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CTR-DB 2.0:一个更新的癌症临床转录组资源,扩展了原发性耐药性并新增了获得性耐药性数据集,增强了预测性生物标志物的发现与验证。

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.

作者信息

Jiang Jianzhou, Ma Yajie, Yang Lele, Ma Shurui, Yu Zixuan, Ren Xinyi, Kong Xiangya, Zhang Xinlei, Li Dong, Liu Zhongyang

机构信息

College of Life Sciences, Hebei University, Baoding 071002, China.

State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China.

出版信息

Nucleic Acids Res. 2025 Jan 6;53(D1):D1335-D1347. doi: 10.1093/nar/gkae993.

DOI:10.1093/nar/gkae993
PMID:39494527
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11701710/
Abstract

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.

摘要

耐药性是癌症治疗中的一个主要限制因素。CTR-DB(癌症治疗反应基因特征数据库)是首个拥有癌症治疗反应临床转录组的数据资源,同时支持各种数据分析功能,为耐药性的分子决定因素提供见解。在此,我们推出了升级版的CTR-DB 2.0(http://ctrdb.ncpsb.org.cn)。已收集了约190个包含原发性耐药信息的最新源数据集(与1.0版本相比增加了129%)和13个获得性耐药数据集(一种新的数据集类型),涵盖10856个患者样本(增加了111%)、39种癌症类型(增加了39%)和346种治疗方案(增加了26%)。在功能方面,对于单数据集分析和多数据集比较模块,CTR-DB 2.0增加了新的基因集富集、肿瘤微环境(TME)和特征连通性分析功能,以帮助阐明耐药机制及其同质性/异质性,并发现候选联合治疗方法。此外,与生物标志物相关的功能得到了极大扩展。CTR-DB 2.0新支持将TME中的细胞类型验证为治疗反应的预测生物标志物,特别是对联合生物标志物面板的验证,甚至使用用户定制的CTR-DB患者样本直接发现最佳生物标志物面板。此外,还增加了用户自己数据集的分析、应用程序编程接口和数据众筹功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/027ea9f284b3/gkae993fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/06343588208b/gkae993figgra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/9ff372b5d315/gkae993fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/6f41016f39b5/gkae993fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/234d3aab144d/gkae993fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/027ea9f284b3/gkae993fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/06343588208b/gkae993figgra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/9ff372b5d315/gkae993fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/6f41016f39b5/gkae993fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/234d3aab144d/gkae993fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c79/11701710/027ea9f284b3/gkae993fig4.jpg

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