{"title":"CTTIME: A Database for Analyzing Cancer Therapy's Impact on Tumor Immune Microenvironment.","authors":"Chengjie Zhang, Yu Dong, Yuan Liu, Jintong Shi, Leng Han, Youqiong Ye","doi":"10.1093/gpbjnl/qzaf086","DOIUrl":null,"url":null,"abstract":"<p><p>Tumor immune microenvironment (TIME) significantly affects the regulation of immune checkpoint blockade (ICB)- based therapy. Anti-cancer drugs also have the potential to modify the TIME, which in turn affects the potency of ICB and combined therapies. Therefore, identifying the prediction of therapeutic efficacy and developing combination therapy strategies will be significantly enhanced by placing the dynamic change of TIME during anti-cancer therapies in cancer types. A computational pipeline and database was designed to identify dynamic molecular profiles under various anti-cancer therapies. This database comprised 92 transcriptomic datasets, including 5311 pre- and post-treatment biopsies from 20 cancer types and 9 treatment strategies. A systematic approach was used to identify differentially expressed genes (DEGs) and functional enrichment, significant associations among immune cell populations, and dynamic alteration of immune cell abundance and ICB-related immune features during various therapeutic strategies. Finally, a user-friendly database, Impact of Cancer Therapy on TIME (CTTIME), was developed to browse, search, visualize, and download data of interest which will serve as a valuable resource for investigating innovative anti-cancer therapies. CTTIME is available at https://www.cttime.yelab.site/.</p>","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9000,"publicationDate":"2025-09-22","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/qzaf086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Tumor immune microenvironment (TIME) significantly affects the regulation of immune checkpoint blockade (ICB)- based therapy. Anti-cancer drugs also have the potential to modify the TIME, which in turn affects the potency of ICB and combined therapies. Therefore, identifying the prediction of therapeutic efficacy and developing combination therapy strategies will be significantly enhanced by placing the dynamic change of TIME during anti-cancer therapies in cancer types. A computational pipeline and database was designed to identify dynamic molecular profiles under various anti-cancer therapies. This database comprised 92 transcriptomic datasets, including 5311 pre- and post-treatment biopsies from 20 cancer types and 9 treatment strategies. A systematic approach was used to identify differentially expressed genes (DEGs) and functional enrichment, significant associations among immune cell populations, and dynamic alteration of immune cell abundance and ICB-related immune features during various therapeutic strategies. Finally, a user-friendly database, Impact of Cancer Therapy on TIME (CTTIME), was developed to browse, search, visualize, and download data of interest which will serve as a valuable resource for investigating innovative anti-cancer therapies. CTTIME is available at https://www.cttime.yelab.site/.
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