Identifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancer.
Identifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancer.
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DOI：
10.1186/s12920-017-0268-z
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发表时间：
2017-05-24
影响因子：
2.7
通讯作者：
Sohn KA
中科院分区：
文献类型：
--
作者：
Lee G;Bang L;Kim SY;Kim D;Sohn KA
乳腺癌是一种复杂的疾病，根据不同的亚型存在不同的基因组模式。最近的研究表明，多种亚型乳腺癌的发病率不同，在计划治疗中起着至关重要的作用。为了更好地了解乳腺癌亚型的潜在生物学机制，研究不同亚型的特定基因调控系统是必要的。基因表达作为一种中间表型，是基于甲基化谱来估计的，以确定表观基因组特征对乳腺癌转录组变化的影响。我们提出了一个核加权l1正则化回归模型，以纳入肿瘤亚型信息，进一步揭示不同乳腺癌亚型对基因调控的影响。为了适当控制亚型特异性估计，根据目标估计以不同的速率学习来自不同乳腺癌亚型的样本。通过Kolmogorov - Smirnov检验来确定每个样本不同亚型的学习率。观察到，当使用我们提出的方法估计时，可能对乳腺癌亚型敏感的基因显示预测改善。与标准方法相比，结合肿瘤亚型也提高了整体性能。此外，我们根据基因表达和DNA甲基化之间的关联确定了亚型特异性网络结构。在这项研究中，提出了核加权lasso模型来识别基因表达和DNA甲基化谱之间的亚型特异性关联。鉴定与表观基因组变化相关的亚型特异性基因表达可能有助于更好地规划治疗和开发新的治疗方法。
Breast cancer is a complex disease in which different genomic patterns exists depending on different subtypes. Recent researches present that multiple subtypes of breast cancer occur at different rates, and play a crucial role in planning treatment. To better understand underlying biological mechanisms on breast cancer subtypes, investigating the specific gene regulatory system via different subtypes is desirable. Gene expression, as an intermediate phenotype, is estimated based on methylation profiles to identify the impact of epigenomic features on transcriptomic changes in breast cancer. We propose a kernel weighted l1-regularized regression model to incorporate tumor subtype information and further reveal gene regulations affected by different breast cancer subtypes. For the proper control of subtype-specific estimation, samples from different breast cancer subtype are learned at different rate based on target estimates. Kolmogorov Smirnov test is conducted to determine learning rate of each sample from different subtype. It is observed that genes that might be sensitive to breast cancer subtype show prediction improvement when estimated using our proposed method. Comparing to a standard method, overall performance is also enhanced by incorporating tumor subtypes. In addition, we identified subtype-specific network structures based on the associations between gene expression and DNA methylation. In this study, kernel weighted lasso model is proposed for identifying subtype-specific associations between gene expressions and DNA methylation profiles. Identification of subtype-specific gene expression associated with epigenomic changes might be helpful for better planning treatment and developing new therapies.