CIEC:癌症跨组织免疫细胞类型富集和表达图谱可视化。

Jinhua He, Haitao Luo, Wei Wang, Dechao Bu, Zhengkai Zou, Haolin Wang, Hongzhen Tang, Zeping Han, Wenfeng Luo, Jian Shen, Fangmei Xie, Yi Zhao, Zhiming Xiang
{"title":"CIEC:癌症跨组织免疫细胞类型富集和表达图谱可视化。","authors":"Jinhua He, Haitao Luo, Wei Wang, Dechao Bu, Zhengkai Zou, Haolin Wang, Hongzhen Tang, Zeping Han, Wenfeng Luo, Jian Shen, Fangmei Xie, Yi Zhao, Zhiming Xiang","doi":"10.1093/gpbjnl/qzae067","DOIUrl":null,"url":null,"abstract":"<p><p>Single-cell transcriptome sequencing technology has been applied to decode the cell types and functional states of immune cells, revealing their tissue-specific gene expression patterns and functions in cancer immunity. Comprehensive assessments of immune cells within and across tissues will provide us with a deeper understanding of the tumor immune system in general. Here, we present Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), the first web-based application that integrates database and enrichment analysis to estimate the cross-tissue immune cell type or state. CIEC version 1.0 consists of 480 samples covering primary tumor, adjacent normal tissue, lymph node, metastasis tissue, and peripheral blood from 323 cancer patients. By applying integrative analysis, we constructed an immune cell-type/state map for each context and adopted our previously developed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm to estimate the enrichment for context-specific immune cell type/state. In addition, CIEC also provides an easy-to-use online interface for users to comprehensively analyze the immune cell characteristics mapped across multiple tissues, including expression map, correlation, similar genes detection, signature score, and expression comparison. We believe that CIEC will be a valuable resource for exploring the intrinsic characteristics of immune cells in cancer patients and for potentially guiding novel cancer-immune biomarker development and immunotherapy strategies. CIEC is freely accessible at http://ciec.gene.ac/.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CIEC: Cross-tissue Immune Cell Type Enrichment and Expression Map Visualization for Cancer.\",\"authors\":\"Jinhua He, Haitao Luo, Wei Wang, Dechao Bu, Zhengkai Zou, Haolin Wang, Hongzhen Tang, Zeping Han, Wenfeng Luo, Jian Shen, Fangmei Xie, Yi Zhao, Zhiming Xiang\",\"doi\":\"10.1093/gpbjnl/qzae067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Single-cell transcriptome sequencing technology has been applied to decode the cell types and functional states of immune cells, revealing their tissue-specific gene expression patterns and functions in cancer immunity. Comprehensive assessments of immune cells within and across tissues will provide us with a deeper understanding of the tumor immune system in general. Here, we present Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), the first web-based application that integrates database and enrichment analysis to estimate the cross-tissue immune cell type or state. CIEC version 1.0 consists of 480 samples covering primary tumor, adjacent normal tissue, lymph node, metastasis tissue, and peripheral blood from 323 cancer patients. By applying integrative analysis, we constructed an immune cell-type/state map for each context and adopted our previously developed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm to estimate the enrichment for context-specific immune cell type/state. In addition, CIEC also provides an easy-to-use online interface for users to comprehensively analyze the immune cell characteristics mapped across multiple tissues, including expression map, correlation, similar genes detection, signature score, and expression comparison. We believe that CIEC will be a valuable resource for exploring the intrinsic characteristics of immune cells in cancer patients and for potentially guiding novel cancer-immune biomarker development and immunotherapy strategies. CIEC is freely accessible at http://ciec.gene.ac/.</p>\",\"PeriodicalId\":94020,\"journal\":{\"name\":\"Genomics, proteomics & bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genomics, proteomics & bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/gpbjnl/qzae067\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics, proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gpbjnl/qzae067","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

单细胞转录组测序技术已被用于解码免疫细胞的细胞类型和功能状态,揭示它们在癌症免疫中的组织特异性基因表达模式和功能。对组织内和组织间免疫细胞的全面评估将使我们对肿瘤免疫系统有更深入的了解。在这里,我们提出了癌症基因列表的跨组织免疫细胞类型或状态富集分析(CIEC),这是第一个基于网络的应用,它整合了数据库和富集分析,以估计跨组织免疫细胞类型或状态。CIEC 1.0 版包含 480 份样本,涵盖原发肿瘤、邻近正常组织、淋巴结、转移组织和外周血,来自 323 名癌症患者。通过综合分析,我们构建了每个背景的免疫细胞类型/状态图,并采用我们之前开发的《京都基因组百科全书》(KEGG)基于选集的注释系统(KOBAS)算法来估算背景特异性免疫细胞类型/状态的富集度。此外,CIEC还提供了一个易于使用的在线界面,供用户全面分析多个组织中免疫细胞的特征,包括表达图谱、相关性、相似基因检测、特征得分和表达比较。我们相信,CIEC 将成为探索癌症患者免疫细胞内在特征的宝贵资源,并有可能指导新型癌症免疫生物标记物的开发和免疫治疗策略。CIEC 可在 http://ciec.gene.ac/ 免费访问。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
CIEC: Cross-tissue Immune Cell Type Enrichment and Expression Map Visualization for Cancer.

Single-cell transcriptome sequencing technology has been applied to decode the cell types and functional states of immune cells, revealing their tissue-specific gene expression patterns and functions in cancer immunity. Comprehensive assessments of immune cells within and across tissues will provide us with a deeper understanding of the tumor immune system in general. Here, we present Cross-tissue Immune cell type or state Enrichment analysis of gene lists for Cancer (CIEC), the first web-based application that integrates database and enrichment analysis to estimate the cross-tissue immune cell type or state. CIEC version 1.0 consists of 480 samples covering primary tumor, adjacent normal tissue, lymph node, metastasis tissue, and peripheral blood from 323 cancer patients. By applying integrative analysis, we constructed an immune cell-type/state map for each context and adopted our previously developed Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) algorithm to estimate the enrichment for context-specific immune cell type/state. In addition, CIEC also provides an easy-to-use online interface for users to comprehensively analyze the immune cell characteristics mapped across multiple tissues, including expression map, correlation, similar genes detection, signature score, and expression comparison. We believe that CIEC will be a valuable resource for exploring the intrinsic characteristics of immune cells in cancer patients and for potentially guiding novel cancer-immune biomarker development and immunotherapy strategies. CIEC is freely accessible at http://ciec.gene.ac/.

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
期刊最新文献
Evolution of Plant Genome Size and Composition. Enzymes Repertoires and Genomic Insights into Lycium Barbarum Pectin Polysaccharides Biosynthesis. Multi-omics Mediated Wide Association Studies: Novel Approaches for Understanding Diseases. Centromere Landscapes Resolved from Hundreds of Human Genomes. The Role of N6-methyladenosine Modification in Gametogenesis and Embryogenesis: Impact on Fertility.
×
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