Centre for Scientific Computing & Complex Systems Modelling (SCI-SYM), School of Computing, Dublin City University, Dublin 9, Ireland,
Interdiscip Sci. 2013 Sep;5(3):175-86. doi: 10.1007/s12539-013-0172-y. Epub 2013 Dec 4.
Cancer, a class of diseases, characterized by abnormal cell growth, has one of the highest overall death rates world-wide. Its development has been linked to aberrant genetic and epigenetic events, affecting the regulation of key genes that control cellular mechanisms. However, a major issue in cancer research is the lack of precise information on tumour pathways; therefore, the delineation of these and of the processes underlying disease proliferation is an important area of investigation. A computational approach to modelling malignant system events can help to improve understanding likely "triggers", i.e. initiating abnormal micro-molecular signals that occur during cancer development. Here, we introduce a network-based model for genetic and epigenetic events observed at different stages of colon cancer, with a focus on the gene relationships and tumour pathways. Additionally, we describe a case study on tumour progression recorded for two gene networks on colon cancer, carcinoma in situ. Our results to date showed that tumour progression rate is higher for a small, closely-associated network of genes than for a larger, less-connected set; thus, disease development depends on assessment of network properties. The current work aims to provide improved insight on the way in which aberrant modifications characterize cancer initiation and progression. The framework dynamics are described in terms of interdependencies between three main layers: genetic and epigenetic events, gene relationships and cancer stage levels.
癌症是一类疾病，其特征是异常细胞生长，其总体死亡率在全球范围内是最高的之一。它的发展与异常的遗传和表观遗传事件有关，影响控制细胞机制的关键基因的调节。然而，癌症研究中的一个主要问题是缺乏关于肿瘤途径的精确信息；因此，描绘这些途径以及疾病增殖的过程是一个重要的研究领域。对恶性系统事件进行建模的计算方法有助于提高对可能的“触发因素”的理解，即发生在癌症发展过程中的异常微观分子信号的起始。在这里，我们引入了一个基于网络的模型，用于观察到的结肠癌不同阶段的遗传和表观遗传事件，重点是基因关系和肿瘤途径。此外，我们还描述了对结肠癌原位癌的两个基因网络的肿瘤进展记录的案例研究。我们目前的研究结果表明，与较大的、连接较少的基因集相比，一小部分密切相关的基因网络的肿瘤进展速度更高；因此，疾病的发展取决于对网络特性的评估。目前的工作旨在提供对异常修饰特征癌症起始和进展方式的深入了解。框架动态是根据三个主要层之间的相互依存关系来描述的：遗传和表观遗传事件、基因关系和癌症阶段水平。
