Zhang Junpeng, Le Thuc Duy, Liu Lin, He Jianfeng, Li Jiuyong
School of Engineering, Dali University, Dali, Yunnan 671003, China.
School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA 5095, Australia.
Gene. 2016 Feb 10;577(1):55-64. doi: 10.1016/j.gene.2015.11.023. Epub 2015 Nov 27.
Recent studies have shown that transcription factors (TFs) and microRNAs (miRNAs), while independently regulate their downstream targets, collaborate with each other to regulate gene expression. However, their synergistic roles in protein-protein interactions (PPIs) remain mostly unknown. In this paper, we present a novel framework (called CoRePPI) for inferring TF and miRNA co-regulation of PPIs. Particularly, CoRePPI is aimed at discovering the co-regulation specific to a condition of interest, by using heterogeneous data, including miRNA and messenger RNA (mRNA) expression profiles, putative miRNA targets, TF targets and PPIs. CoRePPI firstly finds the network motifs indicating the co-regulation of PPIs by TFs and miRNAs in tumor and normal conditions separately. Then by identifying the differential motifs found in one condition but not in the other, it builds the networks consisting of TFs, miRNAs and their co-regulated PPIs specific to different conditions respectively. To validate CoRePPI, we apply it to the Pan-Cancer dataset which includes the expression profiles of 12 cancer types from TCGA. Through network topology analysis, we found that the tumor and normal CoRePPI networks are scale-free. Furthermore, the results of differential and intersected network analysis between the tumor and normal CoRePPI networks suggest that only a small fraction of the regulatory relationships between TFs and miRNAs are conserved in both conditions but they co-regulate different downstream PPIs in tumor and normal conditions; and in different conditions the majority of the regulatory relationships between TFs and miRNAs are different although they may regulate the same PPIs in their respective conditions. The CoRePPI sub-networks constructed for the three types of cancers (breast cancer, lung cancer and ovarian cancer) are all scale-free, and the intersection of these CoRePPI sub-networks can be utilized as the biomarker CoRePPI sub-network of the three types of cancers. The PPI enrichment analyses of the tumor and normal CoRePPI networks suggest that the co-regulating TFs and miRNAs are significantly associated with the specific biological processes, diseases and pathways. In addition, comparing with the two non-condition-specific approaches, the tumor CoRePPI network is found to have the most enriched cancer-related PPIs. Altogether, the results uncover the combined regulatory patterns of TFs and miRNAs on the PPIs, and may provide new insights for research in cancer-associated TFs and miRNAs.
近期研究表明,转录因子(TFs)和微小RNA(miRNAs)虽然各自独立调控其下游靶点,但它们相互协作以调控基因表达。然而,它们在蛋白质-蛋白质相互作用(PPIs)中的协同作用大多仍不为人知。在本文中,我们提出了一种用于推断TF和miRNA对PPIs的共同调控的新框架(称为CoRePPI)。具体而言,CoRePPI旨在通过使用包括miRNA和信使RNA(mRNA)表达谱、假定的miRNA靶点、TF靶点和PPIs在内的异构数据,发现特定感兴趣条件下的共同调控。CoRePPI首先分别在肿瘤和正常条件下找到指示TFs和miRNAs对PPIs共同调控的网络基序。然后,通过识别在一种条件下而非另一种条件下发现的差异基序,它分别构建由TFs、miRNAs及其在不同条件下共同调控的PPIs组成的网络。为了验证CoRePPI,我们将其应用于泛癌数据集,该数据集包括来自TCGA的12种癌症类型的表达谱。通过网络拓扑分析,我们发现肿瘤和正常CoRePPI网络都是无标度的。此外,肿瘤和正常CoRePPI网络之间的差异和交叉网络分析结果表明,TFs和miRNAs之间只有一小部分调控关系在两种条件下都是保守的,但它们在肿瘤和正常条件下共同调控不同的下游PPIs;并且在不同条件下,TFs和miRNAs之间的大多数调控关系是不同的,尽管它们可能在各自条件下调控相同的PPIs。为三种癌症(乳腺癌、肺癌和卵巢癌)构建的CoRePPI子网都是无标度的,并且这些CoRePPI子网的交集可以用作这三种癌症的生物标志物CoRePPI子网。肿瘤和正常CoRePPI网络的PPI富集分析表明,共同调控的TFs和miRNAs与特定的生物学过程、疾病和途径显著相关。此外,与两种非条件特异性方法相比,发现肿瘤CoRePPI网络具有最丰富的癌症相关PPIs。总之,这些结果揭示了TFs和miRNAs对PPIs的联合调控模式,并可能为癌症相关TFs和miRNAs的研究提供新的见解。