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

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.