| Abstract: |
The posttranscriptional control of gene expression bymicroRNAs (miRNAs) is highly redundant, and compensatory effects limit the consequences of the inactivation of individual miRNAs. This implies that only a few miRNAs can function as effective tumor suppressors. It is also the basis of our strategy to define functionally relevant miRNA target genes that are not under redundant control by other miRNAs. We identified a functionally interconnected group of miRNAs that exhibited a reduced abundance in leukemia cells from patients with T cell acute lymphoblastic leukemia (T-ALL). To pinpoint relevant target genes, we applied a machine learning approach to eliminate genes that were subject to redundant miRNA-mediated control and to identify those genes that were exclusively targeted by tumor-suppressive miRNAs. This strategy revealed the convergence of a small group of tumor suppressor miRNAs on the Myb oncogene, as well as their effects on HBP1, which encodes a transcription factor. The expression of both genes was increased in T-ALL patient samples, and each gene promoted the progression of T-ALL in mice. Hence, our systematic analysis of tumor suppressor miRNA action identified a widespread mechanism of oncogene activation in T-ALL. |
