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PharmacoDB 2.0:提高体外药物基因组学分析的可扩展性和透明度。

PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis.

机构信息

Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada.

Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada.

出版信息

Nucleic Acids Res. 2022 Jan 7;50(D1):D1348-D1357. doi: 10.1093/nar/gkab1084.

DOI:10.1093/nar/gkab1084
PMID:34850112
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8728279/
Abstract

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug-response analysis such as tissue distribution of dose-response metrics and biomarker analysis; and (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug-response phenotypes of cancer models.

摘要

癌症药物基因组学研究为疾病进展以及基因组特征与药物反应之间的关联提供了有价值的见解。PharmacoDB 整合了多个癌症药物基因组学数据集,这些数据集对来自不同组织类型的细胞系中的已批准和研究性药物进行了分析。该网络应用程序使用户能够高效地在数据集之间进行导航,查看和比较特定药物-细胞系对的药物剂量反应数据。在 PharmacoDB 的新版本(版本 2.0,https://pharmacodb.ca/)中,我们提供了 (i) 新的数据集,如 NCI-60、Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) 数据集,以及来自 Genomics of Drug Sensitivity in Cancer (GDSC) 和 Genentech Cell Line Screening Initiative (gCSI) 的更新数据;(ii) 使用 ORCESTRA 和 PharmacoDI 实现 FAIR 数据管道;(iii) 对药物反应分析进行了增强,例如剂量反应指标的组织分布和生物标志物分析;以及 (iv) 改进了与社区中药物和细胞系数据库的连接。Web 界面使用现代技术堆栈进行了重写,以确保可扩展性和标准化,从而适应不断增长的药物基因组学数据集。PharmacoDB 2.0 是挖掘药物基因组学数据集、比较和评估癌症模型药物反应表型的有价值的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/4c822d4fc2e6/gkab1084fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/eb2d82df9e3b/gkab1084gra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/ea8a978cc5a0/gkab1084fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/95d5778db452/gkab1084fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/4c822d4fc2e6/gkab1084fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/eb2d82df9e3b/gkab1084gra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/ea8a978cc5a0/gkab1084fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/95d5778db452/gkab1084fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28dc/8728279/4c822d4fc2e6/gkab1084fig3.jpg

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