Substantial changes in gene expression of Wnt, MAPK and TNF
pathways induced by TGF-ß1 in cervical cancer cell lines
Judith N. Kloth *,
Gert Jan Fleuren,
Jan Oosting,
Renee X. de Menezes 1,
Paul H.C. Eilers 1,
Gemma G. Kenter 2 and
Arko Gorter
Department of Pathology, 1 Department of Medical Statistics and 2 Department of Gynecology, Leiden University Medical Center, Leiden, The Netherlands
* To whom correspondence should be addressed. Tel: +31 71 526 65 96; Fax: +31 71 524 81 58; Email: J.N.Kloth{at}lumc.nl
 |
Abstract
|
---|
Transforming growth factor-beta 1 (TGF-ß1) is a potent inhibitor of epithelial cell proliferation. During the development of cervical carcinoma however, an increase in production of TGF-ß1 is accompanied by decreased sensitivity for the growth-limiting effect of TGF-ß1. TGF-ß1 has an anti-proliferative effect on cells of the immune system and thus can be advantageous for tumor progression. The aim of the present study was to determine the effect of TGF-ß1 on mRNA expression profile of genes in pathways involved in cell growth and cell death, in cervical carcinoma cell lines with different sensitivity to TGF-ß1. For this purpose, we have investigated changes in gene expression in TGF-ß1 stimulated cervical cancer cell lines with high (CC10B), intermediate (SiHa) and low (HeLa) sensitivity to the anti-proliferative effect of TGF-ß1, at timepoints 0, 6, 12 and 24 h. Microarray analysis, using Affymetrics focus arrays, representing 8973 genes, was used to measure gene expression. In our study novel target genes involved in tumor necrosis factor alpha (TNF
), mitogen-activated protein kinase (MAPK) and wingless type (Wnt) pathways in response to TGF-ß1 were found. Substantial differences in gene expression between TGF-ß1 sensitive and insensitive cell lines were observed involving genes in TNF
, MAPK, Wnt and Smad pathways. Since these pathways are implicated in cell proliferation and cell death, these pathways may play a role in determining the overall sensitivity of a cell to TGF-ß1 induced cell growth inhibition. The results were subsequently validated by quantitative real-time PCR. Increased resistance to TGF-ß1 induced cell growth inhibition was correlated with an elevated production of TGF-ß1 by the cell lines, as measured by enzyme linked immunosorbent assay. TGF-ß1 production did not inhibit cell growth, since blocking TGF-ß1 protein by anti-TGF-ß had no effect on cell proliferation. TGF-ß1 excretion by tumor cells more likely contributes to paracrine stimulation of tumor development.
Abbreviations: AffyPLM, Affy-Probe Level Model; CDK, cyclin dependent kinase; ECM, extracellular matrix; EGF, epidermal growth factor; EMT, epithelial to mesenchym transition; ERK, extracellular response kinase; FGF, fibroblast growth factor; GO, gene ontology; IFN
, interferon
; MAPK, mitogen-activated protein kinases; NF
B, nuclear factor kappa B; PI3K, phosphatidylinositol-3 kinase; QRTPCR, quantitative real-time PCR; RMA, Robust Multi-Chip Average; SAPK, stress activated protein kinase; SSCG, statistically significant changes in gene expression; TGF-ß1, transforming growth factor ß1; TNF
, tumor necrosis factor
; Wnt, wingless type
 |
Introduction
|
---|
Transforming growth factor-beta 1 (TGF-ß1) plays an essential role in cellular processes such as proliferation, differentiation, embryonic development, angiogenesis, wound healing and inhibition of epithelial cell growth. During cancer development, however, the majority of tumor cells become either partly or completely resistant to TGF-ß1 growth inhibition and TGF-ß1-induced apoptotic responses (1,2). In cervical carcinoma, extracellular levels of TGF-ß1 are increased in late stage of malignancy (3,4), thereby contributing to invasion, metastasis and inhibition of host-tumor immune responses (57).
Defective TGF-ß1 signaling, due to inactivating mutations of TGF-ß receptors and Smad signaling molecules, has been reported in cervical carcinoma (8,9). However, only a few cervical cancers showed mutations in TGF-ß receptors or Smad (10,11) and this does not explain the loss of growth inhibition in the majority of cervical cancers.
Hence, other mechanisms, besides functional loss of TGF-ß receptor I, TGF-ß receptor II and Smad, are likely to exist. In different types of cancers, a defect in the TGF-ß1 pathway downstream of Smad signaling has been suggested (12) and crosstalk of TGF-ß1Smad signaling with other pathways have been demonstrated (13,14). Mitogen-activated protein kinases (MAPK), phosphatidylinositol-3 kinase (PI3K) and Rho signaling via TGF-ß1, with or without crosstalk with Smad signaling, have shown to be involved in the inhibition of apoptosis in cancer cells, invasion and metastatic processes (13,15). In addition, crosstalk between TGF-ß1 and wingless type (Wnt) (16,17), tumor necrosis factor
(TNF
) (18), interferon
(IFN
) (19) and epidermal growth factor (EGF) (20) have been demonstrated, which may influence tumorigenesis. This suggests that differential regulation of TGF-ß1 signaling, other than attenuation of TGF-ß1Smad signaling by reduced expression or functional loss of Smad pathway components, may determine the magnitude of the TGF-ß1 response.
Only a few studies investigated large-scale gene expression changes after stimulation with TGF-ß1 in cancer cells. These studies focused primarily on epithelial to mesenchym transition (EMT) processes and did not address loss of cell growth inhibition (21,22). The aim of the present study was to determine the effect of TGF-ß1 on mRNA expression profile of genes in pathways involved in cell growth and cell death, in cervical carcinoma cell lines with different sensitivity to TGF-ß1. For this purpose we used cDNA microarrays to measure differences in gene expression between cervical cancer cell lines with low (HeLa), intermediate (SiHa) and high (CC10B) sensitivity to TGF-ß1.
 |
Materials and methods
|
---|
Cell lines and cultures
Human cervical cancer cell lines, HeLa, SiHa (ATCC, Rockville, MD) and CC10B (23) were maintained in RPMI 1640 (Life Technologies, Grand Island, NY), supplemented with 10% fetal calf serum (FCS), streptomycin and penicillin at 37°C in a humid atmosphere containing 5% CO2.
Growth inhibition study
Cells were plated onto 24-well plates (Greiner, Frickenhausen, Germany) at a density of 35 x 103 cells/well in 0.5 ml culture medium. The following day, cells were incubated with different amounts of human recombinant TGF-ß1 ranging from 0.00011 ng/ml (Sigma, Saint Louis, MO). Each day recombinant TGF-ß1 was added to the cells over a period of 6 days. Cells were counted every second day in triplicate using a CASY1 cell counter (Schärfe System, Reutlingen, Germany). Growth kinetics experiments were repeated at least two times.
To examine growth arrest, induced by a cell's self-produced TGF-ß1, TGF-ß antibody (2G7) in a concentration ranging from 0.1 to 10 µg/ml was added to the cell culture.
TGF-ß1 enzyme linked immunosorbent assay (ELISA)
For quantification of TGF-ß1 protein in cell culture supernatant, the Quantikine Immunoassay (R&D Systems Europe, Abingdon, UK) was performed according to the manufacturer's instructions. Cells were cultured for 2, 4, 8 and 16 days, starting with 50 000 cells in 4 ml of medium for all cell lines. TGF-ß1 in supernatants was activated by adding 1 N HCl (100 µl/500 µl sample) to the samples for 10 min and subsequently neutralized by the addition of 1.2 N NaOH containing 0.5 M HEPES (100 µl/500 µl sample). To correct for the TGF-ß1 present in the medium, the OD450 values of the HCl treated medium were subtracted from the OD450 value of the supernatants. All samples were assayed as triplicates.
RNA extraction
Total RNA was isolated from cells that were grown to
60% confluence in 250 ml culture flasks (Greiner, Frickenhausen, Germany) using TRIzol reagent (Gibco BRL/Life Technologies, Breda, The Netherlands). The total RNA was phenolchloroform-extracted, ethanol precipitated and cleaned with Rneasy cleanup system columns (Qiagen GmbH, Hilden, Germany).
Oligonucleotide microarray and data analysis
Affymetrics focus arrays (Santa Clara, CA), representing 8793 human sequences from the NCBI Refseq database, were used for mRNA expression profiling according to manufacturer's instructions. Briefly, 10 µg of purified RNA was transcribed by Superscript II reverse transcriptase (Life Technologies, Grand Island, NY) using T7- (dT)24 primer containing a T7 RNA polymerase promoter. After synthesis of the second complementary DNA (cDNA) strand, this product was used in an in vitro transcription reaction to generate biotinylated complementary RNA (cRNA) using the Bioarray RNA transcript labeling kit (Enzo, Farmingdale, NY). Focus arrays were hybridized with 10 µg of biotinylated RNA. After hybridization, microarrays were washed and stained on an Affymetrics fluidics station and scanned with an argon ion confocal laser. Data files of all microarrays were normalized using sequence information in Robust Multi-Chip Average (GCRMA) method (24,25). Quality assurance was performed on the arrays using Affy-Probe Level Model (AffyPLM) (26). Microarrays for each cell line were performed in duplicate for all conditions. Normalized data were statistically analyzed for each cell line separately. A change in gene expression during the four time points was analyzed by one-way ANOVA using R language for statistical computing. Genes that showed significant changes (P
0.01) in expression pattern were selected for further analysis by functional grouping on gene ontology (GO) terms and by screening the public available databases (http://www.ncbi.nlm.nih.gov and http://www.ncbi.nlm.nih.gov/omim).
Real-time quantitative PCR
2 µg of total RNA was transcribed to cDNA with reverse transcriptase of Superscript II (Life Technologies). Amplification reactions were performed with qPCR Core kit for Sybr Green (Eurogentec Hampshire, UK) according to manufacturer's protocol. Fluorescent PCR analysis was performed using the BIO-RAD iCycler (BIO-RAD, Hercules, CA). The following PCR conditions were used: 10 min at 95°C, followed by 40 cycles of 15 s at 95°C and 1 min at the appropriate annealing temperature. Genes for normalization of expression data were selected on the basis of constant high microarray gene expression data during the four time points. Primers were either designed with Beacon designer (BIO-RAD), retrieved from Real Time PCR Primer and Probe Database (http://medgen.ugent.be/rtprimerdb) or ordered (Tebu-Bio, Heerhugowaard, The Netherlands). Expression of the genes of interest was normalized by geometric averaging of multiple internal control genes using the Genorm program (27). Out of five normalization genes the best three were selected within this program: CPSF6, EEF1A1 and RPL13. Relative quantification was performed using standard curves, followed by adjustment with the normalization factor, which is calculated by the Genorm program. Primer sequences are listed in Table I, apart from commercially available primers for CDKN1A and NF
B2.
 |
Results
|
---|
Cell growth response of CC10B, SiHa and HeLa to TGF-ß1
The degree of TGF-ß1 sensitivity was determined in cervical cancer cell lines, CC10B, SiHa and HeLa at day 2, 4 and 6 of cell growth after exposure to TGF-ß1, in a concentration ranging from 0.001 to 1 ng/ml. For all cell lines 0.1 ng/ml TGF-ß1 gave plateau values in cell growth inhibition (data shown for cell line CC10B, Figure 1A). TGF-ß1 induced cell growth inhibition was evident from day 1 onwards for CC10B, after 2 days for SiHa and after 4 days for HeLa. After 6 days of TGF-ß1 treatment, CC10B showed
75% decrease in cell growth, SiHa, 50% and HeLa only 25%, demonstrating that CC10B was most, SiHa intermediate and HeLa least sensitive to TGF-ß1-induced growth inhibition (Figure 1B). Only HeLa and SiHa showed an EMT-like morphology upon TGF-ß1 treatment (data not shown).

View larger version (17K):
[in this window]
[in a new window]
|
Fig. 1. Effect of TGF-ß1 on cell growth of cervical cancer cell lines. (A) Influence of TGF-ß1 concentration on cell growth inhibition of CC10B. Cell growth was determined by measuring the number of cells at day 6 using a cell counter as described in Materials and methods. Cells were stimulated with 0.001, 0.01, 0.1 or 1 ng/ml TGF-ß1 in triplicate. A representative experiment is shown. (B) Sensitivity for cell growth inhibition by TGF-ß1 of HeLa, SiHa and CC10B. The sensitivity for cell growth inhibition by TGF-ß1 was measured in HeLa, SiHa and CC10B, using a cell counter. Cells were treated with 0.1 ng/ml TGF-ß1 during 6 days. For each cell line, growth inhibition by TGF-ß1 was compared between cells in the absence (100%) and presence of TGF-ß1 at the same time point. The assay was performed in triplicate and repeated at least two times.
|
|
Expression profile of CC10B, SiHa and HeLa after TGF-ß1 stimulation
To determine the pathways involved in TGF-ß1-induced cell growth regulation, CC10B, SiHa and HeLa were stimulated with 0.1 ng/ml TGF-ß1 for 0, 6, 12 or 24 h for profiling by microarray. Sampling for each cell line was performed in duplicate for statistical analysis. The reliability of the data after normalization was confirmed by AffyPLM-analysis indicating that arrays between the four time points (0, 6, 12 and 24 h) for each cell line were comparable (data not shown). For each cell line statistically significant changes (P
0.01) in gene expression (SSCG) were selected and calculated by one-way ANOVA analysis. The number of SSCG varied per cell line: for CC10B 253, for SiHa 140 and for HeLa 306 (Figure 2).

View larger version (17K):
[in this window]
[in a new window]
|
Fig. 2. Number of TGF-ß1 induced significant changes in gene expression (ANOVA, P 0.01). Venn diagram demonstrating SSCG for each cell line and the overlap between the cell lines. All cell lines share 2 genes, present within all 3 circles, whereas 8 genes are shared between SiHa and CC10B, 22 genes between SiHa and HeLa and 20 genes between HeLa and CC10B.
|
|
To investigate at which time point TGF-ß1 stimulation resulted in the majority of changes in gene expression, the SSCG were clustered in a hierarchical tree for each cell line (data not shown). Most TGF-ß1-induced gene expression changes occur after 6 h. Time points 12 and 24 h cluster separately from the other time points (0 and 6 h) indicating that in all cell lines most similarities in gene expression are shared between time point 12 and 24 h.
The percentage of SSCG in the cell lines, previously reported to be targets of TGF-ß1 signaling, was determined as 4% for CC10B, 11% for SiHa and 6% for HeLa (data not shown). The majority of these genes were mainly involved in cell cycle, signal transduction, cell adhesion and transport processes.
Next, all SSCG for each cell line were ordered according to biological processes (GO terminology). Most of the SSCG were involved in signal transduction, transport (e.g. electron, cation, protein, etc.) and transcription (Figure 3).

View larger version (25K):
[in this window]
[in a new window]
|
Fig. 3. Biological processes demonstrating numbers of TGF-ß1-induced SSCG. Bars indicate proportions of SSCG for each cell line; HeLa is depicted in black, SiHa in grey and CC10B in white. The bars are categorized by GO terms.
|
|
Pathways induced or altered by TGF-ß1
Then, we wanted to explore which TGF-ß1 affected pathways were involved in cell growth regulation in the different cell lines. Therefore, SSCG were categorized per pathway. For each cell line, growth-regulatory pathways with altered gene expressions were grouped (Figure 4A). Pathways altered in HeLa comprised MAPK, Smad, TNF
, Wnt and nuclear factor kappa B (NF
B). Pathways influenced in SiHa consisted of MAPK, Smad, TNF
, Wnt and NF
B. For CC10B the pathways influenced consisted of MAPK, Smad, TNF
, Wnt, fibroblast growth factor (FGF), IFN
and Rho. Subsequently, the pathways of interest between the cell lines were compared by examining the up- or downregulation of gene expression of SSCG in each particular pathway (Figure 4B). We focused on pathways affected by TGF-ß1 in all cell lines: Smad, MAPK, TNF
and Wnt.


View larger version (67K):
[in this window]
[in a new window]
|
Fig. 4. TGF-ß1 induced alterations in gene expression. (A) Expression profiles of potential TGF-ß1 target genes. Changes in gene expression after TGF-ß1 stimulation of HeLa (on the left), SiHa (in the middle) and CC10B (on the right), grouped by pathway. Dark colors, relative to time point 0, represent upregulation of gene expression, whereas light colors represent downregulation of SSCG. (B) TGF-ß1 induced changes in gene expression of pathways in HeLa, SiHa and CC10B. Pathways, shown in light gray boxes, are associated with TGF-ß1 signaling and involved in regulation of cell proliferation. The boxes below the pathways show in red, genes which are upregulated in expression, in blue, genes which are downregulated and in black, genes which show evident upregulation and downregulation during the four time points compared with time point 0 h. In HeLa, SSCG are observed in MAPK, Smad, Wnt, TNF , NF B and Rho pathways, in SiHa, SSCG are observed in MAPK, Smad, TNF and NF B pathways and in CC10B, SSCG were found in MAPK, Smad, TNF , IFN, FGF and Rho pathways.
|
|
MAPK pathway
In HeLa, the cell line most resistant to TGF-ß1-induced cell growth inhibition, MEF2C, a target gene of p38, and MKK6, an upstream kinase and activator of p38, were upregulated by TGF-ß1. ATF4, a transcription factor possibly involved in MAPK signaling, was also increased by TGF-ß1 in HeLa. Target genes of Smad and MAPK, in particular p38, pathways, such as ATF3, CDKN1A and GADD45B, were upregulated in the TGF-ß1 semi-resistant cell line SiHa. Besides the p38 pathway in HeLa and possibly in SiHa, the Ras pathway may be affected by TGF-ß1 in HeLa and CC10B. In HeLa, PLAT and MNK2, target genes of Ras and Smad signaling, are upregulated. In CC10B, PLAT is upregulated in gene expression.
Smad pathway
In agreement with the EMT-like changes observed in HeLa and SiHa upon TGF-ß1 treatment, target genes of Smad signaling associated with fibrosis were upregulated in these cell lines. Genes involved in growth arrest or cell cycle control, known to be regulated by Smad, were upregulated in HeLa and SiHa. Also, in CC10B, genes involved in growth arrest such as GADD45A (data not shown), not previously shown to be mediated by Smad, were upregulated.
Wnt pathway
In HeLa, enhanced gene expression for two frizzled receptors, FZD2 and FZD4 and the target gene WISP2, known to be part of Wnt signaling, were observed. SFRP4 and DKK1, inhibitors of Wnt signaling, were downregulated in HeLa. In CC10B, DKK1 was downregualted as well. In SiHa and CC10B, LDLR, a putative Wnt coreceptor, was upregulated. No target genes of the Wnt pathway were upregulated in either CC10B or SiHa. In particular, HeLa showed an increase of target and receptor genes in the Wnt-signaling pathway.
TNF
pathway
In HeLa, a decrease in gene expression of TNFAIP3, TNIP1, TNFRSF12a, TNFRSF10C and TRAF3 was observed. SiHa showed downregulation of TNFRSF21 and TNFSF15, whereas CC10B showed upregulation of GG2-1, a target gene of TNF
signaling pathway. Thus, the cell lines with resistance to TGF-ß1 showed down regulation of TNF
signaling components, in contrast to the cell line most sensitive to TGF-ß1, which showed upregulation of a TNF
target gene.
Other pathways
Pathways that were not shared between all the cell lines were Rho, IFN, FGF and NF
B. As for the Rho family of small GTPases, Rac2 was upregulated in HeLa, whereas CDC42EP2 and ARHGEF3 were downregulated in CC10B. Components of the IFN signaling pathway were downregulated in CC10B, whereas FGF signaling components were upregulated in CC10B. Mediators of the NF
B pathway were downregulated in HeLa, which coincides with the downregulation of TNF
pathway genes. NF
B2 was transiently upregulated in SiHa.
Real-time quantitative PCR verification of microarray data
To validate the microarray results, representative gene products of different pathways were subjected to quantitative real-time PCR (QRTPCR). The change, observed with this technique, confirmed results obtained by the microarrays, although variations in magnitude of the change between the two technologies were observed. Twelve SSCG verified in the cell lines exhibited TGF-ß1-induced changes in gene expression that correlated with those observed in the microarray experiments (Figure 5). The respective genes were: DKK1 and ATF4 for HeLa and CC10B, NF
B2 for HeLa and SiHa, TNFRSF12a for HeLa, TNFRSF21, GADD45B, TGFBI, PAI-1 and CDKN1A for SiHa.

View larger version (30K):
[in this window]
[in a new window]
|
Fig. 5. Correlation of expression profile between microarray and QRTPCR. The relative expression levels of SSCG; DKK1, ATF4, TNFRSF12a, TNFRSF21, GADD45B, TGFBI, NF B2, PAI-1 and CDKN1A were measured with microarray and QRTPCR at 0, 6, 12 and 24 h of TGF-ß1 stimulation. Data are normalized to internal control genes (see Materials and methods). The dotted line represents gene expression analyzed by QRTPCR, the straight line represents gene expression generated by microarray.
|
|
TGF-ß1 production and TGF-ß1 growth inhibition
Finally, we investigated the association between decreased sensitivity to TGF-ß1-mediated cell growth inhibition of the cell lines and increased TGF-ß1 production.
TGF-ß1 production was measured in the supernatants of CC10B, SiHa and HeLa cells after 2, 4, 8 and 16 days of cell culture. Only HeLa and SiHa excreted TGF-ß1. HeLa, which was most resistant to TGF-ß1-induced growth inhibition, showed the highest production of TGF-ß1 (Figure 6A). Subsequently, the effect of the produced TGF-ß1 on cell growth was determined. For this purpose SiHa cells were cultured with anti-TGF-ß. Anti-TGF-ß did not alter cell growth kinetics, suggesting that the produced TGF-ß1 is latent TGF-ß1 and does not affect cell growth (Figure 6B).

View larger version (14K):
[in this window]
[in a new window]
|
Fig. 6. (A) TGF-ß1 production of the cell lines. The amount of TGF-ß1 production, measured by ELISA, in supernatants of HeLa, SiHa and CC10B after 8 days of cell culture (measured as described in Materials and methods). To correct for the TGF-ß1 present in the medium, the OD450 values of the HCl treated medium were subtracted from the OD450 value of the supernatants. (B) The effect of anti-TGF-ß on cell growth of SiHa. Cell growth, measured in triplicate by cell counts of SiHa, after 6 days without anti-TGF-ß, with anti-TGF-ß (10 µg/ml), with TGF-ß1 (0.1 ng/ml) and with both TGF-ß1 and anti-TGF-ß. Cell number after 6 days without TGF-ß1 is shown as 100%.
|
|
 |
Discussion
|
---|
The mechanisms by which cancer cells lose their TGF-ß1-induced growth inhibition are not fully understood. Defects in TGF-ß1 signal transduction components, thereby contributing to loss of Smad signaling, does appear in some tumor types, but does not explain the loss of growth inhibition by TGF-ß1 in most cancers, including cervical cancer (28). TGF-ß1 can activate signaling pathways involved in growth control independently of Smads (15,2931). The role of these non-Smad signaling cascades remains to be better characterized. By means of gene expression profiling, we have investigated differences in TGF-ß1-induced response using cervical cancer cell lines with different TGF-ß1 sensitivity.
In all cell lines many SSCG participated in signal transduction and transcription processes. Substantial parts of SSCG genes were involved in Smad, MAPK, TNF
and Wnt pathways. These pathways involved in cell growth and maintenance processes are associated with TGF-ß1 signaling.
Smad signaling is the main route through which TGF-ß1 transduces its effects on cell cycle control. There is evident upregulation of genes that act via Smad activation and are involved in cell cycle control such as CDKN1A, GADD45B and ATF3 (32,33) in SiHa and CDKN1C and TP53 in HeLa. In CC10B, GADD45A (34) and TP73L (data not shown), negative regulators of cell cycle were upregulated, although these have not been described before as targets of Smad signaling. Besides genes involved in cell cycle regulation or apoptosis in HeLa, genes involved in cell division were upregulated, namely cyclin B2 and G2 (data not shown). Thus, in all cell lines, genes that negatively regulate cell growth were induced, but only in HeLa significant upregulation of positive regulators of cell growth were observed, which may explain the resistance to TGF-ß1-induced cell growth inhibition.
MAPK can be activated by TGF-ß1 via TGF-ß1-activating kinase 1 (TAK1) (35,36), which is a potent activator of the Stress activated protein kinases (SAPK/JNK) (37) and the p38 pathway (3739). In HeLa, increase in gene expression of MKK6, the main MAPK that activates p38, and MEF2C, a p38 downstream transcription factor (40), was observed. In a recent report, enhancement of a proliferative pathway in HeLa by TGF-ß1 was shown involving the activation of MAPKs and probably not involving Smad activation (41). They reported that in SiHa, a growth inhibitory pathway involving activation of Smads and a low level of MAPK activation was observed. In agreement with these results, we found more prominent upregulation of specific MAPK targets and signaling molecules in HeLa from our microarray data. However, Maliekal et al. (41) showed extracellular response kinase (ERK) and JNK activation in HeLa, whereas our microarray data supported p38 activation and possibly ERK activation in HeLa. Our results and these observations, showing a strong TGF-ß1-dependent activation of MAPK and insufficient Smad activation by TGF-ß1 in HeLa, suggest that this activation pattern may hamper the growth inhibitory effect of TGF-ß1.
In HeLa we observed downregulation of TNF
receptors, signaling molecules and target proteins, of which TRAF3 (42,43) and TNFRSF12a (44) have been associated, with apoptotic processes or inhibition of cell growth. In SiHa, downregulation of TNFSF15 (45) and TNFRSF21 (46) genes involved in cell death and suppression of cell growth was observed. In the TGF-ß1 sensitive cell line CC10B no downregulation of TNF
signaling proteins was observed. In contrast, upregulation of a TNF
target gene, GG2-1 (47) was observed. In view of the TGF-ß1 resistance of HeLa and SiHa, downregulation of receptors or signaling components involved in death signaling could be a way to impede TGF-ß1-induced apoptosis or cell growth inhibition since TGF-ß1 and TNF
can cooperate in the apoptotic process.
Aberrant Wnt signaling, often leading to activation of the pathway, occurs in many types of cancer including cervical cancer (48,49). In HeLa upregulation of FZD2 and FZD4 was observed. These are receptors of the Frizzled family that transduce signals culminating in intracellular calcium release (50), activation of calmodulin-dependent kinase II (51), PKC (52) and MAPK pathway without activating the canonical ß-catenin pathway. Upregulation of FZD2 (53,54) and FZD4 (55) in cancer has been shown and it suggests a role for Wnt signaling via FZD receptors in tumorigenesis. Downregulation of potent Wnt inhibitory factors such as DKK1 and SFRP4, as observed in HeLa, may enhance Wnt signaling. WISP2, a Wnt-1 target gene of the canonical signaling pathway probably involved in transformation processes (56), is upregulated in HeLa. Since upregulation of Wnt signaling components and downregulation of Wnt inhibitory factors were observed, the Wnt pathway may be primed and play a role in reduced cell growth inhibition in Hela by TGF-ß1.
With regard to oncogenes, in HeLa more than twice as many oncogenes were upregulated than in CC10B and SiHa (data not shown). Increased expression of proto-oncogenes may also provide a mechanism by which tumor cells show diminished responsiveness to TGF-ß1 and can escape its tumor suppressor effects.
Cells undergoing EMT have a more migratory and invasive phenotype, which is a characteristic phenotype of cancer cells resistant to TGF-ß1- induced cell death. In agreement with the observation of an EMT-like appearance of SiHa (5) and HeLa in response to TGF-ß1, these cells are less sensitive to the antiproliferative effect of TGF-ß1, which may associate with increased production of TGF-ß1. TGF-ß1 produced by SiHa was present in a latent form and did not inhibit cell growth since anti-TGF-ß did not affect cell expansion. TGF-ß1 excretion by tumor cells more likely contributes to paracrine stimulation of tumor development.
In our study, novel target genes involved in TNF
, MAPK and Wnt pathways in response to TGF-ß1 were found. Substantial differences in the Smad, TNF
, MAPK and Wnt pathway between TGF-ß1-sensitive and insensitive cell lines were observed. Since these pathways are involved in the integral processes of cell proliferation and cell death, these pathways may play a role in TGF-ß1-induced cell growth inhibition.
 |
Acknowledgments
|
---|
We thank N.ter Haar for technical assistance with the ELISA and QRTPCR and H.Baelde, M.Lombaerts, T.van Wezel and A.Cleton for advice in microarray and QRTPCR techniques. The study was supported by the Dutch Cancer Society, grant no. RUL2001-2465. This study was done within the Centre for Medical Systems Biology (CMSB), a centre of excellence supported by the Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research (NWO).
Conflict of Interest Statement: None declared.
 |
References
|
---|
- Creek,K.E., Geslani,G., Batova,A. and Pirisi,L. (1995) Progressive loss of sensitivity to growth control by retinoic acid and transforming growth factor-beta at late stages of human papillomavirus type 16-initiated transformation of human keratinocytes. Adv. Exp. Med. Biol., 375, 117135.[Medline]
- De Geest,K., Bergman,C.A., Turyk,M.E., Frank,B.S. and Wilbanks,G.D. (1994) Differential response of cervical intraepithelial and cervical carcinoma cell lines to transforming growth factor-beta 1. Gynecol. Oncol., 55, 376385.[CrossRef][ISI][Medline]
- Chopra,V., Dinh,T.V. and Hannigan,E.V. (1998) Circulating serum levels of cytokines and angiogenic factors in patients with cervical cancer. Cancer Invest., 16, 152159.[ISI][Medline]
- Comerci,J.T.Jr, Runowicz,C.D., Flanders,K.C., De Victoria,C., Fields,A.L., Kadish,A.S. and Goldberg,G.L. (1996) Altered expression of transforming growth factor-beta 1 in cervical neoplasia as an early biomarker in carcinogenesis of the uterine cervix. Cancer, 77, 11071114.[CrossRef][ISI][Medline]
- Yi,J.Y., Hur,K.C., Lee,E., Jin,Y.J., Arteaga,C.L. and Son,Y.S. (2002) TGFbeta1-mediated epithelial to mesenchymal transition is accompanied by invasion in the SiHa cell line. Eur. J. Cell Biol., 81, 457468.[ISI][Medline]
- Sheu,B.C., Lin,R.H., Lien,H.C., Ho,H.N., Hsu,S.M. and Huang,S.C. (2001) Predominant Th2/Tc2 polarity of tumor-infiltrating lymphocytes in human cervical cancer. J. Immunol., 167, 29722978.[Abstract/Free Full Text]
- Hazelbag,S., Gorter,A., Kenter,G.G., van den Broek,L. and Fleuren,G. (2002) Transforming growth factor-beta1 induces tumor stroma and reduces tumor infiltrate in cervical cancer. Hum. Pathol., 33, 11931199.[CrossRef][ISI][Medline]
- Lee,S., Cho,Y.S., Shim,C., Kim,J., Choi,J., Oh,S., Kim,J., Zhang,W. and Lee,J. (2001) Aberrant expression of Smad4 results in resistance against the growth-inhibitory effect of transforming growth factor-beta in the SiHa human cervical carcinoma cell line. Int. J. Cancer, 94, 500507.[CrossRef][ISI][Medline]
- Kang,S.H., Won,K., Chung,H.W., Jong,H.S., Song,Y.S., Kim,S.J., Bang,Y.J. and Kim,N.K. (1998) Genetic integrity of transforming growth factor beta (TGF-beta) receptors in cervical carcinoma cell lines: loss of growth sensitivity but conserved transcriptional response to TGF-beta. Int. J. Cancer, 77, 620625.[CrossRef][ISI][Medline]
- Maliekal,T.T., Antony,M.L., Nair,A., Paulmurugan,R. and Karunagaran,D. (2003) Loss of expression, and mutations of Smad 2 and Smad 4 in human cervical cancer. Oncogene, 22, 48894897.[CrossRef][ISI][Medline]
- Chen,T., de Vries,E.G., Hollema,H., Yegen,H.A., Vellucci,V.F., Strickler,H.D., Hildesheim,A. and Reiss,M. (1999) Structural alterations of transforming growth factor-beta receptor genes in human cervical carcinoma. Int. J. Cancer, 82, 4351.[CrossRef][ISI][Medline]
- Dunfield,L.D., Dwyer,E.J. and Nachtigal,M.W. (2002) TGF beta-induced Smad signaling remains intact in primary human ovarian cancer cells. Endocrinology, 143, 11741181.[Abstract/Free Full Text]
- Janda,E., Lehmann,K., Killisch,I., Jechlinger,M., Herzig,M., Downward,J., Beug,H. and Grunert,S. (2002) Ras and TGF beta cooperatively regulate epithelial cell plasticity and metastasis: dissection of Ras signaling pathways. J. Cell Biol., 156, 299313.[Abstract/Free Full Text]
- Calonge,M.J. and Massague,J. (1999) Smad4/DPC4 silencing and hyperactive Ras jointly disrupt transforming growth factor-beta antiproliferative responses in colon cancer cells. J. Biol. Chem., 274, 3363733643.[Abstract/Free Full Text]
- Bhowmick,N.A., Ghiassi,M., Bakin,A., Aakre,M., Lundquist,C.A., Engel,M.E., Arteaga,C.L. and Moses,H.L. (2001) Transforming growth factor-beta1 mediates epithelial to mesenchymal transdifferentiation through a RhoA-dependent mechanism. Mol. Biol. Cell, 12, 2736.[Abstract/Free Full Text]
- Nishita,M., Hashimoto,M.K., Ogata,S., Laurent,M.N., Ueno,N., Shibuya,H. and Cho,K.W. (2000) Interaction between Wnt and TGF-beta signalling pathways during formation of Spemann's organizer. Nature, 403, 781785.[CrossRef][ISI][Medline]
- Attisano,L. and Labbe,E. (2004) TGFbeta and Wnt pathway cross-talk. Cancer Metastasis Rev., 23, 5361.[CrossRef][ISI][Medline]
- Bitzer,M., von Gersdorff,G., Liang,D., Dominguez-Rosales,A., Beg,A.A., Rojkind,M. and Bottinger,E.P. (2000) A mechanism of suppression of TGF-beta/SMAD signaling by NF-kappa B/RelA. Genes Dev., 14, 187197.[Abstract/Free Full Text]
- Ulloa,L., Doody,J. and Massague,J. (1999) Inhibition of transforming growth factor-beta/SMAD signalling by the interferon-gamma/STAT pathway. Nature, 397, 710713.[CrossRef][ISI][Medline]
- Afrakhte,M., Moren,A., Jossan,S., Itoh,S., Sampath,K., Westermark,B., Heldin,C.H., Heldin,N.E. and ten Dijke,P. (1998) Induction of inhibitory Smad6 and Smad7 mRNA by TGF-beta family members. Biochem. Biophys. Res. Commun., 249, 505511.[CrossRef][ISI][Medline]
- Xie,L., Law,B.K., Aakre,M.E., Edgerton,M., Shyr,Y., Bhowmick,N.A. and Moses,H.L. (2003) Transforming growth factor beta-regulated gene expression in a mouse mammary gland epithelial cell line. Breast Cancer Res., 5, R187R198.[CrossRef][ISI][Medline]
- Zavadil,J., Bitzer,M., Liang,D., Yang,Y.C., Massimi,A., Kneitz,S., Piek,E. and Bottinger,E.P. (2001) Genetic programs of epithelial cell plasticity directed by transforming growth factor-beta. Proc. Natl Acad. Sci. USA, 98, 66866691.[Abstract/Free Full Text]
- Koopman,L.A., Szuhai,K., van Eendenburg,J.D., Bezrookove,V., Kenter,G.G., Schuuring,E., Tanke,H. and Fleuren,G.J. (1999) Recurrent integration of human papillomaviruses 16, 45 and 67 near translocation breakpoints in new cervical cancer cell lines. Cancer Res., 59, 56155624.[Abstract/Free Full Text]
- Bolstad,B.M., Irizarry,R.A., Astrand,M. and Speed,T.P. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics, 19, 185193.[Abstract/Free Full Text]
- Irizarry,R.A., Hobbs,B., Collin,F., Beazer-Barclay,Y.D., Antonellis,K.J., Scherf,U. and Speed,T.P. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics, 4, 249264.[Abstract/Free Full Text]
- Gautier,L., Cope,L., Bolstad,B.M. and Irizarry,R.A. (2004) Affyanalysis of Affymetrix GeneChip data at the probe level. Bioinformatics, 20, 307315.[Abstract/Free Full Text]
- Vandesompele,J., De Preter,K., Pattyn,F., Poppe,B., Van Roy,N., De Paepe,A. and Speleman,F. (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol., 3, 112.[CrossRef][Medline]
- Chu,T.Y., Lai,J.S., Shen,C.Y., Liu,H.S. and Chao,C.F. (1999) Frequent aberration of the transforming growth factor-beta receptor II gene in cell lines but no apparent mutation in pre-invasive and invasive carcinomas of the uterine cervix. Int. J. Cancer, 80, 506510.[CrossRef][ISI][Medline]
- Mulder,K.M. and Morris,S.L. (1992) Activation of p21ras by transforming growth factor beta in epithelial cells. J. Biol. Chem., 267, 50295031.[Abstract/Free Full Text]
- Sano,Y., Harada,J., Tashiro,S., Gotoh-Mandeville,R., Maekawa,T. and Ishii,S. (1999) ATF-2 is a common nuclear target of Smad and TAK1 pathways in transforming growth factor-beta signaling. J. Biol. Chem., 274, 89498957.[Abstract/Free Full Text]
- Hocevar,B.A., Brown,T.L. and Howe,P.H. (1999) TGF-beta induces fibronectin synthesis through a c-Jun N-terminal kinase-dependent, Smad4-independent pathway. EMBO J., 18, 13451356.[Abstract/Free Full Text]
- Kang,Y., Chen,C.R. and Massague,J. (2003) A self-enabling TGFbeta response coupled to stress signaling: Smad engages stress response factor ATF3 for Id1 repression in epithelial cells. Mol. Cell, 11, 915926.[CrossRef][ISI][Medline]
- Fan,F., Jin,S., Amundson,S.A., Tong,T., Fan,W., Zhao,H., Zhu,X., Mazzacurati,L., Li,X., Petrik,K.L., Fornace,A.J.Jr, Rajasekaran,B. and Zhan,Q. (2002) ATF3 induction following DNA damage is regulated by distinct signaling pathways and over-expression of ATF3 protein suppresses cells growth. Oncogene, 21, 74887496.[CrossRef][ISI][Medline]
- Fornace,A.J.,Jr., Nebert,D.W., Hollander,M.C., Luethy,J.D., Papathanasiou,M., Fargnoli,J. and Holbrook,N.J. (1989) Mammalian genes coordinately regulated by growth arrest signals and DNA-damaging agents. Mol. Cell. Biol., 9, 41964203.[ISI][Medline]
- Yamaguchi,K., Shirakabe,K., Shibuya,H., Irie,K., Oishi,I., Ueno,N., Taniguchi,T., Nishida,E. and Matsumoto,K. (1995) Identification of a member of the MAPKKK family as a potential mediator of TGF-beta signal transduction. Science, 270, 20082011.[Abstract]
- Shibuya,H., Yamaguchi,K., Shirakabe,K., Tonegawa,A., Gotoh,Y., Ueno,N., Irie,K., Nishida,E. and Matsumoto,K. (1996) TAB1: an activator of the TAK1 MAPKKK in TGF-beta signal transduction. Science, 272, 11791182.[Abstract]
- Shirakabe,K., Yamaguchi,K., Shibuya,H., Irie,K., Matsuda,S., Moriguchi,T., Gotoh,Y., Matsumoto,K. and Nishida,E. (1997) TAK1 mediates the ceramide signaling to stress-activated protein kinase/c-Jun N-terminal kinase. J. Biol. Chem., 272, 81418144.[Abstract/Free Full Text]
- Moriguchi,T., Kuroyanagi,N., Yamaguchi,K., Gotoh,Y., Irie,K., Kano,T., Shirakabe,K., Muro,Y., Shibuya,H., Matsumoto,K., Nishida,E. and Hagiwara,M. (1996) A novel kinase cascade mediated by mitogen-activated protein kinase kinase 6 and MKK3. J. Biol. Chem., 271, 1367513679.[Abstract/Free Full Text]
- Wang,W., Zhou,G., Hu,M.C., Yao,Z. and Tan,T.H. (1997) Activation of the hematopoietic progenitor kinase-1 (HPK1)-dependent, stress-activated c-Jun N-terminal kinase (JNK) pathway by transforming growth factor beta (TGF-beta)-activated kinase (TAK1), a kinase mediator of TGF beta signal transduction. J. Biol. Chem., 272, 2277122775.[Abstract/Free Full Text]
- Han,J., Jiang,Y., Li,Z., Kravchenko,V.V. and Ulevitch,R.J. (1997) Activation of the transcription factor MEF2C by the MAP kinase p38 in inflammation. Nature, 386, 296299.[CrossRef][ISI][Medline]
- Maliekal,T.T., Anto,R.J. and Karunagaran,D. (2004) Differential activation of Smads in HeLa and SiHa cells that differ in their response to transforming growth factor-beta. J. Biol. Chem., 279, 3628736292.[Abstract/Free Full Text]
- VanArsdale,T.L., VanArsdale,S.L., Force,W.R., Walter,B.N., Mosialos,G., Kieff,E., Reed,J.C. and Ware,C.F. (1997) Lymphotoxin-beta receptor signaling complex: role of tumor necrosis factor receptor-associated factor 3 recruitment in cell death and activation of nuclear factor kappaB. Proc. Natl Acad. Sci. USA, 94, 24602465.[Abstract/Free Full Text]
- Eliopoulos,A.G., Dawson,C.W., Mosialos,G., Floettmann,J.E., Rowe,M., Armitage,R.J., Dawson,J., Zapata,J.M., Kerr,D.J., Wakelam,M.J., Reed,J.C., Kieff,E. and Young,L.S. (1996) CD40-induced growth inhibition in epithelial cells is mimicked by EpsteinBarr virus-encoded LMP1: involvement of TRAF3 as a common mediator. Oncogene, 13, 22432254.[ISI][Medline]
- Nakayama,M., Ishidoh,K., Kayagaki,N., Kojima,Y., Yamaguchi,N., Nakano,H., Kominami,E., Okumura,K. and Yagita,H. (2002) Multiple pathways of TWEAK-induced cell death. J. Immunol., 168, 734743.[Abstract/Free Full Text]
- Zhai,Y., Ni,J., Jiang,G.W., Lu,J., Xing,L., Lincoln,C., Carter,K.C., Janat,F., Kozak,D., Xu,S., Rojas,L., Aggarwal,B.B., Ruben,S., Li,L.Y., Gentz,R. and Yu,G.L. (1999) VEGI, a novel cytokine of the tumor necrosis factor family, is an angiogenesis inhibitor that suppresses the growth of colon carcinomas in vivo. FASEB J., 13, 181189.[Abstract/Free Full Text]
- Pan,G., Bauer,J.H., Haridas,V., Wang,S., Liu,D., Yu,G., Vincenz,C., Aggarwal,B.B., Ni,J. and Dixit,V.M. (1998) Identification and functional characterization of DR6, a novel death domain-containing TNF receptor. FEBS Lett., 431, 351356.[CrossRef][ISI][Medline]
- Zhang,H.G., Hyde,K., Page,G.P., Brand,J.P., Zhou,J., Yu,S., Allison,D.B., Hsu,H.C. and Mountz,J.D. (2004) Novel tumor necrosis factor alpha-regulated genes in rheumatoid arthritis. Arthritis Rheum., 50, 420431.[CrossRef][ISI][Medline]
- Shinohara,A., Yokoyama,Y., Wan,X., Takahashi,Y., Mori,Y., Takami,T., Shimokawa,K. and Tamaya,T. (2001) Cytoplasmic/nuclear expression without mutation of exon 3 of the beta-catenin gene is frequent in the development of the neoplasm of the uterine cervix. Gynecol. Oncol., 82, 450455.[CrossRef][ISI][Medline]
- Imura,J., Ichikawa,K., Takeda,J. and Fujimori,T. (2001) Beta-catenin expression as a prognostic indicator in cervical adenocarcinoma. Int. J. Mol. Med., 8, 353358.[ISI][Medline]
- Slusarski,D.C., Corces,V.G. and Moon,R.T. (1997) Interaction of Wnt and a Frizzled homologue triggers G-protein-linked phosphatidylinositol signalling. Nature, 390, 410413.[CrossRef][ISI][Medline]
- Kuhl,M., Sheldahl,L.C., Malbon,C.C. and Moon,R.T. (2000) Ca(2+)/calmodulin-dependent protein kinase II is stimulated by Wnt and Frizzled homologs and promotes ventral cell fates in Xenopus. J. Biol. Chem., 275, 1270112711.[Abstract/Free Full Text]
- Sheldahl,L.C., Park,M., Malbon,C.C. and Moon,R.T. (1999) Protein kinase C is differentially stimulated by Wnt and Frizzled homologs in a G-protein-dependent manner. Curr. Biol., 9, 695698.[CrossRef][ISI][Medline]
- Kirikoshi,H., Sekihara,H. and Katoh,M. (2001) Expression profiles of 10 members of Frizzled gene family in human gastric cancer. Int. J. Oncol., 19, 767771.[ISI][Medline]
- Tanaka,S., Akiyoshi,T., Mori,M., Wands,J.R. and Sugimachi,K. (1998) A novel frizzled gene identified in human esophageal carcinoma mediates APC/beta-catenin signals. Proc. Natl Acad. Sci. USA, 95, 1016410169.[Abstract/Free Full Text]
- Wissmann,C., Wild,P.J., Kaiser,S., Roepcke,S., Stoehr,R., Woenckhaus,M., Kristiansen,G., Hsieh,J.C., Hofstaedter,F., Hartmann,A., Knuechel,R., Rosenthal,A. and Pilarsky,C. (2003) WIF1, a component of the Wnt pathway, is down-regulated in prostate, breast, lung and bladder cancer. J. Pathol., 201, 204212.[CrossRef][ISI][Medline]
- Zoubine,M.N., Banerjee,S., Saxena,N.K., Campbell,D.R. and Banerjee,S.K. (2001) WISP-2: a serum-inducible gene differentially expressed in human normal breast epithelial cells and in MCF-7 breast tumor cells. Biochem. Biophys. Res. Commun., 282, 421425.[CrossRef][ISI][Medline]
Received January 4, 2005;
revised April 13, 2005;
accepted April 26, 2005.