TNFα-senescence initiates a STAT-dependent positive feedback loop, leading to a sustained interferon signature, DNA damage, and cytokine secretion

TNFα induces senescence in HUVECs with continually elevated ROS levels and DNA damage

To determine the long term effects of the pro-inflammatory cytokine TNFα on endothelial cells, HUVECs were chronically exposed to medium alone or different concentrations of TNFα. Cells exposed to TNFα exhibited a dose- and time-dependent decrease in proliferative rate, as apparent from a linear decrease in population doublings with an increase in doubling time (Fig. 1A, Fig. S1A). Cell cycle analysis revealed prolonged exposure to TNFα significantly impaired proliferation of cells, as evidenced by progressive decline in abundance of BrdU-incorporating cells (Fig.1B) accompanied by a decreased percentage of S-phase and increased G1/G2-phase cells compared to control (Fig. S1B), indicating proliferative arrest. Cells exposed to TNFα also developed classic senescent phenotypes, including a flattened, multi-nucleated, giant cell morphology (Fig. S1C), and concomitantly in-creased expression of senescence markers, including p16, p21, and cellular SA-β-gal activity (Figs. 1C, 1D, 1E). At a higher concentration, TNFα (20ng/ml) decreased cell proliferation at 3 days and increased senescence markers at 3 and 6 days of treatment (Fig. S1D, E), whereas cells exposed to a lower concentration (5ng/ml) reached senescence at about 26 days of exposure.

Figure 1. TNFα induces senescence and DNA damage in HUVECs. (A) Long-term growth curve of cells exposed to recombinant human TNFα (5ng/ml). Untreated cells were used as controls. Population doubling and doubling times were calculated based on cell density at confluence. Data represent mean values from 3 independent experiments. (B) The percentage of BrdU-positive cells was determined by FACS analysis in cells untreated or chronically treated with TNFα at the concentration indicated. (C) Western blot analysis of p21, p16, and actin in cells treated with TNFα 5ng/ml for the indicated times. (D) SA-β-gal activity in TNFα (5ng/ml)-treated or control cells for the indicated number of days. (E) Percentages of SA-β-gal-positive cells in control or TNFα-treated cultures. The data represent 2 independent counts of 200 cells from 3 independent experiments. (F) Intracellular ROS levels were monitored by 2',7’-dichlorodihydrofluorescein diacetate staining followed by flow cytometry. Bar graph represents percentage of DCFDA-positive cells treated with TNFα or medium alone. (G) Immunofluorescence detection of γH2AX foci in controls or cells treated with TNFα (5ng/ml) for indicated days. Data in A, B, E, and F represent mean value ± standard deviation (s.d.) from n=3, 2, 3, and 2 independent experiments, respectively.

Increased intracellular ROS and activation of DNA damage responses are linked mediators of senescence [4,41,42]. To delineate the interaction of DNA damage response signals in TNFα-induced senescence, we measured both ROS and DNA damage foci. TNFα-stimulated cells had a robust increase in ROS levels, which subsequently remained elevated (Fig. 1F). Cells exposed to TNFα formed multiple γH2AX foci, a marker of DNA damage, compared to untreated cells (Fig. 1G). Elevated ROS and γH2AX foci were apparent beginning from 24 hours of stimulation and persisted throughout the subsequent period of exposure. The above results demonstrate that TNFα promotes senescence in endothelial cells, accompanied by persistent DNA damage and increased ROS levels.

Network of inflammatory and SASP gene expression during TNFα-induced senescence

To explore the molecular background and genes altered during TNFα-induced senescence, we analyzed gene expression profiles of cells made senescent by TNFα vs. controls. A total of 238 genes was differentially upregulated in TNFα-induced senescence compared to control or non-senescent cells. A list of 78 genes upregulated during TNFα-senescence was selected based on the criteria of adjusted p-value <0.05 and fold change (FC) cut-offs of >1.5. These genes were grouped according to function (Table 1). To identify the biological functions and canonical pathways differentially expressed during TNFα-mediated senes-cence, a gene data set that met the above criteria was exported to the Ingenuity Pathway Analysis (IPA) system. Canonical pathways generated from IPA analysis included NF-kB, p38 MAPK, JAK/STAT, p53, and cytokine-chemokine signaling (Fig 2A). This indicates that molecular crosstalk among diverse signaling pathways occurs during TNFα-induced senescence.

Figure 2. Top canonical pathways identified by IPA analysis in TNFα-induced senescence. (A) Bar chart represents the top canonical signaling pathways that were influenced during TNFα-induced senescence. p-values were determined using Fisher´s exact test with a threshold value of >0.05. Ratios represent the number of genes that mapped to a specific canonical pathway divided by the total number of genes that make up the respective pathway. (B) Relative mRNA expression of SASP components in cells treated with TNFα at 6, 16, or 26 days compared to untreated cells. (C) Relative mRNA expression of p16 and p21 in cells treated with TNFα (5ng/ml) compared to untreated cells. Results are mean ± standard deviation of n=2 independent experiments.

Expression of several inflammatory cytokines, chemokines, interleukins, and their receptors was significantly upregulated during TNFα-induced senescence (Table 1), including the cytokines, IL8, IL6, IL1α, IL1β, and IL32 and the chemokines, CXCL1, CXCL2, CXCL5, CXCL6, CXCL10, CXCL11, CCL2, CCL5, and CCL20. Gene products were organized into an interactome network using IPA (Fig. S2). To validate our microarray data, mRNA expression of selected genes (IL6, IL8, IL1α, IL1β, and CCL2/MCP1) and senescence markers (p21 and p16) was assessed by real time PCR (Figs. 2B & 2C). Our findings indicate that senescence established by TNFα leads to an inflammatory signature involving upregulation of genes associated with the secretory pattern of senescent cells.

Sustained expression of interferon response genes

Among the top scored canonical pathways generated by IPA, the interferon signature was identified as the most prominent gene cluster, involving about 30 of both type I and type II interferon response genes (Table 1). These genes included MX1, ISG15, PSMB9, TAP1, STAT1, three guanylate-binding proteins (GBP1, GBP4, and GBP5), and three 2´5´-oligoadenylate synthetases (OAS1, OAS2, and OAS3). As shown in Fig. S3, the interferon network included several interferon response genes (IFIH1, IFIT5, IFI6, IFI27, IFI30, IFI35, IFI44, IFI44L, DDX58 [RIG-1], and MDA-5) and the p53 target genes, ISG15, and SP110. Several of these genes, including IFI27, IFITM1, IRF1, STAT1, IF16, and TAP1, are known to possess potent anti-proliferative and tumor suppressive properties. Importantly, canonical activation of the JAK/STAT pathway suggests that the transcription factor STAT1 acts as important transcription factor for many of the interferon response genes (Fig. 3). Overall, gene expression analysis reveals a strong and sustained interferon signature during TNFα-induced senescence.

Figure 3. Activation of the canonical JAK/ STAT pathway. Pathway analysis using IPA reveals canonical activation of STAT1 acts as a central regulator for JAK/ STAT-mediated interferon response genes during TNFα-induced senescence. The red symbols represent up-regulated genes, with the intensity of node color indicating degree of up-regulation and white indicating genes absent from the list. Shape of nodes denotes functions of gene products.

Persistent activation of JAK/STAT signaling in TNFα-induced senescence

Gene expression profiling and IPA analysis revealed that the interferon signature and JAK/STAT signaling pathway were preferentially activated and remained sustained during TNFα-mediated senescence. To address the role of the JAK/STAT pathway in TNFα-induced senescence, we examined the long-term kinetics of STAT activation. The abundance of serine-phosphorylated STAT1 in cells undergoing senescence due to TNFα was sustained at day 3 and remained elevated at day 6, concomitant with the establishment of senescence (Figs. 4A & B). Next we measured early kinetics of STAT1 and STAT3 phosphorylation in response to TNFα. Serine phosphorylation of STAT1 at position 727 in cells exposed to TNFα was detected by 30 minutes, while tyrosine phosphorylation of STAT3 at position 705 was observed at 6 hours (Fig. 4C), indicating a time-dependent phosphorylation pattern. Treatment with IFNγ mediated STAT1 phosphorylation at 30 minutes while IL-6 induced STAT3 phosphorylation peaked within 10 minutes and later declined (Fig. 4D). These observations suggest that IL-6 induces a direct and transient activation of STAT3 whereas TNFα-mediated STAT3 expression is delayed, indirect, and sustained. As autocrine/paracrine signaling of several cytokines can promote STAT activation, we next analyzed secretion of the major STAT activating ligands, IL6 and IFNγ, in cells senesced by TNFα exposure. Analysis of supernatants collected from cells incubated with TNFα showed a marked increase in secretion of both IL6 and IFNγ compared to control (Fig. 4E). To confirm the involvement of secreted cytokines, we tested the ability of medium conditioned by TNFα to induce STAT activation using supernatants (diluted 1:4 with fresh culture medium) from cultures of control cells or cells stimulated with TNFα for 3 days. Figure 4F shows that the phosphorylated forms of STAT1 and STAT3 peaked early and then slowly decayed in cells treated with conditioned medium compared to control. Unlike the acute and transient response after exposure to either IL6 or conditioned medium, TNFα-induced STAT1/3 activation was chronic and prolonged, coinciding with the development of senescence and the SASP. Furthermore, chronic treatment with recombinant IL6 or conditioned medium containing SASP factors collected from senescent cells failed to induce senescence (Fig. S4A & B), indicating that prolonged activation of the JAK/STAT pathway by TNFα plays a crucial role in stabilizing and retaining the senescent state.

Figure 4. Prolonged activation of JAK/ STAT signaling in TNFα-induced senescence. (A) Immunoblot detection of p-Ser727-STAT1 and total STAT1 in cells exposed to TNFα 20ng/ml for the indicated times. (B) SA-β-gal activity in TNFα (20ng/ml)-treated or control cells for 3 or 6 days. (C) Immunoblot detection of p-Ser727-STAT1, total STAT1, p-Tyr705-STAT3, and total STAT3 in cells exposed to TNFα (5ng/ml) for the indicated intervals. (D) Immunoblot detection of pSTAT1, total STAT1, pSTAT3, and total STAT3 in cells stimulated with IL6 (10ng/ml) or IFNγ (1ng/ml) for the indicated intervals. (E) Secretion of IFNγ/IL6 quantified by ELISA in conditioned medium collected in the presence or absence of TNFα. (F) Immunoblot detection of p-Ser727-STAT1, p-Tyr705-STAT3, STAT1, and STAT3 in cells treated with conditioned medium (CM) (cell free-culture supernatants from control and cells stimulated with TNFα for 3 days transferred after 1:4 dilution with fresh culture medium) from TNFα-induced senescent cells or from non-senescent cells for the indicated times

TNFα initiates a positive feedback loop via sustained STAT1/3 activation

The above results suggest that sustained and prolonged activation of JAK/ STAT1/3 signaling could play a crucial role in the TNFα-mediated senescent state. This speculation prompted us to question if prolonged activation of STAT1/3 might be involved in developing a positive feedback loop to sustain the inflammatory network. To address this, we examined the post-stimulation effects of TNFα on endothelial cells. Cells were cultured in medium alone or with TNFα for 3 days to induce senescence. Thereafter, cells were washed and cultured in the absence of TNFα for 3 days (post-stimulated, TNFα-PST). Surprisingly, immunoblot analysis showed that phosphorylation of both STAT1 and STAT3 persisted for days in cells senesced by TNFα, even after withdrawal of exogenous TNFα, or in cells that were continuously exposed to TNFα when com-pared to control (Fig. 5A). In contrast, rapid and transient activation of STAT3 was observed in cells treated with IL6 (Fig. 4D), suggesting that primary signals from TNFα specifically contribute to persistent activation of STAT.

Figure 5. Persistent activation of STAT1/3. Cells were exposed to TNFα (20ng/ml) for 3 days, then washed to remove the residual TNFα and cultured for 3 days in the absence of exogenous TNFα (TNFα-PST). Parallel cultures were exposed to exogenous TNFα throughout the experiment. (A) Levels of p-Ser727-STAT1, p-Tyr705-STAT3, and total STAT3 proteins were quantified by immunoblot. (B) Secretion of IL-6/IFNγ was assessed in culture supernatants from cells treated with TNFα as indicated. (C) Immunodetection of ROS production and γH2AX foci in control or cells treated with TNFα or TNFα-post-stimulated (PST), as indicated. (D) Real-time gene expression of IRF1 and MX1 in cells exposed to TNFα or TNFα-PST for 3 days. Results were normalized to internal control TBP and are shown relative to untreated cells. (E) SA-β-gal activity in TNFα-treated cells for 3 days or in cells treated with TNFα (20ng/ml) for three days, then washed to remove residual TNFα and left untreated for another 3 days. (F) mRNA expression of p21 and p16 quantified by real-time PCR in cells exposed to TNFα or TNFα-PST for 3 days. Data in D and F represent mean value of ± sd from 2 independent experiments.

To verify the relationship between sustained STAT1/3 activation and development of inflammation and increased ROS levels, we assessed secretion of IL6, IFNγ, and ROS production after withdrawal of exogenous TNFα. Supernatants showed increased secretion of both IL6 and IFNγ in TNFα- treated and TNFα withdrawn cells compared to control, indicating that effects of TNFα are sustained and irreversible (Fig. 5B). Similarly, increased ROS and γH2AX DNA damage foci were found to persist in TNFα-induced senescent cells for days even after removal of the exogenous TNFα (Fig. 5C). These results suggest that prolonged activation of STAT1/3 stimulates a positive auto-regulatory loop via an IL6/IFNγ axis, promoting sustained secretion of inflammatory cytokines and ROS production in TNFα-induced senescence.

Although STAT1 is a key mediator of IFN-dependent biological responses, most of the interferon response genes regulated by STAT1 require cooperative action of other transcription factors, such as IRF1 [43]. IRF1 is known to synergize with TNFα signals to drive the production of type I interferons [44]. Considering the possible involvement of STAT1 and IRF1 interactions in the TNFα-induced interferon signature, we examined expression of IRF1 and the interferon response gene MX1. We detected increased and sustained expression of IRF1 and MX1, even 3 days after cessation of TNFα exposure (Fig. 5D), accompanied by sustained expression of senescence markers (Figs. 5E, 5F). These results suggest persistent STAT activation establishes a positive feedback loop promoting a sustained interferon signature and cytokine secretion.

STAT1/3 activity is required for senescence-associated inflammation and ROS production, while inhibition of STAT modulates TNFα-induced senescence

To explore the functional role of the JAK/STAT pathway in TNFα-mediated senescence, we inhibited JAK2 receptor kinase using the inhibitor AG-490. As shown in Fig. 6A, pretreatment with AG-490 blunted TNFα-induced activation of both STAT1 and STAT3. Importantly, inhibition of JAK markedly decreased TNFα-induced secretion of both IL6 and ROS (Figs. 6B & 6C), indicating a requirement for STAT1/3 activity in TNFα-mediated inflammatory and DNA damage responses. Conversely, treatment with AG490 alone decreased the percentage of BrdU-incorporating cells, inhibited S phase entry, and resulted in cell cycle arrest (Fig. 6D). The presence of both TNFα and AG-490 decreased proliferation and increased SA-β-gal-positive cells compared to TNFα alone (Fig. 6E). Since the STAT pathway is involved in a wide range of cellular processes including proliferation, apoptosis, and differentiation, we tested if cells treated with AG-490 undergo senescence. Surprisingly, inhibition of STAT1/3 by AG-490 increased expression of senescence markers, including SA-β-gal and p21, whereas expression of cell cycle regulatory genes, such as CDK2 and NDC80, were decreased (Fig. 6F). Similar results were seen using the STAT3 inhibitor curcubitacin (data not shown). As p38MAPK (p38) activation plays a significant role in TNFα signaling and senescence, we also examined the role of p38. Chemical inhibition of p38 activation using SB203580 (SB) rescued cells not only from senescence, but also diminished TNFα-induced IL-6 secretion and ROS (Fig. S5A & B, & C). Furthermore, inhibition of p38 activation attenuated phosphorylation of STAT1, indicating that p38 acts as an upstream regulator of STAT1 and thus its activation requires p38 signals (Fig. S5D). These results indicate that a STAT1/3 pathway plays a dual in role in modulating TNFα-mediated senescence. On the one hand, this pathway is required for promoting TNFα-induced inflammatory and damage responses. On the other, interfering with STAT signaling itself accelerates senescence.

Figure 6. JAK2 inhibitor decreases TNFα-mediated inflammation, ROS levels, and interferon signature. Cells were exposed to TNFα alone, TNFα in combination with AG490 (30μM), or AG490 alone for 3 days. (A) Immunoblot detection of p-Ser727-STAT1, p-Tyr705-STAT3, and total STAT1 and STAT3. (B) Secretion of IL6 was estimated by ELISA in culture supernatants from cells treated with TNFα alone, or in combination with AG490, or AG490 alone for 3 days. (C) FACS analysis of ROS levels in cells stimulated either with TNFα, TNFα along with AG490, or AG490 alone for 3 days using DCFDA staining 2',7’-dichlorofluorescein (DCF) positive cells were analyzed. Inhibition of STAT signals modulates senescence. (D) Cell cycle analysis using BrdU and 7- aminoactinomycin D (7-AAD) staining in cells exposed to TNFα, TNFα in combination with AG490, or AG490 alone for 3 days. (E) Percentage of SA-β-gal-positive cells. Quantification of SA-β-gal activity in cells stimulated with TNFα 20ng/ml, TNFα in combination with AG490, or AG490 alone for 3 days. The data represent means of 3 independent counts of 200 cells from 2 independent experiments. (F) Effect of AG490 on cell cycle regulatory proteins. Western analysis performed using cells treated with AG490 for 3 days and blotted against anti-p21, CDK2, and NDC80. Actin serves as loading control.

Reagents and antibodies

Recombinant human TNFα, IL6, and IFNγ were purchased from Bionova (Madrid, Spain), AG490 from Calbiochem (Darmstadt, Germany), antibodies against pSTAT1Ser727, pSTAT3Ser705, STAT1, STAT3, and p-p38 from Cell Signaling (Danvers, MA, USA), monoclonal antibodies against p21 and p16 from Thermo Scientific (Fremont, CA, USA), γH2AX from Millipore (Billerica, MA, USA), anti-CDK2 from Abcam (Cambridge, MA, USA), anti-NDC80 from BD Biosciences (San Diego, CA, USA), anti-actin, and anti-β-tubulin from Sigma (St Louis, MS, USA), and anti-human CD54 (ICAM-1) and anti-human CD106 (VCAM) from BD Biosciences.

Cell culture

Human umbilical vein endothelial cells (HUVECs) purchased from Clonetics/Lonza (Basel, Switzerland) were grown in EGM-2 medium supplemented with growth factors (EGM-2 bullet kit; Clonetics/Lonza). Monolayer HUVECs were maintained in 25cm2 or 75cm2 tissue culture flasks or 100mm tissue culture plates at 37ºC in a humidified incubator with 5% CO2 and 95% air.

Induction of senescence and long-term growth curves

To induce TNFα-mediated senescence, HUVECs were continuously cultured in the presence or absence of recombinant human TNFα for the indicated periods. Culture medium was changed every other day with new TNFα. Stimulation with TNFα resulted in dose- and time-dependent induction of senescence in endothelial cells. With increasing concentration, TNFα at (20ng/ml) triggered senescence by 3 days of treatment, whereas cells treated with 5ng/ml of TNFα entered senescence at about 26 days (Fig. 1A). Growth curves were plotted by determining cell numbers at the end of each passage in TNFα-treated and -untreated cells. Population doublings (PD) were calculated using the formula PD = (lg [number of cells harvested] – lg [number of cells seeded]) / lg2 [69]. Population doubling time (PDT) was obtained by the formula PDT = tlg2/ (lg [number of cells harvested] – lg [number of cells seeded]), where t is the time of the culture (in hours). In all experiments, early passage HUVECs were used to start (p2-p3).

Experimental design for microarray analysis

To determine the long-term and sustained gene expression changes in senescence driven by TNFα, we compared expression profiles of cells chronically cultured in the presence or absence of 5ng/ml TNFα for 26 days. For the TNFα-treated group, we chose day 26 as the relevant time point, since population doubling times and morphological changes indicated the cells had achieved permanent growth arrest or were senescent. Three independently cultured samples for each experi-mental group of cells made senescent by TNFα were compared with corresponding passaged cells from the untreated control group.

RNA isolation and gene expression analysis

Total RNA was extracted from sub-confluent cultures from the above-mentioned experimental groups using tri-reagent and stored at -80ºC until processed.

Changes in gene transcription were analyzed by hybridization to Affymetrix arrays.

Three biological replicates from each experimental time point were analyzed using the Affymetrix Human Gene Chip® Gene 1.0 ST Array System. The Human Gene Chip® Gene 1.0 ST array interrogates 28,869 well-annotated genes with 764,885 distinct probe sets. The microarray data were deposited to the GEO database (accession number GSE98081).

Data analysis, identification of networks and canonical pathways

Array data were normalized and summarized with RMA software. Gene filtering, pair-wise comparisons, t-tests, and PCA were obtained using Bio-conductor packages http://www.bioconductor.org [70] based on the R package http://www.rproject.org [71]. Genes that were differentially expressed by 1.5-fold or more and with an adjusted P value of p<0.05 were analyzed. Data lists of all the genes that satisfied these criteria were analyzed by Ingenuity Pathway Analysis (IPA) software (Ingenuity® Systems, Redwood City, CA, USA) http://www.ingenuity.com. In order to identify func-tional modules involved in responses to the compared stimuli, genome-wide interactions, networks, and canonical pathways were generated using IPA.

BrdU incorporation

BrdU incorporation was measured using a BrdU Flow Kit (BD Biosciences) following the manufacturer´s protocol with modifications. BrdU was added to culture medium at a final concentration of 10μM. Six hours after addition of BrdU, cells were harvested, washed once with 1x phosphate-buffered saline, and fixed in 100μl of Cytofix/Cytoperm for 30 minutes at room temperature. After DNase treatment, BrdU-incorporated cells were then stained with FITC-conjugated anti-BrdU antibody and 7-aminoactinomycin D. Cell cycle profiles were analyzed using a FACS caliber flow cyto-meter (BD Biosciences). Data analysis was performed using FCS express software.

Senescence-associated β-galactosidase assay (SA-β-gal)

SA-β-gal activity was detected as described previously [11] using a senescence staining kit according to the manufacturer’s recommendations (Sigma). Stained cells were then visualized and photographed with a Nikon microscope. The percentage of cells positive for SA-β-gal was determined in duplicate in 200 cells per sample.

Cytokine secretion

Supernatants from cell cultures were collected on different days of incubation and stored at -80°C until used. Concentrations of IL6 and IFN-gamma (IFNγ) secreted in supernatants were quantified using a comer-cial ELISA kit according to the manufacturer’s instructions (OptEIA; BD Biosciences, San Diego CA, USA).

Western blots

Western blot analysis was performed by eluting whole cell-lysates using 2x Laemmeli sample buffer followed by sonication of samples for 10 seconds. Samples were resolved in SDS-PAGE. Proteins were then transferred onto nitrocellulose membranes. Blocked membranes were incubated with the indicated antibodies. Immuno-reactive bands were developed using supersignal Western substrate (Immobilon, Millipore) and visualized on AGFA (CP-BU) films following auto-mated development.

ROS production

Cells were stimulated with TNFα or medium alone for the indicated times and labeled with 10μM of 2',7’-dichlorodihydrofluorescein diacetate (H2DCFDA; Molecular Probes, Carlsbad, CA, USA) for 30 minutes at 370C. Intracellular ROS levels in labeled cells were assessed using a Becton Dickinson FACS Caliber flow scan.

Indirect immunofluorescence

For indirect immunofluorescence, cells grown on coverslips were fixed with 3% formaldehyde in PBS at room temperature for 10 minutes, blocked with 10% fetal bovine serum in PBS for 30 minutes, and permeabilized with 0.2% Triton X-100, 3% BSA in PBS for 30 minutes. Cells were then incubated with primary antibody against anti-phospho-gamma H2AX (Millipore) for 1 hour and stained with Alexa Fluor 488- (DAKO, Carpinteria, CA, USA) conjugated secondary antibody for 30 minutes. DNA was counter-stained with DAPI to visualize nuclei.

Real-time PCR

cDNA was synthesized using a high capacity cDNA reverse transcription kit from Applied Biosystems. Quantitative real time PCR reactions were performed with 1x Taqman universal PCR master mix (Applied Biosystems) in a MicroAmp optical 96-well reaction plate. All reactions were done in triplicate using two dilutions (1/500, 1/1000) each in 20µl reaction mix consisting of 9µl of cDNA, 1µM of each primer, and 10µl Taqman mastermix. The plates were then covered tightly with an optical adhesive cover and centrifuged at 1400 x g for 30 seconds at 4°C. PCR reactions were run on an ABI Prism 7500 (Applied Biosystems) and results were analyzed using the same software. Probes and primers were purchased from Life Technologies. Relative gene expression levels were normalized to GAPDH/TBP.