乳腺组织差异表达基因的研究

Mengzhen Jiang, Chao Wei, Guannan Chen
{"title":"乳腺组织差异表达基因的研究","authors":"Mengzhen Jiang, Chao Wei, Guannan Chen","doi":"10.1145/3351917.3351983","DOIUrl":null,"url":null,"abstract":"Nowadays, breast cancer has been considered as one of the most common malignant tumors among female diseases, and its incidence is increasing year by year. Genomic and transcriptome changes that affect cellular processes, such as cell proliferation, differentiation, apoptosis, and invasion, are commonly associated with the development of breast cancer. Epidemiological evidence has shown that the risk of breast cancer susceptibility varies among ethnic groups. In this paper, differentially expressed genes between human breast tumors and normal tissues are identified by studying Chinese, Malay and Indian ethnic groups and their paired tissues. The GO and KEGG methods were used for annotation and analysis of genes, and protein interaction networks were used to analyze protein interactions. The results of the study showed that there were 33 genes with significant differences in expression. The differentially expressed genes were CD36, LEP, LPL, ADIPOQ, PCK1, ACASL1, PPARG, PLIN1, ACACB and PPARG. In the protein interaction network, the interaction between AKR1C3 and AKR1C1 is the strongest. The study of differentially expressed genes and the search for proteins with the strongest interactions will contribute to the study of the molecular mechanism of the disease and the discovery of new drug targets, so as to improve the future treatment of breast cancer patients.","PeriodicalId":367885,"journal":{"name":"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on Differentially Expressed Genes in Breast Tissue\",\"authors\":\"Mengzhen Jiang, Chao Wei, Guannan Chen\",\"doi\":\"10.1145/3351917.3351983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, breast cancer has been considered as one of the most common malignant tumors among female diseases, and its incidence is increasing year by year. Genomic and transcriptome changes that affect cellular processes, such as cell proliferation, differentiation, apoptosis, and invasion, are commonly associated with the development of breast cancer. Epidemiological evidence has shown that the risk of breast cancer susceptibility varies among ethnic groups. In this paper, differentially expressed genes between human breast tumors and normal tissues are identified by studying Chinese, Malay and Indian ethnic groups and their paired tissues. The GO and KEGG methods were used for annotation and analysis of genes, and protein interaction networks were used to analyze protein interactions. The results of the study showed that there were 33 genes with significant differences in expression. The differentially expressed genes were CD36, LEP, LPL, ADIPOQ, PCK1, ACASL1, PPARG, PLIN1, ACACB and PPARG. In the protein interaction network, the interaction between AKR1C3 and AKR1C1 is the strongest. The study of differentially expressed genes and the search for proteins with the strongest interactions will contribute to the study of the molecular mechanism of the disease and the discovery of new drug targets, so as to improve the future treatment of breast cancer patients.\",\"PeriodicalId\":367885,\"journal\":{\"name\":\"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3351917.3351983\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 4th International Conference on Automation, Control and Robotics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3351917.3351983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目前,乳腺癌已被认为是女性疾病中最常见的恶性肿瘤之一,其发病率呈逐年上升趋势。影响细胞增殖、分化、凋亡和侵袭等细胞过程的基因组和转录组变化通常与乳腺癌的发生有关。流行病学证据表明,乳腺癌易感性的风险因种族而异。本文通过对中国人、马来人、印度人及其配对组织的研究,鉴定了人乳腺肿瘤与正常组织的差异表达基因。使用GO和KEGG方法对基因进行注释和分析,使用蛋白质相互作用网络分析蛋白质相互作用。研究结果显示,有33个基因在表达上存在显著差异。差异表达基因为CD36、LEP、LPL、ADIPOQ、PCK1、ACASL1、PPARG、PLIN1、ACACB和PPARG。在蛋白相互作用网络中,AKR1C3和AKR1C1之间的相互作用最强。研究差异表达基因,寻找相互作用最强的蛋白,将有助于研究疾病的分子机制,发现新的药物靶点,从而改善乳腺癌患者的未来治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Differentially Expressed Genes in Breast Tissue
Nowadays, breast cancer has been considered as one of the most common malignant tumors among female diseases, and its incidence is increasing year by year. Genomic and transcriptome changes that affect cellular processes, such as cell proliferation, differentiation, apoptosis, and invasion, are commonly associated with the development of breast cancer. Epidemiological evidence has shown that the risk of breast cancer susceptibility varies among ethnic groups. In this paper, differentially expressed genes between human breast tumors and normal tissues are identified by studying Chinese, Malay and Indian ethnic groups and their paired tissues. The GO and KEGG methods were used for annotation and analysis of genes, and protein interaction networks were used to analyze protein interactions. The results of the study showed that there were 33 genes with significant differences in expression. The differentially expressed genes were CD36, LEP, LPL, ADIPOQ, PCK1, ACASL1, PPARG, PLIN1, ACACB and PPARG. In the protein interaction network, the interaction between AKR1C3 and AKR1C1 is the strongest. The study of differentially expressed genes and the search for proteins with the strongest interactions will contribute to the study of the molecular mechanism of the disease and the discovery of new drug targets, so as to improve the future treatment of breast cancer patients.
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
自引率
0.00%
发文量
0
×
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