Tan Xiaodong, Liu Peng, Huang Yinpeng, Zhou Lei, Yang Yifan, Wang Huaitao, Yu Boqiang, Meng Xiangli, Zhang Xiaobo, Gao Feng
Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, P.R.China.
PLoS One. 2016 Mar 25;11(3):e0152280. doi: 10.1371/journal.pone.0152280. eCollection 2016.
Mechanisms of abnormal protein phosphorylation that regulate cell invasion and metastasis in pancreatic cancer remain obscure. In this study, we used high-throughput phosphorylation array to test two pancreatic cancer cell lines (PC-1 cells with a low, and PC-1.0 cells with a high potential for invasion and metastasis). We noted that a total of 57 proteins revealed a differential expression (fold change ≥ 2.0). Six candidate proteins were further validated by western blot with results found to be accordance with the array. Of 57 proteins, 32 up-regulated proteins (e.g. CaMK1-α and P90RSK) were mainly involved in ErbB and neurotrophin signaling pathways as determined using DAVID software, while 25 down-regulated proteins (e.g. BID and BRCA1) were closely involved in apoptosis and p53 signaling pathways. Moreover, four proteins (AKT1, Chk2, p53 and P70S6K) with different phosphorylation sites were found, not only among up-regulated, but also among down-regulated proteins. Importantly, specific phosphorylation sites can affect cell biological functions. CentiScaPe software calculated topological characteristics of each node in the protein-protein interaction (PPI) network: we found that AKT1 owns the maximum node degrees and betweenness in the up-regulation protein PPI network (26 nodes, average path length: 1.89, node degrees: 6.62±4.18, betweenness: 22.23±35.72), and p53 in the down-regulation protein PPI network (17 nodes, average path length: 2.04, node degrees: 3.65±2.47, betweenness: 16.59±29.58). In conclusion, the identification of abnormal protein phosphorylation related to invasion and metastasis may allow us to identify new biomarkers in an effort to develop novel therapeutic drug targets for pancreatic cancer treatment.
调节胰腺癌细胞侵袭和转移的异常蛋白磷酸化机制仍不清楚。在本研究中,我们使用高通量磷酸化芯片检测了两种胰腺癌细胞系(侵袭和转移潜能低的PC-1细胞以及侵袭和转移潜能高的PC-1.0细胞)。我们注意到共有57种蛋白呈现差异表达(倍数变化≥2.0)。通过蛋白质印迹法进一步验证了6种候选蛋白,结果与芯片检测结果一致。在这57种蛋白中,使用DAVID软件确定,32种上调蛋白(如CaMK1-α和P90RSK)主要参与ErbB和神经营养因子信号通路,而25种下调蛋白(如BID和BRCA1)密切参与凋亡和p53信号通路。此外,在上调和下调蛋白中均发现了4种具有不同磷酸化位点的蛋白(AKT1、Chk2、p53和P70S6K)。重要的是,特定的磷酸化位点可影响细胞生物学功能。CentiScaPe软件计算了蛋白质-蛋白质相互作用(PPI)网络中每个节点的拓扑特征:我们发现AKT1在上调蛋白PPI网络中具有最大的节点度和介数(26个节点,平均路径长度:1.89,节点度:6.62±4.18,介数:22.23±35.72),而p53在下调蛋白PPI网络中具有最大的节点度和介数(17个节点,平均路径长度:2.04,节点度:3.65±2.47,介数:16.59±29.58)。总之,鉴定与侵袭和转移相关的异常蛋白磷酸化可能使我们能够识别新的生物标志物,从而努力开发用于胰腺癌治疗的新型治疗药物靶点。