RNAactDrug 2.0: an updated resource for systematically exploring molecular features associated with drug sensitivity across multi-omics datasets

RNAactDrug 2.0 (available at https://bio-bigdata.hrbmu.edu.cn/RNAactDrug or https://bio-datamining.hrbmu.edu.cn/RNAactDrug) is an updated resource for systematically exploring molecular features associated with drug sensitivity across multi-omics datasets. We have updated the RNAactDrug 2.0 database with significantly expanded data and improved features, including (i) ∼30 000 drugs, 38 908 RNA molecules, and 22 800 375 drug-RNA associations from large-scale pharmacogenomic databases, covering four molecular layers: expression, copy number variation (CNV), mutation, and methylation; (ii) 11 099 cases from The Cancer Genome Atlas across 33 cancer types are integrated to support clinical and pan-cancer analyses of drug sensitivity-associated RNA features; (iii) ∼3.8 million cells from >200 single-cell RNA sequencing datasets, spanning 34 cancer types and 38 tissues, enable analysis of cell type-specific patterns and intratumoral heterogeneity; (iv) 26 440 enhancers and 788 444 drug-enhancer associations, combined with potential target prediction, provide an exploratory epigenetic regulatory dimension; (v) enhanced search and browsing functionalities, together with seven tools for functional annotation, pan-cancer analysis, tumor microenvironment profiling, single-cell trajectory and CNV analysis, and enhancer-related analyses. In summary, RNAactDrug 2.0 is a crucial resource for the multi-omics dissection of drug sensitivity-associated molecules, providing important support for the discovery of drug resistance biomarkers and the advancement of personalized therapeutic strategies.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-11-02
DOI
https://doi.org/10.1093/nar/gkag1117
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

RNAactDrug 2.0: an updated resource for systematically exploring molecular features associated with drug sensitivity across multi-omics datasets

Liying Pei, Zhe Chen, Chunlong Zhang, Yanjun Xu et al.
2 links
Nucleic Acids Research
Computational Drug Discovery Methods
article

RNAactDrug 2.0: an updated resource for systematically exploring molecular features associated with drug sensitivity across multi-omics datasets

Liying Pei, Zhe Chen, Chunlong Zhang, Yanjun Xu, 康安辉, Jiangtao Xing, Feng Li, Wensong Liu, Xinyi Wang, Siyao Lu, Longqi Xu
article en

Abstract

RNAactDrug 2.0 (available at https://bio-bigdata.hrbmu.edu.cn/RNAactDrug or https://bio-datamining.hrbmu.edu.cn/RNAactDrug) is an updated resource for systematically exploring molecular features associated with drug sensitivity across multi-omics datasets. We have updated the RNAactDrug 2.0 database with significantly expanded data and improved features, including (i) ∼30 000 drugs, 38 908 RNA molecules, and 22 800 375 drug-RNA associations from large-scale pharmacogenomic databases, covering four molecular layers: expression, copy number variation (CNV), mutation, and methylation; (ii) 11 099 cases from The Cancer Genome Atlas across 33 cancer types are integrated to support clinical and pan-cancer analyses of drug sensitivity-associated RNA features; (iii) ∼3.8 million cells from >200 single-cell RNA sequencing datasets, spanning 34 cancer types and 38 tissues, enable analysis of cell type-specific patterns and intratumoral heterogeneity; (iv) 26 440 enhancers and 788 444 drug-enhancer associations, combined with potential target prediction, provide an exploratory epigenetic regulatory dimension; (v) enhanced search and browsing functionalities, together with seven tools for functional annotation, pan-cancer analysis, tumor microenvironment profiling, single-cell trajectory and CNV analysis, and enhancer-related analyses. In summary, RNAactDrug 2.0 is a crucial resource for the multi-omics dissection of drug sensitivity-associated molecules, providing important support for the discovery of drug resistance biomarkers and the advancement of personalized therapeutic strategies.

Nucleic Acids Research
Harbin Medical University (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 17%
Computational Drug Discovery Methods
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