Identification of Pathway Deregulation – Gene Expression Based Analysis of Consistent Signal Transduction

Signaling pathways belong to a complex system of communication that governs cellular processes. They represent signal transduction from an extracellular stimulus via a receptor to intracellular mediators, as well as intracellular interactions. Perturbations in signaling cascade often lead to detrimental changes in cell function and cause many diseases, including cancer. Identification of deregulated pathways may advance the understanding of complex diseases and lead to improvement of therapeutic strategies. We propose Analysis of Consistent Signal Transduction (ACST), a novel method for analysis of signaling pathways. Our method incorporates information regarding pathway topology, as well as data on the position of every gene in each pathway. To preserve gene-gene interactions we use a subject-sampling permutation model to assess the significance of pathway perturbations. We applied our approach to nine independent datasets of global gene expression profiling. The results of ACST, as well as three other methods used to analyze signaling pathways, are presented in the context of biological significance and repeatability among similar, yet independent, datasets. We demonstrate the usefulness of using information of pathway structure as well as genes’ functions in the analysis of signaling pathways. We also show that ACST leads to biologically meaningful results and high repeatability.信号通路（Signaling pathways）是调控细胞生命活动的复杂通信系统。其涵盖了从细胞外刺激经受体传递至细胞内介质的信号转导过程，以及细胞内的相互作用。信号级联反应发生扰动时，常会引发细胞功能出现有害改变，并导致包括癌症在内的多种疾病。对失调信号通路的识别，有助于深化对复杂疾病的认知，并推动治疗策略的优化。本研究提出了一致性信号转导分析（Analysis of Consistent Signal Transduction，ACST）这一全新的信号通路分析方法。该方法整合了通路拓扑结构相关信息，以及每条通路内各基因的位置数据。为保留基因间的相互作用关系，本方法采用基于样本抽样的置换模型来评估通路扰动的显著性。我们将该方法应用于9组独立的全基因表达谱数据集。本研究从生物学意义以及相似但独立数据集间的可重复性两个维度，展示了ACST与另外3种信号通路分析方法的分析结果。本研究证实了在信号通路分析中整合通路结构与基因功能信息的有效性，同时证明ACST能够获得具备生物学意义的分析结果，且具有较高的可重复性。