Background: De-regulation of microRNAs (miRNAs) is closely related to many complex
diseases, including cancers. In The Cancer Genome Atlas (TCGA), hundreds of differentially
expressed miRNAs are stored for each type of cancer, which are hard to be intuitively interpreted.
To date, several miRNA set enrichment tools have been tailored to predict the potential disease
associations and functions of de-regulated miRNAs, including the miRNA Enrichment Analysis and
Annotation tool (miEAA) and Tool for Annotations of human MiRNAs (TAM1.0 &TAM 2.0).
However, independent benchmarking of these tools is warranted to assess their effectiveness and
robustness, and the relationship between enrichment analysis results and the prognosis significance
Methods: Based on differentially expressed miRNAs from expression profiles in TCGA, we
performed a series of tests and a comprehensive comparison of the enrichment analysis results of
miEAA, TAM 1.0 and TAM 2.0. The work focused on the performance of the three tools, disease
similarity based on miRNA-disease associations from the enrichment analysis results, the
relationship between the overrepresented miRNAs from enrichment analysis results and the
prognosis significance of cancers.
Results: The main results show that TAM 2.0 is more likely to identify the regulatory disease’s
functions of de-regulated miRNA; it is feasible to calculate disease similarity based on enrichment
analysis results of TAM 2.0; and there is weak positive correlation between the occurrence
frequency of miRNAs in the TAM 2.0 enrichment analysis results and the prognosis significance of
the cancer miRNAs.
Conclusion: Our comparison results not only provide a reference for biomedical researchers to
choose appropriate miRNA set enrichment analysis tools to achieve their purpose but also
demonstrate that the degree of overrepresentation of miRNAs could be a supplementary indicator of
the disease similarity and the prognostic effect of cancer miRNAs.