Distinct Biological Roles for the Notch Ligands Jagged-1 and Jagged-2
2009; Elsevier BV; Volume: 284; Issue: 26 Linguagem: Inglês
10.1074/jbc.m109.003111
ISSN1083-351X
AutoresKuicheon Choi, Young‐Ho Ahn, Don L. Gibbons, Hai T. Tran, Chad J. Creighton, Luc Girard, John D. Minna, F. Xiao‐Feng Qin, Jonathan M. Kurie,
Tópico(s)Developmental Biology and Gene Regulation
ResumoNotch signaling is activated in a subset of non-small cell lung cancer cells because of overexpression of Notch3, but the role of Notch ligands has not been fully defined. On the basis of gene expression profiling of a panel of non-small cell lung cancer cell lines, we found that the predominant Notch ligands were JAG1, JAG2, DLL1, and DLL3. Given that Notch ligands reportedly have overlapping receptor binding specificities, we postulated that they have redundant biological roles. Arguing against this hypothesis, we found that JAG1 and JAG2 were differentially regulated; JAG1 expression was dependent upon epidermal growth factor receptor (EGFR) activation in HCC827 cells, which require EGFR for survival, whereas JAG2 expression was EGFR-independent in these cells. Furthermore, HCC827 cells underwent apoptosis following depletion of JAG1 but not JAG2, whereas co-culture experiments revealed that depletion of JAG2, but not JAG1, enhanced the ability of HCC827 cells to chemoattract THP-1 human monocytes. JAG2-depleted HCC827 cells expressed high levels of inflammation-related genes, including interleukin 1 (IL1) and a broad range of IL1-regulated cytokines, which was attenuated by inhibition of IL1 receptor (IL1R). Our findings suggest that JAG1 and JAG2 have distinct biological roles including a previously undiscovered role for JAG2 in regulating the expression of cytokines that can promote antitumor immunity. Notch signaling is activated in a subset of non-small cell lung cancer cells because of overexpression of Notch3, but the role of Notch ligands has not been fully defined. On the basis of gene expression profiling of a panel of non-small cell lung cancer cell lines, we found that the predominant Notch ligands were JAG1, JAG2, DLL1, and DLL3. Given that Notch ligands reportedly have overlapping receptor binding specificities, we postulated that they have redundant biological roles. Arguing against this hypothesis, we found that JAG1 and JAG2 were differentially regulated; JAG1 expression was dependent upon epidermal growth factor receptor (EGFR) activation in HCC827 cells, which require EGFR for survival, whereas JAG2 expression was EGFR-independent in these cells. Furthermore, HCC827 cells underwent apoptosis following depletion of JAG1 but not JAG2, whereas co-culture experiments revealed that depletion of JAG2, but not JAG1, enhanced the ability of HCC827 cells to chemoattract THP-1 human monocytes. JAG2-depleted HCC827 cells expressed high levels of inflammation-related genes, including interleukin 1 (IL1) and a broad range of IL1-regulated cytokines, which was attenuated by inhibition of IL1 receptor (IL1R). Our findings suggest that JAG1 and JAG2 have distinct biological roles including a previously undiscovered role for JAG2 in regulating the expression of cytokines that can promote antitumor immunity. In mammals, there are four Notch homologues (Notch1–4) and five ligands (three Delta-like and two Jagged/Serrate) (1Fiúza U.M. Arias A.M. J. Endocrinol. 2007; 194: 459-474Crossref PubMed Scopus (308) Google Scholar). Receptor and ligand are typically presented on neighboring cells; hence, ligand binding is a means of cell-cell communication. Notch participates in key aspects of organogenesis (lateral inhibition, lineage specification, and boundary formation) in the developing embryo, maintains stem cell viability and renewal in the adult, and has been implicated in multiple human cancers (1Fiúza U.M. Arias A.M. J. Endocrinol. 2007; 194: 459-474Crossref PubMed Scopus (308) Google Scholar). In the developing lung, Notch receptors and ligands are expressed in a cell type-specific manner, increase in abundance from embryonic day 11.5 into adulthood, and contribute to cell lineage specification (2Collins B.J. Kleeberger W. Ball D.W. Semin. Cancer Biol. 2004; 14: 357-364Crossref PubMed Scopus (119) Google Scholar). A growing body of evidence supports a role for Notch in tumorigenesis. Notch1 was first identified in humans as the Tan1 oncogene, fusing the control region of the T-cell receptor B gene to a truncated, active form of Notch1 in T-cell acute lymphoblastic leukemia (3Ellisen L.W. Bird J. West D.C. Soreng A.L. Reynolds T.C. Smith S.D. Sklar J. Cell. 1991; 66: 649-661Abstract Full Text PDF PubMed Scopus (1454) Google Scholar). Subsequently, oncogenic forms of Notch2 were discovered in feline thymic lymphomas, and Notch4 was found to be an insertion site for mouse mammary tumor virus (4Rohn J.L. Lauring A.S. Linenberger M.L. Overbaugh J. J. Virol. 1996; 70: 8071-8080Crossref PubMed Google Scholar, 5Gallahan D. Callahan R. Oncogene. 1997; 14: 1883-1890Crossref PubMed Scopus (169) Google Scholar). In NSCLC 3The abbreviations used are: NSCLCnon-small cell lung cancerEGFepidermal growth factorEGFRepidermal growth factor receptorIL1interleukin-1IL1RIL1 receptorIL1RAinterleukin-1 receptor antagonistsiRNAshort interfering RNATNFtumor necrosis factorPARPpoly(ADP-ribose) polymeraseDMSOdimethyl sulfoxide. cell lines, the Notch3 gene on chromosome 19 is involved in balanced translocations with multiple other chromosomes, leading to Notch3 overexpression, and pharmacologic or genetic inhibition of Notch3 suppresses the proliferation of these cells (6Dang T.P. Gazdar A.F. Virmani A.K. Sepetavec T. Hande K.R. Minna J.D. Roberts J.R. Carbone D.P. J. Natl. Cancer Inst. 2000; 92: 1355-1357Crossref PubMed Scopus (217) Google Scholar, 7Haruki N. Kawaguchi K.S. Eichenberger S. Massion P.P. Olson S. Gonzalez A. Carbone D.P. Dang T.P. Cancer Res. 2005; 65: 3555-3561Crossref PubMed Scopus (150) Google Scholar, 8Konishi J. Kawaguchi K.S. Vo H. Haruki N. Gonzalez A. Carbone D.P. Dang T.P. Cancer Res. 2007; 67: 8051-8057Crossref PubMed Scopus (237) Google Scholar). Although other examples of activation of Notch receptors by genomic rearrangement appear to be rare in human tumors, overexpression is common in a variety of solid tumors including pancreas, cervix, breast, and prostate (9Miyamoto Y. Maitra A. Ghosh B. Zechner U. Argani P. Iacobuzio-Donahue C.A. Sriuranpong V. Iso T. Meszoely I.M. Wolfe M.S. Hruban R.H. Ball D.W. Schmid R.M. Leach S.D. Cancer Cell. 2003; 3: 565-576Abstract Full Text Full Text PDF PubMed Scopus (580) Google Scholar, 10Gray G.E. Mann R.S. Mitsiadis E. Henrique D. Carcangiu M.L. Banks A. Leiman J. Ward D. Ish-Horowitz D. Artavanis-Tsakonas S. Am. J. Pathol. 1999; 154: 785-794Abstract Full Text Full Text PDF PubMed Scopus (157) Google Scholar, 11Weijzen S. Rizzo P. Braid M. Vaishnav R. Jonkheer S.M. Zlobin A. Osborne B.A. Gottipati S. Aster J.C. Hahn W.C. Rudolf M. Siziopikou K. Kast W.M. Miele L. Nat. Med. 2002; 8: 979-986Crossref PubMed Scopus (477) Google Scholar, 12Zayzafoon M. Abdulkadir S.A. McDonald J.M. J. Biol. Chem. 2004; 279: 3662-3670Abstract Full Text Full Text PDF PubMed Scopus (119) Google Scholar). non-small cell lung cancer epidermal growth factor epidermal growth factor receptor interleukin-1 IL1 receptor interleukin-1 receptor antagonist short interfering RNA tumor necrosis factor poly(ADP-ribose) polymerase dimethyl sulfoxide. Unlike the solid body of evidence supporting a role for Notch, less is known about the importance of Notch ligands in cancer. Notch ligands function as Notch signaling agonists through intercellular interactions (trans-interactions) and as Notch signaling antagonists through intracellular interactions (cis-interactions) (13D'Souza B. Miyamoto A. Weinmaster G. Oncogene. 2008; 27: 5148-5167Crossref PubMed Scopus (365) Google Scholar). In mammalian systems, Notch ligands bind to Notch family members non-selectively; for example, Jagged-1 and Jagged-2 can both bind to Notch1, Notch2, and probably Notch3 (14Shimizu K. Chiba S. Kumano K. Hosoya N. Takahashi T. Kanda Y. Hamada Y. Yazaki Y. Hirai H. J. Biol. Chem. 1999; 274: 32961-32969Abstract Full Text Full Text PDF PubMed Scopus (202) Google Scholar, 15Shimizu K. Chiba S. Hosoya N. Kumano K. Saito T. Kurokawa M. Kanda Y. Hamada Y. Hirai H. Mol. Cell Biol. 2000; 20: 6913-6922Crossref PubMed Scopus (141) Google Scholar), suggesting a high degree of redundancy in mammalian cells to maintain Notch activity. However, mice that are null for the genes encoding Jagged-1 (Jag1), Jagged-2 (Jag2), or Delta-like ligand4 (Dll4) exhibit distinct embryonic defects (13D'Souza B. Miyamoto A. Weinmaster G. Oncogene. 2008; 27: 5148-5167Crossref PubMed Scopus (365) Google Scholar), suggesting that these ligands exert unique actions that cannot be explained entirely by their receptor binding activities. Indeed, these ligands have intrinsic ligand signaling activity independent of Notch and undergo multiple post-translational modifications, proteolytic processing, endocytosis, and membrane trafficking (13D'Souza B. Miyamoto A. Weinmaster G. Oncogene. 2008; 27: 5148-5167Crossref PubMed Scopus (365) Google Scholar), all of which may contribute to the multifunctionality of Notch ligands. In this study, we examined Notch ligand expression in a panel of NSCLC cell lines and found that they co-expressed multiple ligands, including JAG1, JAG2, DLL1, and DLL3. Further analysis revealed that the expression of JAG1 and JAG2 was regulated independently, and these ligands had distinct biological roles, including a novel finding that JAG2 regulated the expression of proinflammatory cytokines. Thus, JAG1 and JAG2 have non-redundant functions in NSCLC cells. Gefitinib was a gift (Astra Zeneca Pharmaceuticals, Wilmington, DE). We purchased a recombinant human IL1RA (Santa Cruz Biotechnology, Santa Cruz, CA), Hoechst 33342 (Invitrogen), polyclonal antibodies derived in goat against Jag1 (Santa Cruz Biotechnology) and in rabbits against Jag2 (Santa Cruz Biotechnology), a horseradish peroxidase-linked anti-mouse (Cell Signaling Technology, Danvers, MA), anti-goat secondary antibodies (Santa Cruz Biotechnology), and an antibody against β-actin (Sigma-Aldrich). The NSCLC cell lines used in this study were from the Hamon Center Repository or purchased from the American Type Culture Collection (Manassas, VA) and were grown in 5% CO2 at 37 °C in RPMI 1640 medium with high glucose (4.5 g/liter; Invitrogen), supplemented with 10% fetal bovine serum (HyClone, Logan, UT). THP-1 cells were cultured in RPMI1640 medium supplemented with 10% fetal bovine serum, 10 mm HEPES, 1.5 g/liter sodium bicarbonate, 1 mm sodium pyruvate, and 2 mm glutamine. The siRNA control (siCTL nontargeting pool) and the siRNA pooled oligonucleotides against human JAG1 and JAG2 were purchased (Dharmacon, Denver, CO). Cells were transfected at 50% confluency using 10 nm of each construct over a 16-h period using DharmaFECT 1 (Dharmacon). The short hairpin RNA plasmid constructs against human JAG2 and corresponding empty vector were purchased (Origene, Rockville, MD). Cells were transfected at 50% confluency using 3 μg of each construct over a 4-h period with TransPass D1 transfection reagent (New England Biolabs, Ipswich, MA) according to the manufacturer's protocol. After 48 h, medium was replaced with medium containing 1 μg/ml puromycin. After 14 days, the cells were trypsinized, seeded on 10-cm plates at low density, and single colonies were selected and expanded. RNAs were labeled and hybridized to the Illumina expression array WG6-V2 according to the manufacturer's protocol. The array contains 48,701 probes, which correspond to 26,390 distinct Unigene IDs. Array data were background-corrected using the MBCB R package (16Ding L.H. Xie Y. Park S. Xiao G. Story M.D. Nucleic Acids Res. 2008; 36: e58Crossref PubMed Scopus (54) Google Scholar) and quantile-normalized. All genes on the array were BLAST-verified and annotated using recent versions of public National Center for Biotechnology Information (NCBI) databases, and all cell lines were mycoplasma-tested and DNA-fingerprinted. Heat maps were generated using JavaTreeView (17Saldanha A.J. Bioinformatics. 2004; 20: 3246-3248Crossref PubMed Scopus (2357) Google Scholar) of absolute signal intensities using the equation log2(x + 50) − log2(100). RNA was isolated from the cells transfected with siRNAs against JAG1, JAG2, or scrambled controls by using TRIzol (Invitrogen), and 2 μg of total RNA was converted into cDNA. Expression profiling of inflammatory cytokines and their receptors was performed with human inflammatory cytokines and receptor RT2 Profiler PCR array (SABioscience, Frederick, MD) according to the manufacturer's instructions. PCR was performed with the ABI Prism 7500 fast real-time PCR system (Applied Biosystems, Foster City, CA). The ΔΔCt method was used to analyze the expression level of each gene. After PCR, the dissociation curve for each gene was examined to exclude ones with nonspecific amplification or with undetectable expression. The expression profiling of each gene was displayed as a heat map made by using MeV MultiExperiment Viewer 4.1 (18Rhodes D.R. Tomlins S.A. Varambally S. Mahavisno V. Barrette T. Kalyana-Sundaram S. Ghosh D. Pandey A. Chinnaiyan A.M. Nat. Biotechnol. 2005; 23: 951-959Crossref PubMed Scopus (353) Google Scholar). The level of mRNA for each gene was measured with SYBR Green-based real-time PCR. The primers used for real-time PCR were designed by using Primer Express (Applied Biosystems). The primer sequences used are listed in supplemental Table 1. Each cDNA sample (7 μl after 1:10 dilution with water) was amplified by using SYBR Green PCR Master Mix according to the manufacturer's instructions. The PCR products and their dissociation curves were detected with the ABI Prism 7500 fast real-time PCR system. The level of the housekeeping gene L32 ribosomal gene (Rpl32) was used as an internal control. Quantitative PCR results from triplicate RNA samples were used for calculation of mean expression values for each gene. Gene lists were imported into the HiMAP program (19Saeed A.I. Sharov V. White J. Li J. Liang W. Bhagabati N. Braisted J. Klapa M. Currier T. Thiagarajan M. Sturn A. Snuffin M. Rezantsev A. Popov D. Ryltsov A. Kostukovich E. Borisovsky I. Liu Z. Vinsavich A. Trush V. Quackenbush J. BioTechniques. 2003; 34: 374-378Crossref PubMed Scopus (4021) Google Scholar) for protein-protein interaction network analysis. HiMAP includes both experimentally validated protein-protein interactions (as cataloged in the Human Protein Reference Database, or HPRD) and predicted protein-protein interactions based on a probabilistic model integrating multiple factors, including interactome data from the Database of Interacting Proteins, protein domain data, genome-wide expression data, and functional annotation data from the Gene Ontology Project (GO). Cells were lysed with M-PER mammalian protein extraction reagent (Pierce). Lysates were cleared by centrifugation, and protein concentrations were quantified with 1× Quick Start Bradford dye reagent (Bio-Rad) so that equal amounts of protein (40 μg) could be resolved on 10% SDS-polyacrylamide gels. After transfer to membranes, samples were processed and visualized with ECL Western blotting reagents (Amersham Biosciences). All of the Western blotting data were representative of at least three independent experiments. Cells with nuclear fragmentation were quantified by staining with 10 μg/ml Hoechst 33342 for 15 min at room temperature and counting under fluorescence microscopy. Mean values for each condition were calculated based on results from 12 replicates (three independent experiments with quadruplicate samples in each experiment). In vitro migration assays were performed using a 24-well Transwell unit (BD Biosciences) with polycarbonate filters. HCC827 cells transfected with siRNA for Jag1, Jag2, or control were seeded on the lower compartments of the unit in the complete medium for 16 h. Just before the migration assay, the cells on the lower compartments were washed with phosphate-buffered saline, and culture medium was changed to serum-free medium with treatment. THP-1 cells were placed in the upper compartments in serum-free medium and incubated for 24 h. The medium was aspirated after the incubation, and the cells were removed from the upper compartment by scrubbing with a cotton swab. Cells on the underside of the membrane (migrated cells) were stained with SureStain Wright (Fisher) and then washed with water. Cells were counted by microscopy at ×20 magnification. Mean values were calculated from cell counts in five random fields for each filter. Mean values for each condition were calculated based on results from eight replicates (two independent experiments with quadruplicate samples in each experiment). For analysis of treatment effects and differences between genetically modified cells, the Student's t test was used, and p values <0.05 were considered statistically significant. We profiled gene expression in a panel of 70 NSCLC cell lines by using Illumina arrays. Of the five Notch ligands, JAG1, JAG2, DLL1, and DLL3 were expressed at levels that varied by up to 15-fold between cell lines, whereas DLL4 expression was uniformly low in all cell lines (Fig. 1). The majority of the cell lines expressed at least two ligands, and some (HCC95, HCC4018, H1755, H1666, and HCC1833) expressed four ligands. Quantitative PCR analysis of JAG1, JAG2, and Notch1–4 was performed on a subset of the cell lines, which confirmed the relative expression levels of JAG1 and JAG2 observed in the expression array studies performed on those cells and revealed that most cell lines expressed multiple Notch family members (Fig. 2).FIGURE 2Differential expression of Notch ligands and family members based on EGFR mutational status. Included are NSCLC cell lines with wild-type (black bars) or mutant (gray bars) EGFR. Quantitative PCR analysis of basal gene expression revealed genes that were (A) or were not (B) differentially expressed based on EGFR mutational status. The values represent the means of replicate samples and are normalized to the L32 ribosomal RNA gene.View Large Image Figure ViewerDownload Hi-res image Download (PPT) On the basis of reports that Notch ligands exhibit overlapping Notch binding activities (14Shimizu K. Chiba S. Kumano K. Hosoya N. Takahashi T. Kanda Y. Hamada Y. Yazaki Y. Hirai H. J. Biol. Chem. 1999; 274: 32961-32969Abstract Full Text Full Text PDF PubMed Scopus (202) Google Scholar, 15Shimizu K. Chiba S. Hosoya N. Kumano K. Saito T. Kurokawa M. Kanda Y. Hamada Y. Hirai H. Mol. Cell Biol. 2000; 20: 6913-6922Crossref PubMed Scopus (141) Google Scholar), we postulated that they have redundant biological functions in NSCLC cells and used pharmacologic and genetic approaches to test this hypothesis. The cell lines in Fig. 2 differ with respect to somatic mutations that constitutively activate EGFR (HCC827, HCC2279, H4006, H3255, and H1975) or N-Ras (H1299) or have neither mutation (H1819) (20Fujimoto N. Wislez M. Zhang J. Iwanaga K. Dackor J. Hanna A.E. Kalyankrishna S. Cody D.D. Price R.E. Sato M. Shay J.W. Minna J.D. Peyton M. Tang X. Massarelli E. Herbst R. Threadgill D.W. Wistuba I.I. Kurie J.M. Cancer Res. 2005; 65: 11478-11485Crossref PubMed Scopus (131) Google Scholar). Comparison of their expression levels determined by quantitative PCR analyses revealed that JAG1, NOTCH1, and NOTCH2 were more highly expressed in EGFR mutant cells (p values = 0.025, 0.013, and 0.03, respectively) (Fig. 2A), whereas NOTCH3, NOTCH4, and JAG2 were not differentially expressed (Fig. 2B). Because increased JAG1 expression correlated with the presence of mutant EGFR, we examined whether JAG1 was regulated by EGFR. JAG1 RNA and protein levels decreased sharply in HCC827 cells and H4006 cells treated with the EGFR-specific tyrosine kinase inhibitor gefitinib (Fig. 3, A and B). Gefitinib treatment had no effect on JAG1 levels in H1975 cells, which have a resistance mutation (T790M) (18Rhodes D.R. Tomlins S.A. Varambally S. Mahavisno V. Barrette T. Kalyana-Sundaram S. Ghosh D. Pandey A. Chinnaiyan A.M. Nat. Biotechnol. 2005; 23: 951-959Crossref PubMed Scopus (353) Google Scholar) that inhibits EGFR binding to gefitinib (Fig. 3, A and B), indicating that the decrease in JAG1 levels by gefitinib required EGFR inhibition. In contrast, gefitinib had no effect on JAG2 levels in these cells (Fig. 3A). To examine the role of EGFR using a different approach, EGFR-wild-type H1299 cells, which expressed low levels of JAG1 and JAG2 (Fig. 2), were treated with EGF or transfected with wild-type EGFR, both of which increased the expression of JAG1 (Fig. 3C) but not JAG2 (data not shown), and gefitinib treatment abrogated EGFR-induced JAG1 expression in H1299 cells, indicating that this effect was EGFR kinase-dependent. Collectively, these findings suggest that EGFR regulates the expression of JAG1 but not JAG2. We next sought to examine the biological roles of JAG1 and JAG2 by transfecting siRNAs to selectively deplete JAG1 or JAG2 from cultured cells. Transfection of HCC827 NSCLC cells with JAG1- or JAG2-specific siRNAs achieved greater than 90% reductions in Jagged-1 and Jagged-2, respectively (Fig. 4A). Of note, Jagged-2 protein levels increased in JAG1 siRNA-transfected cells, and Jagged-1 protein levels increased in JAG2 siRNA-transfected cells (Fig. 4A), indicating that JAG1 and JAG2 levels were regulated reciprocally. Relative to the control transfectants, the JAG1 siRNA-transfected HCC827 cells exhibited a reduction in cell density over time (Fig. 4B) and an increase in nuclear fragmentation and cleavage of poly(ADP-ribose) polymerase (PARP) (Fig. 4C), which is consistent with apoptotic cell death. In contrast, JAG2 siRNA-transfected cells exhibited minimal evidence of apoptotic cell death based on the absence of PARP cleavage (Fig. 4C) and nuclear fragmentation (data not shown). Collectively, these findings suggest that HCC827 cell survival was dependent upon JAG1 but not JAG2. In addition to their ability to proliferate in an uncontrolled manner, NSCLC cells recruit inflammatory cells, fibroblasts, and endothelial cells, which constitute the tumor stroma (21Wislez M. Antoine M. Rabbe N. Gounant V. Poulot V. Lavolé A. Fleury-Feith J. Cadranel J. Clin. Cancer Res. 2007; 13: 3518-3527Crossref PubMed Scopus (41) Google Scholar). These cells are required for tumor growth and metastasis (22Tlsty T.D. Coussens L.M. Annu. Rev. Pathol. 2006; 1: 119-150Crossref PubMed Scopus (811) Google Scholar). To determine whether JAG1 and JAG2 are involved in this process, we examined the chemoattraction of THP-1, a human monocytic cell line (23Tsuchiya S. Yamabe M. Yamaguchi Y. Kobayashi Y. Konno T. Tada K. Int. J. Cancer. 1980; 26: 171-176Crossref PubMed Scopus (1690) Google Scholar), by HCC827 cells following transfection with JAG1 or JAG2 siRNAs. HCC827 cells and THP-1 cells were seeded into the lower and upper chambers, respectively, of Transwell plates. These chambers were separated by a porous membrane, allowing bidirectional diffusion of secreted, soluble mediators. Following 24 h of incubation, the numbers of THP-1 cells that had migrated across the porous membrane were counted. Relative to control siRNA, JAG2 siRNA transfection enhanced the ability of NSCLC cells to recruit THP-1 cells, whereas JAG1 siRNA had no effect (Fig. 5). Thus, JAG2 inhibited monocytic recruitment by HCC827 cells. To explore the mechanism by which JAG2 inhibits monocyte recruitment, JAG1 and JAG2 siRNA-transfected HCC827 cells were transcriptionally profiled using a quantitative PCR expression array (RT2 Profiler array, SABiosciences) containing 84 inflammation-related genes (gene lists are in supplemental Table 2). Of these, 33 genes were measurable in all three samples (Fig. 6A); the other genes either were undetectable or did not achieve a technically satisfactory amplification in all samples. JAG1 and JAG2 siRNA transfectants exhibited striking differences; relative to the control transfectants, JAG2 siRNA enhanced the expression of the majority of the measurable genes, whereas JAG1 siRNA reduced the expression of a smaller subset (Fig. 6A). Those increased by JAG2 siRNA include, among others, a broad spectrum of CXC chemokines (CXCL1, CXCL3, CXCL5, CXCL6, and CXCL9), CC chemokines (CCL2, CCL5, CCL13, CCL20, and CCL24), interleukins (IL1α, IL1β, IL1F8, IL1F9, and IL17c) and their receptors (IL1RN, IL10Rα, IL13Rα, CCR1, CCR8, and CXCR1). To validate these findings, quantitative PCR was performed on RNA samples from an independent experiment using different primers from those on the array, which confirmed that JAG2 siRNA enhanced the expression of all four genes tested (CCL20, IL1α, IL1β, and CCL5), whereas JAG1 siRNA had no detectable effect on any of them (Fig. 6B). Thus, JAG2 was unique in its ability to regulate the expression of inflammation-related genes. Given the widespread nature of the gene expression changes induced by JAG2 siRNA, we postulated that JAG2 regulates one or more genes that are central nodes in the inflammatory process. To test this, we analyzed their positions within known or predicted global protein interaction networks (interactomes) by using the HiMAP software program. Interactomes identified by this approach are organized into a series of modular structures characterized by centrally located nodes (called hubs) that have multiple connections with other proteins (18Rhodes D.R. Tomlins S.A. Varambally S. Mahavisno V. Barrette T. Kalyana-Sundaram S. Ghosh D. Pandey A. Chinnaiyan A.M. Nat. Biotechnol. 2005; 23: 951-959Crossref PubMed Scopus (353) Google Scholar). Although this approach is purely exploratory and carries no statistical weight, findings in yeast show that centrality within a protein interactome predicts the biological importance of a protein (24Jeong H. Mason S.P. Barabási A.L. Oltvai Z.N. Nature. 2001; 411: 41-42Crossref PubMed Scopus (4011) Google Scholar). Of the 33 measurable inflammation-related genes from the RT2 Profiler PCR array, 28 mapped within a single interactome based on HiMAP analysis (Fig. 7). The hubs within the network with the highest number of links (≥10) included TNFα, IL1α, IL1β, IL1R, CCL2, and CCL5, all of which were prominently up-regulated by JAG2 siRNA (Fig. 6A). Based on the centrality of IL1R and its ligands within the network, we postulated that IL1R mediates JAG2-induced suppression of inflammation-related genes. To test this, we examined the effects of treatment with IL1R antagonist (IL1RA), a naturally occurring, physiological inhibitor of IL1R (25Liao Z. Grimshaw R.S. Rosenstreich D.L. J. Exp. Med. 1984; 159: 126-136Crossref PubMed Scopus (139) Google Scholar). In co-culture assays, IL1RA treatment abrogated the recruitment of THP-1 cells by JAG2 siRNA-transfected HCC827 cells (Fig. 8A). Furthermore, IL1RA treatment attenuated the effects of JAG2 siRNA on three (CCL20, IL1α, and TNFα) of the 10 inflammation-related genes analyzed (IL1R, CXCL3, CXCL5, CXCL1, IL1α, IL1β, CCL2, CCL5, CCL20, and TNFα) (Fig. 8B). Collectively, these findings suggest that IL1R had a pivotal role in the biological effects of JAG2 in HCC827 cells.FIGURE 8IL1RA treatment inhibits the biological effects of JAG2 in HCC827 cells. A, quantification of migrated THP-1 cells in co-culture with JAG2 siRNA-transfected HCC827 cells treated with IL1RA or bovine serum albumin (BSA) control. Results represent the means of replicate wells. Images illustrate stained, migrated cells on membrane (encircled). SCR, scrambled. *, p < 0.05. B, HCC827 cells transfected with the indicated siRNAs were treated with IL1RA or BSA control. RNA isolated from these cells was subjected to quantitative PCR assays. The values represent the means of replicate samples and are normalized to the L32 ribosomal RNA gene. *, JAG2 versus scrambled siRNA transfectants (BSA treatment), p < 0.05; †, IL1RA versus BSA (JAG2 siRNA transfectants), p < 0.05.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Notch signaling has been implicated in multiple facets of cancer biology, including, among others, stem cell renewal, cancer cell proliferation, tumor angiogenesis, and metastasis (1Fiúza U.M. Arias A.M. J. Endocrinol. 2007; 194: 459-474Crossref PubMed Scopus (308) Google Scholar). The findings presented in the current study advance our understanding of the role of Notch in cancer by demonstrating that the roles of JAG1 and JAG2 in NSCLC cells are quite distinct, including regulation of diverse proinflammatory cytokines, a biological property of Notch signaling that, to our knowledge, has heretofore not been reported. Given the reports that Jagged-1 and Jagged-2 bind to Notch family members with similar specificities (14Shimizu K. Chiba S. Kumano K. Hosoya N. Takahashi T. Kanda Y. Hamada Y. Yazaki Y. Hirai H. J. Biol. Chem. 1999; 274: 32961-32969Abstract Full Text Full Text PDF PubMed Scopus (202) Google Scholar, 15Shimizu K. Chiba S. Hosoya N. Kumano K. Saito T. Kurokawa M. Kanda Y. Hamada Y. Hirai H. Mol. Cell Biol. 2000; 20: 6913-6922Crossref PubMed Scopus (141) Google Scholar), the finding that they had distinct biological functions in HCC827 cells raises the possibility that they mediate their actions in part through Notch-independent mechanisms. Providing further support for this possibility was evidence that treatment with a γ-secretase inhibitor N-(N-(3,5-difluorophenacetyl-l-alanyl))-S-phenylglycine t-butyl ester, which reportedly inhibits Notch activity (26Geling A. Steiner H. Willem M. Bally-Cuif L. Haass C. Embo. Rep. 2002; 3: 688-694Crossref PubMed Scopus (427) Google Scholar), only minimally decreased HCC827 cell density (data not shown). All of the Notch ligands, with the exception of Delta-like ligand-3 and Jagged-2, have PDZ-binding motifs at their extreme C termini (27Pintar A. De Biasio A. Popovic M. Ivanova N. Pongor S. Biol. Direct. 2007; 2: 19Crossref PubMed Scopus (37) Google Scholar). These motifs are dispensable for ligand activation and Notch inhibition (28Ascano J.M. Beverly L.J. Capobianco A.J. J. Biol. Chem. 2003; 278: 8771-8779Abstract Full Text Full Text PDF PubMed Scopus (107) Google Scholar, 29Six E.M. Ndiaye D. Sauer G. Laâbi Y. Athman R. Cumano A. Brou C. Israël A. Logeat F. J. Biol. Chem. 2004; 279: 55818-55826Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar, 30Wright G.J. Leslie J.D. Ariza-McNaughton L. Lewis J. Development. 2004; 131: 5659-5669Crossref PubMed Scopus (47) Google Scholar, 31Mizuhara E. Nakatani T. Minaki Y. Sakamoto Y. Ono Y. Takai Y. J. Biol. Chem. 2005; 280: 26499-26507Abstract Full Text Full Text PDF PubMed Scopus (55) Google Scholar), but they are required for Notch ligands to affect oncogenic transformation (28Ascano J.M. Beverly L.J. Capobianco A.J. J. Biol. Chem. 2003; 278: 8771-8779Abstract Full Text Full Text PDF PubMed Scopus (107) Google Scholar). Although it is unclear whether such interactions might have caused the changes in cytokine expression observed here, some PDZ domain proteins such as calcium/calmodulin-dependent serine protein kinase (CASK), Bridge-1, and glutamate receptor interacting protein 1-τ (GRIP1-τ) act as transcriptional activators (32Hsueh Y.P. Wang T.F. Yang F.C. Sheng M. Nature. 2000; 404: 298-302Crossref PubMed Scopus (293) Google Scholar, 33Nakata A. Ito T. Nagata M. Hori S. Sekimizu K. Genes Cells. 2004; 9: 1125-1135Crossref PubMed Scopus (14) Google Scholar, 34Lee J.H. Volinic J.L. Banz C. Yao K.M. Thomas M.K. J. Endocrinol. 2005; 187: 283-292Crossref PubMed Scopus (16) Google Scholar), whereas others, such as afadin/A6 and Acvrinp1, interact with Ras and Smad3 (28Ascano J.M. Beverly L.J. Capobianco A.J. J. Biol. Chem. 2003; 278: 8771-8779Abstract Full Text Full Text PDF PubMed Scopus (107) Google Scholar, 35Pfister S. Przemeck G.K. Gerber J.K. Beckers J. Adamski J. Hrabé de Angelis M. J. Mol. Biol. 2003; 333: 229-235Crossref PubMed Scopus (33) Google Scholar, 36Shoji H. Tsuchida K. Kishi H. Yamakawa N. Matsuzaki T. Liu Z. Nakamura T. Sugino H. J. Biol. Chem. 2000; 275: 5485-5492Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 37Quilliam L.A. Castro A.F. Rogers-Graham K.S. Martin C.B. Der C.J. Bi C. J. Biol. Chem. 1999; 274: 23850-23857Abstract Full Text Full Text PDF PubMed Scopus (102) Google Scholar), respectively, which regulate diverse transcriptional programs. We observed that JAG1 and JAG2 were regulated inversely in HCC827 cells. Notch signaling interacts with a number of different signaling systems, and many of these affect Notch ligand expression. In particular, fibroblast growth factor, platelet-derived growth factor, transforming growth factor-β, vascular endothelial growth factor, hedgehog, and Wnt have been found to modulate Notch ligand expression (13D'Souza B. Miyamoto A. Weinmaster G. Oncogene. 2008; 27: 5148-5167Crossref PubMed Scopus (365) Google Scholar), any of which might have mediated the mutual suppression between JAG1 and JAG2 in HCC827 cells. Equally intriguing is the possibility of a Notch-mediated feed-forward loop that sensed the loss of Notch ligand through the disengagement of Notch trans-interactions, to which it responded by increasing the expression of other Notch ligands. Findings presented here suggest that following JAG2 inhibition, HCC827 cells can induce THP-1 monocyte recruitment. Because the cells in this study were co-cultured in separate compartments and communicated through a porous barrier, we conclude that these interactions were mediated by secreted factors and did not require cell-cell contact. In fact, JAG2 depletion dramatically increased the expression of a broad spectrum of inflammatory mediators. Within the interactome of inflammation-related genes that were regulated by JAG2 depletion, IL1 receptor occupied a central position, and treatment with IL1RA abrogated the recruitment of monocytic cells and the expression of certain inflammatory mediators. Consistent with these findings, IL1 has been reported to regulate the expression of a vast array of proinflammatory cytokines and chemokines (38Allan S.M. Tyrrell P.J. Rothwell N.J. Nat. Rev. Immunol. 2005; 5: 629-640Crossref PubMed Scopus (817) Google Scholar). Collectively, these findings suggest that IL1 is a critical mediator of inflammation by JAG2, adding to the complexity of cell-cell interactions known to regulate macrophage function (14Shimizu K. Chiba S. Kumano K. Hosoya N. Takahashi T. Kanda Y. Hamada Y. Yazaki Y. Hirai H. J. Biol. Chem. 1999; 274: 32961-32969Abstract Full Text Full Text PDF PubMed Scopus (202) Google Scholar), and these findings constitute the first report, to our knowledge, that Notch pathways can regulate tumor cell-induced inflammation. NSCLC remains the primary cause of cancer-related death in Western countries, which is largely because of the fact that once the disease has metastasized, NSCLC cells are resistant to the current treatment options. Even in the setting of tumors with activating EGFR somatic mutations, which confer a unique sensitivity to treatment with EGFR tyrosine kinase inhibitors that leads to rapid and often sustained tumor shrinkage (39Lynch T.J. Bell D.W. Sordella R. Gurubhagavatula S. Okimoto R.A. Brannigan B.W. Harris P.L. Haserlat S.M. Supko J.G. Haluska F.G. Louis D.N. Christiani D.C. Settleman J. Haber D.A. N. Engl. J. Med. 2004; 350: 2129-2139Crossref PubMed Scopus (10094) Google Scholar, 40Paez J.G. Jänne P.A. Lee J.C. Tracy S. Greulich H. Gabriel S. Herman P. Kaye F.J. Lindeman N. Boggon T.J. Naoki K. Sasaki H. Fujii Y. Eck M.J. Sellers W.R. Johnson B.E. Meyerson M. Science. 2004; 304: 1497-1500Crossref PubMed Scopus (8538) Google Scholar, 41Pao W. Miller V. Zakowski M. Doherty J. Politi K. Sarkaria I. Singh B. Heelan R. Rusch V. Fulton L. Mardis E. Kupfer D. Wilson R. Kris M. Varmus H. Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 13306-13311Crossref PubMed Scopus (3902) Google Scholar), the initial tumor response is typically followed by disease recurrence. The problem of disease recurrence has not been obviated by the addition of standard chemotherapeutic agents to EGFR tyrosine kinase inhibitors. Given the importance of Notch signaling in the development of a variety of malignancies, pharmacologic strategies are under development to inhibit the Notch signaling pathway in cancer patients. The findings presented here suggest that such strategies may benefit NSCLC patients by inhibiting cancer cell viability and possibly by enhancing antitumor immunity. We thank Dror Berel for technical assistance. Download .pdf (.06 MB) Help with pdf files
Referência(s)