{"title":"CTR-DB 2.0:更新的癌症临床转录组资源,扩展了原发性耐药性数据集,并新增加了获得的耐药性数据集,加强了预测性生物标志物的发现和验证。","authors":"Jianzhou Jiang, Yajie Ma, Lele Yang, Shurui Ma, Zixuan Yu, Xinyi Ren, Xiangya Kong, Xinlei Zhang, Dong Li, Zhongyang Liu","doi":"10.1093/nar/gkae993","DOIUrl":null,"url":null,"abstract":"<p><p>Drug resistance is a principal limiting factor in cancer treatment. CTR-DB, the Cancer Treatment Response gene signature DataBase, is the first data resource for clinical transcriptomes with cancer treatment response, and meanwhile supports various data analysis functions, providing insights into the molecular determinants of drug resistance. Here we proposed an upgraded version, CTR-DB 2.0 (http://ctrdb.ncpsb.org.cn). Around 190 up-to-date source datasets with primary resistance information (129% increase compared to version 1.0) and 13 acquired-resistant datasets (a new dataset type), covering 10 856 patient samples (111% increase), 39 cancer types (39% increase) and 346 therapeutic regimens (26% increase), have been collected. In terms of function, for the single dataset analysis and multiple-dataset comparison modules, CTR-DB 2.0 added new gene set enrichment, tumor microenvironment (TME) and signature connectivity analysis functions to help elucidate drug resistance mechanisms and their homogeneity/heterogeneity and discover candidate combinational therapies. Furthermore, biomarker-related functions were greatly extended. CTR-DB 2.0 newly supported the validation of cell types in the TME as predictive biomarkers of treatment response, especially the validation of a combinational biomarker panel and even the direct discovery of the optimal biomarker panel using user-customized CTR-DB patient samples. In addition, the analysis of users' own datasets, application programming interface and data crowdfunding were also added.</p>","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":" ","pages":""},"PeriodicalIF":16.6000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CTR-DB 2.0: an updated cancer clinical transcriptome resource, expanding primary drug resistance and newly adding acquired resistance datasets and enhancing the discovery and validation of predictive biomarkers.\",\"authors\":\"Jianzhou Jiang, Yajie Ma, Lele Yang, Shurui Ma, Zixuan Yu, Xinyi Ren, Xiangya Kong, Xinlei Zhang, Dong Li, Zhongyang Liu\",\"doi\":\"10.1093/nar/gkae993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Drug resistance is a principal limiting factor in cancer treatment. CTR-DB, the Cancer Treatment Response gene signature DataBase, is the first data resource for clinical transcriptomes with cancer treatment response, and meanwhile supports various data analysis functions, providing insights into the molecular determinants of drug resistance. Here we proposed an upgraded version, CTR-DB 2.0 (http://ctrdb.ncpsb.org.cn). Around 190 up-to-date source datasets with primary resistance information (129% increase compared to version 1.0) and 13 acquired-resistant datasets (a new dataset type), covering 10 856 patient samples (111% increase), 39 cancer types (39% increase) and 346 therapeutic regimens (26% increase), have been collected. In terms of function, for the single dataset analysis and multiple-dataset comparison modules, CTR-DB 2.0 added new gene set enrichment, tumor microenvironment (TME) and signature connectivity analysis functions to help elucidate drug resistance mechanisms and their homogeneity/heterogeneity and discover candidate combinational therapies. Furthermore, biomarker-related functions were greatly extended. CTR-DB 2.0 newly supported the validation of cell types in the TME as predictive biomarkers of treatment response, especially the validation of a combinational biomarker panel and even the direct discovery of the optimal biomarker panel using user-customized CTR-DB patient samples. In addition, the analysis of users' own datasets, application programming interface and data crowdfunding were also added.</p>\",\"PeriodicalId\":19471,\"journal\":{\"name\":\"Nucleic Acids Research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":16.6000,\"publicationDate\":\"2024-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nucleic Acids Research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/nar/gkae993\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleic Acids Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/nar/gkae993","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
CTR-DB 2.0: an updated cancer clinical transcriptome resource, expanding primary drug resistance and newly adding acquired resistance datasets and enhancing the discovery and validation of predictive biomarkers.
Drug resistance is a principal limiting factor in cancer treatment. CTR-DB, the Cancer Treatment Response gene signature DataBase, is the first data resource for clinical transcriptomes with cancer treatment response, and meanwhile supports various data analysis functions, providing insights into the molecular determinants of drug resistance. Here we proposed an upgraded version, CTR-DB 2.0 (http://ctrdb.ncpsb.org.cn). Around 190 up-to-date source datasets with primary resistance information (129% increase compared to version 1.0) and 13 acquired-resistant datasets (a new dataset type), covering 10 856 patient samples (111% increase), 39 cancer types (39% increase) and 346 therapeutic regimens (26% increase), have been collected. In terms of function, for the single dataset analysis and multiple-dataset comparison modules, CTR-DB 2.0 added new gene set enrichment, tumor microenvironment (TME) and signature connectivity analysis functions to help elucidate drug resistance mechanisms and their homogeneity/heterogeneity and discover candidate combinational therapies. Furthermore, biomarker-related functions were greatly extended. CTR-DB 2.0 newly supported the validation of cell types in the TME as predictive biomarkers of treatment response, especially the validation of a combinational biomarker panel and even the direct discovery of the optimal biomarker panel using user-customized CTR-DB patient samples. In addition, the analysis of users' own datasets, application programming interface and data crowdfunding were also added.
期刊介绍:
Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.