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首页> 外文期刊>BMC Genomics >A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology
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A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

机译：整合甲基化和表达数据的新颖分析策略揭示了甲状腺癌病因的核心途径

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Background Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics. Results In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer. Conclusion While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as; endocytosis, apoptosis, glutamatergic synapse, MAPK, ErbB, TGF-beta and Toll-like receptor pathways. Overall, in addition to novel analysis framework, our study reveals important thyroid-cancer related mechanisms, secondary molecular alterations and contributes to better knowledge of thyroid cancer aetiology.
机译：背景技术最近，各种各样的疾病与DNA甲基化水平的变化有关，而DNA甲基化水平的变化在基因表达调节中起着至关重要的作用。随着技术的不断发展，表观遗传学和转录组学研究极大地受益于尝试了解疾病机理。在这项工作中，我们以甲状腺癌的表达和甲基化数据作为案例研究，并探讨了在两种数据均可用时如何将表达和甲基化信息最佳地纳入疾病研究。此外，我们还研究了是否存在重要的翻译后修饰子，这些修饰子可以推动对甲状腺癌遗传学的重要见解。结果在这项研究中，我们对不同的甲基化水平进行了阈值分析，以确定设置甲基化水平阈值是否会增加功能富集的性能。此外，为了确定最佳性能的分析策略，我们进行了数据集成分析，包括10种不同分析策略的比较。结果，将甲基化与表达结合并使用甲基化变化超过15％的基因，可在前20个功能富集结果中获得最佳的甲状腺癌相关途径检测率。此外，合并来自不同实验的数据可通过改善数据范围来提高分析信心。因此，我们确定了207个转录因子和245个翻译后修饰因子，其甲基化变化超过15％，这对于了解甲状腺癌的潜在机制可能很重要。结论虽然仅表达或仅甲基化信息不能揭示疾病状态涉及的主要和次要机制，但结合表达和甲基化可以更好地检测甲状腺癌相关基因和最近文献中发现的途径。此外，关注具有一定甲基化水平的基因可改善功能富集结果，从而揭示涉及疾病发展的核心途径，例如;内吞，凋亡，谷氨酸能突触，MAPK，ErbB，TGF-β和Toll样受体途径。总体而言，除新颖的分析框架外，我们的研究还揭示了重要的甲状腺癌相关机制，继发性分子改变，有助于更好地了解甲状腺癌的病因。

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