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Series GSE12870 Query DataSets for GSE12870
Status Public on Jan 20, 2009
Title Regulation of leukemic cell differentiation and retinoid-induced gene expression by statins
Organism Homo sapiens
Experiment type Expression profiling by array
Summary 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.
 
Overall design 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.
 
Contributor(s) Sassano A, Lo Iacono M, Antico G, Jordan A, Uddin S, Calogero RA, Platanias LC
Citation(s) 19240159
Submission date Sep 20, 2008
Last update date Mar 20, 2012
Contact name Raffaele A Calogero
E-mail(s) raffaele.calogero@unito.it
Phone ++39 0116706454
Organization name University of Torino
Department Molecular Biotechnology Center
Lab Bioinformatics and Genomics Unit
Street address Via Nizza 52
City Torino
State/province To
ZIP/Postal code 10126
Country Italy
 
Platforms (1)
GPL2507 Sentrix Human-6 Expression BeadChip
Samples (36)
GSM322161 exp.n 13 atra N atorvastatin N time 8 h
GSM322168 exp.n 15 atra N atorvastatin Y time 8 h
GSM322169 exp.n 17 atra N atorvastatin N time 24 h
Relations
BioProject PRJNA111047

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE12870_RAW.tar 11.7 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table
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