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© 1999 American Society for Clinical Oncology Dissemination Risk Index Based on Plasminogen Activator System Components in Primary Breast CancerFrom the Département de Biologie, Département de Statistiques Médicales, Département d'Anatomie-Pathologique, Département de Médecine, and Département de Chirurgie, Centre René Huguenin, St-Cloud; and Laboratoire de Transfert, Assistance Publique-Hôpitaux de Marseille, Marseille, France. Address reprint requests to Frédérique Spyratos, Laboratoire de Biologie Tissulaire, Centre René Huguenin, 35 Rue Dailly, 92211 St-Cloud, France; email spyratos{at}calva.net
PURPOSE: To study interactions between disease-free survival (DFS) and four components of the plasminogen activator system: urokinase-type plasminogen activator (uPA), its two inhibitors (PAI-1 and PAI-2), and its membrane receptor uPAR. PATIENTS AND METHODS: We conducted a retrospective study of 499 primary breast cancer patients (median follow-up, 6 years). uPA, PAI-1, and PAI-2 were determined on cytosols and uPAR on solubilized pellets, using enzyme-linked immunoadsorbent assay kits (American Diagnostica, Greenwich, CT). Classical univariate and multivariate statistical methods were used together with multiple correspondence analysis to graphically examine interactions between the variables and outcome. RESULTS: By univariate analysis, higher uPA and PAI-1 values were significantly related to shorter DFS (P = .002; P < .00002). PAI-2 was not significantly related to DFS, although patients with high and very low PAI-2 values had a longer DFS. Multiple correspondence analysis showed the parallel impact of uPA and PAI-1 on outcome, and the clearly different behavior of PAI-2 compared with PAI-1. The prognostic contribution of uPAR seemed weak by both methods. A dissemination risk index [uPA x PAI-1/(PAI-2 + 1)], taking into account the modulation of uPA proteolytic activity by the ratio of its two inhibitors, was then tested. Dissemination risk index was selected as an independent variable in the Cox model in the overall population (P < .000001) and in node-positive patients (P < .00001). It was the only variable selected in node-negative patients (P = .003). CONCLUSION: A dissemination risk index determined on primary tumor and taking into account the different effects of PAI-1 and PAI-2 on uPA can be of major help in clinical management of breast cancer, particularly in node-negative patients.
DESPITE NUMEROUS studies showing that several biologic factors can influence the clinical course of breast cancer, node status remains the most important prognostic indicator in making treatment decisions, although axillary node dissection failed to cure most women with node-positive breast cancer.1,2 Notwithstanding sophisticated approaches with large sample sizes,3 no model able to predict lymph node involvement with sufficient confidence has yet been described. Biological characteristics of the primary tumor could be used for adjuvant treatment decisions,4 particularly factors predicting invasion potential, as death by malignancy is partly due to the capacity of tumor cells for invasion. Tumor cell invasion and metastatic processes require coordinated regulation of a series of adhesive, proteolytic, and migratory events. The ability of cells derived from solid tumors to metastasize has been linked to the expression of various proteolytic enzymes originating from different cell types. Urokinase-type plasminogen activator (uPA) is a serine protease that catalyzes the conversion of inactive plasminogen into plasmin, a broadly acting enzyme that is able to degrade a variety of extracellular matrix proteins and to activate metalloproteinases and growth factors. uPA binds to its specific receptor (uPAR), directing plasmin activity to the migrating tumor cell surface, and uPA activity is directly controlled by specific inhibitors, known as the plasminogen activator inhibitors PAI-1 and PAI-2.5 High levels of plasminogen activation system components, uPA6-13 and, paradoxically, the inhibitor PAI-1,10,11,13-15 have been linked to a poor prognosis in several cancers, including breast cancer. Results on PAI-211,16-19 are more controversial, as high values are associated with a good prognosis in some situations. However, individual analysis of each component of the plasminogen activator system fails to take into account their complex interactions. Continuing on from investigations conducted in our laboratory,9,11,20-24 we studied the interactions of four components of the plasminogen activator system (uPA, PAI-1, PAI-2, and uPAR) with disease-free survival, and assessed the prognostic value of a dissemination risk index thus derived. This retrospective study involved a well-characterized cohort of 499 breast cancer patients who were treated in our institution and used classical univariate and multivariate prognostic approaches together with descriptive methods for a better visualization of interaction phenomena.
Patients The study group consisted of 499 breast cancer patients treated at the Centre René Huguenin (CRH) between 1981 and 1989. The median age was 58 years (range, 24 to 84 years). Patients were selected according to the following criteria: (1) primary unilateral breast tumor; (2) full follow-up at CRH; (3) previously untreated and no evidence of metastatic disease or any other malignancy at the time of diagnosis; (4) surgery as the first treatment, and (5) complete clinical, histologic, and biologic information. All tumors were graded according to Scarff-Bloom-Richardson25 (SBR) using the modified SBR system (MSBR), which is a simple rearrangement of the two nuclear scores of the SBR grade.26 The following information was recovered for each patient: age at diagnosis; menopausal status; clinical and macroscopic tumor size; SBR and MSBR grade; axillary lymph node status; steroid receptor status; uPA, PAI-1, PAI-2, and uPAR values; and adjuvant treatment. The selected population was representative of recruitment at the Centre René Huguenin during the same period. Two hundred thirty-five patients (47%) underwent partial mastectomy with axillary lymph node clearance, and 264 patients (53%) had a modified radical mastectomy. Adjuvant postoperative locoregional radiation was given to 237 (47%) patients. Adjuvant chemotherapy was given to 119 patients (24%), adjuvant hormone therapy to 115 patients (23%), and a combination of adjuvant hormone therapy and chemotherapy to 87 patients (17%). Patients were routinely examined every 3 months for the first 2 years and yearly thereafter. At the time of this analysis, 151 patients (30%) had relapsed (local recurrence and/or distant metastasis), 117 (23%) had distant metastases, and 80 (16%) had died of cancer. Follow-up ranged from 1 year to 15 years, with a median of 6 years.
Estrogen Receptor (ER) and Progesterone Receptor (PgR) Assays
Tissue Extracts and uPA, PAI-1, PAI-2, and uPAR Assays The Pierce method28 was used for protein assay. The concentrations of reagents used in the extraction procedure do not interfere with the bicinchoninic acid assay. Standard bovine serum albumin, fraction V (BSA Pierce, Rockford, IL) (2 mg/mL in 0.9% aqueous NaCl solution) was used for calibration. Samples and standards were both assayed in duplicate.
Statistical Methods To identify and graphically describe underlying patterns of relationships between disease-free intervals and the four components of the plasminogen activator system (split into four categories, or quartiles), we used multiple correspondence analysis, a relatively simple and flexible statistical tool.31,32 Multiple correspondence analysis is a special kind of principal components analysis33 that is already used in our center34 and is appropriate for categorical rather than continuous variables. Variables were introduced in two different ways: active variables, which were used when constructing factors, and supplementary variables, ie, variables not taking part in the multiple correspondence analysis but projected onto the factorial planes of the multiple correspondence analysis using transition formulae. The results of multiple correspondence analysis were used to graphically represent the categories of the variables on the best factorial plane derived from the analysis and accounting for the largest amount of variance in the data. When reading the graph, attention should be paid to the three following aspects: (1) the relative distance of a category from the two axes and from the center, (2) the direction of a variable relative to the axes, and (3) the clustering of categories and their position relative to each other. Multivariate analyses based on the Cox proportional hazards model35 were conducted to identify the most significant factors related to disease-free survival. A significance level of 5% was chosen as the criterion for entering factors in the Cox model. There were no missing covariates. The results of the multivariate analyses were expressed in terms of hazard rates derived from the estimated regression coefficients, along with their 95% confidence intervals.
The characteristics of the patients are listed in Table 1. The distribution of uPA, PAI-1, PAI-2, and uPAR in the overall population is shown in Table 2.
Association of uPA, PAI-1, PAI-2, and uPAR With Other Patient and Tumor Characteristics
Univariate Prognosis Analysis of uPA, PAI-1, PAI-2, and uPAR
Multiple Correspondence Analysis
These six variables, representing 22 categories, were projected onto the best factorial plane formed by the first two factorial axes (F1, F2), which were the most stable axes derived from multiple correspondence analysis and accounting for the largest part of the total sample variance. The LDFI is represented as a polygonal curve with the longest survival (LDFI+++) on the left, close to the area of no recurrence (R-), and the shortest survival on the right (LDFI-), with a high rate of recurrence (R+). A first group of correlated variables (shown in quadrant I) consisted of patients with low uPA, PAI-1, and PAI-2 values. From quadrant I to quadrant IV, uPA and PAI-1 values increased gradually, and low, moderate, and high uPA values were always associated with low, moderate, and high PAI-1 values, respectively. The highest uPA and PAI-1 values were associated with the shortest LDFI. Low PAI-2 values are close to low uPA and PAI-1 values in quadrant I, but in quadrants II and III, PAI-2 begins to move away from uPA and PAI-1. Intermediate PAI-2 levels (PAI-2++) are close to the highest uPA and PAI-1 values in quadrant IV, which groups together patients with the worst prognosis. Like uPA and PAI-1, but with less amplitude, uPAR moved gradually from quadrant I to quadrant IV.
Construction of a Dissemination Risk Index We then constructed and tested a dissemination risk index based on uPA, PAI-1, and PAI-2 [uPA [times] PAI-1/(PAI-2 + 1)], taking into account the modulation of uPA proteolytic activity by the ratio of its two inhibitors. Owing to its weak impact on disease-free survival, uPAR was not used in the index. The dissemination risk index was also divided into quartiles. Figure 3 shows the results of univariate analysis, indicating that high dissemination risk index values were strongly associated with shorter disease-free survival (P < .000001). Relative risks associated with the dissemination risk index gradually increased, as indicated in Table 4.
The proportion of patients with a high dissemination index was similar in node-negative patients (24%), patients with one to three invaded nodes (24%), and patients with more than three invaded nodes (29%). Similarly, the proportion of patients with a low dissemination index was very similar in node-negative patients (50%), patients with one to three invaded nodes (52%), and patients with more than three invaded nodes (46%).
Multivariate Analyses
To our knowledge, this is the first time that four components of the plasminogen-activator system have been studied together in a well-characterized cohort of primary breast cancer patients. We confirmed that high uPA values were indicative of shorter disease-free survival and also found an apparently paradoxical strong relationship between protease inhibitor PAI-1 levels, high metastasis rate, and poor survival. The relationship between PAI-2 and outcome was more complex, PAI-2 seeming to partly neutralize the impact of uPA. uPAR had a weak prognostic impact. Finally, a dissemination risk index, taking into account the modulation of uPA by its two inhibitors PAI-1 and PAI-2, was found to be a major prognostic factor in primary breast cancer, being as powerful as axillary node status in our population. uPAR did not add sufficient prognostic information relative to the other components of the uPA system to be included in the dissemination risk index. Many studies have focused on the role of uPA in cell invasion and metastasis. Much of the data supporting the role of uPA in these events derives from in vitro and in vivo experiments that demonstrate a correlation between uPA expression and cell invasion and metastasis, particularly in breast cancer.5 In vitro, metastatic potential is reduced by natural and synthetic serine protease inhibitors, neutralizing antibodies to uPA, and antisense oligonucleotides.36 Clinical studies, particularly in breast cancer patients, have reinforced these data and demonstrated that elevated tumor uPA antigen levels6-10 are associated with poor outcome and defined high-risk groups of breast cancer patients. Several roles have been suggested for PAI-1. First, the localization of PAI-1 in tumor cells but also in endothelial cells points to its involvement in neoangiogenesis.37-39 Second, PAI-1 seems necessary for optimal invasion of cultured lung cancer cells—a surprising feature, as PAI-1 is an inhibitor40—and an increasing number of clinical studies show that high PAI-1 levels are associated with a poor prognosis in patients with a variety of cancers, particularly breast cancer.10,13-15 Recent findings could explain this apparent paradox. Bajou et al41 reported that PAI-1 deficiency in knock-out mice prevented local invasion and tumor vascularization of transplanted malignant keratinocytes, demonstrating that host-produced PAI-1 was essential for invasion and angiogenesis. In addition to its proteolytic and angiogenic effects, there is increasing evidence that the plasminogen activator system may provide both surface-associated protease activity and an adhesion mechanism, through interactions between vitronectin and the tripartite complex formed by uPA, uPAR, and PAI-1.42,43 Indeed, to achieve maximal migration, a cell must adhere appropriately (ie, not too strongly and not too stably) to the extracellular matrix. uPAR binds to vitronectin,44 whereas PAI-1 inhibits this interaction45 and might govern the balance between cell adhesion and cell detachment.46 Differences in uPAR expression among cell lines is reported to correlate with differences in invasive intensity,47 whereas inhibition of uPA/uPAR binding with anti-uPA antibodies or specific antagonists inhibited invasion.48,49 uPAR seems to be a prognostic marker in certain cancers, and high uPAR levels are associated with shorter disease-free and overall survival in breast cancer,12 but its prognostic weight is much lower than that of uPA and PAI-1. PAI-2 is consistently found to inhibit invasion in vitro. It has been reported to suppress pulmonary metastases of a rat mammary cancer,50 and transfection of a human melanoma cell line with PAI-2 cDNA led to a reduced rate of lung metastasis from tumors established with these cells in severe combined immunodeficient mice, through the formation of a fibrous capsule around the tumor.51 In inflammation and pregnancy, PAI-2 plays important roles in controlling extracellular matrix remodelling and tissue repair.52 PAI-2 inhibits apoptosis in cell lines challenged with tumor necrosis factors.53 Clinical results with PAI-2 are less clear-cut. Increased levels of PAI-2 are, at least in some situations, related to a good prognosis. Bouchet et al11 found that high levels of PAI-2 in breast tumors correlated with longer metastasis-free survival in both the overall population and the node-negative subgroup. Foekens et al,17 using a different PAI-2 assay, found no significant link between PAI-2 levels and outcome in their overall population; however, in patients with high uPA levels, PAI-2 correlated significantly with a good prognosis. We tried to obtain further insight into the complex interrelationships of uPA, PAI-1, PAI-2, and uPAR with tumor recurrence by using multiple correspondence analysis to examine links between categories of variables in graphical form. Multiple correspondence analysis indicated that patients with low uPA values were close to patients with low PAI-1 values in the area corresponding to slow-acting dynamics of the tumor. Low PAI-2 values were also close to low uPA and PAI1 values in this area of low invasive potential, a result consistent with the low uPA, PAI-1, and PAI-2 content in benign tumors.20 Moving toward the upper right region of the graph (short disease-free interval and frequent recurrences), uPA and PAI-1 values increase gradually, PAI-1, like uPA, being strongly linked to the invasion process. Multiple correspondence analysis showed that, contrary to uPA and PAI-1, PAI-2 displayed a true inhibitory role, particularly in quadrant III, where the highest PAI-2 values seemed to neutralize moderate uPA values. Finally, in the area grouping high-risk patients, intermediate PAI-2 levels seemed insufficient to neutralize the highest uPA values. These observations support the results of univariate analysis, with a linear relationship between high uPA and PAI-1 levels and shorter disease-free survival, whereas very high PAI-2 levels, as already reported,11 and also very low PAI-2 values were related to longer disease-free survival. The favorable impact of low PAI-2 values had not previously been reported, probably owing to insufficiently sensitive methods. The role of uPAR seemed less important than those of uPA, PAI-1, and PAI-2; indeed, uPAR was not significant in univariate analyses and remained close to the axes. These clinical results recall experimental data on the relative contributions of plasminogen activator system components in tumor invasion. We observed a close association between uPA and PAI-1, confirming recent data on the dual role of PAI-1 in invasion and adhesion. In contrast, PAI-2 clearly does not act like PAI-1, having a true inhibitory function, at least when PAI-2 concentrations are high enough to neutralize uPA. uPAR is clearly involved in the invasion process, but, from a clinical point of view, its contribution seemed weak compared with that of uPA and PAI-1. These observations formed the basis for a dissemination risk index that combined uPA and PAI-1 with the inhibitor PAI-2. In the overall population, this index was the most important predictor of disease-free survival, before axillary node status; furthermore, it was the only factor selected in node-negative patients. In node-positive patients, the dissemination risk index and axillary node status had similar prognostic weights. The dissemination risk index was much more powerful than the individual components of the uPA system; indeed, when the dissemination risk index was not included in the Cox model, PAI-1 was the only invasion factor selected, but with much lower hazard rates (results not shown). The percentage of patients with a high metastatic risk predicted by the dissemination risk index was almost identical (approximately 25%) in the three groups of axillary node involvement (ie, node-negative, one to three positive nodes, and more than three positive nodes), thus this dissemination risk index defined high-risk patients in the node-negative group and, conversely, low-risk patients in the node-positive group. This study was based on well-defined methods and EORTC quality controls programs.27 Values obtained in this study are comparable to those of others series obtained with same extraction procedure.8,12,13,19,54 Among the biologic factors proposed as predictors in breast cancer, components of the plasminogen activator system, possibly combined in a dissemination risk index such as ours, seemed to be major indicators of poor outcome, particularly in node-negative patients. Conversely, it defines a lower-risk group in node-positive patients. Our index has the advantage of being based on established physiopathologic findings and is easily determined with the primary tumor. In early breast cancer, this dissemination risk index could be used as a complement to axillary node dissection as a clinical decision aid.
Supported by the Ligue Nationale Contre Le Cancer, Comités Départementaux des Hauts-de-Seine, des Yvelines et de l'Essonne. We thank all of the pathologists and clinicians of the Centre René Huguenin.
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Copyright © 1999 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
10 fmol/mg of cytosol protein was classified as positive. After 1988 we used an enzyme-linked immunoadsorbent assay method (ER-EIA Monoclonal, PgR-EIA Monoclonal, Abbott Laboratories, Abbott Park, IL) with a cutoff set at 15 fmol/mg of cytosol protein. Our laboratory participated in the regular quality control programs organized by the EORTC.
2 test. The disease-free survival interval was defined as the time between diagnosis and the first relapse (local recurrence and/or distant metastasis) or the end of the study. Patients without relapse were censored at the last follow-up. Actuarial disease-free survival rates were computed using the Kaplan-Meier method
25% quartile, which is equivalent to 
