Induction of microRNAs, mir-155, mir-222, mir-424 and mir-503, promotes monocytic differentiation through combinatorial regulation

Acute myeloid leukemia (AML) involves a block in terminal differentiation of the myeloid lineage and uncontrolled proliferation of a progenitor state. Using phorbol myristate acetate (PMA), it is possible to overcome this block in THP-1 cells (an M5-AML containing the MLL-MLLT3 fusion), resulting in differentiation to an adherent monocytic phenotype. As part of FANTOM4, we used microarrays to identify 23 microRNAs that are regulated by PMA. We identify four PMA-induced micro- RNAs (mir-155, mir-222, mir-424 and mir-503) that when overexpressed cause cell-cycle arrest and partial differentiation and when used in combination induce additional changes not seen by any individual microRNA. We further characterize these prodifferentiative microRNAs and show that mir-155 and mir-222 induce G2 arrest and apoptosis, respectively. We find mir-424 and mir-503 are derived from a polycistronic precursor mir-424-503 that is under repression by the MLL-MLLT3 leukemogenic fusion. Both of these microRNAs directly target cell-cycle regulators and induce G1 cell-cycle arrest when overexpressed in THP-1. We also find that the pro-differentiative mir-424 and mir-503 downregulate the anti-differentiative mir-9 by targeting a site in its primary transcript. Our study highlights the combinatorial effects of multiple microRNAs within cellular systems.

💡 Research Summary

Acute myeloid leukemia (AML) is characterized by a block in terminal differentiation of myeloid progenitors and uncontrolled proliferation. In this study the authors used the M5‑AML cell line THP‑1, which harbors the leukemogenic MLL‑MLLT3 fusion, as a model system. Treatment with phorbol myristate acetate (PMA) forces THP‑1 cells to differentiate into an adherent monocytic phenotype, providing a tractable system to explore the role of microRNAs (miRNAs) in differentiation.

Using Agilent miRNA microarrays and deep‑sequencing of three biological replicates, the authors identified 23 miRNAs whose expression changed ≥3‑fold between undifferentiated (0 h) and fully differentiated (96 h) states. Twenty‑one were up‑regulated and two down‑regulated. Among the up‑regulated miRNAs, mir‑155, mir‑222, mir‑424 and mir‑503 were selected for functional follow‑up because they displayed the strongest “pro‑differentiative” signature when over‑expressed in THP‑1 cells.

Synthetic pre‑miRNA duplexes were transfected individually into undifferentiated THP‑1 cells and transcriptome changes were measured after 48 h with whole‑genome Illumina arrays. The authors defined “PMA‑like” changes (genes that change in the same direction as during PMA‑induced differentiation) and “anti‑PMA‑like” changes (opposite direction). A miRNA was considered pro‑differentiative if it produced at least 1.5‑fold more PMA‑like than anti‑PMA‑like changes and if the proportion of PMA‑like changes exceeded the average by one standard deviation. By these criteria mir‑155, mir‑222, mir‑424 and mir‑503 each induced a modest set of PMA‑like genes, including known monocytic markers such as ITGAL (CD11a) and CSF1R.

When the four miRNAs were co‑transfected in equimolar amounts, the combined effect was synergistic: 69 PMA‑like changes were observed, 39 of which were not seen with any single miRNA. The ratio of PMA‑like to anti‑PMA‑like changes rose to 6.3‑fold, far exceeding the ratios for individual miRNAs, and modest induction of CD14 was detected, indicating a more faithful recapitulation of the PMA response.

Mir‑424 and mir‑503 are derived from a polycistronic primary transcript (mir‑424‑503) located only 383 bp apart. RT‑PCR confirmed that both mature miRNAs are processed from the same precursor. This cluster is repressed by the MLL‑MLLT3 fusion, as knock‑down of MLL‑MLLT3 in the FANTOM4 siRNA panel led to up‑regulation of mir‑424‑503. Both miRNAs share similar seed sequences and target overlapping sets of cell‑cycle regulators. Flow cytometry showed that over‑expression of mir‑424 or mir‑503 caused G1 arrest, mir‑222 induced G2 accumulation, mir‑155 caused G2 depletion with a sub‑G1 (apoptotic) population, and mir‑155 alone promoted apoptosis.

Target validation was performed using luciferase reporter assays. Predicted targets of mir‑424 (CCNE1, CCND1, CDK6) and mir‑503 (CCND1, CCNE1, CDC25A, CHEK1, WEE1, CDKN1A) were indeed down‑regulated at the mRNA level after miRNA over‑expression, and reporter activity was reduced when the corresponding 3′‑UTR sites were present. Importantly, the polycistronic mir‑424‑503 cluster also contains a site complementary to the primary transcript of the anti‑differentiative miR‑9‑3. Over‑expression of mir‑424 or mir‑503 reduced pri‑mir‑9‑3 levels, and a luciferase construct bearing this site was repressed by both miRNAs, indicating direct targeting.

The authors therefore propose a model in which the MLL‑MLLT3 fusion maintains AML proliferation by repressing the tumor‑suppressive mir‑424‑503 cluster. Release of this repression (by PMA or MLL‑MLLT3 knock‑down) allows mir‑424 and mir‑503 to down‑regulate multiple cell‑cycle genes, enforce G1 arrest, and simultaneously suppress the anti‑differentiative miR‑9‑3, thereby facilitating monocytic differentiation. Mir‑155 and mir‑222 contribute additional layers of regulation by promoting apoptosis and G2 arrest, respectively.

Overall, the study demonstrates that a small set of cooperatively acting miRNAs can recapitulate key aspects of a differentiation program, but that full phenotypic conversion requires coordinated changes in transcription factors, cytokine signaling, and additional regulatory layers. The findings highlight the combinatorial nature of miRNA networks in hematopoietic lineage decisions and suggest that therapeutic strategies targeting multiple miRNAs or their upstream regulators (e.g., MLL‑MLLT3) may be more effective than single‑miRNA approaches in AML.