A microRNA activity map of human mesenchymal tumors: connections to oncogenic pathways; an integrative transcriptomic study

Abstract

Background: MicroRNAs (miRNAs) are nucleic acid regulators of many human mRNAs, and are associated with many tumorigenic processes. miRNA expression levels have been used in profiling studies, but some evidence suggests that expression levels do not fully capture miRNA regulatory activity. In this study we integrate multiple gene expression datasets to determine miRNA activity patterns associated with cancer phenotypes and oncogenic pathways in mesenchymal tumors - a very heterogeneous class of malignancies.

Results: Using a computational method, we identified differentially activated miRNAs between 77 normal tissue specimens and 135 sarcomas and we validated many of these findings with microarray interrogation of an independent, paraffin-based cohort of 18 tumors. We also showed that miRNA activity is imperfectly correlated with miRNA expression levels. Using next-generation miRNA sequencing we identified potential base sequence alterations which may explain differential activity. We then analyzed miRNA activity changes related to the RAS-pathway and found 21 miRNAs that switch from silenced to activated status in parallel with RAS activation. Importantly, nearly half of these 21 miRNAs were predicted to regulate integral parts of the miRNA processing machinery, and our gene expression analysis revealed significant reductions of these transcripts in RAS-active tumors. These results suggest an association between RAS signaling and miRNA processing in which miRNAs may attenuate their own biogenesis.

Conclusions: Our study represents the first gene expression-based investigation of miRNA regulatory activity in human sarcomas, and our findings indicate that miRNA activity patterns derived from integrated transcriptomic data are reproducible and biologically informative in cancer. We identified an association between RAS signaling and miRNA processing, and demonstrated sequence alterations as plausible causes for differential miRNA activity. Finally, our study highlights the value of systems level integrative miRNA/mRNA assessment with high-throughput genomic data, and the applicability of paraffin-tissue-derived RNA for validation of novel findings.

Figure 1

Study flow.A) miRNA activity pattern assessment in four public datasets. B) Validation in a paraffin-based tissue cohort. C) Correlation of miRNA activity with miRNA levels. D) miRNA-sequencing. E) Relationship with RAS pathway status.

Figure 2

Validation of miRNA activity patterns in a paraffin-based tissue cohort. Activity patterns of many dysregulated candidate miRNAs were reproducible in the validation set (LEIO and LIPO samples, p = 0.005, FDR = 0.05).

Figure 3

Imperfect correlation between miRNA activity and miRNA expression levels. Hierarchical clustering based on histology-specific miRNAs: A) Using all samples (soft-tissue sarcomas and osteosarcomas), B) using only soft-tissue sarcomas, C) using soft-tissue sarcomas while limiting the analysis to the most variant miRNAs.