Silencing BMI1 eliminates tumor formation of pediatric glioma CD133+ cells not by affecting known targets but by down-regulating a novel set of core genes
- PMID: 25526772
- PMCID: PMC4289398
- DOI: 10.1186/s40478-014-0160-4
Silencing BMI1 eliminates tumor formation of pediatric glioma CD133+ cells not by affecting known targets but by down-regulating a novel set of core genes
Abstract
Clinical outcome of children with malignant glioma remains dismal. Here, we examined the role of over-expressed BMI1, a regulator of stem cell self-renewal, in sustaining tumor formation in pediatric glioma stem cells. Our investigation revealed BMI1 over-expression in 29 of 54 (53.7%) pediatric gliomas, 8 of 8 (100%) patient derived orthotopic xenograft (PDOX) mouse models, and in both CD133+ and CD133- glioma cells. We demonstrated that lentiviral-shRNA mediated silencing of suppressed cell proliferation in vitro in cells derived from 3 independent PDOX models and eliminated tumor-forming capacity of CD133+ and CD133- cells derived from 2 PDOX models in mouse brains. Gene expression profiling showed that most of the molecular targets of BMI1 ablation in CD133+ cells were different from that in CD133- cells. Importantly, we found that silencing BMI1 in CD133+ cells derived from 3 PDOX models did not affect most of the known genes previously associated with the activated BMI1, but modulated a novel set of core genes, including RPS6KA2, ALDH3A2, FMFB, DTL, API5, EIF4G2, KIF5c, LOC650152, C20ORF121, LOC203547, LOC653308, and LOC642489, to mediate the elimination of tumor formation. In summary, we identified the over-expressed BMI1 as a promising therapeutic target for glioma stem cells, and suggest that the signaling pathways associated with activated BMI1 in promoting tumor growth may be different from those induced by silencing BMI1 in blocking tumor formation. These findings highlighted the importance of careful re-analysis of the affected genes following the inhibition of abnormally activated oncogenic pathways to identify determinants that can potentially predict therapeutic efficacy.
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