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Carcinogenesis Advance Access originally published online on June 14, 2006
Carcinogenesis 2007 28(1):49-59; doi:10.1093/carcin/bgl091
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Impact of constitutive IGF1/IGF2 stimulation on the transcriptional program of human breast cancer cells

Margit Pacher, Michael J. Seewald, Mario Mikula1, Susanne Oehler, Maurice Mogg, Ursula Vinatzer, Andreas Eger2, Norbert Schweifer3, Roland Varecka3, Wolfgang Sommergruber3, Wolfgang Mikulits1 and Martin Schreiber*

Department of Obstetrics and Gynecology, Medical University of Vienna A-1090 Vienna, Austria
1 Department of Internal Medicine I, Medical University of Vienna A-1090 Vienna, Austria
2 Department of Medical Biochemistry, Medical University of Vienna A-1090 Vienna, Austria
3 Boehringer Ingelheim Austria A-1120 Vienna, Austria

*To whom correspondence should be addressed Email: martin.schreiber{at}meduniwien.ac.at


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Insulin-like growth factor (IGF) signaling is a key regulator of breast development and breast cancer. We have analyzed the expression of the IGF signaling cascade in 17 human breast cancer and 4 mammary epithelial cell lines. Five cell lines expressed high levels of IGF1 receptor, insulin (INS)/IGF receptor substrate 1, IGF-binding proteins 2 and 4, as well as the estrogen receptor (ESR), indicating a co-activation of IGF and ESR signaling. Next, we stably overexpressed IGF1 and IGF2 in MCF7 breast cancer cells, which did not affect their epithelial characteristics and the expression and localization of the epithelial marker genes E-cadherin and ß-catenin. Conversely, IGF1 and IGF2 overexpression potently increased cellular proliferation rates and the efficiency of tumor formation in mouse xenograft experiments, whereas the resistance to chemotherapeutic drugs such as taxol was unaltered. Expression profiling of overexpressing cells with whole-genome oligonucleotide microarrays revealed that 21 genes were upregulated >2-fold by both IGF1 and IGF2, 9 by IGF1, and 9 by IGF2. Half of the genes found to be upregulated are involved in transport and biosynthesis of amino acids, including several amino acid transport proteins, argininosuccinate and asparagine synthetases, and methionyl-tRNA synthetase. Upregulation of these genes constitutes a novel mechanism apparently contributing to the stimulatory effects of IGF signaling on the global protein synthesis rate. We conclude that the induction of cell proliferation and tumor formation by long-term IGF stimulation may primarily be due to anabolic effects, in particular increased amino acid production and uptake.

Abbreviations: ASNS, asparagine synthetase; ASS, argininosuccinate synthetase; ESR, estrogen receptor; IGF, insulin-like growth factor; INS, insulin INSR, insulin receptor; PCNA, proliferating cell nuclear antigen; PHGDH, phosphoglycerate dehydrogenase; VEGF, vascular endothelial growth factor


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Insulin-like growth factor (IGF) signaling plays an important role in the development and growth of many tissues (1,2). In the mammary gland, IGF1 is the primary mediator of growth hormone signaling and controls ductal development and terminal end bud formation (3). The IGF signaling system is a complex network of ligands (IGF1 and IGF2), receptors [IGF1R, IGF2R and insulin receptor (INSR)] and six IGF-binding proteins (IGFBP1–6) (4). IGF1 and IGF2 are highly homologous to each other (62% amino acid identity) and to INS. They are produced by the stromal cells of the mammary connective tissue, whereas the receptors are expressed by the epithelium, highlighting the importance of stromal–epithelial interactions for mammary gland development (5). IGFs exert their biological functions mainly via the IGF1R, but can also bind to the INSR and IGF1R–INSR heterodimers (6). IGF2 preferentially binds to the IGF2R, which lacks an intracellular kinase domain and does not exhibit any signaling capacity. Thus, IGF2R negatively regulates IGF signaling by reducing the levels of free IGF2. The IGFBPs regulate the bioavailability and half life of IGF1 and IGF2 in the circulation, and also exert IGF-independent effects (5,7). In line with its potent mitogenic and anti-apoptotic effects, aberrant activation of IGF signaling has been implicated strongly in the initiation and progression of breast, prostate, colon and lung cancers (5,6,8). For example, loss of heterozygosity of the IGF2R locus occurs in ~30% of breast cancers, suggesting that IGF2R represents a tumor suppressor gene (9,10). In contrast, IGF1R is frequently overexpressed in mammary tumors (11,12). Epidemiological studies have identified high circulating levels of IGF1 as a risk factor for breast cancer (13,14). Moreover, IGF signaling is closely linked to signaling via the estrogen receptor (ESR), a key player in breast cancer biology, further highlighting the importance of the IGF system in breast cancer (15,16).

Similar to INS, IGFs bind to and activate the INSR, which increases the cellular uptake of glucose and amino acids and stimulates glycogen and protein synthesis (17). The INS and IGF1 receptors are highly homologous and activate similar downstream signaling cascades, yet the INSR is associated with a more ‘metabolic response’, and the IGF1R with a more ‘mitogenic and anti-apoptotic response’ (18). These IGF responses are thought to be mediated by the MAPK and PI3K signaling cascades, which are rapidly and transiently activated when IGFs are added (8). Thus, the pathways relaying IGF signals to the nucleus and their biological outcome are reasonably well understood, whereas the relevant IGF target genes which execute these biological effects are still largely unknown. Expression profiling with small, focused DNA microarrays has aimed at identifying mitogenic and anti-apoptotic IGF target genes in specific cell types (19). Two microarray studies analyzing the difference between transient IGF1R and INSR activation have identified a number of novel, predominantely mitogenic IGF1 target genes such as HB-EGF (18,20). Here we employed Affymetrix GeneChips containing 45 000 probe sets for a genome-wide screen for target genes of long-term IGF1/2 stimulation in MCF7 human breast cancer cells. MCF7 cells stably overexpressing either IGF1 or IGF2 were generated, and genes significantly induced or repressed were identified based on comparison with vector control cells. The majority of upregulated genes identified plays a key role in amino acid transport and biosynthesis. Induction of these genes may significantly contribute to the mechanism by which IGFs accelerate the cellular metabolism, in particular protein biosynthesis, which is a hallmark of tumor cell growth and malignant transformation.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Generation of IGF1- and IGF2-overexpressing MCF7 breast cancer cell lines
A 1032 bp cDNA fragment coding for IGF1 was excised from plasmid IGF-1B (a gift from Dr T.Xiao Tu, Jefferson University, Philadelphia, PA) with XbaI and ligated into expression vector pCI-neo (#E1841; Promega), thus generating pCI-neo-IGF1. The IGF2 cDNA fragment from plasmid phIGF2/pKT218 (a gift from Dr Graeme I. Bell, Howard Hughes Medical Institute, University of Chicago, CA) was amplified with gene-specific primers containing restriction sites for EcoRI and XbaI (forward, 5'-GGG GAA TTC AGC CCC AAC TGC GAG GC-3'; reverse, 5'-GGG TCT AGA GGC TGC AGG ATG GTG GC-3'). The PCR product was inserted into the pCR2.1-TOPO vector, and re-excised using EcoRI and XbaI. The resulting 624 bp fragment was cloned into pCI-neo, now termed pCI-neo-IGF2. Successful insertion and integrity of the inserts were verified by sequencing. To obtain stable cell lines, MCF7 breast cancer cells were transfected with linearized (Asp700) pCI-neo, pCI-neo-IGF1 or pCI-neo-IGF2 using Lipofectamine PLUS (Invitrogen). Transfected clones were selected with 1 mg/ml G418 (Sigma) and expanded, yielding control (MCF7-vector), IGF1-overexpressing (MCF7-IGF1) and IGF2-overexpressing cell lines (MCF7-IGF2). Pools of ~50 clones each were used for further analysis. Overexpression was confirmed by using ELISAs of cellular supernatants (IGF1, Diachrom #DSL-10-5600; IGF2, Diachrom #DSL-10-9100).

Tissue culture and cell lines
All used cell lines except HMEC were obtained from ATCC or DSMZ, and were cultivated at 37°C, 5% CO2 and 100% humidity. The following culture media were used: MCF7-vector, MCF7-IGF1 and MCF7-IGF2: DMEM/10% FCS; BT549, Cal-51, CamaI, HCC-1143, HCC-1937, Kpl1, MDA-MB-231, MCF7, MDA-MB-435s, MDA-MB-468, SK-BR-3, T-47D and ZR75-1: RPMI/5% FCS; AU565 and MDA-MB-453: RPMI/10% FCS; BT474: DMEM/10% NCTC medium/10% FCS; Hs 578.Bst: MDM with 10% NCTC, 10% FCS and 30 ng/ml EGF; Hs 578.T: DMEM with 10% FCS and 10 µg/ml INS; MCF10A: MEGM with 0.1 µg/ml cholera toxin; and MCF10F: DMEM/HamsF12 plus 5% horse serum, 20 ng/ml EGF, 0.1 µg/ml cholera toxin, 10 µg/ml INS and 0.5 µg/ml hydrocortisone. Finite lifespan untransformed HMEC cells were kindly provided by M.R.Stampfer and grown in MEGM medium.

RNA isolation and quality control
Cells were plated at a density of 2 x 104 cells/cm2 and incubated for 4 days, with a change of medium after 2 days. After that time, cells were ~70% confluent. Medium was removed and cells were immediately lysed in Tri Reagent (catalog no. R2020; Sigma), and total RNA was prepared following the manufacturer's instructions and further purified using the RNeasy Mini Kit (Qiagen). RNA quality was assessed using the Bioanalyser 2100 and the RNA 6000 Nano LabChip Kit (Agilent). Only RNAs with a 28S:18S ratio >1.8 were used for microarray analyses. Two independent RNA preparations were made from two independent cultures in different weeks each from MCF7-vector, MCF7-IGF1 and MCF7-IGF2 cell lines (biological replicates).

RNA labeling, hybridization and data acquisition
Generation of labeled cRNA (from 5 µg of total RNA), fragmentation and hybridization were performed according to the manufacturer's instructions (Affymetrix), using the Superscript Choice kit (Invitrogen) for double-stranded cDNA synthesis and the Enzo Bioarray kit for in vitro transcription and labeling of cRNA. Fragmented cRNA (15 µg) were used for hybridizations of the GeneChip HG-U133A (catalog no. 900366) and HG-U133B (catalog no. 900368) oligonucleotide arrays (Affymetrix), each containing probe sets for 22 500 non-overlapping human transcripts. Subsequently, the arrays were washed in a fluidics station (Affymetrix) and scanned using an Agilent GeneArray Scanner (Agilent).

Microarray raw data and fold change analysis
Raw data analysis and scaling were performed in Microarray Suite 5.0 software (Affymetrix), and normalization and further analysis in GeneSpring 6.0 (Silicon Genetics). HG-U133A results for 17 breast cancer and 4 normal mammary epithelial cell lines were subjected to global scaling with a target intensity of 100, and to both ‘per chip’ and ‘per gene’ normalization (S. Oehler, U. Vinatzer and M. Schreiber, unpublished data). To analyze expression of the IGF signaling cascade in this dataset, probe set identifiers specific for the genes of interest were obtained from the Affymetrix NetAffx web page (21). One optimal probe set per gene was selected as follows: mapping of each probe set to the human genome was visually inspected in Ensembl (22), and probe sets without proper alignment with the corresponding mRNA transcript were excluded from further analysis. For genes with probe sets for multiple splice variants, only the probe set for the major transcript was used. The relative expression of the genes of interest was determined by dividing the signal intensity of each selected probe set through the median signal intensity of this probe set in all cell lines. Sample-wise and gene-wise clustering was performed with Pearson's correlation around zero as a similarity measure. To compare MCF7 cells with normal breast-derived cell lines, as well as MCF7-IGF1/2 with MCF7-vector cells, both HG-U133A and B subarrays were used. Scaling was performed based on the set of ~100 ‘housekeeping’ genes present on both subarrays, which were clearly expressed in all samples. Next, median expression values between MCF7 cells (three biological replicates) and the three normal cell lines were compared. To assess the effects of IGF overexpression, comparative analysis was performed in Microarray Suite 5.0, using the arrays hybridized with MCF7-vector cells as control arrays. Two algorithms were employed to obtain a quantitative estimate of the change in gene expression levels (signal log ratio) and the probability and direction of this change (change P-value) (23,24). Change P-values were computed with the Wilcoxon's signed rank test. Genes with a change P-value ≤ 0.01 (genes upregulated by IGFs) or ≥0.99 (downregulated genes) were selected. With two control arrays and two arrays hybridized with MCF7-IGF1 and MCF7-IGF2 each, a total number of eight comparison analyses were performed. The intersecting sets of genes regulated by IGF1, IGF2 or both were determined and those with a minimum 2-fold change in expression were selected.

[3H]thymidine incorporation assay
To determine DNA synthesis rates in cultures, 3000 cells were seeded per well of a 96-well plate and cultured for 24 h in DMEM/10% FCS. After medium removal and one wash with PBS, cells were further cultured in DMEM containing 0.5% FCS for 48 h. Cells were pulse labeled with 1 µCi [3H]thymidine (ICN) for 2 h and harvested on glass-fiber filters (Packard). Radioactivity incorporated into DNA was determined in a microplate scintillation counter (Packard). All values represent the average ± SD of triplicate measurements. Student’s t-test (unpaired, unequal variance) was used to compare the [3H]thymidine incorporation rates of IGF1- or IGF2-overexpressing cells to those of vector controls.

FACS analysis of cellular DNA content
Cells were plated as described for RNA isolation (2 x 104 cells/cm2, DMEM + 10% FCS). After 48 h, medium was changed and half of the samples were cultured further in DMEM containing 0.5% FCS. Cells were fixed in 70% ethanol and stained with PBS containing 40 µg/ml propidium iodide and 1 mg/ml RNAseA. DNA content was measured using a flow cytometer (FACSCalibur; Becton-Dickinson) and the percentage of cells in the various cell cycle phases was calculated using ModFitLT v2.0 software (Verity Software House).

Analysis of cell viability
A total of 5000 cells were seeded per well on a 96-well plate and cultured for 12 h in DMEM/10% FCS. Attached cells were carefully rinsed with PBS and further incubated in DMEM/0.5% FCS for 24 h. Cytotoxic drugs were added at the indicated concentrations, and cells were incubated for another 48 h. Cell viability was assessed using the MTS assay (Promega) according to the manufacturer's instructions. All values represent the average ± SD of triplicate measurements. For statistical analysis of the dose response curves, Pearson's correlation coefficients were used.

In vivo tumor formation assay
Cells were harvested by trypsinization, washed with PBS, counted and resuspended in Ringer solution at 3.5 x 107 cells/ml. Cells (107) were subcutaneously injected into immunodeficient, female, non-ovariectomized SCID/BALB/c recipient mice (nine individual mice per cell line; three independent injection experiments in separate weeks with three mice per cell line each were performed with comparable results). Tumor formation was examined periodically by palpation. The tumor volume was calculated from tumor size by the formula (diameter x diameter x length/2). The animals were killed and the tumors were surgically removed, 35–56 days after injection. All experiments were performed according to the Austrian guidelines for animal care and protection. Student's t-test (unpaired, unequal variance) was used to compare tumors formed by IGF1- or IGF2-overexpressing cells to those formed by vector controls.

Immunofluorescence
Cells were rinsed with Hank's Buffered Salt Solution (HBSS) and fixed for 30 min with 2.5% para-formaldehyde in HBSS. After three washes with HBSS, cells were permeabilized with 0.4% Triton X-100 in PBS. Cells were washed three times with PBS and reactive groups were quenched by incubation with 50 mM NH4Cl/0.1% glycine in PBS for 15 min. Unspecific protein–protein interactions were blocked by incubation with 0.05% fish skin gelatine (catalog no. GEL10; British Biocell International) in PBS for 30 min at room temperature. After three washes with PBS, cells were incubated with primary antibody diluted in 0.05% fish skin gelatine solution for 2 h at room temperature. The following antibodies were used at 1:100 dilutions: ß-catenin, Transduction Laboratories catalog no. C19220 [GenBank] ; E-cadherin, Transduction Laboratories catalog no. 610404. After three washes with PBS, cells were incubated with anti-mouse secondary antibody (1:1000; Molecular Probes catalog no. A-21121) for 30 min. Cells were washed three times with PBS and once with water, dried and cover-slipped. Images were taken with a TCS-SP confocal microscope (Leica, Heidelberg, Germany) with a 60 x 1.3 NA lens objective and immersion oil (n = 1.518).

Western blot analysis
Whole cell lysates were prepared by directly lysing the cells in SDS sample buffer (60 mM Tris, pH 6.8, 1% SDS, 0.005% bromphenol blue and 10% glycerine) and heating at 95°C for 10 min. DTT was added to 20 mM final concentration. The following antibodies were used at 1:1000 dilutions: ß-catenin (catalog no. C19220 [GenBank] ; Transduction Laboratories); E-cadherin (catalog no. 610404; Transduction Laboratories); and ß-actin (catalog no. A1978; Sigma). Anti PLAB antibody (catalog no. 07–217; Upstate) was diluted 1:500.

Immunohistochemistry
Tumors were fixed in 4% phosphate-buffered formaldehyde overnight at 4°C. For immunohistochemical analysis, paraffin-embedded sections (4 µM) were stained with a monoclonal antibody against proliferating cell nuclear antigen (PCNA) (1:100; Dako, Carpinteria, USA). Corresponding biotinylated secondary antibodies were used and visualization was performed with the vectastain ABC kit employing diaminobenzidine as substrate (Vector Laboratories, Burlingame, USA). For each cell line, three areas of three independent tumors were selected (>3000 cells per cell line) and PCNA positive cells were counted. Student's t-test (unpaired, unequal variance) was used to compare tumors formed by IGF1- or IGF2-overexpressing cells to those formed by vector controls.

Quantitative real-time RT–PCR
First strand cDNA was synthesized from total RNA using random primers (catalog no. 4322171; Applied Biosystems). The amount of cDNA reverse transcribed from 100 ng total RNA was used per RT–PCR. TaqMan RT–PCR was performed using the ABI PRISM 7000 Sequence Detection System and ‘Assay-on-Demand’ TaqMan probes and primers according to the manufacturer’s instructions (Applied Biosystems). For each data point, duplicate samples were analyzed in parallel. Duplicate assays of serial dilutions of a cDNA standard (cultured normal breast epithelial cells) were included in each experiment. Transcript levels were normalized to those of ß-actin to account for variability in the amount of cDNA in each sample, and relative expression levels were calculated using the {Delta}{Delta}CT-method (25).


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Expression of the IGF signaling system in human breast cancer cells
A panel of 17 breast cancer and 4 normal mammary epithelial cell lines (HMEC, MCF10A, MCF10F and Hs 571.Bst) was subjected to expression profiling with Affymetrix HG-U133A oligonucleotide microarrays (U.Vinatzer, S.Oehler and M.Schreiber, unpublished data). To determine the expression of the components of the IGF signal transduction cascade in this dataset, one optimal probe set each was selected for IGF1 and IGF2, IGF1R and IGF2R, IGFBP1-6, INS, the INSR, the INSR substrates 1 and 2 (IRS1/2), and for ESR {alpha} and ß (ESR1/2). The expression of these genes in each cell line was compared to the median expression in the 21 cell lines, thus yielding relative expression levels (Figure 1A). IGF1, IGF2 and INS were not expressed at appreciable levels in any of the 21 cell lines. In agreement with published data, a strong correlation between IGF1R and ESR1 expression was observed (15,16). Clustering was performed based upon these 16 genes. One of the clusters obtained consisted of five cell lines (BT474, T47D, Kpl1, MCF7 and ZR75-1) and was characterized by high expression levels of IGF1R, ESR1, and IGFBP2 and IGFBP4, and weak expression of IRS2, IGFBP3 and IGFBP6 (Figure 1A). MCF7 and Kpl1 in addition expressed low levels of IGF2R and high levels of IRS1 (Figure 1A and Supplementary Table 1). MCF7 cells, which are known to be responsive to IGF stimulation were selected for further analysis (26,27). Next, MCF7 breast cancer cells were compared with three normal breast-derived epithelial cell lines (HMEC, MCF10A and MCF10F) with respect to the expression of the IGF axis and the downstream PI3K and MAPK signaling cascades, as determined with Affymetrix U133A and B arrays. Probe sets specific for the genes of interest were selected in NetAffx (21), and median expression in three independent cultures of MCF7 cells was compared with the median expression in the three normal cell lines, yielding fold changes. Compared with untransformed mammary epithelial cells, MCF7 cells expressed very high levels of ESR1, IGF1R, IRS1, GRB2, N-RAS and ERK2, whereas INSR expression was unchanged and the expressions of IGF2R, IRS2, SHC1, H-RAS, A-RAF, MEK1 and ERK1 was reduced (Figure 1B).


Figure 1
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  		Fig. 1 (A) Quantitative expression analysis of the genes of the IGF signaling system in a panel of 17 breast cancer and 4 normal mammary epithelial cell lines (HMEC, MCF10A, MCF10F and HS578Bst). Genes (rows) and cell lines (columns) were clustered to group those with similar expression patterns together. Colors indicate the most highly expressed genes (bright red), the least expressed genes (bright green) and the genes whose expression is equal to the average of the 21 cell lines (black; see color bar to the right). Color intensities indicate the level of trust of the indicated relative expression levels, e.g. INS expression levels are not significantly above background, indicated by hazed colors. Note that no significant expression of IGF1, IGF2, INS and IGFBP1 was detected in any of the cell lines. (B) Expression of the IGF signal transduction cascade in MCF7 breast cancer cells. Three independent cultures of MCF7 cell lines were compared to three normal mammary epithelial cells (HMEC, MCF10A and MCF10F). Color codes of the boxes containing gene names are as described for (A). As a simplification, the interactions of the IRS proteins with GRB2/SOS are not shown. Expression data, trust values and fold changes are provided in Supplementary Tables I and II.

 
Generation and phenotypic analysis of MCF7 cells stably overexpressing IGF1 or IGF2
MCF7 cell lines stably overexpressing IGF1 or IGF2 (termed MCF7-IGF1 and MCF7-IGF2) and control cells containing an empty expression vector (termed MCF7-vector) were generated by transfection and subsequent selection with G418. ELISA of cellular supernatants confirmed that these transfected cells indeed stably and potently overexpressed IGF1 and IGF2. Quantification revealed that 41 ng/ml IGF1 and 100 ng/ml IGF2 were secreted in 48 h by 106 MCF7-IGF1 and MCF7-IGF2 cells, respectively, whereas the levels in control cells were below the limit of detection of ~1 ng/ml (Table I). Similarly, the mRNA levels of IGF1 and IGF2 were >10-fold increased in the overexpressing cell lines, as revealed by GeneChip analysis (Tables III and IV). This constitutive overexpression of IGFs caused an increased activation of downstream signaling molecules such as AKT (M. Pacher and M. Schreiber, unpublished data). Malignant conversion is often accompanied by a conversion of epithelial cells into migratory, fibroblastoid cells, a process known as epithelial–mesenchymal transition (28). To test this possibility, the epithelial morphology of MCF7-IGF1 and MCF7-IGF2 cells was assessed by phase contrast microscopy, immune fluorescence and western blot analysis of key epithelial marker genes (Figure 2). Both MCF7-IGF1 and MCF7-IGF2 cells appeared phenotypically normal in phase contrast microscopy (Figure 2A). Moreover, both the expression levels and membrane localization of the epithelial markers E-cadherin and ß-catenin were unaffected by IGF1 and IGF2 overexpression (Figure 2B and C). Thus, the continuous presence of high levels of IGF1 or IGF2 does not alter the epithelial characteristics of breast cancer cells.


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  		Table I IGF1/2 secreted into 1 ml medium by 106 cells in 48 h

 


Figure 2
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  		Fig. 2 Phenotypic analysis of MCF7 cells overexpressing IGF1 or IGF2. Phase contrast microscopy of untransfected (MCF7-untrans.), control (MCF7-vector), IGF1-overexpressing (MCF7-IGF1) and IGF2-overexpressing (MCF7-IGF2) cell lines (A), and immune fluorescence detection (B) and western blot analysis (C) of the key epithelial markers E-cadherin and ß-catenin is shown.

 
Mitogenic and tumorigenic effects of stable IGF1 or IGF2 overexpression
To determine the impact of IGF1 and IGF2 overexpression on the rates of DNA replication and cell proliferation, [3H]thymidine incorporation assays and FACS analysis of propidium idodide stained cells were performed. [3H]thymidine incorporation rates were more than doubled in both MCF7-IGF1 and MCF7-IGF2 cells grown in 0.5% FCS (P < 0.05, Student's t-test), indicating that long-term stimulation with IGF1 and IGF2 potently induced cell proliferation (Figure 3A). This was confirmed by FACS profiles, which revealed that IGF-overexpressing cells divide significantly faster in 0.5% serum (Figure 3B; ~23% S-phase versus ~10% S-phase in controls). In 10% serum, cell cycle distribution was comparable in all cell lines (Figure 3B; ~30% S-phase). The fraction of apoptotic (sub-G1) cells was unaffected by IGF overexpression (Figure 3B). To assess their tumorigenicity, MCF7-vector, MCF7-IGF1 and MCF7-IGF2 cells were subcutaneously injected into female, non-ovariectomized SCID/BALB/c recipient mice. MCF7-vector control cells were hardly tumorigenic, and small tumors of ~20 mm3 were detectable upon injection of 107 cells, which did not grow until day 35 and even until day 56, when the last six animals were sacrificed (Figure 3C). Moreover, only four out of nine mice formed tumors by day 35. Conversely, seven out of nine mice each formed tumors upon injection of MCF7-IGF1 and MCF7-IGF2 cells already by day 26. In contrast to MCF7-vector cells, these tumors were clearly growing, albeit slowly, and attained a size of >50 mm3 by day 30 (Figure 3B). From day 16 on, the difference in tumor volume between control and MCF7-IGF1, but not MCF7-IGF2 cells was significant (P < 0.05) or even highly significant (P < 0.01, Student’s t-test; Figure 3C). Tumors were analyzed by immunohistochemical staining for PCNA, an S-phase specific protein (Figure 3D). IGF1- and IGF2-overexpressing tumors contained ~35% more cells in S-phase (i.e. PCNA positive tumor cells) than controls (P < 0.001, Student’s t-test), in agreement with the fact that these tumors are larger, and with the in vitro thymidine incorporation and FACS analyses (Figure 3). Colony forming efficiency in soft agar was only slightly increased in MCF7-IGF1 and MCF7-IGF2 cells, and no increase in cell motility could be observed, e.g. in Matrigel transwell migration assays (data not shown). Thus, the IGF-induced increase in malignancy appears to be due to stimulation of cell proliferation and self-sufficiency in growth signals rather than an enhanced anchorage-independent growth or migratory potential.


Figure 3
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  		Fig. 3 Overexpression of IGF1 and IGF2 in MCF7 cells increases their cell proliferation rates and efficiency of tumor formation. (A) [3H]thymidine incorporation assay. The indicated cell lines were grown for 48 h in medium containing 0.5% serum, and the amount of radioactive thymidine incorporated into cellular DNA was quantified. Incorporation rates in cell lines overexpressing IGF1 or IGF2 were about twice those of untransfected cells or vector controls. (B) FACS analysis of cell cycle profiles of the indicated cell lines grown in 0.5 and 10% serum. (C) Tumor formation in female SCID/balb/c mice. Cells (107) suspended in 0.3 ml Ringer solution were injected subcutaneously (three mice per cell line). This experiment was repeated twice with independent cell cultures in separate weeks, and the combined results of all three experiments (nine mice per cell line) are shown. Tumor formation was periodically monitored by palpation at the indicated days until the animals were sacrificed. Tumor volume was determined as described in Materials and methods. The number of tumors formed by each cell line at each time point is shown below the graph. (D) PCNA staining of tumors isolated at day 35. Three independent tumors per cell line were immunohistochemically stained for PCNA. *P < 0.05; **P < 0.01; ***P < 0.001 (unpaired Student’s t-test, one-sided P-values).

 
Chemoresistance of IGF-overexpressing cells
MCF7 cells represent a typical model for investigating chemoresistance (29). Here, MCF7-IGF1, MCF7-IGF2 and control cells were exposed to increasing concentrations of a panel of cytotoxic drugs commonly used in the chemotherapy of human cancer. The viability of drug-exposed cells was determined relative to untreated controls with MTS assays. MCF7 cells exhibited a pronounced resistance to taxol, but the number of viable cells dropped to <20% of untreated controls at higher concentrations (50 µM taxol, i.e. 800% of the peak plasma concentration used in the chemotherapy of breast cancer patients; Figure 4A). IGF1 and IGF2 overexpression did not lead to an increased resistance of MCF7 cells towards this taxol-induced growth inhibition (Figure 4A). An increased resistance of MCF7-IGF1 or MCF7-IGF2 cells was also not observed with novantron (Figure 4B). In contrast, IGF1 and IGF2 overexpression moderately increased the resistance of MCF7 cells to 5-fluoro-uridine and cisplatin (Figure 4C and D). The observed effects were not statistically significant. In all cases, the effects of IGF1 overexpression were almost identical to those of IGF2 overexpression (Figure 4). Pro-survival effects of IGFs protecting breast cancer cells from apoptosis induced by chemotherapy and/or radiation therapy have been reported previously (30–32). Importantly, the parental MCF7 cell line used by us lacks a functional caspase 3 (33), and displayed a high level of drug resistance compared to 16 other breast cancer cell lines, with IC50 values, e.g. for taxol >10 µM (S. Oehler and M. Schreiber, unpublished data). Presumably, this high basal level of drug resistance could not be further enhanced to a large extent by IGF1/IGF2.


Figure 4
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  		Fig. 4 Effect of cytotoxic drugs on the viability of MCF7-IGF1, MCF7-IGF2 and control cells. Cells were grown for 48 h in the presence of the indicated concentrations of taxol (A), novantron (B), 5-fluoro-uridine (C) and cisplatin (D). The fractions of viable cells at each drug concentration (% of untreated controls) were quantified using MTS assays.

 
Genome-wide expression profiling of IGF-overexpressing cells
Total RNA was prepared from two independent cultures each of MCF7-vector, MCF7-IGF1 and MCF7-IGF2 cell lines (biological replicates), labeled, and hybridized to Affymetrix HG-U133A and HG-U133B GeneChips. At the culture conditions used for RNA extraction, all cells were actively proliferating (Figure 3B, 10% serum). We compared each of the 11 probe pairs per gene/probe set individually between each pair of samples (comparison analysis), thus increasing the reliability of the observed changes in gene expression and allowing to determine change P-values. This approach ensured a comprehensive, reliable, biologically and statistically solid analysis of IGF-induced changes gene expression. To identify genes differentially regulated by IGF1 and IGF2, we selected all genes exhibiting a change P-value of ≤0.01 (upregulated genes) or ≥0.99 (downregulated genes) and an at least 2-fold change in expression compared with MCF7-vector control cells. A total of 21 genes were found to be upregulated by both IGF1 and IGF2, 9 genes were upregulated by IGF1 but not IGF2, and 9 genes were upregulated by IGF2 but not IGF1 (Tables II–IV). Six genes were downregulated >2-fold by IGF1, whereas no genes were significantly downregulated by IGF2 (Table V). Importantly, most of the genes identified as being regulated by IGF1 but not IGF2 by these criteria were in fact also regulated by IGF2 (and vice versa); however, this regulation was either <2-fold or did not fulfill the filtering criteria for the change P-value (Tables III and IV). Thus, IGF1 and IGF2 induced very similar biological and transcriptional responses. Among the upregulated genes was vascular endothelial growth factor (VEGF), a known IGF target gene, and also genes that were not associated previously with IGF signaling. Interestingly, the largest group of genes upregulated by IGF1/IGF2 plays an essential role in amino acid synthesis and import as well as protein synthesis and stability. This group of IGF-induced genes included several enzymes involved in amino acid biosynthetic pathways [asparagine synthetase (ASNS), argininosuccinate synthetase (ASS), phosphoglycerate dehydrogenase (PHGDH) and phosphoserine phosphatase (PSPH)], several amino acid transporters (SLC7A11, SLC7A5, SLC1A4 and SLC3A2), methionyl-tRNA synthetase and the chaperone DNAJB9 (Table II).


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  		Table II Genes upregulated by IGF1 and IGF2

 


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  		Table III Genes upregulated by IGF1

 


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  		Table IV Genes upregulated by IGF2

 


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  		Table V Genes downregulated by IGF1

 
Confirmation of the microarray results
To validate the microarray results with an independent method, quantitative real-time RT–PCR was performed. The expression levels of 10 genes were quantified in duplicates using TaqMan real-time RT–PCR with ß-actin as a reference (Figure 5A). Expression levels in MCF7-IGF1 and MCF7-IGF2 cells were determined relative to those in MCF7-vector control cells, thus yielding fold changes, and were compared with the fold changes obtained by GeneChip analysis. This analysis revealed that results obtained by microarray analysis and real-time PCR exhibited a very high concordance, except for a single gene, TRIP-Br2 (Figure 5A). An overall correlation coefficient of 0.9 and 0.8 between microarray and real-time PCR results was determined in MCF7-IGF1 and MCF7-IGF2 cells, respectively. Protein levels of PLAB, one of the upregulated genes, are doubled in IGF-overexpressing cells compared with controls, as shown by western blot analysis (Figure 5B). Cyclin D1 (CCND1) was unaltered at the mRNA and protein level in IGF-overexpressing cells (Figure 5A and B).


Figure 5
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  		Fig. 5 Correlation of the expression levels of 10 genes determined with oligonucleotide microarrays and with quantitative real-time RT–PCR. (A) Fold changes relative to MCF7-vector control cells obtained by microarray analysis and real-time RT–PCR in MCF7-IGF1 and MCF7-IGF2 cells are shown. (B) Western blot anaylsis of PLAB and Cyclin D1 in MCF7 control and IGF-overexpressing cell lines. ß-Actin was used as a loading control.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
The growth-promoting, mitogenic and anti-apoptotic functions of IGFs play a key role in the initiation and progression of breast cancer. Recently, potent antitumor activities were demonstrated for selective IGF1R kinase inhibitors, making the IGF signaling system and/or its target genes a promising potential intervention site for breast cancer therapy (34,35). To monitor the efficacy of such targeted therapies, and to facilitate early detection of potential adverse side effects, identification of diagnostic biomarkers/target genes of long-term IGF stimulation is critical. As an initial survey for biomarker discovery, we stably overexpressed IGF1 and IGF2 in human breast cancer cells to systematically screen for IGF target genes via genome-wide expression profiling, and to determine the effects of long-term IGF stimulation on cell cycle progression, chemosensitivity and tumor formation in xenograft experiments, which are cellular phenotypes highly relevant for tumorigenesis.

First, we compared the expression of the IGF signaling system in 21 cell lines (Figure 1A and Supplementary Table I). A cluster of five cell lines (BT474, Kpl1, T47D, MCF7 and ZR75-1) expressed high levels of ESR1, IGFBP2 and IGFBP4, and low levels of IGFBP3. Three of these five cell lines (MCF7, T47D and ZR75-1) have been reported to proliferate in reponse to IGF stimulation (26,27,36,37). MCF7 cells were selected for further analysis. This cell line expressed high levels of positive regulators of IGF signaling (IGF1R, IRS1 and ESR1), and low levels of negative regulators (IGF2R and IGFBP3). HS578T cells, which are known to be unresponsive to IGF stimulation, express much less IGF1R, IRS1 and ESR, and far more IGF2R and IGFBP3 (Supplementary Table I) (26,27). Although mRNA levels do not directly translate to protein levels, localization and activity, mRNA expression profiles provide a useful starting point for the pre-selection of a cell line, and to exclude those cell lines which express, for example, no or very little IGF1R mRNA and are thus unlikely to respond to IGFs. The comparison of the MCF7 cell line with three normal cell lines showed that at the mRNA level, ESR1 and IGF1R are clearly overexpressed. The expression of IGFBP4 and IGFBP5 was absent in normal cell lines and highly positive in MCF7 cells. In addition, numerous other signaling components showed differential expression at mRNA levels (Figure 1B and Supplementary Table II). Although microarray analyses are necessarily limited to the mRNA levels of all genes, this multitude of changes between non-malignant, differentiated cells and a malignant cell line might ultimately lead to different responsiveness to growth factors and other environmental signals.

Via overexpression, activating mutations or other mechanisms, constitutive dysregulation of growth factor signaling is a key and frequent event in tumorigenesis (38). Stable overexpression resembles this aberrant activation in tumors more closely than the merely transient effects of exogenously added growth factors. To determine the effects of long-term IGF stimulation, we stably overexpressed IGF1 and IGF2 in MCF7 human breast cancer cells. Constitutive IGF stimulation had profound effects on cell cycle progression and malignancy (Figure 3). Overexpressing cells efficiently formed tumors in mouse xenograft experiments, whereas parental MCF7 cells were essentially non-tumorigenic, and only formed small, non-growing tumors upon injection of a large number of cells (107) with a low efficiency. These IGF-overexpressing tumors had a significantly higher fraction of cells in the S-phase of the cell cycle, consistent with in vitro cultures in the presence of limiting amounts of exogenous growth factors. Our mice were not supplemented with estrogen, which is generally required to support the efficient growth of xenografts of estrogen-dependent MCF7 breast cancer cells. This may explain why tumors from the control cells formed with low efficiency and did not grow throughout the experiment, and may indicate that constitutive IGF overexpression is able to abrogate the need for high estrogen in MCF7 cells to some extent. The resistance to various chemotherapeutic agents was very high in the parental cell line and could not be enhanced further by IGF overexpression. A potential explanation for this might be that MCF7 cells are lacking functional caspase 3 and are therefore more resistant to various apoptosis inducing agents (33).

For a systematic survey of the downstream target genes of IGF signaling in the context of human breast cancer, expression profiling of overexpressing cells was performed employing oligonucleotide microarrays containing probe sets for essentially all human genes. All hybridizations were performed in biological replicates, thus minimizing false positives. Agreement with data obtained by real-time RT–PCR was very high. We found that 21 genes were at least 2-fold upregulated by both IGF1 and IGF2. The global patterns in gene expression indicated broadly overlapping functions of IGF1 and IGF2, in spite of their different affinities for IGF1R, IGF2R and IGF1R–INSR heterodimers (6,39). VEGF, a well-established IGF target gene especially in colorectal cancer, is among the upregulated genes (40,41). Owing to its angiogenic effects, VEGF plays an important role in tumorigenesis, and its upregulation may contribute to the known effects of IGFs to promote malignancy. Caveolin-1 mRNA is clearly detectable, although at low absolute levels, in MCF7 cells and downregulated ~2-fold upon IGF1 overexpression. The genomic locus of caveolin-1 is methylated in MCF7 cells. As a consequence, caveolin-1 protein is reduced to undetectable levels (42,43). As the levels of caveolin-1 are already very low in the parental cell line, the potential effects of caveolin-1 downregulation by IGF stimulation should be addressed separately using a more suitable cell line.

Among the genes most prominently upregulated by IGF1 and IGF2 are several amino acid transporters, i.e. SLC7A11, SLC7A5 and SLC1A4. SLC7A11 and SLC7A5 both bind to the activating peptide SLC3A2, which was also upregulated by IGF1 and IGF2. SLC7A5 is a transporter for large neutral amino acids, particularly branched and aromatic amino acids such as Gln, His, Ile, Leu, Met, Phe, Trp, and Tyr (45–47). SLC7A5 is expressed in most tumors and tumor cell lines, indicating an important role in cancer. SLC7A11 primarily exchanges extracellular anionic cysteine for intracellular glutamate (44,45). The SLC1A4 transporter exchanges Na+ for small neutral amino acids such as Ala, Ser, Cys and Thr (48). In addition to these transmembrane proteins required for amino acid import, key factors involved in amino acid biosynthesis and metabolism are upregulated by IGFs: methionyl-tRNA synthetase (MARS) is the only mammalian methionyl-tRNA synthetase and therefore critically involved in the initiation of translation, which is frequently increased in tumor cells. ASNS and ASS are catalyzing two ATP consuming steps and thus hardly reversible steps in the biosynthesis of asparagines (49). PHGDH and PSPH catalyze the first and third step in the biosynthesis of serine, glycine and cysteine (49). DNAJB9 and HERPUD1, both also upregulated by IGF1 and IGF2, are involved in the unfolded protein stress response, which is elicited by unfolded or damaged proteins, and also by growth factor stimulation, via enhanced protein synthesis (50).

IGFs, similar to INS, can increase the cellular uptake of glucose and amino acids and stimulate glycogen and protein synthesis (17). The group of genes with a key role in amino acid import and biosynthesis, whose coordinate upregulation was identified here, provides a novel mechanistic basis for these effects. In addition, cysteine uptake, as mediated by SLC7A11, and its reduction are the rate-limiting steps for biosynthesis of gluthathione (GSH), the major intracellular thiol antioxidant (45). Elevated GSH levels are thought to be necessary for cell survival upon oncogenic transformation and/or constitutive growth factor stimulation, which induces chemical stress by superoxide or hydrogen peroxide production and release (51). Moreover, the accelerated DNA replication observed in IGF1-/IGF2-overexpressing cells requires an increased purine and pyrimidine synthesis. Indeed, ASNS and ASS play a key role in the biosynthesis of asparagine, which is an essential precursor for the synthesis of pyrimidine bases. Similarly, PHGDH and PSPH are key enzymes in the biosynthetic pathway of glycine, which is the major purine precursor (49).

In summary, the majority of genes constitutively upregulated by IGFs are critically involved in amino acid transport and metabolism, protein biosynthesis and stability, and synthesis of nucleic acid bases and gluthathione. All of these processes are an absolute requirement for establishment and maintenance of the accelerated growth and proliferation rates which are a hallmark of tumor cells. Together with its potent mitogenic and anti-apoptotic activities, these concerted anabolic effects could make aberrant activation of IGF signaling a particularly powerful tumorigenic switch. Indeed, overexpression of IGF1 or IGF2 alone was sufficient to potently accelerate cell cycle progression and to induce tumor formation by MCF7 cells. The genes identified here by genome-wide expression profiling provide a useful starting point in the discovery of biomarkers for IGF signaling which warrant further validation in human breast tumors. Moreover, this class of protein synthesis genes now found to be coordinately upregulated by IGF signaling could also significantly contribute to cell growth in normal development.


   Acknowledgments
 
Plasmids with cDNA inserts for IGF1 and IGF2 were kindly provided by Xiao Tu (T.Jefferson University, Philadelphia: IGF-1B-Plasmid) and Graeme I.Bell (Howard Hughes Medical Institute, University of Chicago- phIGF2/pKT218-Plasmid). HMEC cells were kindly provided by Martha R.Stampfer, Lawrence Berkeley National Laboratory, Berkeley, California. We thank Rudolf Oehler and Norbert Kraut for critically reading the manuscript and helpful comments, and Margit Rosner for help with the FACS analysis. This work was supported by funds of the Austrian Ministry of Education, Science and the Arts (Austrian Genome Research Program GEN-AU), the Austrian Central Bank (OeNB, #9339), and the Herzfeldersche Familienstiftung.

Conflict of Interest Statement: None declared.


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 Introduction
 Materials and methods
 Results
 Discussion
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Received September 15, 2005; revised May 19, 2006; accepted May 20, 2006.


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