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Tumor Biology |
Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06520 [J. Y. K., M. D-F., I. T. O., D. L. R., R. L. C.], and Lombardi Cancer Center, Departments of Oncology and Pathology, Georgetown University School of Medicine, Washington, DC 20007 [B. S., C-Y. L., R. B. D.]
| ABSTRACT |
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| INTRODUCTION |
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Several studies have analyzed individual components of the HGF pathway for their association with tumor aggression and/or patient survival. Early biochemical studies demonstrated that overall levels of HGF in breast cancers correlated with worse patient outcome (2 , 3 , 5) . Whether HGF production by tumors and/or surrounding stroma is an important prognostic feature is unclear; although tumor cells themselves are a major producer of HGF (4 , 5 , 12) . The use of matriptase and HAI-1 as prognostic markers in breast cancer has not been reported previously. However, recently, one study demonstrated that high matriptase and low HAI-1 levels were associated with advanced-stage ovarian tumors (13) . Another report demonstrated that the glycosylation of matriptase stabilized and enhanced its proteolytic activity, and promoted tumor aggression (14) .
The expression of Met has been more extensively studied. Met overexpression associates with poor prognosis in a variety of tumors (1) . Whether such expression is ligand- (HGF) dependent or independent is unclear; however, the constitutive activation of Met, via several ligand-independent mechanisms, is established. These mechanisms include activating point mutations (15, 16, 17, 18, 19) , chromosomal translocations (20 , 21) , and truncations of the cytoplasmic domain (22 , 23) . In addition, dysregulation of Met-associated phosphatases may also lead to Met activation (24) .
We have now studied several elements of the HGF pathway including HGF, matriptase, HAI-1, and Met in a single cohort of node-negative breast cancer patients with 30-year follow-up, correlating the expression of each element and determining their prognostic value. This study was facilitated by the use of tissue microarrays: arrays of hundreds of patient histological samples on a single glass slide. Our study demonstrates a significant correlation between members of the HGF pathway and shows that several members have independent prognostic value in determining patient outcome.
| MATERIALS AND METHODS |
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Immunohistochemistry.
Briefly, 5-µm tissue microarray slides were deparaffinized with xylene and ethanol. Antigen retrieval was performed using citrate buffer (pH 6.0) pressure-cooking (29)
. Primary antibodies were incubated overnight at 4°C, with the exception of antibodies to ERs, PRs, and Her2, which were incubated at room temperature for 1 h. Monoclonal anti-matriptase and anti-HAI-1 antibodies were prepared as described previously (9
, 30)
. Commercially acquired antibodies included: polyclonal (goat) anti-HGF antibody (R&D Systems, Minneapolis, MN); monoclonal antibody to the extracellular domain of Met (DO-24; Upstate Biotechnology, Lake Placid, NY); and monoclonal antibody to the intracellular domain of Met (3D4; Zymed, South San Francisco, CA). The specificities of all of the antibodies used were verified using immunoprecipitation and Western blotting. Antibodies to ER, PR, and HER-2/neu were obtained from DAKO (Carpinteria, CA) and used according to the manufacturers specifications. Antibodies were either detected using a Vectastain ABC kit (Vector Laboratories, Burlingame, CA) for anti-HAI-1 or the DAKO Envision TM + System (DAKO) for the others. Signal from the HGF antibody was amplified using biotin-tyramide signal amplification followed by a streptavidin-horseradish peroxidase conjugate (TSA kit; Perkin-Elmer Life Sciences, Boston, MA). Staining was visualized using diaminobenzidine and counterstained with acidified hematoxylin. Slides were also stained in the absence of primary antibody to evaluate nonspecific secondary antibody reactions.
Evaluation of Immunostaining.
Immunostaining was scored on a scale of 0 to 3+ (negative/weak/moderate/intense staining). Distinctions between membrane and cytoplasmic staining were impractical given the diffuse staining of the antigens (visualized using the chromogenic substrate, diaminobenzidine). Therefore, scores represent the combined staining intensity of membranous and cytoplasmic staining. Histospots with <10% of their area covered by tumor were excluded from analysis. Scoring was performed by two independent observers (J. Y. K. and M. D-F.), and histocores with discrepant scores were re-examined by both observers to achieve a consensus score. Cases with scores of 2+ or 3+ were designated as "high," whereas cases with scores of 0 or 1+ were designated as "low."
Statistical Analysis.
All of the analyses were completed using Statview 5.0.1 (SAS Institute Inc., Cary, NC). Correlations between markers were performed using a
2 test. Prognostic significance was assessed using both univariate and multivariate Cox proportional hazards models with 30-year survival as an end point. Survival curves were calculated using the Kaplan-Meier method, with significance evaluated using the Manel-Cox log rank test.
| RESULTS |
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2 analyses, which revealed highly significant associations between the expression of Met, HGF, and matriptase (P < 0.0002; Table 2
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We then determined the independent predictive power of the Met pathway. First, we limited our analysis solely to the Met pathway components. Using multivariate analysis, both the cytoplasmic tail of Met and HAI-1 retained independent predictive power (Table 4)
. When we included these two markers with traditional breast cancer markers, they retained their independence. Tumor size was the only other independent predictor of poor outcome (Table 5)
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| DISCUSSION |
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In addition to their role in the activation of HGF, matriptase and its cognate inhibitor, HAI-1, also play a role in the plasminogen activator cascade (6 , 31 , 32) . This cascade culminates in the activation of plasmin and the coactivation of matrix metalloproteinases, both of which degrade extracellular matrix components and potentiate tumor cell invasion, extravasation, and metastasis (33) . Matriptase promotes this pathway by activating latent uPA, which, in turn, activates plasmin (6 , 34) . Like matriptase, uPA can also cleave pro-HGF, providing another level of interaction between the Met/HGF pathway and plasmin cascade (35) . Given the multiple functions of matriptase, it is not surprising that aggressive breast tumors produce higher levels of this enzyme.
Likewise, HAI-1, as an inhibitor of matriptase, may help modulate both the Met/HGF and plasmin pathways. Interestingly, the expression of HAI-I was independent of the other members of the Met pathway indicating that its expression is regulated differently. Previous reports have suggested that HAI-I is down-regulated in colon carcinoma and high-grade ovarian carcinomas (13
, 36)
. In contrast, our study demonstrates that HAI-1 expression is associated with aggressive breast carcinomas, being an independent predictor of poor outcome (Table 5)
. Although this may be puzzling in light of the role of HAI-1 in inhibiting HGF-dependent Met activation, the coordinated expression of both matriptase and HAI-1 may be far more important in promoting tumor aggression than the unopposed production of active matriptase in the absence of its inhibitor. Coordinated regulation of another inhibitor of the uPA/plasmin cascade, PAI-1, is crucial for inducing tumor invasion (37)
. Furthermore, a recent meta-analysis of the uPA/PAI-1 system in breast cancer demonstrated conclusively that overexpression of both uPA and its inhibitor PAI-1 were associated with poor outcome in breast cancer (32)
. In our study, the importance of matriptase and HAI-1 coexpression is demonstrated in the elevated relative risk of patients with tumor expressing both markers.
Because of lot-to-lot inconsistencies in polyclonal Met-antibodies,4 we analyzed two different monoclonal antibodies, one to the extracellular and one to the intracellular domain. Comparison of Met expression as assessed by these two antibodies showed some interesting results. First, the expression of the intra- and extracellular domains of Met, although highly associated, was not coincident. Second, of cases with mixed expression of intra- and extracellular Met, overexpression of the intracellular domain was far more common, with 12.2% of all of the cases expressing solely the intracellular domain. Third, high levels of the cytoplasmic tail of Met were predictive of poor outcome, whereas expression of the extracellular portion was not. Although this result could be explained by differences in the affinity of the antibodies for Met in formalin-fixed, paraffin-embedded tissue, both antibodies gave strong staining and similar results across a range of titrations (data not shown). A more likely explanation is that the cytoplasmic tail of Met is either cleaved (e.g., after activation) or that mutations in Met lead to an overexpression of the cytoplasmic tail in some tumors. Indeed, recent studies have suggested that the cleavage of the cytoplasmic tail of Met may be important in signal transduction (1 , 22 , 23) . Whether overexpression of the Met intracellular domain relative to the extracellular domain is a ligand-independent or -dependent phenomenon is unclear. Interestingly, expression of the Met extracellular domain correlates with HGF levels but not matriptase levels, whereas the Met intracellular domain correlates with both. This observation would be expected if the binding of matriptase-potentiated HGF to Met induced a subsequent cleavage of the Met intracellular domain.
In summary, we have made use of tissue microarray technology to analyze various components of the Met-signaling pathway. Our studies provide evidence that the expression of the stimulatory members of this pathway (Met, HGF, and matriptase) is tightly correlated. High-level HAI-1 expression is an independent predictor of outcome. Furthermore, studies using antibodies to different domains of the Met receptor suggest that overexpression of the cytoplasmic domain is a strong independent predictor of outcome.
| ACKNOWLEDGMENTS |
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| FOOTNOTES |
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1 Supported by grants from the Patrick and Catherine Weldon Donaghue Foundation for Medical Research, The Connecticut Breast Cancer Alliance, and grants from the NIH, including National Institute of Environmental Health Sciences Grant K0-8 ES11571 (to R. L. C.), National Cancer Institute Grant RO-1 GM57604 (to D. L. R.), United States Army Grant DAMD 01-000436, and NIH Breast Cancer Specialized Programs of Research Excellence 2P50CA72460. ![]()
2 To whom requests for reprints should be addressed, at Department of Pathology, Yale University, School of Medicine, 310 Cedar Street, BML 122, New Haven, CT 06520. E-mail: robert.camp{at}yale.edu ![]()
3 The abbreviations used are: HGF, hepatocyte growth factor; HAI, hepatocyte growth factor activator inhibitor; ER, estrogen receptor; PR, progesterone receptor; CI, confidence interval; uPA, urokinase-type plasminogen activator; PAI, plasminogen activator inhibitor. ![]()
Received 8/28/02. Accepted 1/ 3/03.
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