miREA: a network-based tool for microRNA-oriented enrichment analysis

Abstract

MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level, yet interpreting their function at the pathway level remains challenging. Existing enrichment analysis tools predominantly adopt network node-centric approaches that focus on gene expression profiles, neglecting the regulatory information encoded in miRNA-gene interactions (MGIs) that constitute network edges. This omission introduces analytical bias and limits biological interpretability, underscoring the need for network edge-based enrichment analysis methods that explicitly incorporate MGIs. Therefore, we present miREA, a network-based tool for miRNA enrichment analysis that leverages MGIs to characterize miRNA function at the pathway level. miREA contains five edge-based enrichment methods that integrate paired miRNA-gene expression and interactome profiles with pathway networks to perform MGI overrepresentation, MGI scoring-based, network topology-aware, and network propagation analyses. Benchmarking across multiple cancer types shows that the edge-based methods outperform node-based methods in improving sensitivity to identify relevant pathways and biological interpretability while maintaining controlled false positive rates. We further demonstrate the utility of miREA in elucidating miRNA-gene-pathway regulatory mechanisms in bladder cancer. miREA is a versatile enrichment analysis tool that provides pathway-level interpretation of human miRNA function and facilitates mechanistic hypothesis generation for experimental validation. HighlightsO_LImiREA uses information in miRNA-gene interactions for miRNA enrichment analysis. C_LIO_LImiREA contains five new edge-based algorithms that integrate expression and interactome profiles with pathway networks to characterize miRNA function. C_LIO_LIThe edge-based methods are more sensitive than node-based methods at identifying cancer-relevant pathways and more effective at identifying cancer genes and miRNAs. C_LIO_LIWe perform systematic analysis of the miREA methods to show their robustness on 16 cancer datasets. C_LIO_LIWe present a case study that demonstrates the potential of miREA to elucidate miRNA-gene-pathway regulatory mechanisms in bladder cancer. C_LI