Dataset: Imatinib therapy of chronic myeloid leukemia restores the expression levels of key genes for DNA damage and cell cycle progression

[u'Background: Chronic myeloid leukemia (CML) is a malignant clonal disorder of the hematopoietic system caused by the expression of the BCR/ABL fusion oncogene. It is well known that CML cells are genetically unstable. However, the mechanisms by which these cells acquire genetic alterations are poorly understood. Imatinib mesylate (IM) is the standard therapy for newly diagnosed CML patients. IM targets the oncogenic kinase activity of BCR-ABL. Objective: To study the gene expression profile of BM hematopoietic cells in the same patients with CML before and one month after imatinib therapy. Methods: Samples from patients with CML were analyzed using Affymetrix GeneChip Expression Arrays. Results: A total of 594 differentially expressed genes, most of which (393 genes) were downregulated, as a result of imatinib therapy were observed. Conclusions: The blockade of oncoprotein Bcr-abl by imatinib could cause a decrease in the expression of key DNA repair genes, and cells try to restore the normal gene expression levels required for cell proliferation and chromosomal integrity. Materials and Methods Patients Nine patients with the diagnosis of Ph-positive CML and nine samples from normal donors were analyzed. In all patients bone marrow samples were obtained by bone marrow aspiration. All patients received a daily dose of 400 mg imatinib mesylate (IM). In all patients bone marrow was sampled before IM administration commenced and 4 weeks after the treatment, by which time all cases were in hematological response. In addition, all patients showed a complete cytogenetic response six months after starting therapy. The study was approved by the local research ethics committee and written informed consent was obtained from all patients. RNA isolation, labeling and microarray hybridization Total RNA was isolated from bone marrow in Trizol aliquots, following the manufacturer\u2019s instructions, and purified using an RNeasy kit (Qiagen Inc., Valencia, CA). RNA integrity and yield were assessed by determining sample absorbance at 260 and 280 nm and by analysis on the Agilent RNA 6000 Nano LabChip (Agilent Technologies, Inc., Palo Alto, CA). Microarray assays were performed according to the standard protocol described in the Affymetrix GeneChip Expression Analysis Technical Manual, rev. 3 (', {u'a': {u'href': u'http://www.affymetrix.com/support/index.affx', u'target': u'_blank', u'$': u'http://www.affymetrix.com/support/index.affx'}}, u'). Messenger RNA was amplified and labeled from 5-\xb5g samples, which produced a sufficient yield of cRNA. These samples were fragmented and combined with array hybridization controls (Affymetrix, Santa Clara, CA, USA) in hybridization buffer. 11 \xb5g of cRNA target were then hybridized with the GeneChip HG_U133 Plus 2.0 array (Affymetrix) and scanned with the GeneArray laser scanner (Affymetrix). Genome-wide expression data analysis The expression value for each probe set was calculated using RMA-Express software, which uses the robust multi-array average (RMA) algorithm, as previously described [28]. For an initial analysis, gene-filtering methods were applied following the detection calls calculated using the MAS 5.0 algorithm (Affymetrix). Probe sets with absent calls and those showing minimal variation across all samples (maximum-minimum log2 variation <2.5) were filtered out. The significant analysis of microarrays (SAM) algorithm was used to identify genes with statistically significant differences in expression between classes. All data were permuted over 100 cycles using the two-class (unpaired) and multi-class response format, with no necessity for equal variances. Significant genes were identified on the basis of the lowest false-discovery ratio (FDR), controlling the q-value for the gene list. The FDR was <2% in all class comparisons. A web-delivered bioinformatics tool set, Ingenuity Pathway Analysis (IPA 5.5; ', {u'a': {u'href': u'http://www.ingenuity.com', u'target': u'_blank', u'$': u'http://www.ingenuity.com'}}, u"), was used to identify functional networks. IPA is a knowledge database generated from peer-reviewed scientific publications. It enables the discovery, visualization and exploration of functional biological networks in gene expression data and delineates the most significant functions in those networks. Gene-specific real-time PCR In order to validate the results of the microarray studies, quantitative real-time reverse transcriptase polymerase chain reaction (RT-PCR) was performed at the time of diagnosis and four weeks after imatinib therapy. One microgram of total RNA was subjected to cDNA synthesis, as previously described [29]. Quantification was performed using Fast SYBR-Green Master Mix according to the manufacturer's instructions (Applied Biosystems, Foster City, CA). The expression of the following genes was analyzed: POLE2, FANCD2, PTEN, FOXO3, and ABCB7. The specific primers were designed with Primer Express 3.0 software (Applied Biosystems) and tested for specificity using NCBI's BLAST software. Gene expression was achieved using relative quantitative real-time RT-PCR and the SYBR\xae Green I. Expression was quantified relative to GAPDH expression by the application of the Pfaffl analysis method."]

Species:

human

Samples:

27

Source:

E-GEOD-33075

Updated:

Dec.12, 2014

Registered:

Jul.11, 2014