associated with this reduction, with 72% of the linked genes involved in X chromosome inactivation. Through covariance analysis, we demonstrated that sex differences in cancer are predominantly driven by variations in the magnitude of shared DNAm signals, referred to as "amplification." Based on these patterns, we classified cancers into female- and male-biased groups and identified key CpGs exhibiting sex-specific amplification. These CpGs were enriched in binding sites of critical transcription factors, including P53, SOX2, and CTCF. Integrative multi-omics analyses uncovered 48 CpG-gene-cancer trios for females and 380 for males, showing similar magnitude differences in DNAm and gene expression, pointing to a sex-specific regulatory role of DNAm in cancer risk. Notably, several genes regulated by these trios were previously identified as drug targets for cancers, highlighting their potential as sex-specific therapeutic targets.
These findings advance our understanding of how sex, DNAm, and gene expression interact in cancer, offering insights into the development of sex-specific biomarkers and precision medicine.
DNA甲基化(DNAm)影响性别差异和癌症发展,然而连接这些因素的机制仍不清楚。
利用来自癌症基因组图谱的数据,我们对9种非生殖系统癌症中与性别相关的DNAm效应进行了全面分析,并与配对的正常相邻组织(NATs)进行比较,同时使用独立数据集验证结果。首先,我们评估了癌症组织与NATs之间性别差异DNAm的程度,以探索与性别相关的DNAm差异在癌组织中如何变化。接下来,我们采用多变量自适应收缩方法对性别之间与癌症相关的DNAm效应的协方差进行建模,旨在阐明性别如何影响癌症中异常的DNAm模式。最后,我们研究了甲基化组与转录组之间的相关性,以确定驱动癌症中性别偏向性DNAm调控的关键信号。
我们的分析显示,与正常组织中的基线差异相比,癌组织中DNAm的性别差异显著减弱。我们鉴定出3452个与这种减少相关的CpG位点(P < 0.05),其中72%的相关基因参与X染色体失活。通过协方差分析,我们证明癌症中的性别差异主要由共享DNAm信号强度的变化驱动,这种变化被称为“扩增”。基于这些模式,我们将癌症分为女性偏向组和男性偏向组,并鉴定出表现出性别特异性扩增的关键CpG位点。这些CpG位点在关键转录因子的结合位点中富集,包括P53、SOX2和CTCF。综合多组学分析发现了48个女性CpG-基因-癌症三联体和380个男性三联体,它们在DNAm和基因表达上显示出相似的量级差异,表明DNAm在癌症风险中具有性别特异性的调控作用。值得注意的是,这些三联体调控的几个基因先前被确定为癌症的药物靶点,突出了它们作为性别特异性治疗靶点的潜力。
这些发现推进了我们对性别、DNAm和基因表达在癌症中如何相互作用的理解,为性别特异性生物标志物的开发和精准医学提供了见解。