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The RNA binding protein (RBP) and non-coding RNA (ncRNA) interacting networks are increasingly recognized as the main mechanism in gene regulation, and are tightly associated with cellular malfunction and disease. Here, we present fRNC, a systems biology tool to uncover the dynamic spectrum of RBP-ncRNA circuits (RNC) by integrating transcriptomics, interactomics and proteomics data. fRNC constructs the RBP-ncRNA network derived from CLIP-seq or PARE experiments. Given scoring on nodes and edges according to differential analysis of expression data, it finds an RNC containing global maximum significant RBPs and ncRNAs. Alternatively, it can also capture the locally maximum scoring RNC according to user-defined starting nodes with the greedy search. When compared with existing tools, fRNC can detect more accurate and robust sub-network with scalability. As shown in the cases of esophageal carcinoma, breast cancer and Alzheimer’s disease, fRNC enables users to analyze the collective behaviors between RBP and the interacting ncRNAs, and reveal novel insights into the disease-associated processes. The fRNC R package is available at https://github.com/BioinformaticsSTU/fRNC.

The interactions among non-coding RNA (ncRNA) and RNA binding protein (RBP) are increasingly recognized as one of basic mechanisms in gene regulation, and play a crucial role in cancer progressions. However, the current understanding of this regulation network, especially its dynamic spectrum according to the differentially expressed nodes (i.e. ncRNAs and RBP) is limited. Utilizing transcriptomics and interactomics resources, dysregulated RBP-ncRNA circuits (RNCs) are systematically dissected across 14 tumor types. We found these aberrant RNCs are robust and enriched with cancer-associated ncRNAs, RBPs and drug targets. Notably, the nodes in altered RNCs can jointly predict the clinical outcome while the individual node can’t, underscoring RNCs can serve as prognostic biomarkers. We identified 30 pan-cancer RNCs dysregulated at least in six tumor types. Pan-cancer RNC analysis can reveal novel mechanism of action (MOA) and repurpose for existing drugs. Importantly, our experiments elucidated the novel role of hsa-miR-224-5p, a member of the pan-cancer RNC hsa-miR-224-5p_MAGI2-AS3_MBNL2, in EMT program. Our analysis highlights the potential utilities of RNCs in elucidating ncRNA function in cancer, associating with clinical outcomes and discovering novel drug targets or MOA.