Wang Jiao, Wang Qian, Lu Dongfang, Zhou Fangfang, Wang Dong, Feng Ruili, Wang Kai, Molday Robert, Xie Jiang, Wen Tieqiao
Laboratory of Molecular Neural Biology, School of Life Sciences, Shanghai University, Shanghai, China.
School of Computer Engineering and Science, Shanghai University, Shanghai, China.
PLoS One. 2017 Jun 22;12(6):e0179900. doi: 10.1371/journal.pone.0179900. eCollection 2017.
Understanding the molecular mechanisms underlying cell migration, which plays an important role in tumor growth and progression, is critical for the development of novel tumor therapeutics. Overexpression of transmembrane protein 30A (TMEM30A) has been shown to initiate tumor cell migration, however, the molecular mechanisms through which this takes place have not yet been reported. Thus, we propose the integration of computational and experimental approaches by first predicting potential signaling networks regulated by TMEM30A using a) computational biology methods, b) our previous mass spectrometry results of the TMEM30A complex in mouse tissue, and c) a number of migration-related genes manually collected from the literature, and subsequently performing molecular biology experiments including the in vitro scratch assay and real-time quantitative polymerase chain reaction (qPCR) to validate the reliability of the predicted network. The results verify that the genes identified in the computational signaling network are indeed regulated by TMEM30A during cell migration, indicating the effectiveness of our proposed method and shedding light on the regulatory mechanisms underlying tumor migration, which facilitates the understanding of the molecular basis of tumor invasion.
了解细胞迁移背后的分子机制对新型肿瘤治疗方法的开发至关重要，因为细胞迁移在肿瘤生长和进展中起着重要作用。跨膜蛋白30A（TMEM30A）的过表达已被证明可引发肿瘤细胞迁移，然而，其发生的分子机制尚未见报道。因此，我们建议整合计算方法和实验方法，首先使用a）计算生物学方法、b）我们之前在小鼠组织中对TMEM30A复合物的质谱分析结果以及c）从文献中手动收集的一些与迁移相关的基因来预测由TMEM30A调控的潜在信号网络，随后进行分子生物学实验，包括体外划痕试验和实时定量聚合酶链反应（qPCR），以验证预测网络的可靠性。结果证实，在计算信号网络中鉴定出的基因在细胞迁移过程中确实受TMEM30A调控，这表明我们所提出方法的有效性，并揭示了肿瘤迁移的调控机制，有助于理解肿瘤侵袭的分子基础。
