Introduction

The MAGE antigens are proteins that were first discovered because they elicited cytotoxic T cell and humoral responses in patients with malignant melanoma (Knuth et al., 1989). The genes were called MAGE genes for the acronym Melanoma AntiGen Encoding gene (van der Bruggen et al., 1991; Basarab et al., 1999). The original MAGE antigens were found to be normally expressed only in male gametes and became the first proteins identified in what is now a much larger group of antigens that are expressed in "cancers" and testes, and that are known as Cancer Testes (CT) antigens (reviewed in Simpson et al., 2005). The original MAGE genes included MAGE-A, -B, and -C, which are encoded on the X chromosome and have been called CT-X-MAGE proteins. A number of autosomal gene families, named MAGE D through MAGE L, have more recently been found to be homologous with the MAGE-CT-X genes but appear to be more widely expressed and include some genes which are expressed in all normal tissues (Pold et al., 1999; Chomez et al., 2001). In this report, we will concentrate on the CT-X-MAGE proteins which, because of their tendency for expression in many "cancers" and hematopoetic malignancies and their very limited expression in normal adult tissues, have been used as tumor specific targets for immunotherapy of melanoma and other malignancies (Park et al., 1999; Brossart, 2002; Coulie et al., 2002; Kim et al., 2002; Sun et al., 2002; Godelaine et al., 2003; Zhang et al., 2003; Lonchay et al., 2004; Akiyama et al., 2005; Simpson et al., 2005). The functions of most MAGE proteins remain unknown but several studies have shown correlations between CT-X-MAGE expression and tumor development, aggressive clinical course, or resistance to chemotherapeutic agents (Bertram et al., 1998; Park et al., 2002; Duan et al., 2003; Glynn et al., 2004; Hoek et al., 2004; Gure et al., 2005; Huff, 2005; Jungbluth et al., 2005; Simpson et al., 2005). However, it has not yet been determined whether CT-X-MAGE gene expression is a functionally irrelevant by-product of cellular transformation or could actually contribute to the development of malignancies (Simpson et al., 2005).

There is a high degree of homology between CT-X-MAGE family proteins and they are often co-expressed, suggesting that many perform common or complementary functions (Lucas et al., 1998; Chomez et al., 2001; Simpson et al., 2005). For instance, MAGE-A3 and MAGE-A6 differ mainly in untranslated regions and show 98% identity at the nucleotide level in their coding regions. Similarly, the murine mMage-b family, composed of mMage-b1, b2, and b3, are 98–99 and 97–100% identical at the nucleotide and amino-acid levels. Due to these factors and due to a lack of antibodies that can differentiate between nearly identical sub-family members, most studies of CT-X-MAGE gene expression rely on detection of mRNA, usually by reverse transcription followed by the PCR (RT-PCR) (Lucas et al., 1998; Chomez et al., 2001; Simpson et al., 2005). Using mRNA micro-array analysis, we recently found that MAGE-A1, 2, 3, 5, 6, 12, and C2 are expressed in the HMC1.1 human mast cell line and that they are coordinately downregulated during growth inhibition and induction of apoptosis by Imatinib (Gleevec), a KIT kinase inhibitor (Kanakura et al., 1994; Ma et al., 2002; Yang et al., in preparation). This observation suggested to us that CT-X-MAGE proteins might be involved in control of cell viability and prompted us to look for CT-X-MAGE molecule function by small interfering RNA (siRNA) knockdown of the MAGE genes expressed by HMC1.1 cells and in the p815 murine mast cell line. We found that siRNA suppression of select CT-X-MAGE genes decreases cell growth in vitro and in vivo.

Results

Suppression of MAGE genes inhibits cell viability

Microarray analysis showed that HMC1.1 cells express significant amounts of mRNA encoding MAGE-A1, A2, A3, A5, A6, A12, and MAGE-C2, but only negligible amounts of MAGE-B mRNA and no detectable MAGE-B protein by immunoblotting (data not shown). We did not perform microarray analysis on the murine P815 mast cell line, but we used real-time RT-PCR to determine mRNA levels encoding murine CT-X-mMage family proteins including mMage-a and mMage-b (there is no mMage-c). As mentioned, the mMage-b1, mMage-b2, and mMage-b3 subfamily members have coding regions that are 98–99% identical at the nucleotide level and 97–100% identical at the amino-acid level, so we considered them to be functionally equivalent. Therefore, our real-time PCR assay did not distinguish between different mMage-b family members. We found that unlike HMC1.1 cells, P815 cells express only very low levels of mMage-a family mRNA but they do express mMage-b mRNA at levels about 60-fold higher than the levels of mMage-a (data not shown).

Because the presumed functional equivalence of many of the MAGE proteins, we developed siRNA reagents that suppressed groups of highly homologous MAGE genes and allowed us to screen for general functions of these proteins. These reagents included the A complex reagent which is a pool of siRNA duplexes targeting all MAGE-A genes expressed in HMC1, except MAGE-A1. We used single reagents for MAGE-C2, the single MAGE-C protein expressed in HMC1, and for the mMage-b genes which, as mentioned, are essentially identical. Figure 1a shows representative results using siRNA targeting the MAGE family members expressed by HMC-1.1 cells, including siRNA oligomer pools targeting multiple MAGE-A family members (the MAGE-A complex reagent) and targeting individual MAGE genes (MAGE-C2). We found that cultures of HMC1 cells transfected with MAGE-A and MAGE-C2 siRNAs grew more slowly than cells transfected with control siRNA (Figure 1a). Figure 1a also shows that siRNA targeting the murine Mage-b genes (the mMage-b complex reagent) decreased the viability of P815 cells compared to control siRNA. In contrast, scrambled control and mMage-a siRNAs had almost no effect on p815 cells and MAGE specific siRNAs had no effect on the growth of MAGE negative HACAT cells.

Figure 1.

MAGE siRNAs inhibit MAGE gene expression and mast cell viability in vitro. (a) Select MAGE siRNA Smart-Pools inhibit the growth of human HMC1.1 and murine P815 mast cell lines, but not the HaCat transformed human keratinocyte cell line. The final concentration of each siRNA is 100 nM. Bars are shown as % of growth compared to non-transfected cells. Control bar (clear) is growth of nontransfected cells and is by definition 100%. Nonspecific bar indicates "non-sense" siRNA. Cells were counted 3 days after transfection with 100 nM siRNA in Lipofectamine 2000. MAGE-A complex reagent targets all MAGE-A genes expressed in HMC1.1 except MAGE-A1, which differs significantly in sequence from the other MAGE-A genes. The HMC1.1 cell line does not express significant protein levels of MAGE-B and the P815 line does not express significant levels of mMage-a family members. There is no murine homolog of the human MAGE-C family. The effective MAGE siRNAs showed a dose–response relationship between 50 and 150 nM (data not shown). ^* indicates statistical significant difference from nonspecific siRNA treated group, P<0.05. (b) Representative results with siRNAs targeting individual MAGE-A family members. Except A1, the rest of tested MAGE-A siRNAs showed growth inhibition in HMC-1.1 cells. (c) RT-PCR validates gene targeting by showing loss of amplifiable MAGE mRNAs after treatment with specific siRNAs. Twenty-four hours after transfection with 100 nM of siRNA, total RNA was extracted from cells, reverse transcribed, and amplified with primers bracketing the siRNA target sequences. Gel electrophoresis and staining with ethidium bromide show loss of amplimers with MAGE specific siRNA but not with control siRNA. Specific targeting in HMC1 cells was further validated by immunoblotting showing knockdown of MAGE-A total, MAGE-A1 or MAGE-C2 protein by MAGE-A complex, MAGE-A1, or MAGE-C2 siRNAs, respectively. HMC1.1 human mast cells were transfected with 100 nM MAGE siRNA in Lipofectamine 2000 and MAGE protein was identified by Western blotting 48 hours after transfection. Antibodies against effective individual MAGE proteins (A2, A3, A5, A6, and A12) were not available.

Full figure and legend (130K)

We next used siRNAs designed to target individual MAGE-A genes (Figure 1b). Because MAGE-A3 and MAGE-A6 are 99% identical in their coding regions and are considered functionally equivalent, we used a single siRNA pool to target both these genes. Significant growth inhibition was also seen with siRNAs targeting individual human MAGE-A genes in HMC-1.1 cells (Figure 1b), but not with MAGE-A1 and nonspecific siRNA controls. These experiments show that the effects of these siRNAs are sequence and target specific, making it highly likely that in vitro growth inhibition is a specific result of knocking down these MAGE genes. RT-PCR and immunoblotting when antibodies were available confirmed siRNA-mediated destruction of MAGE mRNA and suppression of protein expression (Figure 1c). Together these studies show that inhibition of specific MAGE gene expression can suppress the viability of mast cell lines in vitro.

Suppression of MAGE genes slows cell proliferation and induces apoptosis

To determine mechanisms of growth suppression by MAGE siRNAs, we concentrated on the effects of the human MAGE-A-complex (all expressed MAGE-As except A1) and murine Mage-b siRNAs, and looked at their ability to affect cell proliferation and to induce apoptosis. The different cell lines we studied had different doubling times, and when we performed preliminary time course experiments we found that apoptosis was induced in different cell lines at different times after siRNA transfection (data not shown). We further noted that significant apoptosis was induced in all cell lines within one half doubling time and that the number of viable cells was greatly reduced in all responding cell lines within the time of one full cell cycle (one full doubling time). We therefore decided to perform measurements of siRNA induced apoptosis at one half the doubling time of each cell line, in an effort to make the studies of different cell lines comparable. At one half doubling time after transfection with nonspecific siRNA, we found that 98% of both HMC1.1 and P815 cells were alive, with intact nuclei that showed the green fluorescence of acridine orange (Figure 2a–f), whereas 27.3% of P815 cells and 25.3% of HMC1.1 cells had condensed or fragmented nuclei that were stained by ethidium bromide and fluoresced red, indicating death by apoptosis at the same time point after transfection with MAGE siRNA. TUNEL analyses showed lower percentages of apoptotic cells, probably because the dead cells and fragmented nuclei were too fragile to survive even the most careful staining and analysis. However, flow cytometry still showed a significant increase in apoptosis (Figure 2g and h). Transfection with MAGE specific siRNA increased the percentage of cells undergoing apoptosis from 2.9 to 19.9% (HMC1.1 at 12 hour after transfection) and 0.29–18.3% (P815 at 3 hour after transfection). These percentages were not significantly changed in the presence of the caspase inhibitor zVAD-FMK (Figure 2g and h). In a limited series of experiments, similar results were seen with zVAD-BAF, and immunoblotting showed no increase in the cleaved form of caspase 3 in HMC1.1 cells after siRNA induction of apoptosis (data not shown). Using flow cytometry to analyze the cell cycle, we found that transfection with MAGE siRNA increased the percentage of cells in S phase. HMC1 cells showed an average of 31% of cells are in S phase after transfection with control siRNA, which increased to 46% in cells transfected with MAGE-A siRNA (Figure 3a). P815 cells showed 60% in S phase after treatment with mMage-b siRNA compared with 51% after treatment with nonspecific siRNA (Figure 3b). Similar results were observed in select experiments with BrdU incorporation analysis (data not shown). Together these studies show that CT-X-MAGE molecules play at least a permissive role in regulating proliferation of these cells and can function as inhibitors of a caspase independent pathway of apoptosis. Thus, expression of select MAGE proteins promotes viability of some mast cell lines by permitting proliferation and by preventing apoptosis.

Figure 2.

MAGE siRNAs induce apoptosis in mast cell lines. Fluorescence microscopy of acridine orange-ethidium bromide stained HMC1.1 cells ((a) 12 hour) and P815 cells ((d) 3 hour) after transfection with nonspecific siRNA shows that essentially all fluoresence green due to uptake of the vital dye acridine orange. After transfection with MAGE-A siRNA ((b) HMC1.1) or mMage-b siRNA ((e) P815), dead apoptotic cells show condensed and fragmented nuclei that stain red with ethidium bromide. (a and b) Bar=50 m and (d and e) bar=25 m. Statistically significant differences of 25.3% ((c) HMC1.1) and 27.3% ((f) P815) were seen in the number of dead apoptotic cells in MAGE siRNA treated cells vs nonspecific siRNA treated cells (P<0.05 HMC1.1, P<0.05 P815). (g and h) TUNEL analysis by flow cytometry at same times after transfection shows MAGE siRNA induced apoptosis is not inhibited by the general caspase inhibitor zVAD-FMK. The percentage of apoptotic cells is given in the upper right corner of each panel.

Full figure and legend (360K)

Figure 3.

MAGE siRNAs inhibit mast cell proliferation. Flow cytometry showed an increase in the percentage of cells in S phase after treatment with MAGE siRNAs. (a) HMC 1.1 cells were stained with PI showed 46% of cells in S phase 24 hour after transfection with MAGE-A complex siRNA, compared to 31% in S phase for cells treated with control siRNA. (b) Similar studies with P815 cells which had 60% in S-phase after mMage-b siRNA treatment compared with 51% after treatment with nonspecific siRNA. ^*Indicates statistical significant difference from nonspecific siRNA treated groups, P<0.05.

Full figure and legend (211K)

Suppression of mMage-b inhibits tumor growth in vivo

To determine whether MAGE siRNA can interfere with mast cell growth in vivo, we inoculated DBA mice with syngenic P815 mast cells that had been transfected with either mMage-b specific siRNA or a nonspecific control siRNA, and compared their growth with those of tumors formed from untreated cells. All 31 of the mice in this study developed tumors that reached the target mean diameter of 13 mm by day 35. The average time to a mean tumor diameter of 13 mm was 21 days among the mice receiving untreated control cells, 19 days for mice receiving cells treated with nonspecific siRNA, and 29 days for mice receiving cells treated with mMage-b siRNA. The Kaplan–Meier plot is shown in Figure 4a. The differences observed between mice receiving mMage-b siRNA treated cells as compared with mice receiving either untreated control or nonspecific siRNA treated cells were statistically significant with P<0.01, according to log-rank analysis. Linear Regression analysis of the Kaplan–Meier data showed that tumors grew an average of 0.63 mm per day postinoculation in the untreated control group, 0.62 mm per day in the nonspecific siRNA treated group, and 0.50 mm per day for the mMage-b siRNA treated group (Figure 4b). The differences observed for growth of tumors in mice receiving mMage-b siRNA treated cells as compared either control or nonspecific siRNA treated cells were statistically significant with P<0.01. These results show that knockdown of MAGE gene expression can inhibit tumor growth in vivo.

Figure 4.

MAGE siRNAs inhibit mast cell tumor growth in vivo. (a) Kaplan–Meier plot. P815 cells were transfected with 100 nM mMage-b siRNA (si-STABLE-PLUS, Dharmacon) or l00 nM control siSTABLE-PLUS siRNA, both administered in Lipafectamine™ 2000. After 6 hours, equal numbers of viable cells were injected subcutaneously into the flanks of syngenic DBA/2 mice and tumor size measured every other day by two independent and blinded investigators. (b) Linear Regression analysis shows that tumor diameters grew an average of 0.62 mm per day postinoculation in the nonspecific siRNA treated group and 0.50 mm per day for the mMage-b siRNA treated group, a statistically significant difference with P<0.01. The observed difference for mice with tumors treated with MAGE siRNA compared to mice with tumors treated with nonspecific siRNA was statistically significant with P<0.01 according to a log-rank analysis of both (c) mean and (d) median data. NS=non-specific siRNA.

Full figure and legend (113K)

Discussion

In this work, we have fulfilled criteria for demonstrating a 'classical' RNAi response including showing specificity of reagents, reduction of expression at the mRNA and protein level, and a biologic function, namely the suppression of cell viability and the induction of apoptosis (Pulverer, 2003). We have included irrelevant control siRNAs and our studies of individual siRNA components of the smart pools serve as multiplicity controls by demonstrating similar biologic effects with two or more siRNAs targeted to different sites in single target mRNAs. In addition, our results with MAGE-A1 siRNAs serve as additional specificity controls, since they are not effective at reducing cell viability and thus confirm that the biologic phenomenon we are studying is not a non-specific result of our siRNA preparations and procedures. The biological result is significant, with suppression of tumor cell growth in vitro and in vivo, and we have identified the basic mechanisms as the suppression of proliferation and the induction of apoptosis. Thus, our data clearly show that CT-X-MAGE proteins can promote cell viability and therefore can provide a growth advantage in neoplastic mast cells.

Little is known regarding the function of CT-X-MAGE molecules. Some studies suggest MAGE proteins can suppress cell viability; MAGE-A4 has been shown to suppress the tumorogenic activity of the liver oncoprotein gankyrin in vitro and in vivo in athymic mice, probably through binding to Miz-1 and downregulation of Cip-1 (Nagao et al., 2003; Sakurai et al., 2004). MAGE-A1 has been shown to act as a potent transcriptional repressor by binding to the Ski Interacting Protein and recruiting histone deacetylase 1, but the net effect of its expression has not been determined (Laduron et al., 2004). Transfection of human MAGE-A3 into a murine myoblast cell line appears to contribute to resistance to apoptosis induced experimentally by prolonged ER stress and human MAGE-A3 has been shown to bind to and inhibit murine caspase-12 in vitro (Morishima et al., 2002). However, the human orthologue of murine caspase 12 appears to be a pseudogene, producing products that are truncated and are without caspase function in most human populations, so the significance of this finding is unclear (Saleh et al., 2004). Recently, the acquisition of resistance to the chemotherapeutic drugs paclitaxel and doxorubicin by the human ovarian cancer cell line SKOV-3 has been associated with expression of multiple MAGE-A subfamily proteins (Duan et al., 2003). Furthermore, expression of MAGE-A family molecules has also been associated with progression of malignant gammopathies and their resistance to chemotherapy (Dhodapkar et al., 2003). Our data support these latter findings and provide the first insight into possible mechanisms for these associations.

It is interesting that so many of the CT-X-MAGE antigens we studied appear to have a similar function in these two different cell lines, although it is not surprising given the high degree of homology of many of these molecules. We do not find it anomalous that MAGE-A1 appears to have a different function than other CT-X-MAGE molecules, since it shows the least common homology among the MAGE-A genes we have studied. Most of the variability in the CT-X-MAGE genes occurs in the noncoding first and second exons, the site of the promoter regions, and their coding sequences predict the same main structural features for the corresponding proteins. These characteristics have previously led to the suggestion that the existence of multiple nearly identical members enables the same function to be expressed under different transcriptional controls (De Plaen et al., 1994). The fact that CT-X-MAGE genes are normally expressed mainly in the spermatogenic series from prespermatogonia through spermatocytes, during the meiotic division and proliferation stages (Takahashi et al., 1995; Rajpert-De Meyts et al., 2003; Yakirevich et al., 2003; Gaskell et al., 2004; Pauls et al., 2006) suggests that MAGE proteins may represent human equivalents of germ line apoptosis genes (Lettre et al., 2004). These genes have recently been shown to be involved in the maintenance of genomic stability and fertility in mammalian germ cells, and may play a role in stabilizing cells undergoing division with abnormal numbers of chromosomes. We speculate that developing neoplastic cells may co-opt these functions and use them to gain a small but real growth advantage. This hypothesis would help explain the increasing amount of correlative data that is accumulating, which suggest that expression of CT-X-MAGE proteins and other CT antigens may actually contribute to the development of malignancies (Bertram et al., 1998; Park et al., 2002; Duan et al., 2003; Glynn et al., 2004; Simpson et al., 2005).

Our desire to use a syngenic murine model and the fact that the P815 murine mast cell line expresses only mMage-b, which the human HMC1.1 cell line does not express, did not allow for a direct trial of exact homologs in the human and murine systems. However, the results of these early studies are dramatic with a significant increase in survival after a single treatment with siRNA. We speculate that survival could be further confirmed by systemic administration of multiple doses. Regardless, we believe our results are biologically relevant and can be generalized since we have obtained similar results with the same molecular targets in human melanoma cells and in a syngenic murine model of advanced melanoma using siRNAs delivered either before tumor implantation or systemically, after tumors are established (Yang et al., 2006, submitted). There is clearly more work to be done to investigate this phenomenon, both in vitro and in vivo. A careful dissection of the molecular pathway(s) involved and studies to identify CT-X-MAGE binding partners will be critical to understanding details of the functioning of individual CT-X-MAGE molecules, but the initial observations in our work merit a critical reappraisal of the clinical relevance of CT-X-MAGE gene expression. The CT-X-MAGE proteins were the first CT antigens discovered, and their limited tissue distribution has long been recognized as a potential key to tumor-specific treatment of many different malignancies (Simpson et al., 2005 and references therein). However, a central question remains as to whether expression of MAGE genes contributes to tumorigenesis or is an irrelevant by-product of the process of cellular transformation (Simpson et al., 2005). Our studies show unequivocally that in the right cellular milieu MAGE-A, MAGE-C2, and mMage-b proteins are capable of promoting survival, perhaps via a common mechanism. Inhibition of selected MAGE genes can decrease the viability of neoplastic mast cells in vitro and in vivo, and our data suggest a new paradigm for the clinical exploitation of MAGE gene expression in tumors.

Materials and Methods

siRNA preparations

All siRNA preparations were purchased from Dharmacon Inc., Boulder, CO. Initial in vitro studies used SmartPool reagents, which consist of a pool of up to four siRNA duplexes designed utilizing a proprietary algorithm targeting different sequences within a single gene or gene family. In the case of reagents identified as "complex", sequence target were picked in regions where multiple subfamily members had sequence identity so that one pool of duplexes allowed suppression of multiple highly homologous genes in a single subfamily, that is, the "A-complex" reagent was able to target all of the MAGE-A sub-family members expressed by HMC1.1, except MAGE-A1, and mMage-b complex reagents targeted all members of murine Mage-b family.

Transfection and cell viability

In vitro studies used Lipofectamine™ 2000 (Invitrogen, Carlsbad, CA) as a transfection reagent according to the manufactures directions. Cells were plated in antibiotic-free media in six-well plate (1 10⁵ cells/well) the day before transfection. Cells were washed once and 0.8 ml antibiotic and serum-free media was added to them. One, two, or three microliters of siRNA (50 M stock) were diluted into 184, 183, 182 l antibiotic, and serum-free media and 1.5, 3, or 4.5 l, of Lipofectamine™ 2000 reagent was diluted into 13.5, 12, or 10.5 l, respectively, of antibiotic and serum-free media in RNase free tubes, then kept at room temperature for 10 minutes. The diluted Lipofectamine was added to the diluted siRNA, mixed gently, and incubated at room temperature for 20 minutes, then added to the cell cultures to a final siRNA concentration of 50–150 nM. Cells were incubated for 4 hours at 37°C in a CO₂ incubator then 1 ml antibiotic-free growth media containing 2 serum was added to each well. Cell viability was determined 72 hours after transfection by counting cells that excluded Trypan blue. In selected experiments, cell viability was also determined by [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay (Sigma, St Louis, MO), which showed similar results to the Trypan blue assay (data not shown). Briefly, 2000–5000 cells were plated in 96-well plates and transfected with siRNAs as above. At 72 h after transfection, cells were washed with sterile phosphate-buffered saline. Five mg/ml of [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide in phosphate-buffered saline was diluted in serum-free medium to a final concentration of 0.5 mg/ml. One hundred microliters of [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide solution was added to each well and incubated at 37°C for 2 hours. Cells were washed then incubated at room temperature for 10 minutes in dark in 200 l DMSO. Optical density was measured at 570 nm.

Target validation

For validation of mRNA cleavage, total RNA was extracted from cells 24 hours post-transfection with 100 nM of siRNA and messenger RNA was reverse transcribed and amplified with primers bracketing the siRNA target sequences. Controls included RT-PCR amplifications of GAPDH (human) or -actin (murine) mRNA were performed in parallel for each MAGE RT-PCR amplification to confirm the presence of adequate mRNA and the specificity of the mRNA cleavage. For protein target validation, cells were lysed in 50 mM Tris-HCl lysis buffer (pH 7.4) containing 150 mM NaCl, 1 mM EDTA, 1% NP-40, 1 mM sodium fluoride, 1 mM sodium orthovanadate, and protease inhibitor cocktail 48 hours after transfection. Total cell lysates were electrophoresed, blotted in a Tris-Glycine buffer onto PVDF membrane (Bio-Rad, Hercules, CA), and probed with anti-human MAGE-A antibody (monoclonal, Zymed laboratories Inc., South San Francisco, CA), MAGE-A1 (monoclonal, Santa Cruz, CA), or MAGE-C2 (monoclonal, kindly supplied by Ludwig Institute for cancer research, New York, NY) and detected with enhanced chemiluminescence. Antibodies specific for mouse Mage proteins expressed by the cells in these experiments were not available.

Proliferation assays and apoptosis assays

Cell cycle analysis was performed using flow cytometry and BrdU incorporation or PI staining. Approximately one doubling time for each cell line after siRNA transfection (24 hour for HMC1.1 and 6 hour for P815) cells were fixed for analysis. For PI staining, the cells were stained with PI/RNase A staining buffer after being fixed. For BrdU incorporation, cells were incubated with 20 M of BrdU for 30 minutes immediately before fixing and stained with anti BrdU, according to recommended protocol (FITC BrdU Flow Kit, Pharmingen™, San Diego, CA). Data were acquired on a Becton Dickenson Calibur and analyzed with ModFit LT software for PI staining or CELLQuest™ software for BrdU-FITC staining. For TUNEL assays we used APO-BrdU™ Tunel Assay Kit (Molecular Probes, Eugene, OR). Cells were fixed approximately one half doubling time after siRNA transfection (12 hour for HMC1.1 and 3 hour for P815) and DNA breaks were labeled with BrdUTP in the presence of deoxynucleotidyl transferase. BrdU incorporation at DNA break sites was detected with an Alexa Fluor 488 dye-labeled anti-BrdU antibody. Data were analyzed with CELLQuest™ software. Apoptosis/programmed cell death was also determined by fluorescence and morphologic analysis following staining with acridine orange and ethidium bromide, according to the standard protocols (Squier and Cohen, 2001; Ribble et al., 2005). Staining in these studies was performed at varying time points from 90 minutes to 36 hours after siRNA transfection. Photomicrographs were taken as digital images on a Bio-Rad Radiance 2100 MP Rainbow Confocal/Multiphoton System using LaserSharp 5.2 software, or on a Nikon Optiphot microscope equipped for epi-illumination using Plan 4/0.13 160/-, Plan 10/0.30 160/0.17, Plan 20/0.50 160/0.17, Plan40/0.70 160/0.17 lenses. Sequential identical fields were acquired using B1-E or G1-B filters, an Insight/Spot photocollector, and a Dell Optiplex 260 computer using SPOT V3.5.6 software (Diagnostic Instruments, Inc., Sterling Heights, MI). Files were saved in TIFF format, signals from the red or green channels were merged using Adobe Photoshop CS2, and saved as JPEG files for export to Microsoft PowerPoint where they were sized and cropped for final presentation. To count live and dead cells, merged images were inverted and printed in black and white on a Hewlett-Packard Laser Jet 4 printer. Ethidium bromide positive dead cells (red) were circled while referencing the colored merged images and all cells in each field were marked as they were counted.

In vivo studies

P815 murine mast cells were injected subcutaneously into the flanks of syngenic DBA/2 mice. Mice were palpated for tumors by two blinded independent investigators beginning on day 7. When tumors reached measurable size, a digital vernier caliper was used to take two measurements at 90° to each other and the square root of the product was calculated to give an estimate of the mean tumor diameter. Cells were transfected with 100 nM mMage-b siRNA or 100 nM control siRNA in Lipofectamine™ 2000. After 6 hours, equal numbers of viable cells were injected subcutaneously into the flanks of DBA/2 mice and tumor growth in each of 31 mice was followed until each had reached the target tumor diameter (n=10 for control group, n=10 for nonspecific siRNA treated group, n=11 for mMage-b siRNA treated group). All procedures were performed in accordance with the guidelines of the Animal Care and approved by Institutional Review Board.

Statistical analyses

For in vitro cell studies, Student's t-test was applied. The data show means.d. from triplicates of each experiment, and each experiment was carried out at least three times independently. For the in vivo experiments, the time for a tumor to reach the target mean tumor diameter of 13 mm was defined as the elapsed time from the date of cell implantation to the date when a 13 mm target was reached, or when the mouse was killed which is considered censored. Kaplan–Meier survival analysis with the corresponding Log-Rank analysis was performed using S-plus Software (Insightful; Seattle, WA). Linear Regression analysis was used to measure the rate of mean tumor diameter growth as a function of time using S-plus Software (Insightful; Seattle, WA).

Conflict of Interest

The authors state no conflict of interest.

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Acknowledgments

This work was supported by the University of Wisconsin Comprehensive Cancer Center (BJL Principle Investigator), and by subsidized use of The WM Keck Laboratory for Biological Imaging and the Laboratory for Optical and Computational Instrumentation at the University of Wisconsin-Madison. We wish to thank Lance Rodenkirch for help with confocal imaging, Kathy Schell for Flow Cytometry technical expertise and Drs Vijay Setaluri and Hasan Mukhtar for useful discussions and critical reading of this manuscript. This work was supported by USPHS Grant RO1AR043356 (BJL).