Pineda Silvia, Gomez-Rubio Paulina, Picornell Antonio, Bessonov Kyrylo, Márquez Mirari, Kogevinas Manolis, Real Francisco X, Van Steen Kristel, Malats Nuria
Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Hum Hered. 2015;79(3-4):124-36. doi: 10.1159/000381184. Epub 2015 Jul 28.
Different types of '-omics' data are becoming available in the post-genome era; still a single -omics assessment provides limited insights to understand the biological mechanism of complex diseases. Genomics, epigenomics and transcriptomics data provide insight into the molecular dysregulation of neoplastic diseases, among them urothelial bladder cancer (UBC). Here, we propose a detailed analytical framework necessary to achieve an adequate integration of the three sets of -omics data to ultimately identify previously hidden genetic mechanisms in UBC.
We built a multi-staged framework to study possible pair-wise combinations and integrated the data in three-way relationships. SNP genotypes, CpG methylation levels and gene expression levels were determined for a total of 70 individuals with UBC and with fresh tumour tissue available.
We suggest two main hypothesis-based scenarios for gene regulation based on the -omics integration analysis, where DNA methylation affects gene expression and genetic variants co-regulate gene expression and DNA methylation. We identified several three-way trans-association 'hotspots' that are found at the molecular level and that deserve further studies.
The proposed integrative framework allowed us to identify relationships at the whole-genome level providing some new biological insights and highlighting the importance of integrating -omics data.
在后基因组时代，不同类型的“组学”数据不断涌现；然而，单一的组学评估对于理解复杂疾病的生物学机制所提供的见解有限。基因组学、表观基因组学和转录组学数据有助于深入了解肿瘤性疾病（包括膀胱尿路上皮癌，UBC）的分子失调情况。在此，我们提出一个详细的分析框架，以实现对这三组组学数据的充分整合，最终识别出UBC中先前隐藏的遗传机制。
我们构建了一个多阶段框架来研究可能的两两组合，并以三向关系整合数据。对总共70例患有UBC且有新鲜肿瘤组织的个体测定了单核苷酸多态性（SNP）基因型、CpG甲基化水平和基因表达水平。
基于组学整合分析，我们提出了两种基于假设的主要基因调控情景，即DNA甲基化影响基因表达，以及遗传变异共同调控基因表达和DNA甲基化。我们在分子水平上识别出了几个三向反式关联“热点”，值得进一步研究。
所提出的整合框架使我们能够在全基因组水平上识别关系，提供一些新的生物学见解，并突出了整合组学数据的重要性。
