探索人类淋巴细胞对电离辐射反应的差异表达基因:一种网络生物学方法。

IF 1.8 Q3 ONCOLOGY
Radiation Oncology Journal Pub Date : 2021-03-01 Epub Date: 2021-03-24 DOI:10.3857/roj.2021.00045
Tamizh Selvan Gnana Sekaran, Vishakh R Kedilaya, Suchetha N Kumari, Praveenkumar Shetty, Pavan Gollapalli
{"title":"探索人类淋巴细胞对电离辐射反应的差异表达基因:一种网络生物学方法。","authors":"Tamizh Selvan Gnana Sekaran,&nbsp;Vishakh R Kedilaya,&nbsp;Suchetha N Kumari,&nbsp;Praveenkumar Shetty,&nbsp;Pavan Gollapalli","doi":"10.3857/roj.2021.00045","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The integration of large-scale gene data and their functional analysis needs the effective application of various computational tools. Here we attempted to unravel the biological processes and cellular pathways in response to ionizing radiation using a systems biology approach.</p><p><strong>Materials and methods: </strong>Analysis of gene ontology shows that 80, 42, 25, and 35 genes have roles in the biological process, molecular function, the cellular process, and immune system pathways, respectively. Therefore, our study emphasizes gene/protein network analysis on various differentially expressed genes (DEGs) to reveal the interactions between those proteins and their functional contribution upon radiation exposure.</p><p><strong>Results: </strong>A gene/protein interaction network was constructed, which comprises 79 interactors with 718 interactions and TP53, MAPK8, MAPK1, CASP3, MAPK14, ATM, NOTCH1, VEGFA, SIRT1, and PRKDC are the top 10 proteins in the network with high betweenness centrality values. Further, molecular complex detection was used to cluster these associated partners in the network, which produced three effective clusters based on the Molecular Complex Detection (MCODE) score. Interestingly, we found a high functional similarity from the associated genes/proteins in the network with known radiation response genes.</p><p><strong>Conclusion: </strong>This network-based approach on DEGs of human lymphocytes upon response to ionizing radiation provides clues for an opportunity to improve therapeutic efficacy.</p>","PeriodicalId":46572,"journal":{"name":"Radiation Oncology Journal","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/63/82/roj-2021-00045.PMC8024183.pdf","citationCount":"7","resultStr":"{\"title\":\"Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach.\",\"authors\":\"Tamizh Selvan Gnana Sekaran,&nbsp;Vishakh R Kedilaya,&nbsp;Suchetha N Kumari,&nbsp;Praveenkumar Shetty,&nbsp;Pavan Gollapalli\",\"doi\":\"10.3857/roj.2021.00045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The integration of large-scale gene data and their functional analysis needs the effective application of various computational tools. Here we attempted to unravel the biological processes and cellular pathways in response to ionizing radiation using a systems biology approach.</p><p><strong>Materials and methods: </strong>Analysis of gene ontology shows that 80, 42, 25, and 35 genes have roles in the biological process, molecular function, the cellular process, and immune system pathways, respectively. Therefore, our study emphasizes gene/protein network analysis on various differentially expressed genes (DEGs) to reveal the interactions between those proteins and their functional contribution upon radiation exposure.</p><p><strong>Results: </strong>A gene/protein interaction network was constructed, which comprises 79 interactors with 718 interactions and TP53, MAPK8, MAPK1, CASP3, MAPK14, ATM, NOTCH1, VEGFA, SIRT1, and PRKDC are the top 10 proteins in the network with high betweenness centrality values. Further, molecular complex detection was used to cluster these associated partners in the network, which produced three effective clusters based on the Molecular Complex Detection (MCODE) score. Interestingly, we found a high functional similarity from the associated genes/proteins in the network with known radiation response genes.</p><p><strong>Conclusion: </strong>This network-based approach on DEGs of human lymphocytes upon response to ionizing radiation provides clues for an opportunity to improve therapeutic efficacy.</p>\",\"PeriodicalId\":46572,\"journal\":{\"name\":\"Radiation Oncology Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/63/82/roj-2021-00045.PMC8024183.pdf\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiation Oncology Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3857/roj.2021.00045\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/3/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiation Oncology Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3857/roj.2021.00045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/3/24 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 7

摘要

目的:大规模基因数据的整合及其功能分析需要各种计算工具的有效应用。在这里,我们试图解开生物过程和细胞途径响应电离辐射使用系统生物学的方法。材料与方法:基因本体分析表明,80个、42个、25个和35个基因分别在生物过程、分子功能、细胞过程和免疫系统途径中发挥作用。因此,我们的研究强调对各种差异表达基因(DEGs)的基因/蛋白质网络分析,以揭示这些蛋白质之间的相互作用及其对辐射暴露的功能贡献。结果:构建了基因/蛋白相互作用网络,共79个相互作用蛋白,共718个相互作用蛋白,其中TP53、MAPK8、MAPK1、CASP3、MAPK14、ATM、NOTCH1、VEGFA、SIRT1和PRKDC是网络中中间度中心性值较高的前10个蛋白。此外,利用分子复合物检测对网络中的相关伙伴进行聚类,根据分子复合物检测(MCODE)得分产生三个有效的聚类。有趣的是,我们发现网络中的相关基因/蛋白质与已知的辐射反应基因具有高度的功能相似性。结论:基于网络的人淋巴细胞对电离辐射反应的deg研究为提高治疗效果提供了线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach.

Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach.

Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach.

Exploring the differentially expressed genes in human lymphocytes upon response to ionizing radiation: a network biology approach.

Purpose: The integration of large-scale gene data and their functional analysis needs the effective application of various computational tools. Here we attempted to unravel the biological processes and cellular pathways in response to ionizing radiation using a systems biology approach.

Materials and methods: Analysis of gene ontology shows that 80, 42, 25, and 35 genes have roles in the biological process, molecular function, the cellular process, and immune system pathways, respectively. Therefore, our study emphasizes gene/protein network analysis on various differentially expressed genes (DEGs) to reveal the interactions between those proteins and their functional contribution upon radiation exposure.

Results: A gene/protein interaction network was constructed, which comprises 79 interactors with 718 interactions and TP53, MAPK8, MAPK1, CASP3, MAPK14, ATM, NOTCH1, VEGFA, SIRT1, and PRKDC are the top 10 proteins in the network with high betweenness centrality values. Further, molecular complex detection was used to cluster these associated partners in the network, which produced three effective clusters based on the Molecular Complex Detection (MCODE) score. Interestingly, we found a high functional similarity from the associated genes/proteins in the network with known radiation response genes.

Conclusion: This network-based approach on DEGs of human lymphocytes upon response to ionizing radiation provides clues for an opportunity to improve therapeutic efficacy.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.50
自引率
4.30%
发文量
24
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信