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[Cancer Research 64, 6978-6988, October 1, 2004]
© 2004 American Association for Cancer Research

Regular Articles

Signaling and Transcriptional Changes Critical for Transformation of Human Cells by Simian Virus 40 Small Tumor Antigen or Protein Phosphatase 2A B56{gamma} Knockdown

Carlos S. Moreno1,2, Sumathi Ramachandran1,2, Danita G. Ashby2,3, Noelani Laycock1,2, Courtney A. Plattner2,3, Wen Chen4, William C. Hahn4,5 and David C. Pallas2,3

1 Department of Pathology and Laboratory Medicine, Emory University School of Medicine, 2 Winship Cancer Institute, and 3 Department of Biochemistry, Emory University School of Medicine, Atlanta, Georgia; 4 Department of Medical Oncology, Dana-Farber Cancer Institute, Department of Medicine, Brigham and Women’s Hospital, and Harvard Medical School, Boston, Massachusetts; and 5 Broad Institute, Cambridge, Massachusetts


   ABSTRACT
Top
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
One set of genes sufficient for transformation of primary human cells uses the combination of Ha-Ras-V12, the telomerase catalytic subunit hTERT, SV40 large tumor antigen (LT), and SV40 small tumor antigen (ST). Whereas SV40 LT inactivates the retinoblastoma protein and p53, the contribution of ST is poorly understood. The essential helper function of ST requires a functional interaction with protein phosphatase 2A (PP2A). Here we have identified changes in gene expression induced by ST and show that ST mediates these changes through both PP2A-dependent and PP2A-independent mechanisms. Knockdown of PP2A B56{gamma} subunit can substitute for ST expression to fully transform cells expressing LT, hTERT, and Ras-V12. We also identify those genes affected similarly in two cell lines that have been fully transformed from a common parental line by two alternative mechanisms, namely ST expression or PP2A B56{gamma} subunit knockdown. ST altered expression of genes involved in proliferation, apoptosis, integrin signaling, development, immune responses, and transcriptional regulation. ST reduced surface expression of MHC class I molecules, consistent with a need for SV40 to evade immune detection. ST expression enabled cell cycle progression in reduced serum and src phosphorylation in anchorage-independent media, whereas B56{gamma} knockdown required normal serum levels for these phenotypes. Inhibitors of integrin and src signaling prevented anchorage-independent growth of transformed cells, suggesting that integrin and src activation are key ST-mediated events in transformation. Our data support a model in which ST promotes survival through constitutive integrin signaling, src phosphorylation, and nuclear factor {kappa}B activation, while inhibiting cell-cell adhesion pathways.


   INTRODUCTION
Top
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The study of DNA tumor viruses and the oncogenes that they encode has provided many critical insights into the essential steps for oncogenesis. SV40 is a potently oncogenic DNA virus that can cause tumors in rodents (1) and possibly humans (2) . The two oncogenic proteins responsible for the transforming activity of SV40 are known as the large tumor antigen (LT) and small tumor antigen (ST). The early region of the SV40 genome encodes the 82 kDa LT and the 20 kDa ST as two alternatively spliced protein products that share a common NH2-terminal sequence of 82 amino acids with similarity to the DnaJ family of molecular chaperones (3) . LT also contains an LXCXE motif in the central region of the protein that enables it to bind and inactivate members of the retinoblastoma family of tumor suppressor proteins (4) , helping to release cells from G1 arrest. The NH2-terminal DnaJ domain is also necessary to functionally inactivate retinoblastoma family tumor suppressors (5) . In addition, the COOH-terminal domain of LT binds and inactivates the p53 tumor suppressor (6) .

The unique COOH-terminal half of ST encodes a domain that enables binding to protein phosphatase 2A (PP2A), a heterotrimeric serine-threonine phosphatase that plays important roles in numerous cellular processes including apoptosis, cell cycle regulation, and signal transduction (7 , 8) . ST provides critical helper functions to LT for transformation of both mouse (9) and human cells (10) . In addition, ST binding to PP2A is essential for ST to provide its helper function for transformation of human cells (11, 12, 13) .

Efforts to delineate a defined set of genetic changes essential for transformation of primary human cells has demonstrated that one combination of genes sufficient to produce anchorage-independent growth in soft agar and tumors in nude mice includes SV40 LT and ST, the catalytic subunit of human telomerase (hTERT), and the constitutively activated V12 mutant of H-Ras (H-Ras-V12; refs. 11 , 12 , 14 ). A COOH-terminal deletion mutant, ST110, that encodes only the first 110 residues of ST, including the DnaJ domain, cannot bind to PP2A and cannot provide the essential helper function needed to transform human cells (12) .

To investigate the ST-induced changes in gene expression that are essential for human tumor formation, we used whole genome expression profiling to compare the expression patterns of four human cell lines. Each of these cell lines stably expresses hTERT, H-Ras-V12, and LT (12) . In addition to these three stably expressed genes, the tumorigenic HEK-TERST cell line expresses wild-type SV40 ST, whereas the nontumorigenic HEK-TERST110 and HEK-TERV cell lines express the ST110 mutant or vector alone, respectively (12) . Introduction of an antisense construct to the B56{gamma}3 subunit of PP2A into the HEK-TER cell line (HEK-TERASB56{gamma}) nearly completely suppresses B56{gamma} expression at the protein level, permits anchorage-independent growth, and enables tumor formation in nude mice in a manner similar to cells expressing ST (15) . Here, we show that introduction of ST or suppression of PP2A B56{gamma} subunits impacts expression of a small subset of genes involved in apoptosis, integrin signaling, transcriptional regulation, and cytoskeletal control. These gene expression and signaling changes may promote growth and oppose apoptotic signals that prevent growth of normal cells in soft agar, enabling anchorage-independent growth and tumor formation.


   MATERIALS AND METHODS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Cell Lines, Culture, and Lysates.
Stable human embryonic kidney (HEK) cell lines HEK-TERST, HEK-TERST110, and HEK-TERV have been described previously (12) . The HEK-TERASB56{gamma} cell line is described elsewhere (15) . Cells were grown in {alpha}-MEM, 10% fetal bovine serum (FBS), 2 mmol/L L-glutamine, and 100 units/ml penicillin/streptomycin and serum-starved in {alpha}-MEM, 0.1% FBS, 2 mmol/L L-glutamine, and 100 units/ml penicillin/streptomycin for 24 hours.

Western Blots and Antibodies.
Cell lysates were prepared as described previously (16) or with the additional step of sonication before centrifugation to generate a whole cell lysate. Antibodies to SV40 LT (monoclonal antibody 419), ST, H-Ras-V12, SERPINB2/PAI-2, plakoglobin (all from Santa Cruz Biotechnology Biotech, Santa Cruz, CA), IQGAP-2 (Upstate Biotechnology, Lake Placid, NY), thymidine kinase (QED Bioscience, San Diego, CA), cyclin A (BD Transduction Laboratories, Lexington, KY), BNIP3, cyclin B (Oncogene Research, San Diego, CA), Src-phospho-Y418 (Biosource Intl, Camarillo, CA), survivin, and inhibitor of NF{kappa}B (I{kappa}B{alpha}, Cell Signaling Technology, Beverly, MA) were used in immunoblots as described previously (16) . The src 327 monoclonal antibody was a generous gift from Joan Brugge (Ariad Pharmaceuticals, Inc., Cambridge, MA).

Fluorescent-Activated Cell Sorting Analysis.
For analysis of MHC class I expression, 106 cells were harvested in PBS and 0.02% EDTA, incubated in 500 µL of PBS and 10 µg/ml W6/32 mouse monoclonal antibody (a generous gift of Dr. Charles A. Parkos, Emory University), washed, and then stained with antimouse FITC-conjugated secondary antibody. For DNA content analysis, cells were incubated in {alpha}-MEM and 0.1% FBS for 24 hours and harvested immediately or collected after 24 hours in 10% FBS. For cell synchronization, 0.5 x 106 cells were treated with 10 µmol/L aphidicolin in 10% FBS for 24 hours and then harvested immediately or released into {alpha}-MEM and 0.1% FBS without aphidicolin for 24 hours. Cells were fixed in 70% EtOH at –20°C overnight, stained with 10 µg/ml propidium iodide, and sorted on a FACScalibur sorter (Becton-Dickinson, Franklin Lakes, NJ).

Quantitative Real-Time PCR.
Quantitative real-time PCR (QRT-PCR) was performed in an I-cycler (Bio-Rad, Hercules, CA) using SYBR Green (Molecular Probes, Eugene, OR). The critical cycle threshold was determined for each gene and the difference relative to the critical cycle threshold for glyceraldehyde-3-phosphate dehydrogenase or {Delta} cycle threshold was computed for each RNA sample. Two independent RNA samples from each cell line were analyzed in quadruplicate, and the mean and SD were computed. Primers were designed using Primer Express software to amplify across splice junctions. The sequences of the primer sets used are given in Supplementary Table S7.

Microarrays and Data Analysis.
Total RNA was prepared using the RNeasy kit (Qiagen Inc., Valencia, CA) according to the manufacturer’s instructions. RNA was reverse transcribed, and labeled probes were fragmented and hybridized to the Human Genome U133 Chip Set (Affymetrix Inc., Santa Clara, CA) according to the manufacturer’s protocols. Analysis of four cell lines in duplicate on both the U133A and U133B GeneChips resulted in 16 microarray hybridizations that generated eight combined U133AB whole genome datasets (ST-1, ST-2, ST110–1, ST110–2, B56–1, B56–2, TERV-1, and TERV-2). Scanned images were analyzed, and all 12 of the possible comparison files against the TERV-1 and TERV-2 datasets were generated using Microarray Suite 5.0 software. Each chip was normalized with a target value of 150. Genes called absent in all of the hybridizations and genes that were called no change in more than one ST-TERV Affymetrix comparison file were filtered out leaving 2,545 probes for Significance Analysis of Microarrays analysis. Data from Affymetrix CEL files was then normalized using the robust multiarray average method (17) . After data normalization, Significance Analysis of Microarrays analysis was performed on the remaining 2,545 probe sets using the following relevant parameters: {Delta} = 0.26, fold-change = 1.5, number permutations = 1000, random number generation seed = 1234567, median false discovery rate = 3%, significant genes = 555, and predicted false positives = 17. Hierarchical clustering with average linkage based on Euclidian distance was performed with Spotfire Decision Site 7.0 software. Annotations were obtained from the NetAffx website6 and the April 2003 assembly of the Human Genome at University of California Santa Cruz.7 P values for gene ontology (GO) categories were computed using GOstat (18) and corrected to false discovery rate using the method of Hochberg and Benjamini (19) .

Soft Agar Assays.
Soft agar assays were performed essentially as described (14) . Briefly, 10,000 cells were seeded in 0.3% Noble Agar and either 10 µg/ml RGD or RAD peptide (Biomol, Plymouth Meeting, PA; ref. 20 ), 10 µmol/L PP1 (21) or PP3 inhibitor (22) , or 1 µmol/L wortmannin. The c-src-specific kinase inhibitor PP1 [4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo(3,4-D)pyrimidine] was obtained from Biomol and the inactive structural analogue PP3 [4-amino-7-phenylpyrazol(3,4-D)pyrimidine] was purchased from CalBiochem (San Diego, CA). Cell viability was determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide dye staining as described (23) .

Methylcellulose Assays.
Methylcellulose assays were performed as described (24) . Briefly, methylcellulose culture medium (final concentration of 1.3% w/v) was made by diluting autoclaved 2.6% methylcellulose (Sigma-Aldrich, St. Louis, MO) in water with an equal volume of 2x concentrated MEM followed by stirring overnight at 4°C. Essentially, 3 x 106 cells were incubated in 10 mL of methylcellulose culture medium in a flask at 37°C. After incubation for 24 hours, the cells were recovered by solubilizing the methylcellulose medium with 5 volumes of chilled PBS followed by gently mixing and centrifugation at 1,500 rpm for 5 minutes.


   RESULTS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
SV40 Small Tumor Antigen Alters the Expression of 452 Genes.
We used a whole genomic profiling approach of ST-expressing (HEK-TERST), ST110 mutant-expressing (HEK-TERST110), PP2A B56{gamma} knockdown (HEK-TERASB56{gamma}), and vector control (HEK-TERV) cell lines to investigate the transcriptional changes in transformation of human cells. Each of these cell lines is actually a pool of hundreds of individual clones derived from retroviral infection of a HEK cell line that stably expresses hTERT, H-Ras-V12, and LT (HEK-TER; ref. 12 ). We reasoned that high levels of serum might cause some of the same changes in gene expression as ST expression or B56{gamma} down-regulation. Therefore, all of the cell lines were grown in low serum for 24 hours to prevent serum effects from masking the impact of ST expression or B56{gamma} down-regulation on global gene expression patterns. Total RNA was prepared from two independent biological replicates and analyzed using the Affymetrix U133 Human Genome GeneChip Array Set. To compensate for multiple testing issues, we have used the Significance Analysis of Microarrays software (25) , which computes false discovery rates. Significance Analysis of Microarrays resulted in a total of 555 probe sets corresponding to 452 unique genes that exhibited at least 1.5 fold-change between HEK-TERST and HEK-TERV cell lines with a predicted false discovery rate of 3% (q < 0.03; see Materials and Methods and Supplementary Table S1). Although a 1.5-fold change in mRNA levels may not be biologically significant for some genes, microarrays often underestimate the actual fold change when compared with QRT-PCR and Northern blots (26) , and Significance Analysis of Microarrays produces fewer false positives than fold change criteria (25) . Moreover, a cutoff of 1.5-fold has been used in several studies (27 , 28) , and the data seen at the 1.5-fold level included genes such as cyclin B, which we confirmed at the protein level were induced much more than 1.5-fold.

We analyzed the GO consortium annotations of the genes that were significantly affected by ST using the GOstat software (18) , which finds GO terms that are statistically over-represented in a gene list compared with the rest of the genome. GOstat analysis of the genes affected by ST expression found five major categories of genes that were significantly over-represented relative to all of the annotated human genes using the Hochberg and Benjamini correction for false discovery rate (Supplementary Table S2; Fig. 1, A and BCitation ). Of the 452 unique genes, only 274 had GO annotations (Fig. 1A)Citation . Of the 274 annotated genes, 109 genes (or 40%) had GO annotations relating to cellular proliferation (Fig. 1B)Citation compared with 4,622 of 19,085 total genes (or 24%) in these categories for the entire genome (Supplementary Table S2; P = 2.55 x 10–7). The other major functional categories significantly over-represented in the genes affected by ST expression included development and morphogenesis (P = 4.8 x 10–5), inflammation (P = 3.5 x 10–4), regulation of transcription (P = 6.2 x 10–4), and antigen presentation (P = 2.6 x 10–3).



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  		Fig. 1. SV40 ST alters expression in genes involved in proliferation, development, transcriptional regulation, and inflammation. A, summary of number of GO annotations and annotated genes used for GOstat analysis. B, GO categories that were significantly over-represented in the 452 genes affected by ST expression as determined by GOstat analysis included genes involved in proliferation, inflammation, antigen presentation, development, and transcription. C, FACS analysis of HEK-TERV and HEK-TERST cells using the pan-HLA monoclonal antibody W6/32 shows decreased surface expression of MHC class I molecules in the HEK-TERST cells as a shift in the peaks to the left relative to the HEK-TERV cells. A representative result from three independent experiments is shown. D, FACS analysis of HEK-TERV and HEK-TERST110 cells as in C. E, FACS analysis of HEK-TERV and HEK-TERASB56{gamma} cells as in C.

 
Although some of the 452 genes affected by ST such as osteopontin (29) and thymidine kinase (30 , 31) agree with earlier studies, the vast majority of these ST targets have not been reported previously (Supplementary Table S1). ST appears to affect proliferation, possibly through changes in developmental programs that are controlled by sequence-specific transcription factors. Our data show for the first time that ST induces expression of the developmental HOX genes HOXA9, HOXB6, and HOXB3; the forkhead family factors FOXD1, FOXM1, and FOXG1b; and the cancer-associated developmental transcription factors c-MYC, ETS1, ID2, and SMAD3. Our observation that ST induces c-myc mRNA complements recent findings that PP2A inhibition stabilizes c-myc at the protein level, contributing to transformation (32) . Moreover, several early developmental markers from multiple tissue types such as endothelial cell-specific molecule 1, epithelial membrane protein 1, stathmin-like 3, osteopontin, and CD24 were induced by ST, suggesting that the changed expression of these developmental transcription factors results in downstream differences between HEK-TERV and HEK-TERST cells. Whereas changes in mRNA levels alone do not necessarily translate into phenotypic alterations, the coordinated alterations of so many genes involved in similar processes, the alterations in cell cycle progression reported here, and previous literature all support the hypothesis that ST-induced changes in mRNA expression likely affect these cellular functions.

ST may also repress immune responses and impair antigen presentation by repressing expression of MHC class I molecules HLA-A, HLA-B, HLA-C, and ß2-microglobulin; the CD74 invariant chain necessary for folding of MHC class II heterodimers; and proinflammatory cytokines such as interleukin (IL)-8, IL-1ß, consistent with the need for SV40 to avoid immune detection. Fluorescence-activated cell sorter (FACS) analysis of MHC class I expression in three independent experiments demonstrated that surface expression of HLA molecules was repressed in the HEK-TERST, HEK-TERST110, and HEK-TERASB56{gamma} cell lines compared with the HEK-TERV line (Fig. 1, C–E)Citation . Whereas MHC class I expression was reduced in all three of the lines, the repression was most effective in the cells that express wild-type ST.

SV40 Small Tumor Antigen Alters the Expression of 171 Genes in a PP2A-Independent Manner and 281 Genes in a PP2A-Dependent Manner.
Expression data from the HEK-TERST110 and HEK-TERASB56{gamma} cell lines was also compared with the HEK-TERV data, and signal-log ratios for all of the cell lines were then analyzed. Comparison of the HEK-TERST110 line with the HEK-TERV line identified 411 genes that were altered in expression levels (Supplementary Table S3). PP2A-independent genes were defined as the intersection of the 452 genes altered by ST expression and the set of 411 genes affected by ST110 expression that changed in the same direction relative to vector control cells. The intersection of these two gene sets resulted in a set of 171 genes that are represented by the magenta and cyan sections of the Venn diagram in Fig. 2ACitation . The expression pattern of all 452 ST-regulated genes was analyzed by hierarchical clustering (Fig. 2B)Citation , and the expression pattern of the 171 PP2A-independent genes is shown in Fig. 2CCitation . Strikingly, 37% of ST-regulated genes (Supplementary Table S4) can be regulated by the NH2-terminal domain of SV40 ST independently of PP2A modulation. Because these changes are induced by ST in cells that already express LT, these data suggest that the NH2-terminal half of ST may have effects that LT, which also contains a DnaJ domain, does not.



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  		Fig. 2. Hierarchical clustering of gene subsets affected by SV40 ST expression. A, Venn diagram of gene sets analyzed. The entire set of 452 ST-regulated genes is represented by the large red circle. Numbers indicate the number of unique genes in each subset. PP2A-independent genes, shown in magenta and cyan, were similar in ST110 and ST. Strongly PP2A-dependent genes, shown in orange, were similar in ASB56{gamma} and ST but not in ST110. Genes shown in cyan were affected similarly in ST, ST110, and ASB56{gamma}. B, hierarchical clustering of 555 probe sets affected at least 1.5-fold by wild-type ST expression. Signal log ratios for all 12 possible comparisons of ST/TERV (HEK-TERST versus HEK-TERV cells), B56/TERV (HEK-TERASB56{gamma} versus HEK-TERV cells), and ST110/TERV (HEK-TERST110 versus HEK-TERV cells) were clustered by gene and by sample. As an example, the dataset label of ST-1/TERV-1 corresponds to a comparison of HEK-ST (repeat 1) versus HEK-TERV (repeat 1). Increased and decreased expression levels are indicated by red and green intensities, respectively. C, hierarchical clustering of 205 probe sets corresponding to 171 genes significantly affected by wild-type ST expression in a PP2A-independent manner. This gene set shows similar expression effects for wild-type ST and the ST110-mutant. D, hierarchical clustering of 128 probe sets corresponding to 99 genes with similar expression patterns in fully transformed HEK-TERST and HEK-TERASB56{gamma} cells.

 
Given that the transforming helper function of ST is known to be PP2A dependent, genes that are affected by ST in a PP2A-dependent manner are of particular interest. The 281 genes affected by ST that were not similarly affected by the ST110 mutant represent this PP2A-dependent gene set (red and orange sections of Fig. 2ACitation ). Fig. 2BCitation shows that many of the genes affected by ST are unaffected by down-regulation of the PP2A B56{gamma} subunit in the HEK-TERASB56{gamma} cell line or are even affected in the opposite direction. Thus, the subset of genes similarly affected by B56{gamma} antisense and ST expression (Fig. 2D)Citation are PP2A-dependent via two different molecular mechanisms that transform human cells.

The fact that knockdown of PP2A B56{gamma} subunits produced changes in 843 genes (green section of Fig. 2ACitation ) that are not affected by ST or ST110 is not surprising, given the many cellular functions of PP2A. It is difficult to know what mechanism would affect the 161 genes represented in blue in Fig. 2ACitation that were affected by ST110 alone. One could speculate that the truncated NH2-terminal portion of ST could gain new functions that are not necessarily biologically relevant. More likely, the effects of the COOH-terminal portion of ST on PP2A activity could counteract or attenuate effects that are mediated by the NH2-terminal portion of ST. The 79 genes affected by both ST110 and B56{gamma} knockdown (but not by wild-type ST) are interesting (Supplementary Table S5), because several of them are altered in human cancers (AMACR, TWIST, TGFßR2, and MMP-10) or are involved in the wnt signaling pathway (SFRP1, GSK3ß, and Frizzled). Two genes (SFRP1 and tropomysin 1) were repressed by ST110 and B56{gamma} knockdown but induced by ST, whereas 1 gene (stem cell growth factor) was induced by ST110 and B56{gamma} knockdown but repressed by ST.

Western Blotting and Real-Time PCR Data Confirm the Microarray Data.
To confirm our microarray observations, we prepared total RNA from independently treated samples and performed QRT-PCR on 29 PP2A-dependent genes and 12 PP2A-independent genes and compared expression changes relative to glyceraldehyde-3-phosphate dehydrogenase. The magnitude of the changes observed in the QRT-PCR assays varied somewhat from that observed in the microarray experiments (Fig. 3, A–D and G–I)Citation . Nevertheless, the directionality of the QRT-PCR changes confirmed the microarray results for 40 of 41 (98%) of the genes assayed in the ST versus TERV ratios, in 34 of 41 (83%) of the genes in the ST110 versus TERV ratios, and in 22 of 25 (88%) of the genes in the ASB56{gamma} versus TERV ratios. Thus, the QRT-PCR data confirmed our microarray observations in 96 of 107 comparisons, or 90% of the time. Among the numerous novel ST targets that we confirmed by QRT-PCR are two thrombin protease-activated receptors, F2R and F2R2, which are expressed in prostate cancers and are implicated in motility, metastasis, angiogenesis, and src kinase activation (33, 34, 35) .



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  		Fig. 3. QRT-PCR and immunoblotting data confirm microarray observations. Expression ratios from QRT-PCR and microarray data are shown for 41 sample genes compared with mRNA levels in HEK-TERV cells. The average fold change for four independent samples are shown; bars, ±SE. A. Expression ratios are shown for four genes up-regulated by ST in a PP2A-independent manner. B. Expression ratios are shown for 8 genes down-regulated by ST in a PP2A-independent manner. C. Expression ratios are shown for 10 genes up-regulated by ST in a PP2A -dpendent manner. D. Expression ratios are shown for 6 genes down-regulated by ST in a PP2A-dependent manner. E, immunoblot verification of microarray data at the protein level for plakoglobin, IQGAP2, and thymidine kinase. PP2A C subunit is shown as a loading control. IQGAP2 was difficult to detect, indicating that it is expressed at a very low level even in the HEK-TERV cells. Blotting of IQGAP2 immunoprecipitates from these cell lines (data not shown) confirmed the reduction in IQGAP2 protein seen in this figure. F. I{kappa}B{alpha} levels are decreased in the tumorigenic HEK-TERST and HEK-TERASB56{gamma} cell lines, but not in HEK-TERST110 cells. Quantitation of three independent experiments (data not shown) by chemilumimager demonstrated that I{kappa}B{alpha} levels were reduced to 55% and 28% of HEK-TERV levels in the HEK-TERST and HEK-TERASB56{gamma} cells, respectively, whereas I{kappa}B{alpha} in the HEK-TERST110 cells was unchanged. Immunoblotting also confirms of expression changes at the protein level for BNIP3 and the NF{kappa}B targets SERPINB2/PAI-2 and survivin. G. Expression ratios are shown in HEK-TERST, HEK-TERST110, and HEK-TERASB56{gamma} cell lines for 10 genes regulated by ST in a PP2A-independent manner. H. Expression ratios are shown in HEK-TERST, HEK-TERST110, and HEK-TERASB56{gamma} cell lines for 8 genes up-regulated by ST in a PP2A-dependent manner. I. Expression ratios are shown in HEK-TERST, HEK-TERST110, and HEK-TERASB56{gamma} cell lines for 7 genes down-regulated by ST in a PP2A-dependent manner.

 
To confirm changes at the protein level, we first immunoblotted for 3 genes representative of different expression patterns. In agreement with mRNA data, junction plakoglobin (JUP) decreased in a PP2A-dependent manner, IQGAP2 decreased in a PP2A-independent manner, and thymidine kinase 1 (TK-1) increased in HEK-TERST110 cells and even more so in the HEK-TERST cells (Fig. 3E)Citation . We also confirmed changes at the protein level for BNIP3 and SERPINB2 (Fig. 3F)Citation . Nevertheless, one of the limitations of microarray analyses is that changes at the mRNA level are not always reflected at the protein level, and, thus, it is not possible to be certain that the mRNA changes reported here are all reflected at the protein level. Protein levels of LT and H-Ras-V12 were also measured in the HEK-TERST, HEK-TERST110, HEK-TERASB56{gamma}, and HEK-TERV by immunoblotting, quantitated using a chemiluminescence imager as described (36) , and determined to be within 2-fold for each of the matched lines (data not shown).

Expression Profiling of PP2A B56{gamma} Knockdown Cells Identifies 99 Potentially Critical Genes Correlated with Tumorigenicity.
Antisense knockdown of PP2A B56{gamma} subunits has been shown previously to nearly completely suppress B56{gamma} expression at the protein level (15) . However, our comparison of microarray expression data in the HEK-TERASB56{gamma} and HEK-TERV cells showed only a 1.5-fold decrease of B56{gamma} at the mRNA level, suggesting that much of the loss of B56{gamma} protein may be due to translational inhibition. Because down-regulation of the PP2A B56{gamma} subunit can substitute for ST (15) , we reasoned that the set of genes similarly affected by ST expression and B56{gamma} knockdown would include some of the ST targets that are the most relevant to tumorigenesis. The intersection of the genes affected by B56{gamma} knockdown with those genes affected by ST (shown in orange and cyan in Fig. 2ACitation ) was 128 probe sets corresponding to 99 unique genes (Supplementary Table S6 and Fig. 2DCitation ). Among these 99 genes were 37 genes (cyan section of Fig. 2ACitation ) that were similarly affected in the HEK-TERASB56{gamma}, HEK-TERST, and HEK-TERST110 cell lines. These 37 genes included matrix metalloproteinase MMP-1, the apoptosis-related genes TRAIL, MFGE8, and BNIP3, and the microfilament-associated protein palladin. The fact that this set of genes was similarly affected by the ST110 mutant and by knockdown of B56{gamma} suggests that these genes can be regulated by both PP2A-dependent and PP2A-independent mechanisms. Of these 99 newly described targets that are similarly affected by ST expression and B56{gamma} knockdown, 62 genes (orange section of Fig. 2ACitation ) were differentially affected in the HEK-TERST110 cell line (orange bar, Fig. 2DCitation ), suggesting that they are strongly dependent on ST-PP2A interactions (Table 1)Citation . Among these genes were the transcription factors FOXD1 and HOXB3; the apoptosis-related genes, gelsolin, ALDH1A3, and SERPINB2; and cell-cell adhesion molecule protocadherin {gamma}A11.


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  		Table 1 PP2A-dependent genes with similar profiles in tumorigenic HEK-TERST and HEK-TERASB56{gamma} lines that are clustered in Fig. 2DCitation .

 
It has been shown previously that ST activates nuclear factor {kappa}B (NF{kappa}B) via protein kinase C {zeta} and phosphatidylinositol 3'-kinase (PI3K) signaling (37) . Our observation that the antiapoptotic NF{kappa}B targets ALDH1 and SERPINB2 were up-regulated in HEK-TERST and HEK-TERASB56{gamma} cells (Table 1)Citation prompted us to test the steady-state protein levels of the inhibitor of NF{kappa}B (I{kappa}B{alpha}). Quantitation of three independent immunoblots (Fig. 3F)Citation by chemilumimager demonstrated that I{kappa}B{alpha} levels are reduced to 55% and 28% of HEK-TERV levels in the HEK-TERST and HEK-TERASB56{gamma} cells, respectively, whereas I{kappa}B{alpha} in the HEK-TERST110 cells was unchanged. In addition, the NF{kappa}B targets SERPINB2 and survivin are increased at the protein level in HEK-TERST and HEK-TERASB56{gamma} cells compared with the HEK-TERV controls (Fig. 3F)Citation . Activation of NF{kappa}B might be expected to be due to downstream effects of enhanced integrin and src signaling (see below), because NF{kappa}B mediates endothelial cell survival signals from the integrin {alpha}vß3–src pathway (38) or via inhibition of PP2A dephosphorylation of the I{kappa}B kinase (39) or a combination of mechanisms. Thus, expression of ST and knockdown of B56{gamma} PP2A subunits both appear to result in PP2A-dependent decreased I{kappa}B{alpha} protein and subsequent NF{kappa}B activation. Nevertheless, the increase in SERPINB2 and survivin expression in the HEK-TERST110 line suggests that some antiapoptotic NF{kappa}B targets can also be activated by ST by PP2A-independent mechanisms.

ST repressed expression of the proinflammatory NF{kappa}B targets IL-8 and IL-1ß, whereas it enhanced expression of the antiapoptotic targets of NF{kappa}B, ALDH1, survivin, and SERPINB2. QRT-PCR and Western blotting confirmed microarray observations for 22 common targets of ST and B56{gamma} including SERPINB2, TRABID, DNER, ALDH1, SMAD3, gelsolin, MMP1, FOXD1, CTGF, PRSS11, and ICAM1 (Fig. 3, F–I)Citation .

Normally, NF{kappa}B activation results in activation of both proinflammatory and antiapoptotic target genes. Consistent with this typical response, the knockdown of PP2A B56{gamma} subunits in HEK-TERASB56{gamma} cells increased expression of both proinflammatory (IL-8 and IL-1ß) and antiapoptotic targets of NF{kappa}B (ALDH1, survivin, and SERPINB2). However, ST effects on expression of NF{kappa}B targets were unusual in that proinflammatory and antiapoptotic targets are affected in opposite directions. These differences were due to the general repression by STs of immune system genes such as MHC class I genes, invariant chain (CD74), and tumor necrosis factor-related apoptosis-inducing ligand among others (Supplementary Table S1).

Small Tumor Antigen Affects Expression of Cell Cycle Genes and Cell Cycle Progression in Low Serum.
As expected, ST induced a general pattern of increased expression of genes associated with cell cycle progression and decreased expression of genes associated with cell cycle arrest. In agreement with published studies (30 , 31) in which coexpression of SV40 LT and ST drives cells into S phase, thymidine kinase (TK-1) and dihydrofolate reductase (DHFR) were up-regulated by ST. Notably, some S-phase and cell cycle regulated genes, such as TK-1 (Fig. 3, A and C)Citation , were also up-regulated by ST110. Immunoblotting for cyclin A showed high expression in the HEK-TERV cells, demonstrating that LT and H-Ras-V12 can activate the cyclin A promoter in the absence of ST (Fig. 4A)Citation . Cyclin A levels were decreased in HEK-TERST and HEK-TERST110 cells compared with HEK-TERV cells at both the protein and mRNA levels (Fig. 4ACitation ; Supplementary Table S1). This may be because protein and mRNA were prepared after 24 hours in low serum, causing an arrest of HEK-TERV cells at the G1-S-phase transition, whereas HEK-TERST and HEK-TERST110 cells progressed into G2-M. Consistent with this hypothesis, the HEK-TERST and HEK-TERST110 cells have elevated cyclin B levels, demonstrating the ability of these lines to progress through the cell cycle under conditions of low serum. The HEK-TERASB56{gamma} cells showed intermediate changes, with a partial decrease in cyclin A levels and partial increase in cyclin B levels, suggestive of fewer cells progressing through the cell cycle. Moreover, TK-1 and DHFR mRNA were not increased in HEK-TERASB56{gamma} cells (Supplementary Table S1), indicating that unlike ST or ST110 expression, the reduction of B56{gamma} is not sufficient to enable cell cycle progression in low serum even in the presence of activated Ras.



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  		Fig. 4. ST and ST110-expressing cells progress through S phase, whereas B56{gamma} knockdown and vector control cell lines are serum-dependent. A. Immunoblots show decreased cyclin A levels and increased cyclin B levels in HEK-TERST and HEK-TERST110 cells. B. Cell cycle distribution of each cell line is shown as determined by propidium iodide staining and FACS. Peaks corresponding to cells with 2N DNA content in G1 phase or 4N DNA content in G2-M are indicated on the X axis in arbitrary units. Sub-2N peaks presumably correspond to subpopulations of aneuploid cells in lines that express LT but not ST. Shown are cell populations corresponding to asynchronous cells in 10% FBS (black) or to cell populations after 24 hours in low serum conditions (gray). C, similar FACS analysis to that shown in B except that all lines were synchronized in the G1 phase by 24 hours of aphidicolin treatment in 10% FBS and then immediately harvested (black) or released into low serum conditions without aphidicolin for an additional 24 hours (gray).

 
To ascertain the cell cycle distribution of these cell lines after 24 hours in low serum, DNA content was measured by FACS analysis (Fig. 4B)Citation . HEK-TERST and HEK-TERST110 cells exhibited highly similar cell cycle distributions, with >35% in S phase and little sign of cell cycle arrest. However, the 4N peak composed of cells in G2-M dropped dramatically in HEK-TERASB56{gamma} cells, indicative of a strong dependence on serum. To additionally investigate the serum dependence of the four cell lines, all of the lines were synchronized in the G1 phase by aphidicolin treatment in 10% FBS for 24 hours and then either harvested or released into low serum conditions without aphidicolin. The HEK-TERST and HEK-TERST110 cells progressed through the cell cycle in a serum-independent manner, whereas most of the HEK-TERV and HEK-TERASB56{gamma} cells remained arrested in G1 in a serum-dependent manner (Fig. 4C)Citation . Thus, ST and ST110 can drive HEK cells through the cell cycle in the presence of LT and activated Ras, whereas knockdown of B56{gamma} subunits cannot.

Small Tumor Antigen-Induced Gene Expression Patterns Suggest Increased Integrin Signaling and Reduced Cell-Cell Adhesion.
A large number of genes involved in cellular adhesion, cytoskeletal structure, and motility were affected by the presence of ST. In particular, several genes known to affect the integrin signaling pathway such as osteopontin, paxillin, f-spondin, gelsolin, and matrix metalloproteinase-1 (MMP-1) were changed in directions consistent with integrin activation by microarray analysis (Supplementary Table S1) and by QRT-PCR (Fig. 3, A and B)Citation . Our data confirmed previous studies (29) that SV40 activates expression of osteopontin (SPP1) and show that ST does this in a PP2A-dependent manner. In addition, ST up-regulated expression of integrin signaling targets such as MMP-1, {alpha} collagens, c-myc, and paxillin by both PP2A-dependent and PP2A-independent mechanisms. These data suggest, but do not prove, that ST may activate integrin signaling directly or indirectly.

In contrast to the apparent up-regulation of integrin signaling, expression of many genes important for cell-cell adhesion such as ICAM-1 and VCAM-1 were down-regulated. Components of junctional adhesion complexes were also repressed, such as ß-catenin, plakoglobin, junctional adhesion molecule 1 (JAM), claudin 11, and protocadherin {gamma} family members. In addition, secreted-frizzled related protein 1, which binds directly to wingless and can inhibit wnt signaling through destabilization of ß-catenin (40) , was up-regulated by ST.

HEK-TERST Activation of Src Shows Less Serum Dependence Than HEK-ASB56{gamma}.
The tyrosine kinase c-src and the PI3K are downstream components of integrin signaling pathways (41 , 42) , and integrin activation of c-src can block proper assembly of cell-cell contacts (43) . To determine whether activation of integrin signaling through c-src and PI3K is essential for the anchorage-independent growth phenotype of the HEK-TERST cell line, soft agar assays were performed in the presence of inhibitors of integrin, c-src, or PI3K signaling. To test the effect of inhibition of integrin signaling on growth in soft agar, HEK-TERST and HEK-ASB56{gamma} cells were plated in the presence of 10 µg/mL of a circularized arginine-glycine-aspartic acid (RGD) peptide that acts as an integrin {alpha}vß3 antagonist, or an equal concentration of a control arginine-alanine-aspartic acid (RAD) peptide. To determine whether c-src signaling is essential for HEK-TERST and HEK-ASB56{gamma} growth in soft agar, a c-src-specific kinase inhibitor PP1 and an inactive structural analogue, PP3, were used. HEK-TERST and HEK-ASB56{gamma} cells were also plated in the presence of wortmannin to test for the requirement of PI3K signaling in anchorage-independent growth. The integrin RGD inhibitor, c-src PP1 inhibitor, and wortmannin all dramatically interfered with the HEK-TERST and the HEK-ASB56{gamma} cell line’s ability to form colonies in soft agar (Fig. 5A)Citation , whereas the control inhibitors had minimal effects. These data show that integrin signaling is essential for transformation by ST expression and by B56{gamma} knockdown and suggest that both of these transformation events activate integrin signaling directly or indirectly. The viability of HEK-TERST cells was determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide dye assay after 2 weeks of treatment with each of these inhibitors in soft agar, demonstrating that none of the inhibitors had a direct killing effect, but rather prevented colony growth (Fig. 5B)Citation .



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  		Fig. 5. Integrin-src-PI3K signaling is essential for anchorage-independent growth. A, soft agar assays of HEK-TERV, HEK-TERST110, HEK-TERST, and HEK-TERASB56{gamma} cells either untreated or with an inhibitor of integrin signaling (RGD peptide), a control peptide (RAD), a src inhibitor (PP1), a control inhibitor (PP3), or a PI3K inhibitor (wortmannin). Results for the HEK-TERASB56{gamma} line were similar to the HEK-TERST line except that HEK-TERASB56{gamma} colonies were generally smaller than HEK-TERST colonies (data not shown). The mean of data from six replicates are shown; bars, ±SD. B, viability of HEK-TERST cells after 2 weeks in soft agar in the presence of treatments used in A as measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. The mean of four replicates are shown; bars, ±SD. C, HEK-TERV, HEK-TERST110, HEK-TERST, and HEK-TERASB56 were grown in 1.3% methycellulose for 24 h in either 5% or 10% FBS and whole cell lysates prepared. Immunoblots were probed for total src and with antibodies specific to src kinase phosphorylated at tyrosine 418. PP2A C subunit is shown as a loading control. ST induced phosphorylation and activation of Src under all conditions, whereas in B56{gamma} knockdown cells src phosphorylation was detected only in 10% serum. Src was not phosphorylated in the HEK-TERV or HEK-TERST110 cells under any conditions, demonstrating that ST-induced activation of src is PP2A-dependent. D, model of the role of ST and B56{gamma} in anchorage-independent growth. HEK-TERST cells: integrin signaling and ST together activate src and NF{kappa}B to increase expression of antiapoptotic genes. ST represses proinflammatory genes by an unknown mechanism. HEK-TERASB56 cells: lack of B56{gamma} together with integrin signaling and growth factors from serum enable src activation, NF{kappa}B activation, and increases in both proinflammatory and antiapoptotic genes.

 
To determine whether ST expression or B56{gamma} knockdown affects src activation and phosphorylation on tyrosine 418, HEK-TERST and HEK-ASB56{gamma} cells were also grown in anchorage-independent 1.3% methylcellulose in both 5% and 10% FBS. After 24 hours in anchorage-independent media, cells were spun down and harvested as described (24) , lysed, and whole cell lysates were probed for the presence of phospho-Y418-src (Fig. 5C)Citation . ST induced phosphorylation and activation of src under all conditions, whereas src-Y418 phosphorylation in HEK-ASB56{gamma} cells was detected only in 10% serum. The dependence of HEK-ASB56{gamma} cells on serum for src phosphorylation is consistent with the observation that B56{gamma} knockdown does not transform human cells as efficiently as ST transformation in soft agar or tumor formation assays (15) . Src-Y418 was not phosphorylated in the HEK-TERV or HEK-TERST110 cells under any conditions, demonstrating that ST-induced activation of src is PP2A-dependent. Whereas it is not possible to determine whether the changes in src phosphorylation are direct or indirect effects of ST based on these data, we hypothesize that ST may indirectly activate src through PP2A-dependent activation of integrins (Fig. 5D)Citation .


   DISCUSSION
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Here we have identified the changes in gene expression that are generated by SV40 ST and determined that many of these targets are highly relevant to cancer growth, survival, motility, and metastasis. Our data provide new insights that support a model (Fig. 5D)Citation in which ST promotes growth and prevents apoptosis through constitutive integrin signaling and NF{kappa}B activation while inhibiting components of cell-cell adhesion pathways that might provide cell cycle arrest and prodifferentiation signals. Whereas many of the effects of ST were shown to be independent of PP2A binding and inhibition, the key changes shared by the tumorigenic HEK-TERST and HEK-TERASB56{gamma} cell lines were largely PP2A-dependent and included up-regulation of antiapoptotic effectors like SERPINB2/PAI-2, as well as developmental homeobox and forkhead box transcription factors. Moreover, ST appeared to be able to differentially regulate proinflammatory and antiapoptotic targets of NF{kappa}B.

The 137 genes that were affected by ST in a PP2A-independent manner but were unaffected by B56{gamma} knockdown may enhance, but not be essential, for transformation. Many of these genes were cell cycle regulated genes and may reflect the inability of the HEK-TERASB56{gamma} line to progress through S phase under conditions of low serum. In agreement with published literature (10 , 30 , 31 , 44, 45, 46, 47, 48) , coexpression of SV40 LT and ST drove cells into S phase in low serum, and we observed corresponding increases in expression of S-phase genes such as TK-1, DHFR, and G0S2. In contrast to earlier studies in which S-phase entry mediated by polyoma or SV40 LT and ST was PP2A-dependent (13 , 49) , we observed that the ST110 mutant could also support S-phase entry, although to a lesser degree than wild-type ST. One potential reason for the ability of the ST110 mutant to support cell cycle progression in our model system is that our cell lines also express the constitutively activated H-Ras-V12 mutant. Thus, in the presence of LT and activated Ras signaling, the NH2-terminal domain of ST appears to be sufficient to drive cells into S phase. Consistent with this hypothesis, mutations in the DnaJ domain of polyoma ST has been shown to strongly inhibit activation of the cyclin A promoter (50) .

The set of 99 genes that were regulated similarly by ST and B56{gamma} knockdown may represent some of the most critical ST-induced changes for transformation of human cells. Many of these expression changes likely result from previously identified effects of SV40 ST in signal transduction pathways such as p27/Kip1 down-regulation (30) , AKT and telomerase activation (51) , mitogen-activated protein kinase pathway activation (52) , protein kinase C {zeta} activation of NF{kappa}B (37 , 53) , and induction of cyclins (46 , 47) . The remainder of the expression alterations may result from still unidentified effects of ST on other signal transduction pathways or from direct effects of ST on transcription factors. It is important to note that HEK-TERASB56{gamma} cells are serum-dependent, grow more slowly, and are less potently transformed than the HEK-TERST cells. Thus, whereas the set of 99 genes are probably the most critical ones for tumorigenesis, other ST-regulated genes outside of this group may account for the rapidly proliferating, serum-independent phenotype of the HEK-TERST cells.

Whereas 99 genes were affected similarly by ST and B56{gamma} knockdown, several hundred genes were not. Several different reasons could account for these observations. First, B56{gamma} antisense down-regulates B56{gamma} to a greater extent than ST (15) . Second, ST is known to target PP2A isoforms other than B56 (52) , although knockdown of B55 subunits cannot fully transform human cells as B56{gamma} knockdown does (15) . Third, the NH2-terminal domain of ST may influence the pattern of gene expression caused by PP2A inhibition. Finally, because our microarray experiments were performed in low serum and HEK-ASB56{gamma} cells are serum-dependent, more similarities with ST expression may be identified if these cells were compared in normal serum conditions.

Several of the genes regulated by ST have roles in prevention or induction of apoptosis. ST up-regulated ALDH1, which protects cells by metabolizing oxidized lipids; moreover, inhibitors of ALDH1 can drive Bcl-2 overexpressing cells into apoptosis (54) . ST also increased expression of SERPINB2, which inhibits tumor necrosis factor-induced apoptosis and strongly repressed expression of tumor necrosis factor-related apoptosis-inducing ligand. ST also inhibits apoptosis through repression of gelsolin, a regulator and effector of apoptosis. Gelsolin plays a key role in actin remodeling and motility, and associates with integrin {alpha}v, c-src, focal adhesion kinase, PI3K, and paxillin in response to integrin activation by osteopontin (55) .

Using an RGD peptide inhibitor, we showed that integrin signaling was essential for anchorage independent growth of both HEK-TERST and HEK-TERASB56{gamma} cell lines. Besides increases in integrin signaling targets, we also observed increased expression of three protease-activated receptors (PAR-1, PAR-2, and PAR-3), which could also contribute toward activation of PI3K and AKT. Consistent with recent work showing that constitutive PI3K signaling can substitute for ST to fully transform human cells (56) , we have shown that integrin signaling is critical for ST-helper function in tumorigenesis. Our data demonstrated that ST expression induces activation of src in low serum, whereas knockdown of B56{gamma} subunits results in serum-dependent src phosphorylation. Thus, the effects of ST on the integrin-src-PI3K pathway are critical for transformation of human cells.

It has been shown recently that {alpha}6ß4 integrin signaling can confer resistance to apoptosis in mammary epithelium via NF{kappa}B activation (57) . It is known that ST activates NF{kappa}B via protein kinase C {zeta} and PI3K signaling (37) and that PP2A regulates NF{kappa}B activation by dephosphorylation of the I{kappa}B kinase (39) . Thus, ST may be impacting NF{kappa}B activation in multiple ways, by mimicking and/or stimulating growth factor and integrin signaling and by modulation of PP2A activity.

ST affected expression of several developmental transcription factors, including HOXA9, HOXB3, HOXB6, Ets-1, FOXD1, FOXG1, and FOXM1. Additional developmental markers induced by ST included markers of pre-B and pro-B lymphocytes, cardiac, epithelial, endothelial, and neuronal tissues. The expression of early differentiation makers from such a wide variety of tissue types (see Supplementary Table S1) suggests that part of the helper function of ST results in a "dedifferentiated" phenotype of transformed cells. The observations that we report here suggest that ST may achieve this function in part by repression of components of junctional adhesion complexes such as ß-catenin, plakoglobin, JAM1, and protocadherin family members. Our conclusions are consistent with reports that overexpression of plakoglobin can suppress tumorigenicity of SV40-transformed cells (58) and that ST can alter distribution of and reduce levels of tight junction proteins such as occludin and claudin in polarized epithelial cells (59) .

In conclusion, we have identified the changes in gene expression induced by ST in transformation of human cells and determined that many of the critical changes are in genes that influence cellular adhesion, apoptosis, proliferation, development, and transcriptional regulation. Many of these factors may regulate pathways essential for tumor formation in human cells and could represent potential therapeutic targets.


   ACKNOWLEDGMENTS
 
The authors would like to thank Suresh Karanam, Wenjian Li, and Annise Chung for technical assistance, Dr. Joan Brugge, Ariad Pharmaceuticals, for src 327 monoclonal antibody, Dr. Charles Parkos for the W6/32 MHC Class-I monoclonal antibody, Dr. Andrew Young for assistance with QRT-PCR primer design, and Drs. Paul Wade, Andrew Neish, Jeremy Boss, and Guy Benian for critical reading of this manuscript.


   FOOTNOTES
 
Grant support: NIH Grant K22 CA96560 (C. S. Moreno), NIH Grant CA57327 (D. C. Pallas), NIH Grants K01 CA94223 and P01 CA50661, a Doris Duke Clinical Scientist Development Award, a Dunkin Donuts Rising Stars Award, and a Kimmel Scholar Award (W. C. Hahn).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: C. S. Moreno and S. Ramachandran contributed equally to this work. Supplementary data for this article can be found at http://morenolab.whitehead.emory.edu/pubs/ST/. Raw microarray data can be accessed at Array Express, accession number E-MEXP-156.

Requests for reprints: Carlos Moreno, Pathology and Laboratory Medicine, Whitehead Room 105J, 615 Michael Street, Emory University, Atlanta, GA 30322. E-mail: cmoreno{at}emory.edu, dpallas{at}emory.edu

6 Internet address: http://www.affymetrix.com/analysis/index.affx. Back

7 Internet address: http://genome.ucsc.edu. Back

Received 3/31/04. Revised 6/ 9/04. Accepted 7/23/04.


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 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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