Gene Expression Profiles for Normal Human Bone Marrow-Derived CD34+ Stem Cells and CD34−/CD33+ Myeloid-Committed Progenitor Cells in Response to Daily Granulocyte-Colony-Stimulating Factor (G-CSF) Treatment.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4162-4162
Author(s):  
Andrew A.G. Aprikyan ◽  
David Pritchard ◽  
Conrad W. Liles ◽  
Steve Schwartz ◽  
David C. Dale

Abstract G-CSF is widely used to accelerate marrow recovery after cancer chemotherapy, to facilitate collection of hematopoietic progenitor cells, and to treat severe chronic neutropenia. Although G-CSF was originally defined as a stimulus for myeloid cell proliferation, it has potent anti-apoptotic properties, affects synthesis of proteins stored in neutrophil granules, and has many other effects on cells of the myeloid lineage. To improve understanding of the molecular and cellular effects of G-CSF, particularly related to its use for the treatment of severe chronic neutropenia, we performed gene expression profile studies using Affymetrix oligonucleotide arrays and purified bone marrow cell sub-populations from normal volunteers treated with daily subcutaneous G-CSF (300 mcg/sc/qd) for five days. Under local anaesthesia, paired marrow aspirates were obtained from the posterior iliac crest before and after 5 daily doses of G-CSF. CD34+ and CD34−/CD33+ cells were purified using Miltenyi immunomagnetic beads. Two rounds of amplification of total RNA isolated from purified CD34+ or CD33+cells was used to obtain sufficient cRNA for hybridization. Expression data from scanned chips were first analyzed using the RMA algorithm. The limma package of the Bioconductor project was used to identify differentially expressed genes. Limma uses an empirical Bayes method to moderate the standard errors of the estimated log-fold changes. The statistical analysis of CD33+ cells revealed that 150 of more than 12,000 genes examined were up- or down-regulated >2-fold in response to G-CSF treatment. The top 10 genes with up- or down-regulated level of expression include clusterin, neutrophil elastase, two transcription factors, gelsolin, Grb2, phospholipase D3, protein kinase C, the major vault protein, and serine-threonine kinase. In the myeloid-committed CD34-/CD33+ progenitor cells, genes with altered expression level represent those with gene products involved in the cell cycle, regulation of apoptosis, the cytoskeleton, the inflammatory response, or serine proteases and transcription factors. Most of the genes up-regulated in CD33+ cells (e.g. neutrophil elastase, phospholipase D, protein kinase C) were down-regulated in CD34-positive cells in response to G-CSF. The results of the comparative analyses revealed the normal signature gene expression profiles for CD34+ and CD34−/CD33+ cells and identified genes that may mediate specific G-CSF effects.

Blood ◽  
2000 ◽  
Vol 95 (2) ◽  
pp. 510-518 ◽  
Author(s):  
June Helen Myklebust ◽  
Erlend B. Smeland ◽  
Dag Josefsen ◽  
Mouldy Sioud

Protein kinase C (PKC) is a family of serine/threonine protein kinases involved in many cellular responses. Although the analysis of PKC activity in many systems has provided crucial insights to its biologic function, the precise role of different isoforms on the differentiation of normal hematopoietic progenitor cells into the various lineages remains to be investigated. The authors have assessed the state of activation and protein expression of PKC isoforms after cytokine stimulation of CD34+ progenitor cells from human bone marrow. Freshly isolated CD34+ cells were found to express PKC-, PKC-β2, and PKC-ɛ, whereas PKC-δ, PKC-γ, and PKC-ζ were not detected. Treatment with erythropoietin (EPO) or with EPO and stem cell factor (SCF) induced a predominantly erythroid differentiation of CD34+ cells that was accompanied by the up-regulation of PKC- and PKC-β2 protein levels (11.8- and 2.5-fold, respectively) compared with cells cultured in medium. Stimulation with EPO also resulted in the nuclear translocation of PKC- and PKC-β2 isoforms. Notably, none of the PKC isoforms tested were detectable in CD34+ cells induced to myeloid differentiation by G-CSF and SCF stimulation. The PKC inhibitors staurosporine and calphostin C prevented EPO-induced erythroid differentiation. Down-regulation of the PKC-, PKC-β2, and PKC-ɛ expression by TPA pretreatment, or the down-regulation of PKC- with a specific ribozyme, also inhibited the EPO-induced erythroid differentiation of CD34+ cells. No effect was seen with PKC-β2–specific ribozymes. Taken together, these findings point to a novel role for the PKC- isoform in mediating EPO-induced erythroid differentiation of the CD34+ progenitor cells from human bone marrow.


1998 ◽  
Vol 66 (4) ◽  
pp. 1795-1799 ◽  
Author(s):  
Sabine Pingel ◽  
Zhi-En Wang ◽  
Richard M. Locksley

ABSTRACT We characterized the effects of Leishmania infection on activation-induced translocation of protein kinase C (PKC) isoforms in murine bone marrow-derived macrophages. Although PKC-dependent gene expression was attenuated by infection, the distribution and translocation of PKC isoforms were unaffected. However, subsequent dissociation from membranes was substantially delayed for some isoforms, particularly PKCβ.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 394-394
Author(s):  
Marc J. Braunstein ◽  
Daniel R. Carrasco ◽  
Fabien Campagne ◽  
Piali Mukherjee ◽  
Kumar Sukhdeo ◽  
...  

Abstract Background: In multiple myeloma (MM), bone-marrow-derived endothelial progenitor cells (EPCs) contribute to tumor neoangiogenesis, and their levels covary with tumor mass and prognosis. Recent X-chromosome inactivation studies showed that EPCs are clonally restricted in MM. In addition, high-resolution array comparative genomic hybridization (aCGH) found that the genomes of EPCs and MM cells display similar chromosomal gains and losses in the same patient. In this study, we performed an integrative analysis of EPCs and tumor cells by genome-wide expression profiling, and applied a bioinformatics approach that leverages gene expression data from cancer datasets to mine MM gene pathways common to multiple tumor tissues and likely involved in MM pathogenesis. Methods: Confluent EPCs (>98% vWF/CD133/KDR+ and CD38−) were outgrown from 22 untreated MM patients’ bone marrow aspirates by adherence to laminin. The fractions enriched for tumor cells were >50% CD38+. For gene expression profiling, total RNA from EPCs, MM cells, and control HUVECs were hybridized to cDNA microarrays, and comparisons were made by analysis of variance. Results: Two sets of EPC gene profiles were of particular interest. The first contained genes that differ significantly between EPCs and HUVEC, but not between EPCs and tumor (Profile 1). We hypothesize that this profile is a consequence of the clonal identity previously reported between EPCs and tumor, and that a subset of these genes is largely responsible for MM progression. The second set of important EPC genes are differentially regulated compared both to HUVECs and to tumor cells (Profile 2). These genes may represent the profile of EPCs that are clonally diverse from tumor cells but nevertheless display common gene expression patterns with other cancers. Profile 2 genes may also represent genes that confer a predisposition to clonal transformation of EPCs. When genes in Profile 1 and Profile 2 were overlapped with published lists of cancer biomarkers, significant similarities (P<.05) were apparent. The largest overlaps were observed with the HM200 gene list, a list composed of 200 genes most consistently differentially expressed in human/mouse cancers (Campagne and Skrabanek, BMC Bioinformatics 2006). More than 80% of genes in either EPC profile have not been previously characterized in MM, but have been identified as cancer biomarkers in other cancer studies. These genes will be presented and discussed in the context of MM. Current studies are aimed at integrating Profile 1 and Profile 2 genes in each patient with chromosomal copy number abnormalities (CNAs) found in EPCs, and also with clinical stage and disease severity, in order to elucidate the pathogenic information that the profiles hold. Conclusions: The genomes of EPCs display ranges of overlap with tumor cells in MM, evidenced by gene expression profiles with varying similarity to those found in MM tumor cells. More importantly, MM EPC gene expression profiles, in contrast to normal endothelial cells, contain cancer biomarker genes in tumors not yet associated with MM. Results strongly support the concept that EPCs are an integral part of the neoplastic process in MM.


2010 ◽  
Vol 139 (6) ◽  
pp. 2061-2071.e2 ◽  
Author(s):  
Mohamad El–Zaatari ◽  
Yana Zavros ◽  
Art Tessier ◽  
Meghna Waghray ◽  
Steve Lentz ◽  
...  

1992 ◽  
Vol 152 (2) ◽  
pp. 264-273 ◽  
Author(s):  
John R. Bethea ◽  
G. Yancey Gillespie ◽  
Etty N. Benveniste

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