Cancer seriously threatens human life and health, and the structure and function of genes within cancer cells have changed relative to normal cells. Essentially, cancer is a polygenic disorder, and the core of its occurrence and development is caused by polygenic synergy. Non-coding RNAs (ncRNAs) act as regulators to modulate gene expression levels, and they provide theoretical basis and new technology for the diagnosis and preventive treatment of cancer. However, the study of ncRNA regulation and its role as biomarkers in cancer remain largely unearthed. Driven by multi-omics data, an abundance of computational methods, tools, and databases have been developed for predicting ncRNA-cancer association/causality, inferring ncRNA regulation, and modeling ncRNA synergistic regulation. This chapter aims to provide a comprehensive perspective of modeling ncRNA synergistic regulation. Since the ncRNAs involved in cancer contribute to modeling cancer-associated ncRNA synergistic regulation, we first review the databases and tools of cancer-related ncRNAs. Then we investigate the existing tools or methods for modeling ncRNA-directed and ncRNA-mediated regulation. In addition, we survey the available computational tools or methods for modeling ncRNA synergistic regulation, including synergistic interaction and synergistic competition. Finally, we discuss the future directions and challenges in modeling ncRNA synergistic regulation.
Keywords: Cancer; ceRNA; mRNA; miRNA; ncRNA; ncRNA regulation; ncRNA synergistic regulation.
© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.