通过生物信息学分析,确定与转移性乳腺癌和耐受性树突状细胞相关的重要枢纽基因和通路。

IF 7 2区 医学 Q1 BIOLOGY Computers in biology and medicine Pub Date : 2024-11-16 DOI:10.1016/j.compbiomed.2024.109396
Kirstie Wong Chee Ching , Noor Fatmawati Mokhtar , Gee Jun Tye
{"title":"通过生物信息学分析,确定与转移性乳腺癌和耐受性树突状细胞相关的重要枢纽基因和通路。","authors":"Kirstie Wong Chee Ching ,&nbsp;Noor Fatmawati Mokhtar ,&nbsp;Gee Jun Tye","doi":"10.1016/j.compbiomed.2024.109396","DOIUrl":null,"url":null,"abstract":"<div><div>Metastatic breast cancer (MBC) is an advanced-stage breast cancer associated with more than 90 % of cancer-related deaths. Immunosuppressive properties of tolerogenic dendritic cells (tolDCs) in tumour immune microenvironment (TIME) may be a risk factor for the rapid progression to MBC. However, the exact connections between the two are unknown. The aim of the current study is to uncover gene signatures and key pathways associated with MBC and tolDCs via an integrated bioinformatics approach. Gene expression profiles of MBC and tolDCs were retrieved from Gene Expression Omnibus (GEO) to identify common differentially expressed genes (DEGs). From DGE analysis, 529 upregulated common DEGs and 367 downregulated common DEGs had been identified. In enrichment analysis, common DEGs enriched in GO terms of defense response to virus and KEGG pathway of transcriptional misregulation in cancer were reported to be significantly associated with MBC and tolDCs. From the constructed PPI networks, 23 hub genes were identified, although only 5 genes were significant; 3 upregulated (<em>ISG15</em>, <em>OAS2</em> and <em>RSAD2</em>) and 2 downregulated (<em>eEF2</em> and <em>PPARG</em>) as they were found to be significantly correlated and had the same expression trend as predicted in validation analysis of overall survival (OS) analysis, expression levels, immune infiltration analysis and immunohistochemistry (IHC) analysis. These 5 hub genes can now be exploited in developing novel therapeutic interventions and as diagnostic biomarkers for enhancing the clinical outcomes of MBC patients.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"184 ","pages":"Article 109396"},"PeriodicalIF":7.0000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of significant hub genes and pathways associated with metastatic breast cancer and tolerogenic dendritic cell via bioinformatics analysis\",\"authors\":\"Kirstie Wong Chee Ching ,&nbsp;Noor Fatmawati Mokhtar ,&nbsp;Gee Jun Tye\",\"doi\":\"10.1016/j.compbiomed.2024.109396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Metastatic breast cancer (MBC) is an advanced-stage breast cancer associated with more than 90 % of cancer-related deaths. Immunosuppressive properties of tolerogenic dendritic cells (tolDCs) in tumour immune microenvironment (TIME) may be a risk factor for the rapid progression to MBC. However, the exact connections between the two are unknown. The aim of the current study is to uncover gene signatures and key pathways associated with MBC and tolDCs via an integrated bioinformatics approach. Gene expression profiles of MBC and tolDCs were retrieved from Gene Expression Omnibus (GEO) to identify common differentially expressed genes (DEGs). From DGE analysis, 529 upregulated common DEGs and 367 downregulated common DEGs had been identified. In enrichment analysis, common DEGs enriched in GO terms of defense response to virus and KEGG pathway of transcriptional misregulation in cancer were reported to be significantly associated with MBC and tolDCs. From the constructed PPI networks, 23 hub genes were identified, although only 5 genes were significant; 3 upregulated (<em>ISG15</em>, <em>OAS2</em> and <em>RSAD2</em>) and 2 downregulated (<em>eEF2</em> and <em>PPARG</em>) as they were found to be significantly correlated and had the same expression trend as predicted in validation analysis of overall survival (OS) analysis, expression levels, immune infiltration analysis and immunohistochemistry (IHC) analysis. These 5 hub genes can now be exploited in developing novel therapeutic interventions and as diagnostic biomarkers for enhancing the clinical outcomes of MBC patients.</div></div>\",\"PeriodicalId\":10578,\"journal\":{\"name\":\"Computers in biology and medicine\",\"volume\":\"184 \",\"pages\":\"Article 109396\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2024-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in biology and medicine\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0010482524014811\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in biology and medicine","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010482524014811","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

转移性乳腺癌(MBC)是一种晚期乳腺癌,与超过 90% 的癌症相关死亡有关。肿瘤免疫微环境(TIME)中的耐受性树突状细胞(tolDCs)的免疫抑制特性可能是导致 MBC 快速发展的一个风险因素。然而,两者之间的确切联系尚不清楚。本研究旨在通过综合生物信息学方法发现与 MBC 和 tolDCs 相关的基因特征和关键通路。研究人员从基因表达总库(GEO)中检索了 MBC 和 tolDCs 的基因表达谱,以确定常见的差异表达基因(DEGs)。通过 DGE 分析,确定了 529 个上调的常见 DEGs 和 367 个下调的常见 DEGs。在富集分析中,富集在对病毒的防御反应的GO术语和癌症转录失调的KEGG通路中的常见DEGs被报道与MBC和tolDCs显著相关。从构建的 PPI 网络中,发现了 23 个枢纽基因,但只有 5 个基因是显著的;3 个上调(ISG15、OAS2 和 RSAD2)和 2 个下调(eEF2 和 PPARG),因为在总生存期(OS)分析、表达水平、免疫浸润分析和免疫组化(IHC)分析等验证分析中,发现这些基因与预测的表达趋势显著相关并具有相同的表达趋势。现在可以利用这5个枢纽基因开发新的治疗干预措施,并将其作为诊断生物标志物,以提高MBC患者的临床疗效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Identification of significant hub genes and pathways associated with metastatic breast cancer and tolerogenic dendritic cell via bioinformatics analysis
Metastatic breast cancer (MBC) is an advanced-stage breast cancer associated with more than 90 % of cancer-related deaths. Immunosuppressive properties of tolerogenic dendritic cells (tolDCs) in tumour immune microenvironment (TIME) may be a risk factor for the rapid progression to MBC. However, the exact connections between the two are unknown. The aim of the current study is to uncover gene signatures and key pathways associated with MBC and tolDCs via an integrated bioinformatics approach. Gene expression profiles of MBC and tolDCs were retrieved from Gene Expression Omnibus (GEO) to identify common differentially expressed genes (DEGs). From DGE analysis, 529 upregulated common DEGs and 367 downregulated common DEGs had been identified. In enrichment analysis, common DEGs enriched in GO terms of defense response to virus and KEGG pathway of transcriptional misregulation in cancer were reported to be significantly associated with MBC and tolDCs. From the constructed PPI networks, 23 hub genes were identified, although only 5 genes were significant; 3 upregulated (ISG15, OAS2 and RSAD2) and 2 downregulated (eEF2 and PPARG) as they were found to be significantly correlated and had the same expression trend as predicted in validation analysis of overall survival (OS) analysis, expression levels, immune infiltration analysis and immunohistochemistry (IHC) analysis. These 5 hub genes can now be exploited in developing novel therapeutic interventions and as diagnostic biomarkers for enhancing the clinical outcomes of MBC 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
Computers in biology and medicine
Computers in biology and medicine 工程技术-工程:生物医学
CiteScore
11.70
自引率
10.40%
发文量
1086
审稿时长
74 days
期刊介绍: Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.
期刊最新文献
An adaptive enhanced human memory algorithm for multi-level image segmentation for pathological lung cancer images. Integrating multimodal learning for improved vital health parameter estimation. Riemannian manifold-based geometric clustering of continuous glucose monitoring to improve personalized diabetes management. Transformative artificial intelligence in gastric cancer: Advancements in diagnostic techniques. Artificial intelligence and deep learning algorithms for epigenetic sequence analysis: A review for epigeneticists and AI experts.
×
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