TIGER:肿瘤免疫治疗基因表达资源门户网站。

IF 11.5 2区 生物学 Q1 GENETICS & HEREDITY
Zhihang Chen , Ziwei Luo , Di Zhang , Huiqin Li , Xuefei Liu , Kaiyu Zhu , Hongwan Zhang , Zongping Wang , Penghui Zhou , Jian Ren , An Zhao , Zhixiang Zuo
{"title":"TIGER:肿瘤免疫治疗基因表达资源门户网站。","authors":"Zhihang Chen ,&nbsp;Ziwei Luo ,&nbsp;Di Zhang ,&nbsp;Huiqin Li ,&nbsp;Xuefei Liu ,&nbsp;Kaiyu Zhu ,&nbsp;Hongwan Zhang ,&nbsp;Zongping Wang ,&nbsp;Penghui Zhou ,&nbsp;Jian Ren ,&nbsp;An Zhao ,&nbsp;Zhixiang Zuo","doi":"10.1016/j.gpb.2022.08.004","DOIUrl":null,"url":null,"abstract":"<div><p><strong>Immunotherapy</strong> is a promising cancer treatment method; however, only a few patients benefit from it. The development of new immunotherapy strategies and effective <strong>biomarkers</strong> of response and resistance is urgently needed. Recently, high-throughput bulk and single-cell <strong>gene expression</strong> profiling technologies have generated valuable resources. However, these resources are not well organized and systematic analysis is difficult. Here, we present TIGER, a tumor immunotherapy gene expression resource, which contains bulk transcriptome data of 1508 tumor samples with clinical immunotherapy outcomes and 11,057 tumor/normal samples without clinical immunotherapy outcomes, as well as single-cell transcriptome data of 2,116,945 immune cells from 655 samples. TIGER provides many useful modules for analyzing collected and user-provided data. Using the resource in TIGER, we identified a tumor-enriched subset of CD4<sup>+</sup> T cells. Patients with melanoma with a higher signature score of this subset have a significantly better response and survival under immunotherapy. We believe that TIGER will be helpful in understanding anti-tumor immunity mechanisms and discovering effective biomarkers. TIGER is freely accessible at <span>http://tiger.canceromics.org/</span><svg><path></path></svg>.</p></div>","PeriodicalId":12528,"journal":{"name":"Genomics, Proteomics & Bioinformatics","volume":"21 2","pages":"Pages 337-348"},"PeriodicalIF":11.5000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"TIGER: A Web Portal of Tumor Immunotherapy Gene Expression Resource\",\"authors\":\"Zhihang Chen ,&nbsp;Ziwei Luo ,&nbsp;Di Zhang ,&nbsp;Huiqin Li ,&nbsp;Xuefei Liu ,&nbsp;Kaiyu Zhu ,&nbsp;Hongwan Zhang ,&nbsp;Zongping Wang ,&nbsp;Penghui Zhou ,&nbsp;Jian Ren ,&nbsp;An Zhao ,&nbsp;Zhixiang Zuo\",\"doi\":\"10.1016/j.gpb.2022.08.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><strong>Immunotherapy</strong> is a promising cancer treatment method; however, only a few patients benefit from it. The development of new immunotherapy strategies and effective <strong>biomarkers</strong> of response and resistance is urgently needed. Recently, high-throughput bulk and single-cell <strong>gene expression</strong> profiling technologies have generated valuable resources. However, these resources are not well organized and systematic analysis is difficult. Here, we present TIGER, a tumor immunotherapy gene expression resource, which contains bulk transcriptome data of 1508 tumor samples with clinical immunotherapy outcomes and 11,057 tumor/normal samples without clinical immunotherapy outcomes, as well as single-cell transcriptome data of 2,116,945 immune cells from 655 samples. TIGER provides many useful modules for analyzing collected and user-provided data. Using the resource in TIGER, we identified a tumor-enriched subset of CD4<sup>+</sup> T cells. Patients with melanoma with a higher signature score of this subset have a significantly better response and survival under immunotherapy. We believe that TIGER will be helpful in understanding anti-tumor immunity mechanisms and discovering effective biomarkers. TIGER is freely accessible at <span>http://tiger.canceromics.org/</span><svg><path></path></svg>.</p></div>\",\"PeriodicalId\":12528,\"journal\":{\"name\":\"Genomics, Proteomics & Bioinformatics\",\"volume\":\"21 2\",\"pages\":\"Pages 337-348\"},\"PeriodicalIF\":11.5000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genomics, Proteomics & Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1672022922000997\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics, Proteomics & Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1672022922000997","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 19

摘要

免疫疗法是一种很有前途的癌症治疗方法;然而,只有少数患者从中受益。迫切需要开发新的免疫治疗策略和有效的反应和耐药性生物标志物。近年来,高通量批量和单细胞基因表达谱技术产生了宝贵的资源。然而,这些资源没有得到很好的组织,很难进行系统的分析。在这里,我们介绍了肿瘤免疫疗法基因表达资源TIGER,它包含1508个具有临床免疫疗法结果的肿瘤样本和11057个没有临床免疫治疗结果的肿瘤/正常样本的大量转录组数据,以及655个样本的2116945个免疫细胞的单细胞转录组数据。TIGER为分析收集的数据和用户提供的数据提供了许多有用的模块。利用TIGER中的资源,我们鉴定了CD4+T细胞的肿瘤富集亚群。该亚群特征得分较高的黑色素瘤患者在免疫治疗下的反应和生存率明显更好。我们相信TIGER将有助于了解抗肿瘤免疫机制和发现有效的生物标志物。TIGER可在http://tiger.canceromics.org/.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TIGER: A Web Portal of Tumor Immunotherapy Gene Expression Resource

Immunotherapy is a promising cancer treatment method; however, only a few patients benefit from it. The development of new immunotherapy strategies and effective biomarkers of response and resistance is urgently needed. Recently, high-throughput bulk and single-cell gene expression profiling technologies have generated valuable resources. However, these resources are not well organized and systematic analysis is difficult. Here, we present TIGER, a tumor immunotherapy gene expression resource, which contains bulk transcriptome data of 1508 tumor samples with clinical immunotherapy outcomes and 11,057 tumor/normal samples without clinical immunotherapy outcomes, as well as single-cell transcriptome data of 2,116,945 immune cells from 655 samples. TIGER provides many useful modules for analyzing collected and user-provided data. Using the resource in TIGER, we identified a tumor-enriched subset of CD4+ T cells. Patients with melanoma with a higher signature score of this subset have a significantly better response and survival under immunotherapy. We believe that TIGER will be helpful in understanding anti-tumor immunity mechanisms and discovering effective biomarkers. TIGER is freely accessible at http://tiger.canceromics.org/.

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
Genomics, Proteomics & Bioinformatics
Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
14.30
自引率
4.20%
发文量
844
审稿时长
61 days
期刊介绍: Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.
×
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