- Research article
- Open Access
Functional blockade of α5β1 integrin induces scattering and genomic landscape remodeling of hepatic progenitor cells
© Vellón et al; licensee BioMed Central Ltd. 2010
- Received: 16 April 2010
- Accepted: 19 October 2010
- Published: 19 October 2010
Cell scattering is a physiological process executed by stem and progenitor cells during embryonic liver development and postnatal organ regeneration. Here, we investigated the genomic events occurring during this process induced by functional blockade of α5β1 integrin in liver progenitor cells.
Cells treated with a specific antibody against α5β1 integrin exhibited cell spreading and scattering, over-expression of liver stem/progenitor cell markers and activation of the ERK1/2 and p38 MAPKs signaling cascades, in a similar manner to the process triggered by HGF/SF1 stimulation. Gene expression profiling revealed marked transcriptional changes of genes involved in cell adhesion and migration, as well as genes encoding chromatin remodeling factors. These responses were accompanied by conspicuous spatial reorganization of centromeres, while integrin genes conserved their spatial positioning in the interphase nucleus.
Collectively, our results demonstrate that α5β1 integrin functional blockade induces cell migration of hepatic progenitor cells, and that this involves a dramatic remodeling of the nuclear landscape.
- Wound Healing Assay
- Transwell Assay
- Cell Scattering
- Hepatic Progenitor Cell
Cell scattering is a physiological process executed by stem and progenitor cells during embryonic liver development and postnatal organ regeneration. Metastasis seems to arise from the same genetic program that instructs cells to detach, adhere, and migrate through extracellular matrices, crossing tissue boundaries and escaping death due to an unsuitable tissue context . The Hepatocyte Growth Factor/Scattering Factor 1 (HGF/SF1) is the paradigmatic example of a molecule that induces cell scattering with optimal spatial and chronological coordination. This process takes place through a complex network of signaling pathways triggered by the HGF/SF1 tyrosine kinase receptor, Met, which includes the Grb2-Ras-Mitogen Activated Protein Kinases (MAPK), the PI-3'K, and the Signal Transducer and Activator of Transcription (STAT) cascades . Integrins are thought to be essential for cell migration and penetration of the basement membrane, in addition to playing a major role in cellular adhesion to the extracellular matrix (ECM) and certain cell surface proteins. These adhesion receptors also convey a series of mechanical and biochemical extracellular stimuli in signaling cascades that favor cell migration and proliferation [3, 4]. Interestingly, growth factor and integrin-emanating signals can interact to promote cell migration. For instance, c-Met signaling can be modulated by the α6β4 integrin when co-expressed on the cell surface , and HGF/SF1, conversely, can regulate the adhesive status and aggregation rate of αvβ3 integrin in epithelial cells .
The genome is highly organized within the cell nucleus . Indeed, chromosomes and genes exhibit cell type specific preferential positioning, and this non-random distribution of genetic elements in the interphase nucleus is related to genome function . Genome organization has been broadly investigated, in particular during cell differentiation and tumorigenesis. For example, the stem cell specific genes Nanog and Oct4 acquire differential positioning in the nucleus as their expression levels change during differentiation of human embryonic stem cells . Additionally, changes in the spatial distribution of cancer related genes have been shown in a cell-model of breast cancer during induced malignant evolution . However, much still remains to be elucidated regarding the genomic events associated with cell migration.
MLP29 cells are murine liver progenitor cells that respond to HGF/SF1 treatment with a well characterized sequence of events that resemble the cell invasion program, including cell scattering, migration, proliferation, and tubular morphogenesis . Considering that α5β1 integrin is one of the main ECM receptors of hepatocytes, and that changes in integrin-mediated contacts between the cell and ECM are necessary for cell migration , we speculate that functional blockade of α5β1 integrin may result in cell migration, and that the changes in the cell microenvironment will be sensed and transduced into specific nuclear responses. Here, we investigated the molecular and cellular genomic events associated with cell migration triggered by the functional blockade of α5β1 integrin in liver progenitor cells.
Integrin expression profile and adhesion properties of hepatic progenitor and HCC cells
α5β1 integrin functional blockade induces cell scattering and migration in hepatic progenitor cells
α5β1 integrin functional blockade of hepatic progenitor cells triggers cell signaling pathways involved in cell motility
We checked the activation status of the different members of the MAPKs family in response to α5β1 functional blockade or stimulation with HGF/SF1. Using a MAPK array kit, we determined that both treatments induced the long-term activation (twenty hours) of p38 MAPK, partly matching the hyperactivation of the ERK1/2 and p38 MAPKs cell transduction cascades of the highly invasive Hep16 HCC cells (Figure 2B). Activation of ERK 1/2 MAPKs was also observed, however, the peak of this kinase phosphorylation occurred two hours after α5β1 integrin functional blockade. These effects were reversed by the MEK pharmacological inhibitor U0126 (Figure 2B).
Gene expression profile of migrating liver progenitor cells
Most significant up-regulations in MLP29 cells upon α5β1 integrin functional blockade
Biological Processes (BP)
Aromatic compound metabolic process
Response to external stimulus
Regulation of biological process
Response to stress
Cellular Components (CC)
Most significantly up-regulated genes (p < 0.0005) in MLP29 cells upon α5β1 integrin functional blockade
Aromatic compound metabolic process
Response to external stimulus
Sfpq- Dido1- Ncoa5- Sap18- Traf3- Hif1a+ Maff+ Bnc1+ Tgfb2+ Gpx1+
Regulation of biological processes
Sfpq- Hif1a+ Tgfb2+ Gpx1+
Response to stress
Mgat2- Ncoa5- Nmt1- Hif1a+ Tgfb2+
Ide- Lman2- Vnn3+ Tgfb2+ Slpi+
Distinct expression profile of chromatin-remodeling and transcription factors
Cell scattering is associated with nuclear architecture remodeling
To further explore the nuclear effects of α5β1 block or HGF/SF1 stimulation we analyzed the pattern of histone H3 trimethylated at lysine 9 (Me3K9H3) and acetylated at lysine 9 and 14 (Ac3K9/K14H3) by immunofluorescence analysis. Mouse cells have the majority of Me3K9H3 localized to prominent clusters of pericentromeric heterochromatin  and, consistent with previous reports, microscopic inspection of MLP29 cell preparations revealed that Me3K9H3 localized to chromocenters (Figure 6). However, detailed 3D analysis revealed that α5β1 functional blockade increased the average number of foci per nucleus, and this was concomitant with a decrease in their volume (Figure 7B). The changes in centromeres and Me3K9H3 foci spatial organization were not related to alterations in the nuclear volume due to technical artifact (mean nucleus volume ~250 μm3) or variation of the mean fluorescence intensity.
Since acetylated histone H3 exhibited a homogeneous nuclear distribution (Figure 6), rather than a focal pattern, we analyzed the levels of Ac3K9/K14H3 by flow cytometry and western blot, in addition to immunofluorescence, in order to determine the protein expression level and measure the mean intensity of Ac3K9/K14H3 more accurately. Interestingly, α5β1 functional blockade or HGF/SF1 stimulation significantly increased the levels of Ac3K9/K14H3 (Figure 7C; Additional files 8 and 9). Altogether, these observations indicate that alterations of the α5β1-mediated cell-ECM interactions during cell migration influence the overall spatial and functional organization of the nucleus.
Positioning of genes encoding integrins during cell scattering
Invasive cell growth occurs not only during malignancy, but also takes place under physiological conditions during embryonic development and organ formation. In the present work, we demonstrate that functional blocking of α5β1 integrin induces cell dissociation and motility, and that this program involves changes in the structural and functional organization of the genome. Cell scattering induced by functional blockade of α5β1 integrin was statistically demonstrated by the wound healing assay, but the transwell assays did not show invasive capacity. Gerlitz et al. have reported that overexpression of the C-terminal domain of the histone H1E accelerated cell migration in the wound healing assays, but inhibited cell migration as measured by the transwell assay . Likewise, our results for this test are contrasting, and this may be due to the fact that the experimental procedure includes the pre-treatment of the cells with the α5β1 functional blocking antibody, which may inhibit their adhesion to components of the transwell membrane and consequently cells can not invade. Alternatively, different migration mechanisms may be used in these two assays: In the wound healing assay, the cells use mesenchymal-like polarized motility and the transwell assay implies amoeboid-like movements . Cell migration was accompanied by the activation of ERKs 1/2 and p38 MAPKs cell signaling pathways and a drastic increase in metabolic status. ERK 1/2 and p38 MAPKs phosphorylation occurs during migration of different cell types in response to various growth factors such as VEGF, EGF and TGF-β, and to components of the ECM . Functional blockade of α5β1 in MLP29 cells, on the other hand, was able to up-regulate the expression of the hepatic stem/progenitor cell markers EpCAM, AFP and CK19, all shown to be associated with migration of epithelial and embryonic stem cells in vitro . Furthermore, EpCAM participates in intercellular and cell-ECM interactions, and is expressed during liver regeneration .
Gene expression profiles documented here strongly support the notion that α5β1 integrin-mediated cell migration was associated with a larger number of differentially regulated genes than the process induced by HGF/SF1. Moreover, the number of up-regulated genes was higher than the number of down-regulated genes. These data fit very well with the results obtained from human fibroblasts which exhibited extensive down-regulation of genes when seeded onto low adhesion surfaces, which reduced cell scattering . Following functional blockade of α5β1 integrin or stimulation with HGF/SF1, the most significantly up-regulated genes fell into the GO categories concerning response to external stimuli, biosynthesis and cell growth, and in particular genes involved in cell adhesion and migration. We also detected drastic changes in the expression of several members of the SWI/SNF family of chromatin remodeling complex. This consist of approximately ten ATP-dependent components and are thought to regulate genome function by altering the structure of chromatin .
One key question in cell biology is how cells reorganize their genome in response to mechanical conditioning. We detected that migration of MLP29 cells involved morphological changes, cytoskeleton reorganization, and nuclear architecture remodeling. The FISH analyses for the β1- and β3-integrin subunits revealed that the radial position of these genes within the interphase nucleus did not change. Meaburn and Misteli analyzed the radial distribution of four genes related to cell survival, mobility and migration, namely AKT1, VEGF, ERBB2, and FGFR1 in a cell-model of breast cancer. They found that, except for VEGF, the other loci underwent repositioning during tumorigenic differentiation . However, it has also been shown that positional changes of chromosome territories only occur transiently at the beginning of the G1 phase, and then arrangements are stably maintained from mid G1 to early prophase during cell cycle , Our results are in agreement with this, and are supported by the flow cytometric analysis of DNA content which showed that MLP29 cells did not progress through the G1 phase of the cell cycle after α5β1 functional blockade. Furthermore, Harnicarova and collaborators have reported that nuclear arrangement of the c-Myc gene and its transcripts was conserved during enterocitic differentiation of HT-29 cells . In contrast to this conserved spatial positioning of β1- and β3-integrin gene loci, FISH analysis with a pan-centromeric probe revealed that the average number of chromocenters per nucleus increased, while their mean volume decreased following α5β1 functional blockade and HGF/SF1 stimulation, indicating that the spatial distribution of individual centromeres changes in response to the forces generated during cell migration. In close agreement with these results, a study on the position of centromeres of human chromosomes 3, 11 and 16 showed that the distance between centromeres decreases when fibroblasts are seeded onto matrices resembling 3D structures, compared to flat 2D surfaces, which generate different tensile forces and activate distinct signaling cascades . We also found that during MLP29 cell migration, the volume of Me3K9H3 foci decreased concomitantly with an increase in their average number. These findings, although expected because Me3K9H3 localizes preferentially to pericentromeric heterochromatin, corroborate the data obtained by FISH with pan-centromeric probes demonstrating chromocenter disaggregation during cell scattering. It has been shown that progressive chromocenter clustering occurs during cell differentiation and that this is associated with increasing levels of DNA methylation . Our immunostaining assays with antibodies against Me3K9H3 showed that the nuclear fluorescent intensity level was the same after functional blockade of α5β1, suggesting that cell migration may occur without changes in the methylation status of histone H3. Most important, these experiments demonstrated that the architectural changes of chromocenters associated with this program are completely opposite to those leading to terminally differentiated or quiescent cells. Thus, it appears that cell scattering involves significant spatial reorganization of the heterochromatic blocks of the genome associated with substantial changes in the expression level of genes encoding for chromatin remodeling factors.
We provide evidence that the functional blockade of α5β1 integrin in hepatic progenitor cells induces cell scattering and cytoskeleton reorganization in a manner similar to stimulation with HGF/SF1. This process is accompanied by activation of the MAPK pathway and an increase in the expression levels of the early HCC markers, Ep-CAM, AFP and CK19. Gene expression arrays showed a massive change in the expression of chromatin remodeling and transcription factors. These functional changes of hepatic progenitor cells are associated with conspicuous structural reorganization of the cell nucleus.
Cell Culture and treatments
Mouse hepatic progenitor MLP29 and mouse HCC Hep16 cells were maintained in RPMI 1640 medium supplemented with 10% Fetal Bovine Serum (FBS) at 37°C in a humidified 5% CO2 atmosphere. For experiments, after cell plating, the old medium was replaced with fresh medium containing low FBS (0.1%) and the cells were maintained under this serum starvation condition for at least 16 hours. Then the cells were treated with 10 μg/ml of a specific function-blocking anti-α5β1 integrin antibody (clone BMB5) purchased from Chemicon-Millipore (Temecula, CA, USA) or 20 ng/ml of HGF/SF1. When appropriate, 20 μM of U0126 (ERK inhibitor) was used for 24 hours. Control experiments were carried out by adding equal amounts of DMSO, ethanol or an IgG control Ab.
Antibodies and reagents
MEK1 and MEK2 specific inhibitor U0126 was purchased from Calbiochem (San Diego, CA), dissolved in DMSO, and stored in the dark as a 10 mM stock solution at -20°C. The components of the ECM, fibronectin (FN) and vitronectin (VN) were purchased from Sigma (St Louis, MO), laminin (LMN) was purchased from Chemicon (Temecula, CA) and collagen type I (COL I) was purchased from BD Biosciences-Europe (Erembodegem, Belgium). hrHGF was purchased from Peprotech (Rocky Hills, NJ). Specific antibodies against β1 and β3 integrin subunits, CK19, Acetyl histone H3 (Lys9/14), and tri-Methyl histone H3 were purchased from Chemicon-Millipore (Temecula, CA), and E-Cadherin antibody was from R&D systems. Phospho p42/p44 MAPKinase antibody (Thr 202/Tyr204), total MAPKinase; phospho PKB/Akt (Ser 473) and total PKB/Akt antibodies were purchased from Cell Signaling Biotechnologies (Beverly, MA, USA). β-actin, Ep-CAM and AFP antibodies were purchased from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Pan-centromeric STAR-FISH™ probe were purchased from Cambio (Cambridge, UK).
Sub-cellular localization of β1 integrins, Ac3K9/k14H3, Me3K9H3 and phospho-ERKs was assessed by immunofluorescence. Briefly, the cells were fixed in 4% paraformaldehyde (w/v) in PBS, rinsed in TBS and then permeabilized in 0.5% TBS-Triton X-100 (T-TBS 0.5%) for 10 minutes at RT. After blocking with 2% BSA in TBS for 10 min at RT, the cells were incubated with the primary antibody for 1 hour at RT. The detection was performed with secondary antibodies conjugated to FITC or Texas Red. To study the actin cytoskeleton and morphological changes, the cells were stained with phalloidin conjugated to Texas-red. After exhaustive washings with cold TBS, the slides were mounted with Vectashield containing DAPI (Vector Laboratories, CA, USA). Images were acquired with an Olympus BX61 epifluorescence microscope or a Leica DMIRE-2 confocal microscope.
Flow cytometric evaluation of RGD-binding integrins
MLP29 hepatic progenitor and Hep16 HCC cells were seeded and allowed to attach for 24 hours. Cells were then harvested by scraping, subsequently counted, and then incubated with antibodies against the α5β1 heterodimer and β1 integrin subunit (3 μg/500 × 103 cells/100 μl) for 1 hour at 4°C. After that, cells were washed twice with cold PBS containing 1% FBS, and incubated with a CY2-conjugated secondary antibody for 30 minutes at 4°C. Cells were then analyzed in a FACScanto II flow cytometer (Becton Dickinson). FACS Diva software (Becton Dickinson) was used for data acquisition and analysis.
Flow cytometric analysis of Ac3K9/K14H3 and DNA content
MLP29 hepatic progenitor cells were treated with the α5β1 blocking antibody or HGF/SF1 for 6 hours, and then the cells were harvested. For Ac3K9/K14H3 detection, cells were fixed in 1% paraformaldehyde for 15 minutes and stored in 70% ethanol at -20°C. After fixation, cells were permeabilized with PBS-0.25% Triton X-100 for 10 minutes, washed with cold PBS-1% FBS and incubated with an anti-Ac3K9/K14H3 antibody for 2 hours at room temperature. Then, the samples were washed twice and incubated with a FITC-conjugated secondary antibody. For DNA staining, the cells were washed again and treated with RNAse A (0.2 mg/ml) in PBS at 37°C for 20 minutes. Propidium Iodide (20 μg/ml) was added to the cell suspension, and incubated 30 minutes at RT protected from light. FACSDiva software (Becton Dickinson) was used for data acquisition and analysis.
Cell adhesion studies
Cell adhesion was assessed by the MTT assay using the CellTiter 96® Non-Radioactive Cell Proliferation assay (Promega Corporation, WI). Briefly, MLP29 and Hep16 cells were seeded at 50 × 103 cells/well in 96-well plates coated with FN (10 μg/ml), VN (1 μg/ml), LMN (10 μg/ml), COL I (0.05 mg/ml) and BSA (0.2 mg/ml) as a control, and allowed to attach for 1 hour. After extensive washings, the medium was aspirated carefully and the dye solution added. After 3-5 hours of incubation, the reaction was stopped with the "Solubilization/Stop" buffer provided with the kit. Following overnight incubation at 37°C, absorbance at 570 nm was determined with a SpectraMax M2 plate reader (Molecular Devices, Sunnyvale, CA, USA).
Cell migration and cell invasion assays
To study cell migration we performed the wound healing assay. MLP29 and Hep16 cells were plated seeded on six wells plastic tissue culture dishes and grown to confluence. Then, the cell monolayer was scratched with a p200 pipette tip, washed twice, and incubated in growth medium with 0.1% FBS containing 10 μg/ml of α5β1 functional-blocking antibody or 40 ng/ml of HGF/SF1 for 20 hours. Microscope images were taken from at least three fields for each experiment. The distance covered by the migrating cells was calculated as the mean of six different measurements along the scratch using the Gimp 2.0 image software.
To assess cell invasion, we used the QCM™ 24 wells Cell Invasion Assay from Chemicon-Millipore (Temecula, CA, USA) according to manufacturer's instructions. Briefly, 500 × 103 MLP29 or Hep16 serum starved cells were loaded into an insert containing an eight μm pore size and polycarbonate membrane coated with ECMatrix™ in the presence of α5β1 functional-blocking antibody or HGF/SF1 at the concentrations stated above and incubated for 48 and 72 hours. Invaded cells at the bottom of the membrane were detached, lysed and detected by the CyQUANT™ GR Dye in a SpectraMax M2 plate reader (Molecular Devices, Sunnyvale, CA, USA).
Immunoblotting analysis of ERK1/ERK2 MAPK, p-ERK1-ERK2 MAPK, AKT, pAKT, integrin sub-units and histone acetylation
Cells were cultured in a serum free medium for 16-18 hours and then stimulated with HGF/SF1 or treated with α5β1 functional-blocking antibodies for up to 24 hours. After treatment, cells were harvested, washed twice in PBS, and lysed with the Cell Lysis Buffer (Cell Signaling Biotechnologies) and 1 mM phenylmethylsulfonylfluoride for 30 minutes on ice. The lysates were then cleared by centrifugation (14000 rpm for 15 minutes at 4°C). Protein concentration was determined using the Pierce protein assay kit (Rockford, IL, USA). For analysis of ERK1/2 MAPKs and Akt, equal amounts of protein (20 μg) were resuspended in 5× Laemli buffer (10 minutes at 100°C), resolved by electrophoresis on a 10% SDS-PAGE, and transferred onto nitrocellulose membranes (Amersham Biosciences). For analysis of histone H3 acetylation, 50 μg of protein was resolved on a 15% SDS-PAGE and transferred onto a nitrocellulose membrane. The membranes were then blocked with TBS-T (25 mM Tris-HCl, 150 mM NaCl (pH 7.5), and 0.05% Tween 20) containing 5% (w/v) non-fat dry milk and incubated overnight at 4°C with specific antibodies. After incubation, the membranes were washed in TBS-T, and HRP-conjugated anti-rabbit, anti-mouse or anti-goat antibodies were added for 1 hour as secondary antibodies. Immunodetection was performed using the Western Lighting chemiluminescence reagent from Perkin Elmer (Boston, MA, USA).
Fluorescent in Situ Hybridization (FISH)
Cells were fixed following protocols designed for the preservation of the three dimensional structure of the nuclei. For centromere analysis, the cells were fixed in 4% paraformaldehyde in PBS 0.3× (w/v) for 10 minutes and then permeabilized in PBS/Triton X-100 0.5% for 20 minutes at RT and transferred to 20% Glycerol/PBS. After 1 hour, the cells were further permeabilized by freezing and thawing cycles in liquid nitrogen. The probe was dissolved in 50%formamide/20% dextran-sulfate, denatured and incubated along with the denatured cell-targets in a humid chamber at 37°C overnight. For locus-specific 3D FISH, the fixation of the cells was performed according to the protocol described previously , with slight modifications. Briefly, the coverslips were fixed for 10 minutes in 4% paraformaldehyde in PBS (w/v). After permeabilization in 0.5% saponin (w/v) PBS/Triton X-100 0.5% (v/v) for 30 minutes, the slides were washed in PBS for 2 minutes at RT and treated with 0.1 N HCl for 20 minutes. Next, the cells were washed with PBS and 2 × SSC for 2 minutes, treated with RNAse A, transferred to 2 × SSC/50% formamide 0.1% NaAz and stored at 4°C. We used probes prepared with the BAC clones RP23-303A11 y RP23-343N12 specific for the Itgb1 or the Itgb3 genes, respectively. The probes were labeled by nick translation with dUTP conjugated with biotin (Roche) or digoxigenin (Roche). Before hybridization, the probes were pre-denatured at 80°C for 5 minutes, then denatured along with the target DNA at 75°C for 5 minutes and incubated at 37°C for 72 hours in a humified chamber. For the post-hybridization washings, the coverslips were immersed in 50% formamide/2 × SSC, 1 × SSC, and 4 × SSC/tween-20 0.1% (v/v) (4T) each for 5 minutes at 47°C. Following one more wash with 4T at RT, the coverslips were blocked with 3% BSA in 4T (wt/v), washed in 4T at RT for 5 minutes and incubated for 1 h with antibodies against biotin or digoxigenin in blocking solution. Then the coverslips were incubated with the respective secondary antibodies for 1 hour, washed twice with PBS for 5 minutes and mounted with Vectashield containing DAPI (Vector Laboratories, CA, USA).
Image acquisition and analysis
Stacks of images scanning the whole nucleus were acquired with an axial separation of 250 nm using a laser-scanning microscope Leica DM IRE2 (Leica Microsystems Heidelberg GmbH). For quantitative analysis of chromocenters and Me3K9H3 foci, regions of interest (ROI) including each nucleus were directly generated on the z-stack using the Volocity.4.3® software (Improvision, Image, Processing and Vision Company Limited) and then the intensity level, volume and center of mass of all objects contained within each ROI was automatically recorded. Between 500-1000 elements (chromocenters or Me3K9H3 foci) per treatment were analyzed. For statistical analysis, the "proportions test" was used to compare the average number of elements per nucleus for each treatment. For the comparison of mean volumes and mean fluorescence intensity, we applied the "t-student" test. Fluorescence intensity of Ac3K9/K14H3 was directly measured on the Z-stack using the Volocity.4.3® software (Improvision, Image, Processing and Vision Company Limited).
To determine the 3D radial position of any given signal, the shortest distance from the center of mass of the nucleus to the periphery, which included the center of mass of the fluorescent signal, was directly measured on the z-stack using the Volocity.4.3® software. The absolute distances from the nucleus center to the gene were normalized as a fraction of nuclear radius, to account for natural variations in nuclear size that may influence positioning. Cell nuclei were subdivided into five concentric shells each corresponding to 20% of the nuclear radius, and the radial positioning data was binned into these five sub-domains. Graphs were made using Microsoft Excel Software. For quantitative measurements, 50-70 nuclei from multiple experiments were analyzed. Statistical differences (p < 0.05) between the distributions of a gene in different conditions were determined using the 1D Kolmogorov-Smirnov test.
Microarray data acquisition and analysis
RNA was isolated from cell plates subjected to the different treatments using the RNAeasy Mini kit (Qiagen) and treated with RNAase-free DNAase (Qiagen). The cDNA was synthesized from 1 μg of RNA using the Reverse Transcriptase kit (Promega) following the manufacturer's recommendations. Expression profiling was performed using the Affimetrix GeneChip ® technology, following the protocols recommended by the manufacturers. Affymetrix raw files (.cel, Mouse430A_2) obtained from untreated control cells, treated with anti-α5β1 antibodies, and stimulated with HGF/SF1 were collectively analyzed by using the R package "AFFYLMGUI" (http://www.bioconductor.org) . Data were background corrected by the rma method . The p-values obtained by testing for differentially expressed genes were calculated using "AFFYLMGUI" and exported as text. Extraction of GO terms for all genes on the Mouse430A_2 chips was used for functional analysis. Hypergeometric p-values for testing over representation of genes in GO categories were calculated as described in Masseroli et al., and the p-values were corrected for multiple testing by the Holm method [26, 27]. The gene set enrichment analysis was done as described previously [28, 29]. The permutation statistics for the heat-plots were calculated for each gene set. This was done by considering the expression level for all genes of each set defined by Molecular Signatures Database. The p-values for the heat-plots were calculated as ndown/N for down-regulated genes and as 1-nup/N for up-regulated genes, where ndown is the number of times a permutated data set resulted in a down regulation that was stronger or equal to the one observed for the unpermutated data. nup was calculated in a similar way for up-regulated genes. N was the total number of permutation which was set to 10000. To assess if a specific gene set was up- or down-regulated for a specific sample class the expression values from a specific class were compared with the expression values in all other sample classes . The calculation of 1-nup/N for up-regulated gene sets allows co-plotting both up and down-regulated gene sets in the same heat-diagram. Mouse genes were mapped to human genes by using HomologGene available at NCBI. Microarray data is publicly available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23853, Gene Expression Omnibus (GEO) accession number GSE23853.
We would like to thank Dr. David Gisselsson for his critique of the manuscript. This work was supported by funding from Fondo de Investigación Sanitaria (ISCiii), Grant # 05/1117 to LAP; Department of Industry and Department of Health of the Basque Government. FR is a CIBERHED postdoctoral fellow associated with CIC bioGUNE.
- Boccaccio C, Comoglio PM: Invasive growth: a MET-driven genetic programme for cancer and stem cells. Nat Rev Cancer. 2006, 6 (8): 637-645. 10.1038/nrc1912.View ArticlePubMedGoogle Scholar
- Gentile A, Trusolino L, Comoglio PM: The Met tyrosine kinase receptor in development and cancer. Cancer Metastasis Rev. 2008, 27 (1): 85-94. 10.1007/s10555-007-9107-6.View ArticlePubMedGoogle Scholar
- Chan PC, Chen SY, Chen CH, Chen HC: Crosstalk between hepatocyte growth factor and integrin signaling pathways. J Biomed Sci. 2006, 13 (2): 215-223. 10.1007/s11373-005-9061-7.View ArticlePubMedGoogle Scholar
- Streuli CH: Integrins and cell-fate determination. J Cell Sci. 2009, 122 (Pt 2): 171-177. 10.1242/jcs.018945.PubMed CentralView ArticlePubMedGoogle Scholar
- Bertotti A, Comoglio PM, Trusolino L: Beta4 integrin is a transforming molecule that unleashes Met tyrosine kinase tumorigenesis. Cancer Res. 2005, 65 (23): 10674-10679. 10.1158/0008-5472.CAN-05-2827.View ArticlePubMedGoogle Scholar
- Trusolino L, Serini G, Cecchini G, Besati C, Ambesi-Impiombato FS, Marchisio PC, De Filippi R: Growth factor-dependent activation of alphavbeta3 integrin in normal epithelial cells: implications for tumor invasion. J Cell Biol. 1998, 142 (4): 1145-1156. 10.1083/jcb.142.4.1145.PubMed CentralView ArticlePubMedGoogle Scholar
- Parada LA, Sotiriou S, Misteli T: Spatial genome organization. Exp Cell Res. 2004, 296 (1): 64-70. 10.1016/j.yexcr.2004.03.013.View ArticlePubMedGoogle Scholar
- Royo F, Paz N, Espinosa L, McQueen PG, Vellon L, Parada LA: Spatial link between nucleoli and expression of the Zac1 gene. Chromosoma. 2009, 118 (6): 711-722. 10.1007/s00412-009-0229-1.PubMed CentralView ArticlePubMedGoogle Scholar
- Wiblin AE, Cui W, Clark AJ, Bickmore WA: Distinctive nuclear organisation of centromeres and regions involved in pluripotency in human embryonic stem cells. J Cell Sci. 2005, 118 (Pt 17): 3861-3868. 10.1242/jcs.02500.View ArticlePubMedGoogle Scholar
- Meaburn KJ, Misteli T: Locus-specific and activity-independent gene repositioning during early tumorigenesis. J Cell Biol. 2008, 180 (1): 39-50. 10.1083/jcb.200708204.PubMed CentralView ArticlePubMedGoogle Scholar
- Medico E, Mongiovi AM, Huff J, Jelinek MA, Follenzi A, Gaudino G, Parsons JT, Comoglio PM: The tyrosine kinase receptors Ron and Sea control "scattering" and morphogenesis of liver progenitor cells in vitro. Mol Biol Cell. 1996, 7 (4): 495-504.PubMed CentralView ArticlePubMedGoogle Scholar
- Ingber DE: Tensegrity II. How structural networks influence cellular information processing networks. J Cell Sci. 2003, 116 (Pt 8): 1397-1408. 10.1242/jcs.00360.View ArticlePubMedGoogle Scholar
- Alison MR, Murphy G, Leedham S: Stem cells and cancer: a deadly mix. Cell Tissue Res. 2008, 331 (1): 109-124. 10.1007/s00441-007-0510-7.View ArticlePubMedGoogle Scholar
- Wu R, Terry AV, Singh PB, Gilbert DM: Differential subnuclear localization and replication timing of histone H3 lysine 9 methylation states. Mol Biol Cell. 2005, 16 (6): 2872-2881. 10.1091/mbc.E04-11-0997.PubMed CentralView ArticlePubMedGoogle Scholar
- Gerlitz G, Livnat I, Ziv C, Yarden O, Bustin M, Reiner O: Migration cues induce chromatin alterations. Traffic. 2007, 8 (11): 1521-1529. 10.1111/j.1600-0854.2007.00638.x.View ArticlePubMedGoogle Scholar
- Huang C, Jacobson K, Schaller MD: MAP kinases and cell migration. J Cell Sci. 2004, 117 (Pt 20): 4619-4628. 10.1242/jcs.01481.View ArticlePubMedGoogle Scholar
- Kirkland SC, Ying H: Alpha2beta1 integrin regulates lineage commitment in multipotent human colorectal cancer cells. J Biol Chem. 2008, 283 (41): 27612-27619. 10.1074/jbc.M802932200.PubMed CentralView ArticlePubMedGoogle Scholar
- Trzpis M, Popa ER, McLaughlin PM, van Goor H, Timmer A, Bosman GW, de Leij LM, Harmsen MC: Spatial and temporal expression patterns of the epithelial cell adhesion molecule (EpCAM/EGP-2) in developing and adult kidneys. Nephron Exp Nephrol. 2007, 107 (4): e119-131. 10.1159/000111039.View ArticlePubMedGoogle Scholar
- Dalby MJ, Gadegaard N, Herzyk P, Sutherland D, Agheli H, Wilkinson CD, Curtis AS: Nanomechanotransduction and interphase nuclear organization influence on genomic control. J Cell Biochem. 2007, 102 (5): 1234-1244. 10.1002/jcb.21354.View ArticlePubMedGoogle Scholar
- Smith CL, Peterson CL: A conserved Swi2/Snf2 ATPase motif couples ATP hydrolysis to chromatin remodeling. Mol Cell Biol. 2005, 25 (14): 5880-5892. 10.1128/MCB.25.14.5880-5892.2005.PubMed CentralView ArticlePubMedGoogle Scholar
- Walter J, Schermelleh L, Cremer M, Tashiro S, Cremer T: Chromosome order in HeLa cells changes during mitosis and early G1, but is stably maintained during subsequent interphase stages. J Cell Biol. 2003, 160 (5): 685-697. 10.1083/jcb.200211103.PubMed CentralView ArticlePubMedGoogle Scholar
- Harnicarova A, Kozubek S, Pachernik J, Krejci J, Bartova E: Distinct nuclear arrangement of active and inactive c-myc genes in control and differentiated colon carcinoma cells. Exp Cell Res. 2006, 312 (20): 4019-4035. 10.1016/j.yexcr.2006.09.007.View ArticlePubMedGoogle Scholar
- Brero A, Easwaran HP, Nowak D, Grunewald I, Cremer T, Leonhardt H, Cardoso MC: Methyl CpG-binding proteins induce large-scale chromatin reorganization during terminal differentiation. J Cell Biol. 2005, 169 (5): 733-743. 10.1083/jcb.200502062.PubMed CentralView ArticlePubMedGoogle Scholar
- Wettenhall JM, Simpson KM, Satterley K, Smyth GK: affylmGUI: a graphical user interface for linear modeling of single channel microarray data. Bioinformatics. 2006, 22 (7): 897-899. 10.1093/bioinformatics/btl025.View ArticlePubMedGoogle Scholar
- Bolstad BM, Irizarry RA, Astrand M, Speed TP: A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003, 19 (2): 185-193. 10.1093/bioinformatics/19.2.185.View ArticlePubMedGoogle Scholar
- Masseroli M, Martucci D, Pinciroli F: GFINDer: Genome Function INtegrated Discoverer through dynamic annotation, statistical analysis, and mining. Nucleic Acids Res. 2004, W293-300. 10.1093/nar/gkh432. 32 Web ServerGoogle Scholar
- Holm S: A simple sequentially rejective multiple test procedure. Scand J Stat. 1979, 6: 65-70.Google 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 (3): 267-273. 10.1038/ng1180.View ArticlePubMedGoogle Scholar
- Virtaneva K, Wright FA, Tanner SM, Yuan B, Lemon WJ, Caligiuri MA, Bloomfield CD, de La Chapelle A, Krahe R: Expression profiling reveals fundamental biological differences in acute myeloid leukemia with isolated trisomy 8 and normal cytogenetics. Proc Natl Acad Sci USA. 2001, 98 (3): 1124-1129. 10.1073/pnas.98.3.1124.PubMed CentralView ArticlePubMedGoogle Scholar
- Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES: Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005, 102 (43): 15545-15550. 10.1073/pnas.0506580102.PubMed CentralView ArticlePubMedGoogle Scholar
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