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Peer-reviewedCC BY 4.0Nucleic Acids Research

LncACTdb 4.0: an updated resource of experimentally supported ceRNA interactions and multi-level regulatory networks for precision oncology

  • Qiuyan Guo1
  • Qian Liu2
  • Yuting He2
  • Ximing Zhang2
  • Zhehe Xu2
  • Rui Sun2
  • Baokui Wang2
  • Xinxin Shan2
  • Borui Xu2
  • Yue Gao2
  • Shangwei Ning2
  • Hui Zhi2
1 more authors
  • Peng Wang2
  1. 1Department of Gynecology, the First Affiliated Hospital of Harbin Medical University , Harbin 150081 ,
  2. 2College of Bioinformatics Science and Technology, Harbin Medical University , Harbin 150081 ,
Open at sourcePDFDOICite

Abstract

Non-coding RNAs (ncRNAs) can function as competing endogenous RNAs (ceRNAs) to sequester microRNAs, assembling complex regulatory networks that exert critical roles in diverse diseases. Although experimentally validated ceRNA interactions have rapidly accumulated, few resources systematically curate disease-associated ceRNA networks across multi-scale biological contexts. Here, we present LncACTdb 4.0 (https://bio-bigdata.hrbmu.edu.cn/LncACTdb), an updated repository housing manually curated, experimentally supported ceRNA interactions and multi-level regulatory networks for precision oncology. This release includes major data expansions: 15 008 high-confidence ceRNA–disease associations, 18 974 cancer-related biomarkers, as well as transcriptomic profiles from >60 000 individuals and ∼600 000 single cells covering 69 tissues. It implements a four-tier data architecture spanning tissue, cell line, organoid, and single-cell levels and provides a panel of 12 web-based tools to perform bulk-cohort, single-sample, and single-cell ceRNA analyses, with specialized single-cell modules supporting quantification, clustering, trajectory reconstruction, and cell-state annotation. Featuring a user-friendly interface and integrative analytical utilities, LncACTdb 4.0 enables investigation of ceRNA regulatory mechanisms ranging from tissue architecture to cellular resolution and facilitates biomarker mining for precision oncology research.

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Cite

BibTeXRIS
BibTeX
@article{guo2026lncactdb,
  title = {{LncACTdb 4.0: an updated resource of experimentally supported ceRNA interactions and multi-level regulatory networks for precision oncology}},
  author = {Qiuyan Guo and Qian Liu and Yuting He and Ximing Zhang and Zhehe Xu and Rui Sun and Baokui Wang and Xinxin Shan and Borui Xu and Yue Gao and Shangwei Ning and Hui Zhi and Peng Wang},
  journal = {Nucleic Acids Research},
  year = {2026},
  month = oct,
  doi = {10.1093/nar/gkag1030},
  url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1030/9001950},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - LncACTdb 4.0: an updated resource of experimentally supported ceRNA interactions and multi-level regulatory networks for precision oncology
AU  - Qiuyan Guo
AU  - Qian Liu
AU  - Yuting He
AU  - Ximing Zhang
AU  - Zhehe Xu
AU  - Rui Sun
AU  - Baokui Wang
AU  - Xinxin Shan
AU  - Borui Xu
AU  - Yue Gao
AU  - Shangwei Ning
AU  - Hui Zhi
AU  - Peng Wang
PY  - 2026
DA  - 2026/10/26
JO  - Nucleic Acids Research
DO  - 10.1093/nar/gkag1030
UR  - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1030/9001950
AB  - Non-coding RNAs (ncRNAs) can function as competing endogenous RNAs (ceRNAs) to sequester microRNAs, assembling complex regulatory networks that exert critical roles in diverse diseases. Although experimentally validated ceRNA interactions have rapidly accumulated, few resources systematically curate disease-associated ceRNA networks across multi-scale biological contexts. Here, we present LncACTdb 4.0 (https://bio-bigdata.hrbmu.edu.cn/LncACTdb), an updated repository housing manually curated, experimentally supported ceRNA interactions and multi-level regulatory networks for precision oncology. This release includes major data expansions: 15 008 high-confidence ceRNA–disease associations, 18 974 cancer-related biomarkers, as well as transcriptomic profiles from >60 000 individuals and ∼600 000 single cells covering 69 tissues. It implements a four-tier data architecture spanning tissue, cell line, organoid, and single-cell levels and provides a panel of 12 web-based tools to perform bulk-cohort, single-sample, and single-cell ceRNA analyses, with specialized single-cell modules supporting quantification, clustering, trajectory reconstruction, and cell-state annotation. Featuring a user-friendly interface and integrative analytical utilities, LncACTdb 4.0 enables investigation of ceRNA regulatory mechanisms ranging from tissue architecture to cellular resolution and facilitates biomarker mining for precision oncology research.
SN  - 0305-1048
SN  - 1362-4962
ER  -