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Molecular Cancer Research 3:1-13 (2005)
© 2005 American Association for Cancer Research

Angiogenesis, Metastasis, and the Cellular Microenvironment

Genomic Analysis of a Spontaneous Model of Breast Cancer Metastasis to Bone Reveals a Role for the Extracellular Matrix1

Bedrich L. Eckhardt1, Belinda S. Parker1, Ryan K. van Laar1, Christina M. Restall1, Anthony L. Natoli1, Michael D. Tavaria1, Kym L. Stanley1, Erica K. Sloan1, Jane M. Moseley2 and Robin L. Anderson1

1 Trescowthick Research Laboratories, Peter MacCallum Cancer Centre, East Melbourne, Melbourne, Victoria, Australia and 2 Department of Medicine, University of Melbourne, St. Vincent's Hospital, Fitzroy, Victoria, Australia

Requests for reprints: Robin L. Anderson, Trescowthick Research Laboratories, Peter MacCallum Cancer Centre, Locked Bag 1, A'Beckett Street, Melbourne, Victoria, Australia 8006. Phone: 61-3-9656-1285; Fax: 61-3-9656-1411. E-mail: robin.anderson{at}petermac.org


   Abstract
Top
 Notes
 Abstract
Introduction
 Results
 Discussion
 Materials and Methods
 Acknowledgements
 References
 
A clinically relevant model of spontaneous breast cancer metastasis to multiple sites, including bone, was characterized and used to identify genes involved in metastatic progression. The metastatic potential of several genetically related tumor lines was assayed using a novel real-time quantitative RT-PCR assay of tumor burden. Based on this assay, the tumor lines were categorized as nonmetastatic (67NR), weakly metastatic to lymph node (168FARN) or lung (66cl4), or highly metastatic to lymph node, lung, and bone (4T1.2 and 4T1.13). In vitro assays that mimic stages of metastasis showed that highly metastatic tumors lines were more adhesive, invasive, and migratory than the less metastatic lines. To identify metastasis-related genes in this model, each metastatic tumor was array profiled against the nonmetastatic 67NR using 15,000 mouse cDNA arrays. A significant proportion of genes relating to the extracellular matrix had elevated expression in highly metastatic tumors. The role of one of these genes, POEM, was further investigated in the model. In situ hybridization showed that POEM expression was specific to the tumor epithelium of highly metastatic tumors. Decreased POEM expression in 4T1.2 tumors significantly inhibited spontaneous metastasis to the lung, bone, and kidney. Taken together, our data support a role for the extracellular matrix in metastatic progression and describe, for the first time, a role for POEM in this process.

Key Words: Breast cancer • spontaneous metastasis • mouse model • microarray • POEM


   Introduction
Top
 Notes
 Abstract
 Introduction
Results
 Discussion
 Materials and Methods
 Acknowledgements
 References
 
Metastasis is the main cause of morbidity and mortality in cancer patients. In late-stage breast cancer, patients have tumor involvement in several tissues, including bone, lung, lymph node, and liver (1). The selective distribution of metastases is dictated by several factors, including the pattern of vascular flow from the primary site, complementary adhesive contacts, and molecular interactions between the tumor cell and the stroma at the secondary site (2).

Breast cancer metastases have a strong avidity for bone (3, 4), leading to metastases that cause intractable pain, spinal cord compression, bone fractures, and hypercalcemia (5, 6). Current therapies, including cytotoxic chemotherapy and the administration of bisphosphonates, are rarely curative but can alleviate symptoms arising from bone metastases (7). An improved understanding of the biological and genetic regulation of breast cancer metastasis to bone is essential to identify novel and more effective molecular targets for therapy.

The advent of microarray technology has greatly enhanced the search for genetic regulators and markers of metastasis. Indeed, arrays have been employed to identify genetic patterns that are predictive of metastatic relapse (8-10). They have also been used in animal models of metastasis to determine molecular mechanisms that dictate metastatic spread (11-14). Animal models provide an essential and powerful resource to investigate mechanisms of metastasis. However, breast cancer metastasis research is dominated by the use of xenograft models of experimental metastasis, typically involving the injection of human breast tumor cells directly into the circulatory system of immunocompromised mice, resulting in metastases in either lung (following tail vein injection) or bone (following intracardiac injection; refs. 14-17). These models have been valuable for studying the final stages of metastasis, and when coupled with microarray analysis, they can identify genes that regulate the colonization of specific tissues (13, 14). However, these models of experimental metastasis involve human tumors in a mouse host and may lack some of the critical tumor-host interactions. In addition, they do not encompass the initial stages of primary tumor growth, invasion, and metastasis from an orthotopic site. Thus, array analysis using these experimental metastasis models provides little insight into the biology of spontaneous metastasis.

A clinically relevant animal model of spontaneous breast cancer metastasis to multiple sites, including bone, is now available (18). Several syngeneic tumor lines with a spectrum of metastatic phenotypes have been isolated from a spontaneous mammary tumor in a BALB/cfC3H mouse (19). When injected into the mammary gland of mice, these tumor lines are either nonmetastatic (67NR; ref. 20), produce spontaneous metastases to lymph node (168FARN; ref. 21), lung (66cl4; ref. 22), or both (4T1; ref 20). 4T1.2 and 4T1.13 tumor lines are rare variants isolated from 4T1 cells that closely mimic the metastatic distribution of human breast cancer (18). When grown as a primary tumor in the mammary fat pad of a mouse, these tumor lines develop overt metastases in bone, lung, and lymph nodes (18). Furthermore, mice bearing 4T1.2 and 4T1.13 tumors occasionally develop hind limb paralysis and have elevated plasma levels of calcium and parathyroid hormone-related protein (PTHrP), two pathologic hallmarks of the human disease (18, 23). With a diverse range of metastatic capacities, these genetically related tumor lines provide a powerful model to investigate the molecular events that dictate metastasis of breast cancer.

For more accurate analysis of metastasis, a real-time quantitative reverse transcription-PCR (q-RT-PCR) assay for the measurement of tumor burden within a tissue has been developed. All tumor lines are tagged with a neomycin resistance gene, allowing them to be detected by q-RT-PCR of genomic DNA. Using this model of spontaneous breast cancer metastasis, critical metastasis-related genes can be identified. Gene expression profiles of metastatic tumors in this model were compared with the nonmetastatic 67NR using cDNA arrays consisting of 15,000 mouse gene elements. Array analysis revealed altered expression of extracellular matrix (ECM) genes in highly metastatic tumors. One of these genes, POEM, was shown to have a functional role in spontaneous breast cancer metastasis in the model.


   Results
Top
 Notes
 Abstract
 Introduction
 Results
Discussion
 Materials and Methods
 Acknowledgements
 References
 
Characterization of the Metastatic Dissemination of Several Syngeneic Mammary Tumor Lines
The spontaneous metastatic distribution of each tumor line was profiled using a sensitive q-RT-PCR assay for tumor burden (Fig. 1A). Tumor cells were inoculated into the fourth inguinal mammary glands of mice. Mice were culled and tissues were excised for genomic DNA extraction when the average primary tumor weight of each group was ~1.5 g or if the mice were displaying signs of distress. The result of a screen for spontaneous metastasis in mice bearing different tumor lines is shown in Fig. 1B. Corresponding tissues were also removed from a non-tumor-bearing mouse to measure background signal. The highest RTB signal detected in any tissue from a non-tumor-bearing mouse was 31; thus, RTB values below this were considered background. As expected, strong RTB scores were evident in all primary tumors. Consistent with previous observations (20), no RTB signals were detected in any tissue tested from mice bearing nonmetastatic 67NR tumors, confirming that this tumor line cannot develop spontaneous metastases.



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  		FIGURE 1. Metastatic dissemination of several genetically related tumor subpopulations by q-RT-PCR. A. Tumor burden within a tissue was measured using a novel multiplexed q-RT-PCR assay. This assay quantitates the relative amount of neomycin (tumor tissue) compared with vimentin (endogenous mouse tissue) from the genomic DNA extracted from the tissue of interest. B. Distribution of spontaneous metastases in mice bearing different tumor lines was measured using the q-RT-PCR assay described above. Average RTB scores from an experiment using five mice per tumor line. Tumor lines were grouped into three categories based on metastatic burden: nonmetastatic (67NR), weakly metastatic (168FARN and 66cl4), and highly metastatic (4T1.2 and 4T1.13). C. Presence of metastases (M) identified by q-RT-PCR were confirmed by H&E staining of representative sections of kidney, heart, femur, spine, and lung of mice bearing 66cl4 or 4T1.2 tumors. Visible metastases were confirmed in tissues identified with tumor burden by q-RT-PCR assay. N, normal tissue. Bar, 0.5 mm.

 
Mice bearing 168FARN and 66cl4 tumors presented with enlarged axillary lymph node (ALN) and metastatic lung nodules, respectively. This was reflected in modest RTB scores of ~200 (2% of the tissue consisted of metastatic cells) in both the ALN of 168FARN tumor-bearing mice and the lungs of mice with 66cl4 tumors. These tumors did not metastasize to any other tissues (Fig. 1B). 4T1.2 tumor-bearing mice also had enlarged ALN along with numerous metastatic foci in the lungs (Fig. 1C). When analyzed by q-RT-PCR, high RTB signals were detected in the lung (54% tumor tissue), ALN (29%), femur (17%), spine (10%), kidney (10%), and heart (8%; Fig. 1B). A similar metastatic pattern was observed for the 4T1.13 tumor line. Bone lysis was evident in bone metastases derived from 4T1.2 and 4T1.13 tumors (data not shown), consistent with previous reports of these tumor lines (18, 24). Tumor signals were also detected in the brain, liver, and spleen in mice harboring 4T1.2 and 4T1.13 tumors albeit to a minor extent (<1%). Thus, 4T1.2 and 4T1.13 can spontaneously metastasize to several organs, but preferential growth occurs in specific tissues (lung, ALN, and bone). The presence of tumor within the ALN of mice bearing 4T1.2 and 4T1.13 tumors suggests that these lines can also metastasize via a lymphogenous route.

The extent of metastasis from 4T1.2 and 4T1.13 tumors to ALN and lung was ~20-fold higher than metastases produced by 168FARN and 66cl4 tumors, respectively, indicating that 4T1.2 and 4T1.13 have a greater metastatic capacity than 168FARN and 66cl4. Furthermore, the metastatic distribution of 4T1.2 and 4T1.13 tumors is similar to that observed in advanced human breast cancer and, to our knowledge, provides the only syngeneic mouse model of spontaneous breast cancer metastasis to bone.

Representative sections of the kidney, heart, lung, spine, and femur provide further evidence of the difference in extent of metastatic dissemination of the 4T1.2 and 66cl4 tumors (Fig. 1C). Metastatic lung nodules from 4T1.2 tumors were larger and more numerous compared with those in the lungs of mice with 66cl4 tumors. Overt metastases in the spine and femur were detected in 4T1.2 and 4T1.13 tumors but not from 66cl4 tumors (Fig. 1C; data not shown). These histologic data agree with the RTB values determined by q-RT-PCR.

Increased Adhesion, Migration, and Invasion, but Not Angiogenesis and Proliferation, Correlate with Enhanced Metastatic Capacity
The processes of angiogenesis, proliferation, cell motility, invasion, and adhesion are critical for the formation of distant metastases. Thus, we determined whether highly, weakly, and nonmetastatic tumor lines differed in these metastasis-related processes using functional assays. As the recruitment of a blood supply is of vital importance for tumor growth in vivo, the angiogenic capacity of each tumor line was measured. After 6 days, Matrigel plugs containing tumor cells were removed from mice to assess hemoglobin content as a surrogate marker for the extent of angiogenesis. The use of hemoglobin content as a measure of angiogenesis has been validated previously (25). Whereas, as expected, all tumor lines could stimulate angiogenesis (6- to 8-fold higher compared with Matrigel without cells; P < 0.01), there were no significant differences observed between any tumor lines.3

The doubling time of each line was calculated as the rate of log-phase growth between 24 and 96 hours. All metastatic lines had faster in vitro doubling times than 67NR; however, doubling time could not distinguish highly from weakly metastatic tumor lines.3 The in vivo growth rates of the primary tumors were also monitored, but again no correlation was found with metastatic potential or in vitro proliferation.3

Adhesion is critical for metastasis related events, such as the initiation of cellular motility and for the extravasation into a tissue (26); hence, the adhesion of the tumor lines to Matrigel (a substrate similar to the ECM components of basement membranes) was measured. After 30 minutes of adhesion, the highly metastatic tumor lines displayed a significant 2-fold increase in adhesion to Matrigel compared with 67NR (P < 0.01; Fig. 2A). There was no difference in adhesion between the weakly metastatic tumor lines and 67NR. At later time points, all cell lines showed a similar extent of adhesion to Matrigel (data not shown).



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  		FIGURE 2. Differences in adhesion, migration, and invasion distinguish weakly and highly metastatic tumor lines. A. Ability of tumor cells to adhere to Matrigel-coated surfaces after 30-minute incubation at 37°C. B. Chemotactic migration of tumor cells toward a 10% FCS chemoattractant using a modified Boyden chamber assay. After 5 hours, the number of cells traversing the membrane was counted. C. Invasion of tumor cells through a Matrigel barrier in response to a 10% FCS chemoattractant. After 24 hours, the number of cells invading through the Matrigel and traversing the membrane was counted. In migration and invasion assays, five fields per sample were counted and averaged. Columns, mean of two experiments with triplicate samples; bars, SE (in all assays). *, P < 0.05; **, P < 0.01, Student's t test for metastatic tumor line compared with 67NR.

 
Chemotactic migration of the tumor lines was determined using a modified Boyden chamber assay. Migration was measured as the number of cells that were able to traverse from the apical to basal surface through pores within the membrane of the insert in response to a chemoattractant (10% FCS). 4T1.2 and 4T1.13 clearly showed a 10- to 20-fold increase in migration compared with other tumor lines (P < 0.01; Fig. 2B).

The invasive capacity of the tumor lines was examined by their ability to invade through a Matrigel barrier. Highly metastatic 4T1.2 and 4T1.13 cells were 4- to 10-fold more invasive than weakly metastatic tumor lines (P < 0.01; Fig. 2C). Interestingly, although the nonmetastatic 67NR showed negligible migration (Fig. 2B), this tumor line was clearly able to invade through a Matrigel barrier. In fact, the level of invasion displayed by 67NR was significantly greater than that of 168FARN and 66cl4 but significantly less than 4T1.2 and 4T1.13 (P < 0.01). The invasion response was not seen in the negative controls (no chemoattractant), indicating a possible interplay between Matrigel and FCS to stimulate an invasive phenotype of 67NR in vitro. Despite this invasive phenotype, 67NR was incapable of metastasizing in vivo (Fig. 1B).

Identification of Genes Associated with Highly and Weakly Metastatic Tumors
To identify genes associated with metastasis in our model, pooled RNA from five primary tumors was arrayed using RNA from the nonmetastatic 67NR primary tumor as a common reference. Array experiments were repeated four times for each tumor line, including two replicates with dye reversals to control for dye incorporated bias (as described in Materials and Methods). To identify genes that were altered between the two metastatic phenotypes, we grouped the expression profiles of 168FARN and 66cl4 tumors (weakly metastatic group) and compared these with the grouped expression profiles of 4T1.2 and 4T1.13 tumors (highly metastatic group). Gene elements (n = 216) were identified with significant (P < 0.01 between the two groups) and ≥2-fold difference in expression.3 Of the 216 genes, 125 were known genes, 9 were duplicated genes, and 82 were either expressed sequence tags or had weak homology to genes from other species.3 Of the 125 known genes, 36 and 89 genes were expressed at higher levels in the weakly and highly metastatic tumors, respectively. Genes with at least 4-fold altered expression between the two groups are displayed in Table 1


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  		Table 1. Genes with Differential Expression between Highly and Weakly Metastatic Tumors and Their Correlation to Cancer and Metastasis-Related Processes

 
A survey of the current literature on the genes presented in Table 1 revealed that 65% have been associated previously with human cancer, 33% with human breast cancer, and 21% with metastasis. The close association of the mouse genes with human cancer shows their clinical relevance, especially to breast cancer. Further support for the use of this model to identify genetic regulators of metastasis comes from the 21% of the genes that have been associated previously with metastasis. Eight genes identified by microarray analysis were selected for verification by q-RT-PCR. Analysis of replicate samples from 66cl4 and 4T1.2 tumors confirmed a close correlation with the level of expression as revealed by microarray analysis (Fig. 3).



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  		FIGURE 3. Differential expression of candidate genes identified by microarray analysis was confirmed by RT-PCR. Comparative expression levels of a panel of eight genes were assayed by RT-PCR to validate microarray results. Columns, fold difference in gene expression of 4T1.2 tumors compared with 66cl4 tumors. Full names of the eight genes analyzed are shown in Table 1.

 
Of the genes listed in Table 1, 18 (41%) were associated with adhesion, migration, or invasion, all aspects of the metastatic process that distinguished the highly metastatic phenotype in our model. Interestingly, a significant number of genes encoding ECM molecules (9 of 89) were altered in highly metastatic tumors (P = 0.037; Table 2). One of these genes, POEM, was examined further for functional relevance in metastasis.


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  		Table 2. Genes Encoding ECM That Were Altered in Highly Metastatic Tumors

 
POEM Expression in Primary Tumors
Although this recently identified ECM protein has been implicated in cellular adhesion and morphogenesis (27, 28), no association with cancer has been reported. POEM was expressed 30- to 80-fold higher in highly metastatic compared with weakly metastatic tumors (Table 1; Fig. 3). Furthermore, RT-PCR analysis indicated that the cell lines also express POEM in vitro and that the level of expression is ~30-fold higher in 4T1.2 cells compared with 67NR and 66cl4 cells (data not shown).

To confirm the microarray result, POEM expression was measured by in situ hybridization in primary tumors of varying metastatic potential. Using the mouse embryo as a positive control, it was found that the POEM antisense riboprobes specifically stained the inner muscle layer of the stomach as reported previously (28). This staining was not observed using the control sense riboprobes, indicating that any staining observed was due to the presence of POEM RNA transcripts (Fig. 4). POEM expression was compared between primary tumors of the mouse model, revealing a lack of expression in the nonmetastatic and weakly metastatic primary tumors and high level POEM expression in the highly metastatic 4T1.2 primary tumor. The staining was epithelial cell specific (Fig. 4). The expression of POEM in 4T1.2 primary tumors indicates that this gene may have a role in promotion of metastasis.



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  		FIGURE 4. In situ hydridization of POEM in 67NR, 66cl4, and 4T1.2 primary tumors. Gut lining of a mouse day 15 embryo was used as a positive control for POEM expression using a mixture of POEM antisense riboprobes, with sense riboprobes as a negative control. Serial sections of primary tumors were stained with H&E and with the sense and antisense probes. 3,3'-Diaminobenzidine staining (brown) reveals positive riboprobe annealing. Sections were counterstained with hematoxylin (blue). Bar, 50 µm.

 
Reduced POEM Expression Impairs Tumor Growth and Metastasis
Using RNA interference we tested the effect of decreased POEM expression on tumor growth and metastasis in the 4T1.2 tumor model. We engineered the previously described pRetroSuper (pRS) vector (29) to encode short-hairpin RNAs specific for either POEM or GFP (nonsilencing control) and transfected these constructs into 4T1.2 cells, creating tumor lines 4T1.2pRS-POEM and 4T1.2pRS-GFP, respectively. Reduced POEM expression was detected by RT-PCR, which has been shown previously to be an accurate measure of gene knockdown (30). A 60% reduction in POEM expression was observed in 4T1.2pRS-POEM compared with 4T1.2 and 4T1.2pRS-GFP cells (P < 0.01; Fig. 5A). Decreased POEM expression was stable for at least 8 weeks in culture (data not shown). The 4T1.2pRS-GFP and 4T1.2pRS-POEM lines were injected into the mammary glands of BALB/c mice (15 per group) and tumor growth was monitored. Reduced POEM expression did not alter primary tumor growth rate (Fig. 5B) or the final tumor weight (Fig. 5C). Reduced POEM expression at the end of the experiment was confirmed in 4T1.2pRS-POEM primary tumors as analyzed by RT-PCR of three primary tumors from each group (Fig. 5D). Metastatic burden was reduced significantly in the lungs, spine, and kidney but not the in heart of mice bearing 4T1.2pRS-POEM tumors (P < 0.05; Fig. 5E). In a repeat experiment, similar results were found, with a reduction in lung and bone metastases, but no difference in ALN metastases between groups (data not shown).



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  		FIGURE 5. Reduced POEM in the bone metastasizing tumor line 4T1.2 inhibits spontaneous metastasis. A. RT-PCR analysis of POEM expression in cultured cells. 4T1.2pRS-GFP and 4T1.2pRS-POEM lines were produced by stable transfection of vectors encoding short-hairpin RNA specific for either GFP or POEM, respectively. Gene expression is displayed relative to GAPDH. Columns, average of three replicates; bars, SE. B. Tumor cells were injected into the fat pad of mice (15 mice per group) and tumor growth was monitored by caliper measurements (hard line, 4T1.2pRS-GFP; dashed line, 4T1.2pRS-POEM). Mice were culled and tissues were harvested for assay of metastatic burden on day 30. C. Average weights of the primary tumors at the end of the study indicate no difference between the two groups. D. At the end of the experiment, POEM expression in three primary tumors from each group was analyzed by RT-PCR. E. q-RT-PCR analysis of metastatic tumor burden in tissues from mice bearing 4T1.2pRS-GFP (open columns) or 4T1.2pRS-POEM tumors (black columns). Columns, average RTB for each tissue; bars, SE. *, P < 0.05.

 

   Discussion
Top
 Notes
 Abstract
 Introduction
 Results
 Discussion
Materials and Methods
 Acknowledgements
 References
 
In this study, we have identified a set of genes linked to spontaneous breast cancer metastasis, and we have reported a sensitive q-RT-PCR assay of tumor burden. Several genetically related tumor lines were assayed to reveal that 67NR is nonmetastatic, 66cl4 spontaneously metastases to lung and 168FARN metastases to lymph nodes (20, 21). 4T1.2 and 4T1.13 are highly metastatic variants, derived from the lung metastasizing 4T1 tumor line, and spread to several organs including heart, kidney, lung, lymph node, and bone. Low metastatic burden was also noted in the brain, spleen, and liver. The pattern of secondary growth observed in 4T1.2 and 4T1.13 tumors is similar to that of human metastatic breast cancer. Moreover, these tumors cause the characteristic in vivo markers of metastatic bone disease, including pathologic fractures, hypercalcemia, and increased plasma PTHrP (18). To our knowledge, this is the only mouse model where overt bone metastases are observed following spontaneous metastasis from the mammary gland.

The genetic regulation of breast cancer metastasis is an area of intense research (8, 9, 14, 31, 32). With the advent of microarray technology, the transcriptional profile of a tumor can be obtained and linked to its phenotype. Previous array studies have been useful in delineating genes involved in the metastatic process (11, 12, 14, 33); however, the interpretation of such data is limited by the restraints of the model being used. For example, array analysis on tumor lines that form experimental metastases in bone following intracardiac inoculation is ideal for the identification of genes that regulate bone colonization but not for genes that are involved in the earlier events of metastasis. Here, primary tumors in the spontaneous metastasis model were profiled to identify genes associated with aggressive metastatic disease.

We identified a panel of 216 genes with altered expression between highly and weakly metastatic tumors. Interestingly, a large number of genes identified using this model have been associated previously with human breast cancer or metastatic progression, thus demonstrating the relevance of this model for the identification of clinically relevant genes. To narrow the spectrum of genes, we adopted a previously described method of linking known genes to their putative biological functions and then correlating this with the metastatic processes that were altered between tumor phenotypes (12). In other studies, metastatic tumor lines have been shown to display a greater capacity to adhere to the ECM, to proliferate, to attract a blood supply, and to acquire a motile and invasive phenotype (12, 34–36). Using functional assays that mimic these processes, we found that adhesion, migration, and invasion, but not tumor angiogenesis or proliferative capacity, best characterized the differences observed between highly and weakly metastatic tumors in our model.

Notably, a significant proportion of genes that had elevated expression in highly metastatic tumors were those that encode ECM proteins. These include matrix {gamma}-carboxyglutamate protein, POEM, laminin {alpha}5 and ß1 subunits, and several procollagen isoforms. Previous array studies of other metastatic tumors have also revealed altered expression of ECM genes (11, 37). Interaction between the ECM and the tumor cell can alter physiologic processes within the tumor microenvironment and thereby influence metastatic progression (38, 39). ECMs have also been implicated in epithelial cell differentiation and branching morphogenesis within the mammary gland, biological events that reflect the invasion of breast cancer cells (40). Depending on the subunit composition, laminins exert varied cellular effects (41). The {alpha}5 and ß1 subunits (major components of laminin-10) have been detected in breast cancer lesions and implicated in the motility and invasion of human colon carcinoma cells via interactions with {alpha}3ß1 and {alpha}6ß4 integrins (42). A role for laminin-10 in breast cancer metastasis remains unresolved. Overexpression of the matrix Gla protein in human breast carcinoma lines and in human metastatic melanoma has been reported (11, 43). Likewise, many of the procollagen isoforms have also been associated with metastatic progression. The amino-terminal propeptide of procollagen I has been implicated as a marker for prostate cancer metastasis to bone (44), whereas procollagen isoforms V, VI, and XVIII are involved in remodeling of the tumor microenvironment and in promoting cellular adhesion and motility (37, 45-47).

POEM is a novel secreted ECM molecule that showed a striking increase in expression (30- to 80-fold) in the highly metastatic 4T1.2 and 4T1.13 lines. Whereas POEM expression has not been implicated previously in cancer, we have shown a selective reduction in breast cancer metastasis to the lung, kidney, and bone using the 4T1.2 model. As POEM has been reported to be involved in kidney morphogenesis and the development of bone (preosteoblastic cells; refs. 27, 28), the expression of POEM by the tumor cells may be critical for establishment in these sites.

POEM consists of five epidermal growth factor–like domains, an Arg-Gly-Asp integrin binding motif and a meprin, A5 protein and receptor protein-tyrosine phosphatase µ (MAM) domain (27). The Arg-Gly-Asp and MAM domains have been linked to adhesion, spreading, and survival of preosteoblastic cells (25). As these processes are crucial to metastasis, they provide an explanation for the diminished metastatic capacity of 4T1.2 cells with reduced POEM expression. The Arg-Gly-Asp site in POEM binds to several integrin receptors, including {alpha}vß3, {alpha}vß5, {alpha}vß6, and {alpha}4ß7 (27), although the favored receptor pairing is the {alpha}8ß1 integrin (27, 28). It is thought that adhesive and survival signals are conveyed through {alpha}8ß1, which is similarly expressed in 66cl4 and 4T1.2 cells.4 However, in tumors with decreased POEM expression (i.e., 66cl4), these signals may not be effectively conveyed and thus result in a weaker metastatic phenotype. The precise mechanism of POEM function and the involvement of {alpha}8ß1 integrin in tumor growth and metastasis in this model are the subjects of ongoing studies.

The function of human POEM is yet to be investigated due to the lack of a full-length clone of the human gene. Recently, using a high-throughput screen for transmembrane and secreted proteins, a hypothetical human protein, LOC255743 (National Center for Biotechnology Information reference NM_198278), was identified with high similarity (82% identity) to POEM (48). Further analysis of LOC255743 using SAGE map (National Center for Biotechnology Information) identified two SAGE tags5 that were detectable in libraries derived from normal kidney, thyroid, brain, and lung as well as libraries from two patients with invasive ductal breast carcinoma, one patient with metastatic gastric cancer, and one patient with a grade 3 brain astrocytoma (49). These observations implicate POEM in human tumor progression; however, further study is required to establish a role for POEM in the growth and metastasis of human breast cancer.

In summary, we have characterized a unique, clinically relevant model of breast cancer metastasis at both genomic and phenotypic levels. By combining our model with array technology, we have identified a set of metastasis-related genes, some of which have been implicated in human breast cancer, but many remain to be characterized. A significantly high proportion of these genes were ECM molecules, which is consistent with current views on the importance of cell-ECM interactions in metastasis (39). Finally, we have shown that POEM, a gene identified by array analysis, has a role in primary breast tumor growth and in spontaneous metastasis.


   Materials and Methods
Top
 Notes
 Abstract
 Introduction
 Results
 Discussion
 Materials and Methods
Acknowledgements
 References
 
Cell Culture and Reagents
The tumor lines 67NR, 168FARN, 66cl4, and 4T1 were provided by Dr. Fred Miller (Karmanos Cancer Institute, Detroit, MI). These lines are clonal populations of cells derived from a spontaneous mammary carcinoma arising in a BALB/cfC3H mouse (19). The 4T1 line was further cloned to isolate lines 4T1.2 (18) and 4T1.13. All lines were transfected with a plasmid containing the neomycin resistance gene to discriminate tumor cells from endogenous mouse tissue in a q-RT-PCR assay (see below). Cells were maintained in {alpha}-MEM medium supplemented with 10% FCS, penicillin, and streptomycin (1:100 dilution, Life Technologies, Rockville, MD) and incubated at 37°C with 5% CO2. Cells were not allowed to reach confluence and were passaged for a maximum of 4 weeks. Before experimentation, viability was assessed by trypan blue exclusion.

Detection of Tumor Growth and Spontaneous Metastases
Female BALB/c mice (6-8 weeks old, ARC, Perth, Western Australia, Australia) were anaesthetized and injected with 1 x 105 viable cells into the fourth mammary fat pad. When palpable, tumor growth was monitored twice weekly using electronic calipers: tumor volume = (length x width2) / 2. Entire organs, including primary tumor, lung, liver, ALN, spleen, both kidneys, both femurs, spine, brain, and heart, were excised from mice once the average primary tumor weight of a group of mice was 1.5 g or sooner if mice displayed signs of distress. All mice bearing one tumor line were sacrificed on the same day. Tissues were snap frozen in liquid nitrogen and homogenized and the genomic DNA was isolated. Tumor burden for each individual tissue was measured using q-RT-PCR incorporating Taqman chemistry (Applied Biosystems, Foster City, CA). Genomic DNA was subjected to multiplexed q-RT-PCR to detect the cycle threshold (Ct) for vimentin (total mouse tissue) and neomycin (tumor cells only). By comparing the Ct values of vimentin and neomycin ({Delta}Ct), a score for relative tumor burden was calculated using the following formula: Relative tumor burden = 10,000 x 1 / 2Corr{Delta}Ct. Corr{Delta}Ct is a {Delta}Ct value that includes correction for the difference in neomycin copy number in each tumor line as determined by multiplexed q-RT-PCR. Note that genomic DNA (not RNA) is being amplified in this assay; hence, difference in vimentin gene expression between tissues is not a factor. Using this formula, a tissue without tumor scores zero, whereas a tissue composed entirely of tumor cells scores 10,000. PCR was done using an ABI Prism 7000 thermocycler (Applied Biosystems) using standard cycling methods. All PCR reagents were obtained from Applied Biosystems, except for neomycin and vimentin forward and reverse primers (GeneWorks, Adelaide, South Australia, Australia). Sequences for primers and probes used in Taqman assays were designed using Primer Express version 2.0 software (Applied Biosystems).3 Multiplex PCR reactions consisted of the following primer/probe concentrations: vimentin probe 50 nmol/L, vimentin forward and reverse primers 50 nmol/L, neomycin probe 75 nmol/L, and neomycin forward and reverse primers 150 nmol/L.

Microarray Design, Hybridization, Scanning, and Analysis
The NIA mouse 15K cDNA clone set (50) contains 15,272 elements, comprising 13,739 unique UniGene identifiers (UniGene Build 127) and ~30% novel genes (51). PCR products from the clone set were purified and arrayed onto glass slides using in-house facilities according to published methods (52). RNA was isolated from tumors as described previously (53). The purity of the RNA was confirmed by spectrophotometry and the quality was checked by electrophoresis on a formaldehyde-1% agarose gel. For the cDNA microarray analysis, pools of five primary tumors were used. RNA from the nonmetastatic 67NR tumor was used as a reference for all the other tumor lines. Microarray analysis for each primary tumor was repeated four times using dye reversals for two arrays to account for dye-incorporated bias. Total RNA (100 µg) was labeled with fluorescent Cy3 or Cy5 dyes, hybridized, and washed as described (53). Arrays were scanned using an Agilent confocal laser scanner (Agilent Technologies, Palo Alto, CA), and fluorescence intensities from both Cy3 and Cy5 channels of each scanned image were quantified using GenePix Pro version 4.1 (Axon Instruments, Union City, CA). Spots displaying altered morphology or with low fluorescence intensities in both channels were excluded from the data set. Data were imported into Genespring version 6 (Silicon Genetics, Redwood City, CA), and each clone was averaged over the four replicates and normalized using the LOWESS regression model (54). Nonparametric ANOVA (Kruskal-Wallis test) with the Benjamini and Hochberg false discovery rate correction for multiple testing was used to identify genes differentially expressed between highly and weakly metastatic tumors. All expression data and microarray experimental details were stored on a local MIAME-complaint relational database system (55).

RT-PCR Analysis
To validate results obtained from microarray analysis, real-time RT-PCR of selected genes was done. cDNA was synthesized from primary tumor RNA, primed with random hexamers (Promega, San Luis Obispo, CA), and reverse transcribed by SuperScript II transcriptase (Promega) according to manufacturer's instructions. RT-PCR was done on an ABI Prism 7000 thermocycler using SYBR Green I chemistry (Applied Biosystems). Primers used in all PCR analyses were designed using the Primer Express version 2.0 program.3 PCR consisted of 20 ng cDNA, 0.1 µmol/L forward and reverse primers, and 2x SYBR Green I master mix reagent. Standard cycling procedures were employed. Specific amplicon formation with each primer pair was confirmed by dissociation curve analysis and by visualization of a single band on a 2% agarose gel. Gene expression was measured relative to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) using the following formula: Relative transcript abundance = 10,000 / 2 (CtGene – CtGAPDH). GAPDH was used as a baseline for RT-PCR analysis, because microarray experiments showed no significant change in GAPDH expression between the tumor lines.

In vivo Angiogenesis Assay
The angiogenic capacity of each tumor line (five mice per group) was measured by the recruitment of vascular endothelium toward tumor cells embedded in a Matrigel plug in a BALB/c mouse. Cells (2 x 106) were resuspended in 200 µL Matrigel (BD Biosciences, Franklin Lakes, NJ) and injected s.c. into BALB/c mice. Plugs were removed 6 days later and assayed for hemoglobin content (Sigma Diagnostics, St. Louis, MO).

Sulforhodamine B Proliferation Assay
Cells (500) were fluorescence-activated cell sorted based on propidium iodide exclusion into 96-well plates. At 12-hour time points, cells were fixed in 10% trichloroacetic acid, rinsed, and stained in 0.4% sulforhodamine B dissolved in 1% acetic acid. Protein-bound dye was released with 10 mmol/L Tris base, and the absorbance was measured by spectrophotometry at 550 nm. Five replicate wells were used per time point. In vitro growth rate was calculated from readings over a period of 72 hours.

Adhesion Assay
Plates (96-well) were coated overnight at 4°C with Matrigel diluted 1:50 in PBS. Excess Matrigel was aspirated, and the wells were rinsed with PBS, blocked for 1 hour at 37°C with 2% bovine serum albumin, and rinsed again in PBS. Cells (1 x 105) were seeded in serum free {alpha}-MEM medium and incubated at 37°C with 5% CO2 for 30 minutes. The 30-minute time point was chosen because it showed the best resolution between the tumor lines. At later time points, all tumor lines had adhered almost completely. After 30 minutes, cells were washed and stained with 2% crystal violet in 50% methanol. Bound dye was released with 1% SDS, and absorbance was measured at 550 nm.

Migration and Invasion Assays
Migration and invasion assays were done according to previously established methods (56). The time points used in the migration (5 hours) and invasion (24 hours) assays were optimized previously to reveal the most significant differences between the tumor lines.

In situ Hybridization
A mixture of 450- to 550-bp riboprobes for POEM was generated by amplification of the POEM DNA region of interest and insertion into a PCR cloning vector (pGEM-T Easy Vector System, Promega) containing a T7/SP6 bidirectional promoter system for generating sense and antisense transcripts. T7 and SP6 polymerase were used for in vitro transcription, with generation of sense and antisense probes depending on the orientation of the insert. The in vitro transcription included labeling of transcripts with FITC (using FITC-UTP according to manufacturer's instruction, Roche Diagnostics, Basel, Switzerland).

Tissues were fixed overnight in 10% buffered formalin at 4°C and paraffin embedded. Sections of a 15.5-day embryo and 67NR, 66cl4, and 4T1.2 primary mammary tumors were used for in situ hybridization. Individual riboprobes were used initially to determine those that gave the best signal with minimal background DNA binding, and these were pooled into a cocktail to be used for all subsequent hybridizations (including sense and antisense cocktails). The protocol was as described previously, including dewaxing and fixation of tissues and pretreatment for access to target nucleic acid sequence, except that FITC labeling replaced DIG (57, 58). Riboprobe/FITC signal was detected and amplified using the GenPoint Fluorescein Tyramide Signal Amplification System (DakoCytomation, Carpenteria, CA). The signal was visualized using 3,3'-diaminobenzidine staining followed by nuclear counterstaining with hematoxylin.

Preparation of 4T1.2 Cells with Decreased POEM Expression
The mammalian expression vector pRS, a gift from Dr. Reuven Agami (Netherlands Cancer Institute, Amsterdam, the Netherlands), was used for the expression of short-hairpin RNA (29). A synthesized oligonucleotide encoding a short-hairpin RNA sequence specific for POEM was ligated into the BglII/HindIII sites of pRS vector (pRS-POEM). The oligonucleotide encoded a gene-specific 19-bp sequence corresponding to nucleotides 1,328 to 1,346 downstream of the transcription start site of POEM (5'-AGGACGACCCAGGTATTCT-3'), which was separated by a 9-bp noncomplementary spacer (5'-TTCAAGAGA-3') from the reverse complement of the same 19-bp sequence. A nonsilencing vector control was similarly fashioned to target GFP (5'-CCACTACCTGAGCACCCAG-3'; pRS-GFP), a protein not expressed in mammalian cells. Functionality of the pRS-GFP vector was shown when transient transfection of this vector greatly diminished GFP expression in 293 cells stably expressing GFP (data not shown). pRS-GFP or pRS-POEM were transfected into neomycin-tagged 4T1.2 cells using LipofectAMINE 2000 reagent according to manufacturer's instructions. Stable cell lines were selected by culturing the cells in {alpha}-MEM medium containing 5 µg/mL puromycin for 2 weeks. Following single cell cloning of both 4T1.2pRS-GFP and 4T1.2pRS-POEM cells, five clones with normal levels of POEM were pooled from 4T1.2pRS-GFP and five clones with a similar level of reduction of POEM were pooled from 4T1.2pRS-POEM. POEM expression was assessed by RT-PCR as described above. The pooled clones were used in subsequent experiments.


   Acknowledgements
Top
 Notes
 Abstract
 Introduction
 Results
 Discussion
 Materials and Methods
 Acknowledgements
References
 
We acknowledge Dr. Fred Miller for supplying some of the tumor lines used in this study; Dr. Jeannie Javni for the isolation of the 4T1.2 tumor line; Clare Fritzlaff for valuable technical assistance; Drs. David Bowtell, Izhak Haviv, Grant McArthur, and Normand Pouliot for constructive discussions; and the Peter MacCallum Microarray Facility for technical assistance and for the fabrication of the cDNA arrays used in this study.


   Notes
Top
 Notes
Abstract
 Introduction
 Results
 Discussion
 Materials and Methods
 Acknowledgements
 References
 
1 Department of Defense Breast Cancer Research Program grants DAMD17-98-1-8144 (R.L. Anderson) and DAMD17-01-1-0371 (M.D. Tavaria), Susan G. Komen Breast Cancer Foundation predoctoral fellowship (E.K. Sloan), and NIH/National Cancer Institute grant ROI CA90291 (R.L. Anderson). Back

3 Supplementary data for this are available at Molecular Cancer Research Online (http://mcr.aacrjournals.org/). Back

4 B.L. Eckhardt, unpublished results. Back

5 SAGE tags scrutinized were GTAAAGGTAT and CATTTTTAAT. Back

Received June 1, 2004; revised November 19, 2004; accepted November 30, 2004.


   References
Top
 Notes
 Abstract
 Introduction
 Results
 Discussion
 Materials and Methods
 Acknowledgements
 References
 

  1. Patanaphan V, Salazar OM, Risco R. Breast cancer: metastatic patterns and their prognosis. South Med J 1988;81:1109–12.[Medline]
  2. Chambers AF, Groom AC, MacDonald IC. Dissemination and growth of cancer cells in metastatic sites. Nat Rev Cancer 2002;2:563–72.[CrossRef][Medline]
  3. Coleman RE, Rubens RD. The clinical course of bone metastases from breast cancer. Br J Cancer 1987;55:61–6.[Medline]
  4. Mundy GR. Metastasis to bone: causes, consequences and therapeutic opportunities. Nat Rev Cancer 2002;2:584–93.[CrossRef][Medline]
  5. Stewart AF, Vignery A, Silverglate A, et al. Quantitative bone histomorphometry in humoral hypercalcemia of malignancy: uncoupling of bone cell activity. J Clin Endocrinol Metab 1982;55:219–27.[Abstract]
  6. Lipton A. Bone metastases in breast cancer. Curr Treat Options Gastroenterol 2003;4:151–8.
  7. Green JR. Antitumor effects of bisphosphonates. Cancer 2003;97:840–7.[CrossRef][Medline]
  8. van't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530–6.[CrossRef][Medline]
  9. Ramaswamy S, Ross KN, Lander ES, Golub TR. A molecular signature of metastasis in primary solid tumors. Nat Genet 2003;33:49–54.[CrossRef][Medline]
  10. Sotiriou C, Neo SY, McShane LM, et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A 2003;100:10393–8.[Abstract/Free Full Text]
  11. Clark EA, Golub TR, Lander ES, Hynes RO. Genomic analysis of metastasis reveals an essential role for RhoC. Nature 2000;406:532–5.[CrossRef][Medline]
  12. Khanna C, Khan J, Nguyen P, et al. Metastasis-associated differences in gene expression in a murine model of osteosarcoma. Cancer Res 2001;61:3750–9.[Abstract/Free Full Text]
  13. Kakiuchi S, Daigo Y, Tsunoda T, Yano S, Sone S, Nakamura Y. Genome-wide analysis of organ-preferential metastasis of human small cell lung cancer in mice. Mol Cancer Res 2003;1:485–99.[Abstract/Free Full Text]
  14. Kang Y, Siegel PM, Shu W, et al. A multigenic program mediating breast cancer metastasis to bone. Cancer Cell 2003;3:537–49.[CrossRef][Medline]
  15. Arguello F, Baggs RB, Frantz CN. A murine model of experimental metastasis to bone and bone marrow. Cancer Res 1988;48:6876–81.[Abstract/Free Full Text]
  16. Price JE, Polyzos A, Zhang RD, Daniels LM. Tumorigenicity and metastasis of human breast carcinoma cell lines in nude mice. Cancer Res 1990;50:717–21.[Abstract/Free Full Text]
  17. Duivenvoorden WC, Popovic SV, Lhotak S, et al. Doxycycline decreases tumor burden in a bone metastasis model of human breast cancer. Cancer Res 2002;62:1588–91.[Abstract/Free Full Text]
  18. Lelekakis M, Moseley JM, Martin TJ, et al. A novel orthotopic model of breast cancer metastasis to bone. Clin Exp Metastasis 1999;17:163–70.[CrossRef][Medline]
  19. Dexter DL, Kowalski HM, Blazar BA, Fligiel Z, Vogel R, Heppner GH. Heterogeneity of tumor cells from a single mouse mammary tumor. Cancer Res 1978;38:3174–81.[Abstract/Free Full Text]
  20. Aslakson CJ, Miller FR. Selective events in the metastatic process defined by analysis of the sequential dissemination of subpopulations of a mouse mammary tumor. Cancer Res 1992;52:1399–405.[Abstract/Free Full Text]
  21. Aslakson CJ, Rak JW, Miller BE, Miller FR. Differential influence of organ site on three subpopulations of a single mouse mammary tumor at two distinct steps in metastasis. Int J Cancer 1991;47:466–72.[Medline]
  22. Miller BE, McInerney D, Jackson D, Miller FR. Metabolic cooperation between mouse mammary tumor subpopulations in three-dimensional collagen gel cultures. Cancer Res 1986;46:89–93.[Abstract/Free Full Text]
  23. Rankin W, Grill V, Martin TJ. Parathyroid hormone-related protein and hypercalcemia. Cancer 1997;80:1564–71.[CrossRef][Medline]
  24. Parker BS, Eckhardt BL, Anderson RL. Models of breast cancer metastasis to bone: characterization of a clinically relevant model. In: Singh G, Orr FW, editors. Bone metastasis. The Netherlands: Kluwer Press; 2004; p. 1–18.
  25. Lee MS, Moon EJ, Lee SW, Kim MS, Kim KW, Kim YJ. Angiogenic activity of pyruvic acid in in vivo and in vitro angiogenesis models. Cancer Res 2001;61:3290–3.[Abstract/Free Full Text]
  26. Muller A, Homey B, Soto H, et al. Involvement of chemokine receptors in breast cancer metastasis. Nature 2001;410:50–6.[CrossRef][Medline]
  27. Brandenberger R, Schmidt A, Linton J, et al. Identification and characterization of a novel extracellular matrix protein nephronectin that is associated with integrin {alpha}8ß1 in the embryonic kidney. J Cell Biol 2001;154:447–58.[Abstract/Free Full Text]
  28. Morimura N, Tezuka Y, Watanabe N, et al. Molecular cloning of POEM: a novel adhesion molecule that interacts with {alpha}8ß1 integrin. J Biol Chem 2001;276:42172–81.[Abstract/Free Full Text]
  29. Brummelkamp TR, Bernards R, Agami R. Stable suppression of tumorigenicity by virus-mediated RNA interference. Cancer Cell 2002;2:243–7.[CrossRef][Medline]
  30. Zhang L, Fogg DK, Waisman DM. RNA interference-mediated silencing of the S100A10 gene attenuates plasmin generation and invasiveness of Colo 222 colorectal cancer cells. J Biol Chem 2004;279:2053–62.[Abstract/Free Full Text]
  31. Sgroi DC, Teng S, Robinson G, LeVangie R, Hudson JR Jr, Elkahloun AG. In vivo gene expression profile analysis of human breast cancer progression. Cancer Res 1999;59:5656–61.[Abstract/Free Full Text]
  32. Sloan EK, Anderson RL. Genes involved in breast cancer metastasis to bone. Cell Mol Life Sci 2002;59:1491–502.[CrossRef][Medline]
  33. Khanna C, Wan X, Bose S, et al. The membrane-cytoskeleton linker ezrin is necessary for osteosarcoma metastasis. Nat Med 2004;10:182–6.[CrossRef][Medline]
  34. Tester AM, Ruangpani N, Anderson RL, Thompson EW. MMP-9 secretion and MMP-2 activation distinguish invasive and metastatic sublines of a mouse mammary carcinoma system showing epithelial-mesenchymal transition traits. Clin Exp Metastasis 2000;18:553–60.[CrossRef][Medline]
  35. Marneros AG, Olsen BR. The role of collagen-derived proteolytic fragments in angiogenesis. Matrix Biol 2001;20:337–45.[CrossRef][Medline]
  36. Gu YC, Kortesmaa J, Tryggvason K, et al. Laminin isoform-specific promotion of adhesion and migration of human bone marrow progenitor cells. Blood 2003;101:877–85.[Abstract/Free Full Text]
  37. Wang W, Wyckoff JB, Frohlich VC, et al. Single cell behavior in metastatic primary mammary tumors correlated with gene expression patterns revealed by molecular profiling. Cancer Res 2002;62:6278–88.[Abstract/Free Full Text]
  38. Pupa SM, Menard S, Forti S, Tagliabue E. New insights into the role of extracellular matrix during tumor onset and progression. J Cell Physiol 2002;192:259–67.[CrossRef][Medline]
  39. Liotta LA, Kohn EC. The microenvironment of the tumour-host interface. Nature 2001;411:375–9.[CrossRef][Medline]
  40. Fata JE, Werb Z, Bissell MJ. Regulation of mammary gland branching morphogenesis by the extracellular matrix and its remodeling enzymes. Breast Cancer Res 2004;6:1–11.[Medline]
  41. Patarroyo M, Tryggvason K, Virtanen I. Laminin isoforms in tumor invasion, angiogenesis and metastasis. Semin Cancer Biol 2002;12:197–207.[CrossRef][Medline]
  42. Pouliot N, Nice EC, Burgess AW. Laminin-10 mediates basal and EGF-stimulated motility of human colon carcinoma cells via {alpha}(3)ß(1) and {alpha}(6)ß(4) integrins. Exp Cell Res 2001;266:1–10.[CrossRef][Medline]
  43. Chen L, O'Bryan JP, Smith HS, Liu E. Overexpression of matrix Gla protein mRNA in malignant human breast cells: isolation by differential cDNA hybridization. Oncogene 1990;5:1391–5.[Medline]
  44. Koizumi M, Yonese J, Fukui I, Ogata E. The serum level of the amino-terminal propeptide of type I procollagen is a sensitive marker for prostate cancer metastasis to bone. BJU Int 2001;87:348–51.[CrossRef][Medline]
  45. Somasundaram R, Schuppan D. Type I, II, III, IV, V, and VI collagens serve as extracellular ligands for the isoforms of platelet-derived growth factor (AA, BB, and AB). J Biol Chem 1996;271:26884–91.[Abstract/Free Full Text]
  46. Kuo CJ, LaMontagne KR Jr, Garcia-Cardena G, et al. Oligomerization-dependent regulation of motility and morphogenesis by the collagen XVIII NC1/endostatin domain. J Cell Biol 2001;152:1233–46.[Abstract/Free Full Text]
  47. Daniels KJ, Boldt HC, Martin JA, Gardner LM, Meyer M, Folberg R. Expression of type VI collagen in uveal melanoma: its role in pattern formation and tumor progression. Lab Invest 1996;75:55–66.[Medline]
  48. Clark HF, Gurney AL, Abaya E, et al. The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment. Genome Res 2003;13:2265–70.[Abstract/Free Full Text]
  49. Lash AE, Tolstoshev CM, Wagner L, et al. SAGEmap: a public gene expression resource. Genome Res 2000;10:1051–60.[Abstract/Free Full Text]
  50. Tanaka TS, Jaradat SA, Lim MK, et al. Genome-wide expression profiling of mid-gestation placenta and embryo using a 15,000 mouse developmental cDNA microarray. Proc Natl Acad Sci U S A 2000;97:9127–32.[Abstract/Free Full Text]
  51. Kargul GJ, Dudekula DB, Qian Y, et al. Verification and initial annotation of the NIA mouse 15K cDNA clone set. Nat Genet 2001;28:17–8.[CrossRef][Medline]
  52. Bowtell DD, Sambrook JF. DNA microarrays: a molecular cloning manual. New York: Cold Spring Harbor Laboratory Press; 2002.
  53. Boussioutas A, Li H, Liu J, et al. Distinctive patterns of gene expression in premalignant gastric mucosa and gastric cancer.Cancer Res2003;63:2569–77.[Abstract/Free Full Text]
  54. Yang YH, Dudoit S, Luu P, et al. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.Nucleic Acids Res2002;30:E15.
  55. Saal LH, Troein C, Vallon-Christersson J, Gruvberger S, Borg A, Peterson C. BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol 2002;3:SOFTWARE0003.
  56. Sloan EK, Stanley KL, Anderson RL. Caveolin-1 inhibits breast cancer growth and metastasis. Oncogene 2004;23:7893–7.[CrossRef][Medline]
  57. Parker BS, Argani P, Cook BP, et al. Alterations in vascular gene expression in invasive breast carcinoma. Cancer Res 2004;64:7857–66.[Abstract/Free Full Text]
  58. Bardelli A, Saha S, Sager JA, et al. PRL-3 expression in metastatic cancers. Clin Cancer Res 2003;9:5607–15.[Abstract/Free Full Text]



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