The CXCR4 Antagonist AMD3100 Impairs Survival of AML Cells and Induces Their Differentiation.

Abstract The chemokine stromal cell-derived factor-1 (SDF-1) and its receptor, CXCR4, participate in the retention of AML cells within the bone marrow microenvironment and their release into the circulation. We previously showed that the expression of cell surface elastase in AML cells is dependent on the SDF-1/CXCR4 axis, giving a first evidence for the association between the SDF-1 and elastase pathways. In the present study, we hypothesized that inhibition of the SDF-1/CXCR4 axis or elastase may regulate similar pathways and genes in AML cells. In order to test our hypothesis, we compared gene expression profiles of U937 AML cells that express high level of membrane CXCR4, treated with neutralizing CXCR4 mAb or elastase inhibitor (EI), with non-treated cells, by employing gene-array technology. Unsupervised hierarchical clustering analysis demonstrated similar gene expression profiles of anti-CXCR4 antibody or EI treated cells, as compared to control. Analysis of the 364 genes that were differentially expressed in both anti CXCR4 mAb or EI treated cells under both treatment agents identified genes that correspond to the transcriptional profiles of differentiated myeloid cells in a significantly high prevalence. Quantitative Real-time RT-PCR for 4 selected genes C/EBPe, FLT3, HOXA9 and G-CSFR, demonstrated gene expression profiles identical to the microarray expression profiles. Given thus, we further analyzed the effect of CXCR4 inhibition on AML cell growth and differentiation using the antagonist AMD3100. AMD3100 arrested proliferation in five AML cell lines as was suggested by proliferation assay, cell cycle and caspase 3 activity analyses. Moreover, cell differentiation was demonstrated by: Modifications in cell morphology, Increased expression of myeloid differentiation antigens Acquisition of the ability to produce oxidative bursts An increase in DNA ploidy in megakaryoblasts. Our study defines a new role for the SDF-1/CXCR4 axis in the regulation of leukemic cell survival and differentiation.

Download Full-text

Inhibition of Elastase or SDF-1/CXCR4 Axis Promotes Differentiation of Human AML Cells.

Blood ◽

10.1182/blood.v108.11.1891.1891 ◽

2006 ◽

Vol 108 (11) ◽

pp. 1891-1891

Author(s):

Sigal Tavor ◽

Jasmine Jacob-Hirsch ◽

Manny Eisenbach ◽

Sigi Kay ◽

Shoshana Baron ◽

...

Keyword(s):

Gene Expression ◽

Cell Line ◽

Expression Profiles ◽

Expression Patterns ◽

Critical Role ◽

Marker Genes ◽

Granulocytic Differentiation ◽

Elastase Inhibitor ◽

Granule Proteins ◽

Cxcr4 Axis

Abstract Elastase, along with other azurophil granule proteins like proteinase 3 regulates normal and leukemic granulopoiesis in an un-defined mechanism. We have recently showed that human acute myeloid leukemic (AML) cells constitutively express and secrete stromal derived factor 1 (SDF-1) dependent cell surface elastase, which regulates their migration and proliferation. To elucidate the molecular events and genes regulated by elastase and SDF-1/CXCR4 axis in AML cells, we examined gene expression of U937 AML cell line treated with neutralizing anti-CXCR4 Abs or elastase inhibitor (EI) compared to untreated cells, using DNA microarray technology. Unsupervised hierarchical clustering analysis showed very similar gene expression profiles of EI and anti CXCR4 Abs treated cells as compared to control. 230 of 8400 genes interrogated were repressed, and 164 were induced after culturing AML cells in the presence of EI or anti CXCR4 Abs at different time points as compared to untreated cells. Inhibition of elastase or CXCR4 was accompanied by down regulation of the transcripts of primary granule proteins. Functional classification of elastase or SDF-1/CXCR4 axis regulated genes revealed downregulation of HOXA9, HOXA10, ETS2, as well as other transcription factors that are over expressed in AML and are important for the development of leukemia. Whereas, transcriptional factors and regulators known to be induced during myeloid differentiation like C/EBPε, ID1, RUNX3 and HHEX were up-regulated in treated cells. Expression patterns of apoptosis genes indicated decline in death control by the p53 dependent pathway and a more prominent control by mitochondrial mediated apoptotic pathway like bcl2 related genes. In addition, receptors for interleukins, growth factors (G-CSFR and GM-CSF), complement component (C1QR1) were upregulated in the treated cells. In contrast, FLT-3, a growth factor receptor stimulating growth of early progenitor cells and AML blasts, was down regulated in AML cell treated with EI or anti CXCR4 Abs. These data were confirmed by real time PCR for selected marker genes of granulocytic differentiation. Interestingly, many of the differentially expressed genes were common to the transcriptional program of normal terminal granulocytic differentiation (Theilgaard-Monch & Borregarrd 2005. Blood 105:1785) suggesting that inhibition of elastase may induce differentiation in AML cells. Thus we further analyzed the effect of elastase inhibition on AML cell differentiation and growth. Treatment of HL60 AML cell line with EI triggered a proliferative arrest, apoptosis and mimicked terminal granulocytic differentiation, including morphologic changes, increased CD11b expression, and the ability to produce oxidative bursts. In summary, our study showed that inhibition of elastase or SDF-1/CXCR4 axis in AML cells affects similar pathways related to differentiation and malignant transformation, implying a critical role for those molecules in regulating leukemic development. Repression of elastase decreases proliferation and induces differentiation of AML cells, suggesting a potential new therapeutic approach for AML.

Download Full-text

Comparison of Global Brain Gene Expression Profiles Between Inbred Long-Sleep and Inbred Short-Sleep Mice by High-Density Gene Array Hybridization

Alcoholism Clinical and Experimental Research ◽

10.1111/j.1530-0277.2001.tb02284.x ◽

2001 ◽

Vol 25 (6) ◽

pp. 810-818 ◽

Cited By ~ 31

Author(s):

Yan Xu ◽

Marissa Ehringer ◽

Fan Yang ◽

James M. Sikela

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Array ◽

Gene Expression Profiles ◽

High Density ◽

Short Sleep ◽

Brain Gene Expression ◽

Long Sleep ◽

Global Brain ◽

Array Hybridization

Download Full-text

Gene expression of vasoactive intestinal contractor/endothelin-2 in ovary, uterus and embryo: comprehensive gene expression profiles of the endothelin ligand-receptor system revealed by semi-quantitative reverse transcription-polymerase chain reaction analysis in adult mouse tissues and during late embryonic development

Journal of Molecular Endocrinology ◽

10.1677/jme.0.0220161 ◽

1999 ◽

Vol 22 (2) ◽

pp. 161-171 ◽

Cited By ~ 25

Author(s):

T Uchide ◽

H Masuda ◽

Y Mitsui ◽

K Saida

Keyword(s):

Gene Expression ◽

Embryonic Development ◽

Adult Mouse ◽

Expression Profiles ◽

Physiological Role ◽

Gene Expression Profiles ◽

Polymerase Chain Reaction Analysis ◽

Receptor System ◽

Mouse Tissues ◽

High Level

Vasoactive intestinal contractor (VIC)/endothelin-2 (ET-2) is a 21 amino acid intestinal peptide characterized as a potent vasoactive and intestinal smooth muscle-contracting compound. To investigate the physiological roles of VIC/ET-2 further, we characterized the specificity of VIC gene expression relative to that of other members of the endothelin (ET) ligand-receptor system in adult mouse tissues and during embryonic development. Gene expression of ET-1, ET-3, ETA and ETB was ubiquitous in almost all tissues we examined while gene expression of VIC was localized to certain tissues. A high level of VIC gene expression was observed in ovary and uterus. The gene expression of VIC, relative to that of glyceraldehyde-3-phosphate dehydrogenase, was approximately 2.0%, 0.4%, and 2.3% in ovary, uterus, and intestine respectively, and was approximately 1.6 and 7. 1 times higher than that of ET-1 in ovary and intestine respectively. Thus, VIC may have some physiological role in adult ovary and uterus as well as intestine. In embryonic development, VIC gene expression sharply increased between 11 and 15 days post coitus and decreased after birth, suggesting an involvement in the later stages of embryonic development.

Download Full-text

Boosting Gene Expression Clustering with System-Wide Biological Information: A Robust Autoencoder Approach

10.1101/214122 ◽

2017 ◽

Cited By ~ 2

Author(s):

Hongzhu Cui ◽

Chong Zhou ◽

Xinyu Dai ◽

Yuting Liang ◽

Randy Paffenroth ◽

...

Keyword(s):

Gene Expression ◽

Deep Learning ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Dataset ◽

Biological Information ◽

Clustering Methods ◽

Genome Wide ◽

A Cell ◽

High Level

AbstractGene expression analysis provides genome-wide insights into the transcriptional activity of a cell. One of the first computational steps in exploration and analysis of the gene expression data is clustering. With a number of standard clustering methods routinely used, most of the methods do not take prior biological information into account. In this paper, we propose a new approach for gene expression clustering analysis. The approach benefits from a new deep learning architecture, Robust Autoencoder, which provides a more accurate high-level representation of the feature sets, and from incorporating prior biological information into the clustering process. We tested our approach on two distinct gene expression datasets and compared the performance with two widely used clustering methods, hierarchical clustering and k-means, as well as with a recent deep learning clustering approach. As a result, our approach outperformed all other clustering methods on the labeled yeast gene expression dataset. Furthermore we showed that it is better in identifying the functionally common clusters than k-means on the unlabeled human gene expression dataset. The results demonstrate that our new deep learning architecture could generalize well the specific properties of gene expression profiles. Furthermore, the results confirm our hypothesis that the prior biological network knowledge could be helpful in the gene expression clustering task.

Download Full-text