- Open Access
15 kDa Granulysin versus GM-CSF for monocytes differentiation: analogies and differences at the transcriptome level
© Castiello et al; licensee BioMed Central Ltd. 2011
- Received: 10 March 2011
- Accepted: 18 April 2011
- Published: 18 April 2011
Granulysin is an antimicrobial and proinflammatory protein with several isoforms. While the 9 kDa isoform is a well described cytolytic molecule with pro-inflammatory activity, the functions of the 15 kDa isoform is less well understood. Recently it was shown that 15 kDa Granulysin can act as an alarmin that is able to activate monocytes and immature dendritic cells. Granulocyte Macrophage Colony Stimulating Factor (GM-CSF) is a growth factor widely used in immunotherapy both for in vivo and ex vivo applications, especially for its proliferative effects.
We analyzed gene expression profiles of monocytes cultured with 15 kDa Granulysin or GM-CSF for 4, 12, 24 and 48 hours to unravel both similarities and differences between the effects of these stimulators.
The analysis revealed a common signature induced by both factors at each time point, but over time, a more specific signature for each factor became evident. At all time points, 15 kDa Granulysin induced immune response, chemotaxis and cell adhesion genes. In addition, only 15 kDa Granulsyin induced the activation of pathways related to fundamental dendritic cell functions, such as co-stimulation of T-cell activation and Th1 development. GM-CSF specifically down-regulated genes related to cell cycle arrest and the immune response. More specifically, cytokine production, lymphocyte mediated immunity and humoral immune response were down-regulated at late time points.
This study provides important insights on the effects of a novel agent, 15 kDa granulysin, that holds promise for therapeutic applications aimed at the activation of the immune response.
- Gene Ontology
- Granulocyte Macrophage Colony Stimulate Factor
- Late Time Point
- Immune Response Gene
- Proliferation Related Gene
Many immunotherapies are based on the use of immunomodulators for the activation or suppression of the immune response. These immunomodulators include cytokines, chemokines and growth factors that act on specific subsets of immune cells in vivo or ex vivo, alone or in combination, to modulate an immune response.
GM-CSF is a growth factor encoded by the CSF2 gene. It is a glycoprotein naturally produced by lymphocytes and monocytes that induces the ex vivo proliferation of hematopoietic progenitor cells to form colonies of mature blood cells. In addition, GM-CSF induces the proliferation of monocytes-macrophages and secretion of inflammatory cytokines such as tumor necrosis factor (TNF) and interleukin 1 (IL-1). It plays an important role in the activation of dendritic cells (DCs), T cells and natural killer (NK) cells. Because of its role in modulating both the innate and adaptive immune responses, GM-CSF has been used for immunotherapies both in vivo and ex vivo. In vivo alone and in combination with other cytokines, it enhances antigen presentation of cancer cells [4, 5] and stimulates autologous immune responses [1, 2]. It has also been used as a tumor vaccine adjuvant. Ex vivo applications of GM-CSF are mainly related to the differentiation of monocytes into immature DCs in combination with IL-4 , IL-15 , interferon α (IFN- α) , or as a single agent . At a molecular level, GM-CSF induces monocyte expression of IL-10 , IL-3R , CD23 (FCER2) , CD1  and regulates the expression of MHC class II antigens . However, the molecular effects of GM-CSF on monocytes in vitro have not yet been completely characterized.
Granulysin is a member of the saposin-like protein (SAPLIP) family and colocalizes in the granular compartments of human cytotoxic T lymphocytes (CTL) and NK cells along with granzymes and perforin . It is encoded by GNLY and is a glycoprotein with at least 4 different isoforms. The "mature" granulysin protein (9 kDa) results from the proteolytic maturation of a "secretory" 15 kDa precursor. The 9 kDa isoform is a well characterized proinflammatory cytokine with cytolitic activity. It is able to induce cytolysis of various types of tumors and microbes and induces the expression of several cytokines, such as CCL5 (RANTES), CCL2 (MCP1), CCL4 (MIP-1β), IFNα, and IL-1. The 15 kDa protein is constitutively secreted but its physiological roles have only recently been elucidated . Several diseases, including infections, cancer, autoimmune and skin ailments, are characterized by an abnormal level of expression of Granulysin, suggesting a possible role in regulating immune response and the normal physiology. Recently it has been shown that both 9 and 15 kDa recombinant Granulysin are able to activate antigen presenting cells and act as immune alarmins . In fact, they induced in vitro chemotaxis and activation of both human and mice DCs and inflammatory leukocytes. Of note, 15 kDa Granulysin is much more potent in chemotaxis and proinflammatory activities than the 9 kDa isoform  and while the 9 kDa isoform is a potent antimicrobial and tumoricidal agent, the 15 kDa form has no cytolytic activity in vitro (Clayberger et al., submitted for publication).
In the present study, we performed gene expression analysis of monocytes cultured for 4, 12, 24 and 48 hours in presence of either GM-CSF or 15 kDa Granulysin. This analysis showed that a common signature could be identified at each time point, but over time, different specific effects could be assigned to each of the cytokines relevant to monocyte differentiation and potential therapeutic use. In particular, GM-CSF specifically modulated the expression of several genes involved in the cell differentiation, whereas Granulysin specifically induced the expression of proinflammatory cytokines.
15 kDa Granulysin expression and purification
A detailed description of the procedure has been previously described by Finn et al, 2011. Briefly, a cDNA clone of the 15 kDa Granulysin gene was generated from human peripheral blood cells and cloned into a pet28A E. coli expression vector. After being engineered for insect expression and secretion, the vector was transfected in Hi5 insect cells and after 2 days of culture at 21 C the supernatant was filtered using a 0.45 μM filter and applied to a 5 ml HiTrap Heparin HP (GE Health Care, Uppsala, Sweden). Fractions containing the 15 kDa Granulysin were pooled, purified on 1 ml Resource S column (GE Health Care), concentrated and stored at -80°C.
Human peripheral blood from three healthy donors was collected by apheresis in the Department of Transfusion Medicine of the Clinical Center (NIH) using Amicus Separator (Baxter Healthcare Corp., Fenwal Division, Deerfield, IL). The monocyte fraction was immediately separated by elutriation (Elutra®, Gambro BCT, Lakewood, CO, USA) according to the manufacturer's instructions and the purity achieved was greater than 80%. Fresh monocytes were cultured in 6-well plates (Corning Costar, Corning Incorporated, Corning, NY, USA) at a concentration of 2 ×10 6 cell/ml in 90% RPMI-1640 media, 10% AB heat inactivated plasma, 10 mcg/ml gentamicin in the presence of 15 kDa Granulysin (10 nM) or GM-CSF (Leukine Sagramostin, 10 ng/ml, 56 IU/ml, Genzyme, Cambridge, MA, USA) and harvested at 4, 12, 24 and 48 hours.
At times 0, 4 h, 12 h, 24 h and 48 h 20 ×10 6 cells from each culture condition were used for total RNA extraction using miRNA Easy Kits (Qiagen, Valencia, CA, USA). RNA quantity and quality were assessed by ND-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) and Agilent 2100 Bioanalyser (Agilent Technologies, Waldbronn, Germany), respectively.
Samples and universal Human Reference RNA (Stratagene, Santa Clara, CA, USA) were amplified and labeled using Agilent kit according to the manufacturer's instructions and hybridized on Agilent Chip (Whole Human genome, 4 × 44 k, Agilent Technologies, Santa Clara, CA, USA). The arrays were scanned with Agilent Microarray Scanner and the images were analyzed using Agilent Feature Extraction Software 18.104.22.168. Resulting data were uploaded onto mAdb Gateway http://madb.nci.nih.gov, retrieved and analyzed with BRB Array Tools http://linus.nci.nih.gov/BRB-ArrayTools.html. The raw data set was filtered according to a standard procedure to exclude spots below a minimum intensity of 20 in both fluorescence channels. If the fluorescence intensity of one channel was higher than 20, but the other was below 20, the fluorescence of the low intensity channel was arbitrarily set to 20. Flagged spots were also excluded from the analysis. A total of 33757 genes passed the filter and were used for the analysis.
Real Time PCR Analysis
A total of 0.5 μg of purified RNA was used to synthesize cDNA using Random Hexamers (Qiagen, Valencia, CA, USA) and Superscript II RT (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instruction. The expression of CCL2, CCR7, CD209 and PIM1 were tested using specific TaqMan Gene Expression Assays (Applied Biosystems, Carlsbad, CA, USA). HPRT1 was selected as the housekeeping gene, due to the fact that it has been described as a housekeeping gene in monocytes  and it showed low variability in our microarray dataset. RT-PCR reactions were setup with TaqMan Universal PCR Master Mix (Applied Biosystems) in 384-well plates in a final reaction volume of 10 μl. PCR was conducted using a 7900 HT Sequence Detection System (Applied Biosystems) and data were analyzed using SDS 2.3 software package (Applied Biosystems).
Class comparison was conducted with BRB Array Tools using a random variance model. Significant genes were defined as p-value < 0.001 and FDR < 0.1. Hierarchical cluster analysis and TreeView software were used for data visualization (Eisen Lab, http://rana.lbl.gov). Partek Genomic Suite 6.4 (Partek Inc., St. Louis, MO, USA) was used for the Principal Component Analysis. Database for Annotation, Visualization and Integrated Discovery (DAVID) 2008 software[22, 23] was used for Gene Ontology (GO) enrichment analysis. For the analysis of specific pathways related to DC functions all the genes that, according to Biocarta (http://www.biocarta.com), are part of a specific pathway were selected. For each pathway, similarly to Chaussabel et al 2008 a less stringent p- value (0.05) and FDR (0.15) filter was applied and the remaining number of genes was arithmetically computed according to their up/down-regulation.
GM-CSF and 15 kDa Granulysin induce partially overlapping monocyte signatures
In order to stratify changed transcripts associated with treatment and time in an unbiased fashion, the complete gene set was further filtered to include genes with expression levels ≥ 1.75-fold from the median in at least 20% of the samples. 9951 out of 33757 genes were obtained and used for an unsupervised hierarchical cluster analysis which clearly separated early time point samples (T0 and T4) from the late time point samples (Figure 1b). Moreover, within the cluster of the late time point samples, three subclusters emerged: all 12-hour samples, the late 15 KDa Granulysin and late GM-CSF samples. This analysis revealed that GM-CSF and Granulysin induce in monocytes similar changes at the transcriptome level at early time points, but differences become more evident at later time points.
GM-CSF and 15 kDa Granulysin induce the expression of several genes related to apoptosis and cell differentiation
The GM-CSF-specific gene expression signature
The 15 kDa Granulysin-specific gene expression signature
Granulysin, but not GM-CSF, activated pathways are related to DC function and common-host-response
To validate the microarray data, we performed real-time PCR on CCL2, CCR7, PIM1 and CD209 genes. The selection of CCL2 and CCR7 was based on their up-regulation in Granulysin-treated, but not GM-CSF-treated monocytes in array data. PIM1 was selected because it has been described as being induced by GM-CSF, and CD209 was selected since it is a marker of DC differentiation. The analysis was performed only on untreated T0 monocytes and hour 4 and 48 GM-CSF- and Granulysin-treated monocytes. Both CCL2 and CCR7 were statistically up-regulated by both agents at 4 hours, however, at 48 hours they were only up-regulated by Granulysin (p-value < 0.01) with a fold change greater than 70 for CCR7 and greater than 800 for CCL2 compared to time 0 monocytes, confirming the finding by microarray analysis (Additional file 1). At 4 hours the expression of both CCL2 and CCR7 was greater in Granulysin-treated monocytes than in monocytes treated with GM-CSF, with a fold change in Granulysin samples more than doubled for CCR7 and more than quadrupled for CCL2 compared to GM-CSF. Although PIM1 was filtered out in our analysis, RT-PCR showed a statistically significant induction of PIM1 at 48 hours (p- value < 0.05) by both GM-CSF and Granulysin, but its expression was greater in GM-CSF treated cells. This difference can be easily ascribed to the high stringency we used for statistical analysis of the microarray data (p-value < 0.001) where we preferred to select and analyze only those genes showing strong induction compared time 0 monocytes. In addition, we observed that CD209 was up-regulated by both agents at 48 hours (p-value < 0.01, with fold changes between 5 and 20 versus time 0 monocytes), which is similar to what we observed in the microarray dataset (both agents increased the expression CD209 genes with p- values < 0.0001).
GM-CSF has been used for immunotherapy both in vivo and ex vivo because of its stimulatory effect on immune system cells. Its main application for ex vivo immunotherapy is the differentiation of monocytes into DCs . The broad utilization of GM-CSF in experimental conditions as well as in clinical use is partially due to the lack of alternative agents with similar activity. In this study, we performed a functional characterization of 15 kDa Granulysin side by side with GM-CSF and reported their impact on gene expression changes and kinetics in monocytes. Considering the stronger reliability of analyses of functional modules of genes compared to the analysis of single genes[24, 27, 28], we focused our analysis only on the pathways overrepresented among genes differently expressed with highly stringent p-values. Although it could be argued that several genes were not included in the analysis due to the high stringency, the use of these criteria ensured high sensitivity and specificity.
Our analysis showed that GM-CSF and 15 kDa Granulysin share similar functional property illustrated by their induction of large number of gene expression changes at different time points. The genes common to both agents were mainly related to cell differentiation and apoptosis; these genes enhanced the differentiation of monocytes and negatively impacted apoptosis. In addition, the common signature included immune response genes that were initially up-regulated in a similar fashion by both cytokines and were then down-regulated. However, beyond these overlapping functional characteristics, two different signatures specific to the agent were detected. The GM-CSF-specific signature revealed a down-regulation of immune response genes, among which were several co-stimulatory molecules. In contrast, Granulysin specifically and strongly induced genes related to the immune response with an initial activation on innate immune related genes followed by lymphocyte proliferative genes at later time points. In addition, cell adhesion genes were also specifically induced by Granulysin.
GM-CSF is a growth factor whose cellular effects had been studied for more than twenty years . At low concentrations (< 1 pM) it induces only cell survival, but at higher concentrations it leads to monocyte proliferation, differentiation and functional activation. We found that, although both GM-CSF and Granulysin induced genes related to cell differentiation and silenced genes related to cell death, only GM-CSF treated monocytes showed the down-regulation of cell cycle arrest genes, as previously described [31, 32] and the up-regulation of genes involved in the myeloid cell differentiation. Moreover, our gene expression analysis not only confirmed the induction by GM-CSF of previously described genes, such as the anti-apoptotic gene IRF4, the proliferative gene PIM1, CSF1 and the macrophage inducer PPARG[35, 36]; but also showed the up-regulation of the proliferation/differentiation regulator dimer RUNX1 -CBFB. RUNX1 -CBFB has not been previously reported to be up-regulated by GM-CSF and this observation merits further investigation.
Monocytes cultured in presence of GM-CSF alone are able to differentiate into iDCs, although these iDCs show a reduced ability to induce an effective activation of lymphocytes after maturation[36–38]. Our gene expression analysis clearly showed that GM-CSF leads to a specific down-regulation of several immune-related genes. Although we observed that GM-CSF induced a specific up-regulation of the well-known CD1 family genes , which play an important role in lipid antigen presentation; gene profiling also revealed a specific down-regulation of the co-stimulatory genes CD27, CD28, FYB (ADAP) and TNFSF4 (OX40L). Recent studies have shown how the proteins encoded by these genes are fundamental for the interaction of monocyte-derived dendritic cells and T and B cells [39–44]. In particular, GM-CSF derived DCs show a reduced ability to secret IL-12 after maturation [9, 37]. Consistent with this, we observed a general specific down-regulation of the IL-12 and STAT4 Dependent Signaling Pathway in Th1 Development and the Co-stimulatory Signal during T-cell Activation Pathway. While these data suggest that GM-CSF treated monocytes might have a diminished ability to positively stimulate lymphocytes following antigen presentation, further focused functional studies are needed to test this hypothesis. Of particular interest is the observation that in the setting tested, GM-CSF specifically down-regulated IL-10, both the gene and the pathway, whereas previous results suggest that monocytes cultured in presence of GM-CSF produce high amounts of IL-10 once stimulated with LPS, IFN-γ, TNFα or anti-CD40 Ab [9, 37]. This discrepancy could be the result of the differences in the concentration of GM-CSF used in the monocyte culture conditions or it may be that the higher expression of IL-10 by GM-CSF cultured monocytes is only subsequent to the stimulation with maturating agents.
15 kDa Granulysin is constitutively secreted in vivo by CTL and NK cells, but its function is still incompletely defined [15, 17]. The ability of Granulysin to replicate some GM-CSF-induced monocyte responses is shown by the observation that between 4 and 48 hours thousands of genes were induced by both GM-CSF- and Granulysin. On the other hand, the gene expression analysis revealed that Granulysin, but not GM-CSF, treated monocytes showed an overexpression of several immune-related genes at each time point. Moreover, our data showed that Granulysin induced a specific time-coordinated activation of the immune system. At early time points, several genes involved in the activation of the innate immune system were induced whereas, at later time points, lymphocyte proliferation genes and humoral immune response were up-regulated. In addition, the pathway analysis clearly demonstrated that Granulysin-treated monocytes specifically induced the IL-12 and Stat4 Dependent Signaling Pathway in Th1 Development, suggesting that Granulysin might induce a shift towards Th1 T cell differentiation.
Recently, co-stimulatory molecules have been shown to play a role in chemotaxis . We found that, in contrast to GM-CSF-treatment, Granulysin treatment did not lead to the down-regulation of co-stimulatory molecules; rather Granulysin specifically showed an up-regulation of the co-stimulatory pathways and overexpressed chemotactic genes at each time point. In particular, Granulysin induced the expression of a wide group of chemokines that are able to attract neutrophils (CXCL1, CXCL3), memory and activated T cells (CXCL11, CCL20, CCR7)[47, 48], monocytes (CCL2, CCL20), macrophages and dendritic cells (NRP2). Several studies have shown that chemokines act synergistically[51, 52], strengthening their signals and overcoming eventual antagonists secreted by pathogens[53, 54]. Interestingly a partially overlapping time-fashioned chemokine induction has been described by myeloid and plasmacytoid DCs exposed to influenza virus. This observation might indicate that 15 kDa Granulysin plays an important role in activating the immune system in response to pathogens by inducing monocytes to recruit other immune cells. Moreover, the observation that Granulysin acts as an alarmin strengthen this hypothesis [16, 18].
In conclusion, the analysis of gene expression profiles of monocytes cultured in presence of GM-CSF and 15 kDa Granulysin revealed that although both induce many of the same genes, these two cytokines induce two different monocyte responses. Considering the greater induction of several immune related functions by 15 kDa Granulysin, this study suggests that 15 kDa Granulysin may prove a useful therapeutic immunomodulator for in vitro production of Th-1 polarized monocyte-derived DCs for adoptive immunotherapy.
Acknowledgements and funding
This work is supported by the Intramural Programs of the National Institutes of Health Clinical Center and National Cancer Institute.
- Waller EK: The role of sargramostim (rhGM-CSF) as immunotherapy. Oncologist. 2007, 12 (Suppl 2): 22-26.PubMedGoogle Scholar
- Everly JJ, Lonial S: Immunomodulatory effects of human recombinant granulocyte-macrophage colony-stimulating factor (rhuGM-CSF): evidence of antitumour activity. Expert Opin Biol Ther. 2005, 5: 293-311. 10.1517/14712522.214.171.1243.View ArticlePubMedGoogle Scholar
- Mitsuyasu RT, Golde DW: Clinical role of granulocyte-macrophage colony-stimulating factor. Hematol Oncol Clin North Am. 1989, 3: 411-425.PubMedGoogle Scholar
- Boyer MW, Waller EK, Bray RA, Unangst T, Johnson TS, Phillips C, Jurickova I, Winton EF, Yeager AM: Cytokine upregulation of the antigen presenting function of acute myeloid leukemia cells. Leukemia. 2000, 14: 412-418. 10.1038/sj.leu.2401685.View ArticlePubMedGoogle Scholar
- Arellano ML, Langston A, Winton E, Flowers CR, Waller EK: Treatment of relapsed acute leukemia after allogeneic transplantation: a single center experience. Biol Blood Marrow Transplant. 2007, 13: 116-123. 10.1016/j.bbmt.2006.09.005.View ArticlePubMedGoogle Scholar
- Sallusto F, Lanzavecchia A: Efficient presentation of soluble antigen by cultured human dendritic cells is maintained by granulocyte/macrophage colony-stimulating factor plus interleukin 4 and downregulated by tumor necrosis factor alpha. J Exp Med. 1994, 179: 1109-1118. 10.1084/jem.179.4.1109.View ArticlePubMedGoogle Scholar
- Mohamadzadeh M, Berard F, Essert G, Chalouni C, Pulendran B, Davoust J, Bridges G, Palucka AK, Banchereau J: Interleukin 15 skews monocyte differentiation into dendritic cells with features of Langerhans cells. J Exp Med. 2001, 194: 1013-1020. 10.1084/jem.194.7.1013.PubMed CentralView ArticlePubMedGoogle Scholar
- Santini SM, Lapenta C, Logozzi M, Parlato S, Spada M, Di PT, Belardelli F: Type I interferon as a powerful adjuvant for monocyte-derived dendritic cell development and activity in vitro and in Hu-PBL-SCID mice. J Exp Med. 2000, 191: 1777-1788. 10.1084/jem.191.10.1777.PubMed CentralView ArticlePubMedGoogle Scholar
- Conti L, Gessani S: GM-CSF in the generation of dendritic cells from human blood monocyte precursors: recent advances. Immunobiology. 2008, 213: 859-870. 10.1016/j.imbio.2008.07.017.View ArticlePubMedGoogle Scholar
- Lehmann MH: Recombinant human granulocyte-macrophage colony-stimulating factor triggers interleukin-10 expression in the monocytic cell line U937. Mol Immunol. 1998, 35: 479-485. 10.1016/S0161-5890(98)00043-1.View ArticlePubMedGoogle Scholar
- Smith WB, Guida L, Sun Q, Korpelainen EI, van den HC, Gillis D, Hawrylowicz CM, Vadas MA, Lopez AF: Neutrophils activated by granulocyte-macrophage colony-stimulating factor express receptors for interleukin-3 which mediate class II expression. Blood. 1995, 86: 3938-3944.PubMedGoogle Scholar
- Alderson MR, Tough TW, Ziegler SF, Armitage RJ: Regulation of human monocyte cell-surface and soluble CD23 (Fc epsilon RII) by granulocyte-macrophage colony-stimulating factor and IL-3. J Immunol. 1992, 149: 1252-1257.PubMedGoogle Scholar
- Kasinrerk W, Baumruker T, Majdic O, Knapp W, Stockinger H: CD1 molecule expression on human monocytes induced by granulocyte-macrophage colony-stimulating factor. J Immunol. 1993, 150: 579-584.PubMedGoogle Scholar
- Hornell TM, Beresford GW, Bushey A, Boss JM, Mellins ED: Regulation of the class II MHC pathway in primary human monocytes by granulocyte-macrophage colony-stimulating factor. J Immunol. 2003, 171: 2374-2383.View ArticlePubMedGoogle Scholar
- Hanson DA, Kaspar AA, Poulain FR, Krensky AM: Biosynthesis of granulysin, a novel cytolytic molecule. Mol Immunol. 1999, 36: 413-422. 10.1016/S0161-5890(99)00063-2.View ArticlePubMedGoogle Scholar
- Zitvogel L, Kroemer G: The multifaceted granulysin. Blood. 2010, 116: 3379-3380. 10.1182/blood-2010-08-299214.View ArticlePubMedGoogle Scholar
- Krensky AM, Clayberger C: Biology and clinical relevance of granulysin. Tissue Antigens. 2009, 73: 193-198. 10.1111/j.1399-0039.2008.01218.x.PubMed CentralView ArticlePubMedGoogle Scholar
- Tewary P, Yang D, de la RG, Li Y, Finn MW, Krensky AM, Clayberger C, Oppenheim JJ: Granulysin activates antigen-presenting cells through TLR4 and acts as an immune alarmin. Blood. 2010, 116: 3465-3474. 10.1182/blood-2010-03-273953.PubMed CentralView ArticlePubMedGoogle Scholar
- Finn MW, Clayberger C, Krensky AM: Expression and purification of 15 kDa granulysin utilizing an insect cell secretion system. Protein Expr Purif. 2011, 75: 70-74. 10.1016/j.pep.2010.07.009.PubMed CentralView ArticlePubMedGoogle Scholar
- Mane VP, Heuer MA, Hillyer P, Navarro MB, Rabin RL: Systematic method for determining an ideal housekeeping gene for real-time PCR analysis. J Biomol Tech. 2008, 19: 342-347.PubMed CentralPubMedGoogle Scholar
- Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA. 1998, 95: 14863-14868. 10.1073/pnas.95.25.14863.PubMed CentralView ArticlePubMedGoogle Scholar
- Huang dW, Sherman BT, Zheng X, Yang J, Imamichi T, Stephens R, Lempicki RA: Extracting biological meaning from large gene lists with DAVID. Curr Protoc Bioinformatics. 2009, 13: UnitGoogle Scholar
- Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA: DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 2003, 4: 3-10.1186/gb-2003-4-5-p3.View ArticleGoogle Scholar
- Chaussabel D, Quinn C, Shen J, Patel P, Glaser C, Baldwin N, Stichweh D, Blankenship D, Li L, Munagala I: A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus. Immunity. 2008, 29: 150-164. 10.1016/j.immuni.2008.05.012.PubMed CentralView ArticlePubMedGoogle Scholar
- Simon R: Using DNA microarrays for diagnostic and prognostic prediction. Expert Rev Mol Diagn. 2003, 3: 587-595. 10.1586/14737126.96.36.1997.View ArticlePubMedGoogle Scholar
- Guthridge MA, Barry EF, Felquer FA, McClure BJ, Stomski FC, Ramshaw H, Lopez AF: The phosphoserine-585-dependent pathway of the GM-CSF/IL-3/IL-5 receptors mediates hematopoietic cell survival through activation of NF-kappaB and induction of bcl-2. Blood. 2004, 103: 820-827. 10.1182/blood-2003-06-1999.View ArticlePubMedGoogle Scholar
- Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstrale M, Laurila E: PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003, 34: 267-273. 10.1038/ng1180.View ArticlePubMedGoogle Scholar
- Segal MR, Dahlquist KD, Conklin BR: Regression approaches for microarray data analysis. J Comput Biol. 2003, 10: 961-980. 10.1089/106652703322756177.View ArticlePubMedGoogle Scholar
- Shi L, Jones WD, Jensen RV, Harris SC, Perkins RG, Goodsaid FM, Guo L, Croner LJ, Boysen C, Fang H: The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies. BMC Bioinformatics. 2008, 9 (Suppl 9): S10-10.1186/1471-2105-9-S9-S10.PubMed CentralView ArticlePubMedGoogle Scholar
- Hamilton JA: Colony-stimulating factors in inflammation and autoimmunity. Nat Rev Immunol. 2008, 8: 533-544. 10.1038/nri2356.View ArticlePubMedGoogle Scholar
- Guthridge MA, Powell JA, Barry EF, Stomski FC, McClure BJ, Ramshaw H, Felquer FA, Dottore M, Thomas DT, To B: Growth factor pleiotropy is controlled by a receptor Tyr/Ser motif that acts as a binary switch. EMBO J. 2006, 25: 479-489. 10.1038/sj.emboj.7600948.PubMed CentralView ArticlePubMedGoogle Scholar
- Williams GT, Smith CA, Spooncer E, Dexter TM, Taylor DR: Haemopoietic colony stimulating factors promote cell survival by suppressing apoptosis. Nature. 1990, 343: 76-79. 10.1038/343076a0.View ArticlePubMedGoogle Scholar
- Lehtonen A, Matikainen S, Miettinen M, Julkunen I: Granulocyte-macrophage colony-stimulating factor (GM-CSF)-induced STAT5 activation and target-gene expression during human monocyte/macrophage differentiation. J Leukoc Biol. 2002, 71: 511-519.PubMedGoogle Scholar
- Gruber MF, Gerrard TL: Production of macrophage colony-stimulating factor (M-CSF) by human monocytes is differentially regulated by GM-CSF, TNF alpha, and IFN-gamma. Cell Immunol. 1992, 142: 361-369. 10.1016/0008-8749(92)90297-3.View ArticlePubMedGoogle Scholar
- Ricote M, Huang J, Fajas L, Li A, Welch J, Najib J, Witztum JL, Auwerx J, Palinski W, Glass CK: Expression of the peroxisome proliferator-activated receptor gamma (PPARgamma) in human atherosclerosis and regulation in macrophages by colony stimulating factors and oxidized low density lipoprotein. Proc Natl Acad Sci USA. 1998, 95: 7614-7619. 10.1073/pnas.95.13.7614.PubMed CentralView ArticlePubMedGoogle Scholar
- Skorokhod OA, Alessio M, Mordmuller B, Arese P, Schwarzer E: Hemozoin (malarial pigment) inhibits differentiation and maturation of human monocyte-derived dendritic cells: a peroxisome proliferator-activated receptor-gamma-mediated effect. J Immunol. 2004, 173: 4066-4074.View ArticlePubMedGoogle Scholar
- Ganguly D, Paul K, Bagchi J, Rakshit S, Mandal L, Bandyopadhyay G, Bandyopadhyay S: Granulocyte-macrophage colony-stimulating factor drives monocytes to CD14low CD83+ DC. Immunology. 2007, 121: 499-507. 10.1111/j.1365-2567.2007.02596.x.PubMed CentralView ArticlePubMedGoogle Scholar
- Chitta S, Santambrogio L, Stern LJ: GMCSF in the absence of other cytokines sustains human dendritic cell precursors with T cell regulatory activity and capacity to differentiate into functional dendritic cells. Immunol Lett. 2008, 116: 41-54. 10.1016/j.imlet.2007.11.013.View ArticlePubMedGoogle Scholar
- Lippert U, Zachmann K, Ferrari DM, Schwarz H, Brunner E, Mahbub-Ul Latif AH, Neumann C, Soruri A: CD137 ligand reverse signaling has multiple functions in human dendritic cells during an adaptive immune response. Eur J Immunol. 2008, 38: 1024-1032. 10.1002/eji.200737800.View ArticlePubMedGoogle Scholar
- Hashimoto-Okada M, Kitawaki T, Kadowaki N, Iwata S, Morimoto C, Hori T, Uchiyama T: The CD70-CD27 interaction during the stimulation with dendritic cells promotes naive CD4(+) T cells to develop into T cells producing a broad array of immunostimulatory cytokines in humans. Int Immunol. 2009, 21: 891-904. 10.1093/intimm/dxp056.View ArticlePubMedGoogle Scholar
- Hendriks J, Xiao Y, Rossen JW, van der Sluijs KF, Sugamura K, Ishii N, Borst J: During viral infection of the respiratory tract, CD27, 4-1BB, and OX40 collectively determine formation of CD8+ memory T cells and their capacity for secondary expansion. J Immunol. 2005, 175: 1665-1676.View ArticlePubMedGoogle Scholar
- Wang J, Guo Z, Dong Y, Kim O, Hart J, Adams A, Larsen CP, Mittler RS, Newell KA: Role of 4-1BB in allograft rejection mediated by CD8+ T cells. Am J Transplant. 2003, 3: 543-551. 10.1034/j.1600-6143.2003.00088.x.View ArticlePubMedGoogle Scholar
- Croft M, So T, Duan W, Soroosh P: The significance of OX40 and OX40L to T-cell biology and immune disease. Immunol Rev. 2009, 229: 173-191. 10.1111/j.1600-065X.2009.00766.x.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang X, Voskens CJ, Sallin M, Maniar A, Montes CL, Zhang Y, Lin W, Li G, Burch E, Tan M: CD137 promotes proliferation and survival of human B cells. J Immunol. 2010, 184: 787-795. 10.4049/jimmunol.0901619.View ArticlePubMedGoogle Scholar
- Zhong W, Zhang Z, Hinrichs D, Wu X, Hall M, Xia Z, Rosenbaum JT: OX40 induces CCL20 expression in the context of antigen stimulation: an expanding role of co-stimulatory molecules in chemotaxis. Cytokine. 2010, 50: 253-259. 10.1016/j.cyto.2010.03.021.PubMed CentralView ArticlePubMedGoogle Scholar
- Scimone ML, Lutzky VP, Zittermann SI, Maffia P, Jancic C, Buzzola F, Issekutz AC, Chuluyan HE: Migration of polymorphonuclear leucocytes is influenced by dendritic cells. Immunology. 2005, 114: 375-385. 10.1111/j.1365-2567.2005.02104.x.PubMed CentralView ArticlePubMedGoogle Scholar
- Sallusto F, Schaerli P, Loetscher P, Schaniel C, Lenig D, Mackay CR, Qin S, Lanzavecchia A: Rapid and coordinated switch in chemokine receptor expression during dendritic cell maturation. Eur J Immunol. 1998, 28: 2760-2769. 10.1002/(SICI)1521-4141(199809)28:09<2760::AID-IMMU2760>3.0.CO;2-N.View ArticlePubMedGoogle Scholar
- Schutyser E, Struyf S, Van DJ: The CC chemokine CCL20 and its receptor CCR6. Cytokine Growth Factor Rev. 2003, 14: 409-426. 10.1016/S1359-6101(03)00049-2.View ArticlePubMedGoogle Scholar
- Deshmane SL, Kremlev S, Amini S, Sawaya BE: Monocyte chemoattractant protein-1 (MCP-1): an overview. J Interferon Cytokine Res. 2009, 29: 313-326. 10.1089/jir.2008.0027.PubMed CentralView ArticlePubMedGoogle Scholar
- Rey-Gallardo A, Escribano C, Delgado-Martin C, Rodriguez-Fernandez JL, Gerardy-Schahn R, Rutishauser U, Corbi AL, Vega MA: Polysialylated neuropilin-2 enhances human dendritic cell migration through the basic C-terminal region of CCL21. Glycobiology. 2010, 20: 1139-1146. 10.1093/glycob/cwq078.View ArticlePubMedGoogle Scholar
- Vanbervliet B, Bendriss-Vermare N, Massacrier C, Homey B, de Bouteiller O, Briere F, Trinchieri G, Caux C: The inducible CXCR3 ligands control plasmacytoid dendritic cell responsiveness to the constitutive chemokine stromal cell-derived factor 1 (SDF-1)/CXCL12. J Exp Med. 2003, 198: 823-830. 10.1084/jem.20020437.PubMed CentralView ArticlePubMedGoogle Scholar
- Gouwy M, Struyf S, Proost P, Van Damme J: Synergy in cytokine and chemokine networks amplifies the inflammatory response. Cytokine Growth Factor Rev. 2005, 16: 561-580. 10.1016/j.cytogfr.2005.03.005.View ArticlePubMedGoogle Scholar
- Rosenkilde MM: Virus-encoded chemokine receptors--putative novel antiviral drug targets. Neuropharmacology. 2005, 48: 1-13. 10.1016/j.neuropharm.2004.09.017.View ArticlePubMedGoogle Scholar
- Alcami A, Saraiva M: Chemokine binding proteins encoded by pathogens. Adv Exp Med Biol. 2009, 666: 167-179. full_text.View ArticlePubMedGoogle Scholar
- Piqueras B, Connolly J, Freitas H, Palucka AK, Banchereau J: Upon viral exposure, myeloid and plasmacytoid dendritic cells produce 3 waves of distinct chemokines to recruit immune effectors. Blood. 2006, 107: 2613-2618. 10.1182/blood-2005-07-2965.PubMed CentralView ArticlePubMedGoogle Scholar
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