Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
Bioinformatics Unit, George Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
Front Endocrinol (Lausanne). 2020 Jul 7;11:435. doi: 10.3389/fendo.2020.00435. eCollection 2020.
Insulin and insulin-like growth factor-1 (IGF1), acting respectively via the insulin (INSR) and IGF1 (IGF1R) receptors, play key developmental and metabolic roles throughout life. In addition, both signaling pathways fulfill important roles in cancer initiation and progression. The present study was aimed at identifying mechanistic differences between INSR and IGF1R using a recently developed bioinformatics tool, the Biological Network Simulator (BioNSi). This application allows to import and merge multiple pathways and interaction information from the KEGG database into a single network representation. The BioNsi network simulation tool allowed us to exploit the availability of gene expression data derived from breast cancer cell lines with specific disruptions of the INSR or IGF1R genes in order to investigate potential differences in protein expression that might be linked to biological attributes of the specific receptor networks. Modeling-generated information was corroborated by experimental and biological assays. BioNSi analyses revealed that the expression of 75 and 71 genes changed during simulation of IGF1R-KD and INSR-KD, compared to control cells, respectively. Out of 16 proteins that BioNSi analysis was based on, validated by Western blotting, nine were shown to be involved in DNA repair, eight in cell cycle checkpoints, six in proliferation, eight in apoptosis, seven in oxidative stress, six in cell migration, two in energy homeostasis, and three in senescence. Taken together, analyses identified a number of commonalities and, most importantly, dissimilarities between the IGF1R and INSR pathways that might help explain the basis for the biological differences between these networks.
胰岛素和胰岛素样生长因子-1(IGF1)分别通过胰岛素(INSR)和 IGF1 受体(IGF1R)发挥作用,在整个生命周期中发挥关键的发育和代谢作用。此外,这两个信号通路在癌症的发生和发展中都起着重要作用。本研究旨在使用一种新开发的生物信息学工具,即生物网络模拟器(BioNSi),来识别 INSR 和 IGF1R 之间的机制差异。该应用程序允许从 KEGG 数据库导入和合并多个途径和相互作用信息到单个网络表示中。BioNsi 网络模拟工具使我们能够利用来自具有特定 INSR 或 IGF1R 基因缺失的乳腺癌细胞系的基因表达数据,以研究可能与特定受体网络的生物学特征相关的潜在蛋白质表达差异。建模生成的信息通过实验和生物学测定得到了证实。BioNSi 分析显示,与对照细胞相比,IGF1R-KD 和 INSR-KD 模拟过程中分别有 75 个和 71 个基因的表达发生了变化。在基于 BioNSi 分析的 16 种蛋白质中,有 9 种被证实参与 DNA 修复,8 种参与细胞周期检查点,6 种参与增殖,8 种参与凋亡,7 种参与氧化应激,6 种参与细胞迁移,2 种参与能量稳态,3 种参与衰老。总之,分析结果确定了 IGF1R 和 INSR 通路之间的一些共性和最重要的差异,这可能有助于解释这些网络之间生物学差异的基础。