Identification of microprocessor-dependent cancer cells allows screening for growth-sustaining micro-RNAs

Peric, D; Chvalova, K; Rousselet, G
April 2012
Oncogene;4/19/2012, Vol. 31 Issue 16, p2039
Academic Journal
Micro-RNAs are deregulated in cancer cells, and some are either tumor suppressive or oncogenic. In addition, a link has been established between decreased expression of micro-RNAs and transformation, and several proteins of the RNA interference pathway have been shown to be haploinsufficient tumor suppressors. Oncogenic micro-RNAs (oncomiRs) could represent new therapeutic targets, and their identification is therefore crucial. However, structural and functional redundancy between micro-RNAs hampers approaches relying on individual micro-RNA inhibition. We reasoned that in cancer cells that depend on oncomiRs, impairing the micro-RNA pathway could lead to growth perturbation rather than increased tumorigenesis. Identifying such cells could allow functional analyses of individual micro-RNAs by complementation of the phenotypes observed upon global micro-RNA inhibition. Therefore, we developed episomal vectors coding for small hairpin RNAs targeting either Drosha or DGCR8, the two components of the microprocessor, the nuclear micro-RNA maturation complex. We identified cancer cell lines in which both vectors induced colony growth arrest. We then screened for individual micro-RNAs complementing this growth arrest, and identified miR-19a, miR-19b, miR-20a and miR-27b as major growth-sustaining micro-RNAs. However, the effect of miR-19a and miR-19b was only transient. In addition, embryonic stem cell-derived micro-RNAs with miR-20a seeds were much less efficient than miR-20a in sustaining cancer cell growth, a finding that contrasted with results obtained in stem cells. Finally, we showed that the tumor suppressor phosphatase and tensin homologue deleted on chromosome 10, a shared target of miR-19 and miR-20, was functionally involved in the growth arrest induced by microprocessor inhibition. We conclude that our approach allowed to identify microprocessor-dependent cancer cells, which could be used to screen for growth-sustaining micro-RNAs. This complementation screen unveiled functional differences between homologous micro-RNAs. Phenotypic characterization of the complemented cells will allow precise functional studies of these micro-RNAs.


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