Cava Claudia, Colaprico Antonio, Bertoli Gloria, Bontempi Gianluca, Mauri Giancarlo, Castiglioni Isabella
Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Milan, Italy.
Interuniversity Institute of Bioinformatics in Brussels (IB), Brussels, Belgium.
BMC Bioinformatics. 2016 Nov 8;17(Suppl 12):348. doi: 10.1186/s12859-016-1196-1.
An important challenge in cancer biology is to understand the complex aspects of the disease. It is increasingly evident that genes are not isolated from each other and the comprehension of how different genes are related to each other could explain biological mechanisms causing diseases. Biological pathways are important tools to reveal gene interaction and reduce the large number of genes to be studied by partitioning it into smaller paths. Furthermore, recent scientific evidence has proven that a combination of pathways, instead than a single element of the pathway or a single pathway, could be responsible for pathological changes in a cell.
In this paper we develop a new method that can reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways. We applied the method to subtypes of breast cancer. The basic idea is the identification of pathways significantly enriched with differentially expressed genes among the different breast cancer subtypes and normal tissue. Looking at the pairs of pathways that were found to be functionally related, we created a network of dependent pathways and we focused on identifying miRNAs that could act as miRNA drivers in a coordinated regulation process.
Our approach enables miRNAs identification that could have an important role in the development of breast cancer.
癌症生物学中的一个重要挑战是理解该疾病的复杂方面。越来越明显的是,基因并非彼此孤立,理解不同基因之间的相互关系有助于解释导致疾病的生物学机制。生物通路是揭示基因相互作用的重要工具,通过将大量基因划分为较小的路径来减少待研究的基因数量。此外,最近的科学证据表明,通路的组合而非单个通路元件或单一通路,可能是导致细胞病理变化的原因。
在本文中,我们开发了一种新方法,该方法能够揭示以协调方式调节基因通路网络的微小RNA(miRNA)。我们将该方法应用于乳腺癌亚型。基本思路是识别在不同乳腺癌亚型和正常组织中显著富集差异表达基因的通路。通过观察发现功能相关的通路对,我们构建了一个依赖通路网络,并专注于识别在协调调控过程中可作为miRNA驱动因子的miRNA。
我们的方法能够识别可能在乳腺癌发展中起重要作用的miRNA。