Jaygude Unmani, Hughes Graham M, Simpson Jeremy C
School of Biology and Environmental Science, University College Dublin, Dublin, Ireland.
Cell Screening Laboratory, School of Biology and Environmental Science, University College Dublin, Dublin, Ireland.
Bioinform Adv. 2024 Dec 14;5(1):vbae200. doi: 10.1093/bioadv/vbae200. eCollection 2025.
Rab GTPases (Rabs) are crucial for membrane trafficking within mammalian cells, and their dysfunction is implicated in many diseases. This gene family plays a role in several crucial cellular processes. Network analyses can uncover the complete repertoire of interaction patterns across the Rab network, informing disease research, opening new opportunities for therapeutic interventions.
We examined Rabs and their interactors in the context of epithelial-to-mesenchymal transition (EMT), an indicator of cancer metastasizing to distant organs. A Rab network was first established from analysis of literature and was gradually expanded. Our Python module, , assessed its network resilience and selected an optimally sized, resilient Rab network for further analyses. Pathway enrichment confirmed its role in EMT. We then identified 73 candidate genes showing a strong up-/down-regulation, across 10 cancer types, in patients with metastasized tumours compared to only primary-site tumours. We suggest that their encoded proteins might play a critical role in EMT, and further studies are needed to confirm their role as predictive markers of cancer metastasis. The use of within the systematic analysis approach described here can be easily applied to assess other gene families and their role in biological events of interest.
Source code for is freely available at https://github.com/Unmani199/resnet.
Rab GTP酶（Rabs）对哺乳动物细胞内的膜运输至关重要，其功能障碍与多种疾病有关。这个基因家族在几个关键的细胞过程中发挥作用。网络分析可以揭示Rab网络中完整的相互作用模式，为疾病研究提供信息，为治疗干预开辟新机会。
我们在上皮-间质转化（EMT）的背景下研究了Rabs及其相互作用分子，EMT是癌症转移到远处器官的一个指标。首先通过文献分析建立了一个Rab网络，并逐步扩展。我们的Python模块评估了其网络弹性，并选择了一个大小合适、有弹性的Rab网络进行进一步分析。通路富集证实了其在EMT中的作用。然后，我们确定了73个候选基因，与仅患有原发性肿瘤的患者相比，这些基因在10种癌症类型的转移瘤患者中表现出强烈的上调/下调。我们认为它们编码的蛋白质可能在EMT中起关键作用，需要进一步研究来证实它们作为癌症转移预测标志物的作用。这里描述的系统分析方法中使用的[具体内容缺失]可以很容易地应用于评估其他基因家族及其在感兴趣的生物学事件中的作用。
[具体内容缺失]的源代码可在https://github.com/Unmani199/resnet上免费获取。
