Regulation of leukemic cell differentiation and retinoid-induced gene expression by statins

There is emerging evidence that, beyond their cholesterol lowering properties, statins exhibit important antileukemic effects in vitro and in vivo, but the precise mechanisms by which they generate such responses remain to be determined. We have previously shown that statins promote differentiation of acute promyelocytic leukemia (APL) cells and enhance generation of all-trans-retinoic acid (ATRA)-dependent antileukemic responses. We now provide evidence that statin-dependent leukemic cell differentiation requires engagement and activation of the JNK kinase pathway. In addition, in experiments to define the molecular targets and mediators of statin-induced differentiation we found a remarkable effect of statins on ATRA-dependent gene transcription, evidenced by the selective induction of over 400 genes by the combination of atorvastatin and ATRA. Altogether, our studies identify novel statin molecular targets linked to differentiation, establish that statins modulate ATRA-dependent transcription, and suggest that combined use of statins with retinoids may provide a novel approach to enhance antileukemic responses in APL and possibly other leukemias. To determine whether the effects of statin-treatment on ATRA-induced leukemic cell differentiation reflect induction of specific genes, the patterns of gene expression induced by ATRA, atorvastatin, or by the combination of atorvastatin + ATRA were subsequently examined using DNA microarrays. We analyzed three prototypic situations (ATRA, atorvastatin, ATRA + atorvastatin) using Illumina Sentrix® Human-6 Expression BeadChips over three points time course (8, 24, 48 hours), and time course points were replicated in three independent experiments performed at different days. A total of 36 arrays were hybridized. After average probe intensity 9 calculation, log2 transformation and normalization, probes characterized by low quality signal or invariant expression within the experimental conditions were discarded. A total of 11287 out of the 47293 RefSeq BeadChip probes were used to identify significantly differentially expressed genes. Statistical analysis was performed using a two step regression strategy. 1901 RefSeqs were found significantly differentially expressed in at least one condition over the time course treatments. After calculating the log2 (fold change) variation for all treatments with respect to the corresponding control time point, 782 out of 1901 RefSeq probes were characterized by a |log2(fold change)| ≥ 1 for at least one of the time points.