Exploring the role of the Rab network in epithelial-to-mesenchymal transition.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2024-12-14 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbae200
Unmani Jaygude, Graham M Hughes, Jeremy C Simpson
{"title":"Exploring the role of the Rab network in epithelial-to-mesenchymal transition.","authors":"Unmani Jaygude, Graham M Hughes, Jeremy C Simpson","doi":"10.1093/bioadv/vbae200","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>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.</p><p><strong>Results: </strong>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, <i>resnet</i>, 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 <i>in vitro</i> studies are needed to confirm their role as predictive markers of cancer metastasis. The use of <i>resnet</i> within the systematic analysis approach described here can be easily applied to assess other gene families and their role in biological events of interest.</p><p><strong>Availability and implementation: </strong>Source code for <i>resnet</i> is freely available at https://github.com/Unmani199/resnet.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbae200"},"PeriodicalIF":2.4000,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11684074/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Motivation: 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.

Results: 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, resnet, 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 in vitro studies are needed to confirm their role as predictive markers of cancer metastasis. The use of resnet within the systematic analysis approach described here can be easily applied to assess other gene families and their role in biological events of interest.

Availability and implementation: Source code for resnet is freely available at https://github.com/Unmani199/resnet.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
探索 Rab 网络在上皮细胞向间质转化过程中的作用。
目的:rabb GTPases (Rabs)在哺乳动物细胞内的膜运输中起着至关重要的作用,其功能障碍与许多疾病有关。这个基因家族在几个关键的细胞过程中起作用。网络分析可以揭示Rab网络中相互作用模式的完整曲目,为疾病研究提供信息,为治疗干预开辟新的机会。结果:我们在上皮-间质转化(EMT)的背景下研究了Rabs及其相互作用物,EMT是癌症转移到远处器官的一个指标。拉布网络首先从文献分析中建立起来,并逐渐扩大。我们的Python模块resnet评估了其网络弹性,并选择了一个最佳大小的弹性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,在10种癌症类型中,与仅原发部位肿瘤相比,在转移性肿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可能在EMT中发挥关键作用,需要进一步的体外研究来证实它们作为癌症转移的预测标志物的作用。在这里描述的系统分析方法中使用resnet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。可用性和实现:resnet的源代码可在https://github.com/Unmani199/resnet免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
1.60
自引率
0.00%
发文量
0
期刊最新文献
Imputation for Lipidomics and Metabolomics (ImpLiMet): a web-based application for optimization and method selection for missing data imputation. estiMAge: development of a DNA methylation clock to estimate the methylation age of single cells. Integrative co-registration of elemental imaging and histopathology for enhanced spatial multimodal analysis of tissue sections through TRACE. Predicting CRISPR-Cas9 off-target effects in human primary cells using bidirectional LSTM with BERT embedding. Genal: a Python toolkit for genetic risk scoring and Mendelian randomization.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1