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Clinical Chemistry 52: 838-844, 2006. First published March 16, 2006; 10.1373/clinchem.2005.064253
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(Clinical Chemistry. 2006;52:838-844.)
© 2006 American Association for Clinical Chemistry, Inc.

Cancer Diagnostics

Enhanced Discrimination of Benign from Malignant Prostatic Disease by Selective Measurements of Cleaved Forms of Urokinase Receptor in Serum

Timo Piironen1,2, Alexander Haese2, Hartwig Huland2, Thomas Steuber2, Ib Jarle Christensen6, Nils Brünner3, Keld Danø1, Gunilla Høyer-Hansen1 and Hans Lilja4,5,a

1 The Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark.
2 Department of Urology, University Clinic Hamburg Eppendorf, Hamburg, Germany.
3 Institute of Pathobiology, Royal Veterinary and Agricultural University, Copenhagen, Denmark.
4 Department of Laboratory Medicine, Division of Clinical Chemistry, Lund University, University Hospital (UMAS), Malmö, Sweden.
5 Departments of Clinical Laboratories, Urology, and Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY.
6 Department of Surgical Gastroenterology, Hvidovre University Hospital, Hvidovre, Denmark.

aAddress correspondence to this author at: Memorial Sloan-Kettering Cancer Center, 1275 York Ave., Box 213, New York, NY 10021. Fax 646-422-2379; e-mail LiljaH{at}mskcc.org.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Early detection of prostate cancer (PCa) centers on measurements of prostate-specific antigen (PSA), but current testing practices suffer from lack of specificity and generate many unnecessary prostate biopsies. Soluble urokinase plasminogen activator receptor (uPAR) is present in blood in both intact and cleaved forms. Increased uPAR in blood is correlated with poor prognosis in various cancers, but uPAR has not been shown to be useful in PCa diagnostics. We assessed the ability of immunoassays for specific uPAR forms to discriminate PCa from benign conditions.

Methods: We measured total PSA (tPSA), free PSA (fPSA), intact uPAR [uPAR(I-III)], intact uPAR + cleaved uPAR domains II+III [uPAR(I-III) + uPAR(II-III)], and cleaved uPAR domain I [uPAR(I)] in sera from 224 men with and 166 men without PCa. We assessed differences in serum concentrations between the PCa and noncancer groups within the entire cohort and in men with tPSA concentrations of 2–10 µg/L. The diagnostic accuracy of individual analytes and analyte combinations was explored by logistic regression and ROC analyses and evaluations of sensitivity and specificity pairs.

Results: Serum uPAR(I) and uPAR(II-III) were higher in PCa than in benign disease. In men with tPSA between 2 and 10 µg/L, the combination of %fPSA with the ratio uPAR(I)/uPAR(I-III) had a greater area under the ROC curve (0.73) than did %fPSA (0.68).

Conclusions: Specific measurements of different uPAR forms in serum improve the specificity of PCa detection. The uPAR forms may therefore be complementary to PSA for PCa detection, most importantly in men with moderately increased PSA.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Prostate-specific antigen (PSA)1 in serum is used for detection of prostate cancer (PCa), but it is also increased in benign prostatic diseases, which leads to many prostatic biopsies. The proportion of free (unbound) PSA (fPSA) is higher in benign prostatic hyperplasia (BPH) than in PCa. This has led to the use of the ratio of fPSA to total PSA (%fPSA) and improved the specificity for PCa; however, approximately two thirds of patients still undergo unnecessary biopsies.

The major cause of PCa morbidity and mortality is metastatic disease. During the process of tissue remodeling associated with cancer invasion and metastasis, a complex array of proteolytic enzymes participates in matrix degradation (1). The proteases and their regulators can be candidate prognostic or diagnostic tumor markers.

Cell-surface plasminogen activation catalyzed by urokinase plasminogen activator (uPA) is a major step in the activation of the matrix-degrading protease system in cancer (2). uPA is secreted as an inactive proenzyme, which localizes on the cell surface by binding to a glycolipid-anchored cell surface receptor, urokinase plasminogen activator receptor (uPAR). Binding to uPAR enhances the activation of uPA proenzyme because of the proximity of cell-surface–bound plasminogen. uPAR consists of 3 homologous 3-finger domains, of which the amino-terminal domain (I) is required for binding to uPA. However, all domains are needed for high-affinity binding (3)(4). uPA can cleave uPAR in the linker region between domains I and II, liberating domain I [uPAR(I)] and leaving the remainder of the molecule [uPAR(II-III)] on the cell surface (5). In addition, uPAR can be shed from cells by cleavage at the lipid anchor by phospholipases or proteases, liberating full-length uPAR(I-III) and/or uPAR(II-III) (6)(7).

uPAR is expressed in many types of human cancers, often primarily by stromal cells (1). In PCa tissue, uPAR is expressed by macrophages and neutrophils (8). Cleaved uPAR forms are present in several neoplastic cell lines and tissues (9)(10). Increased plasma concentrations of soluble uPAR forms (suPAR) have been found in patients with non–small cell lung cancer (11) and colon cancer (12). Furthermore, ovarian cancer cyst fluid contains soluble uPAR(II-III) (13), and urine from patients with acute myeloid leukemia contains uPAR(I) and uPAR(II-III) (14).

Measurements of uPAR forms carry prognostic significance. The concentrations of uPAR in tumor tissue indicate prognosis in squamous cell lung cancer (15), colon cancer(16), and breast cancer (17). In squamous cell lung cancer, uPAR(I) is a stronger prognostic indicator than is total uPAR immunoreactivity (18), and in colorectal cancer(19) and breast cancer (20), the concentration of suPAR in blood is significantly associated with prognosis. For PCa, however, measurement of suPAR has not been useful (21)(22). Individual forms of uPAR, however, have not yet been tested for association with PCa. In this study, we assessed the ability of newly developed immunoassays designed for the specific measurement of different suPAR forms (10) in serum to discriminate between benign and malignant prostatic disease and compared the performance of theses assays with the performance of %fPSA, free and total PSA.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
immunoassays
uPAR.
Three uPAR immunoassays, TR-FIA 1, TR-FIA 2 and TR-FIA 3, have been designed for the specific measurement of uPAR(I-III), uPAR(I-III) + uPAR(II-III), and uPAR(I), respectively (10). The detection limits were 0.3 pmol/L uPAR(I-III) for TR-FIA 1 and TR-FIA 2 and 1.9 pmol/L uPAR(I) for TR-FIA 3. The assays were previously validated for use in citrate plasma. To validate these assays for use in serum, we made 2 serum pools, using sera from 50 men with total PSA (tPSA) concentrations ranging from 0.2 to 28.7 µg/L for each pool. We assessed the linearity of the assays by assaying serum diluted (1:2 to 1:128) in assay buffer.

To determine the limit of quantification, we added purified uPAR to uPAR-depleted serum and calculated the CV. To prepare uPAR-depleted serum, we diluted the serum 1:5 in 0.2 mol/L phosphate buffer (pH 7.4) containing 0.1 mol/L NaCl and passed the diluted serum over a protein A–Sepharose CL-4B (Pharmacia Biotech) to adsorb the uPAR. We then passed the eluate from the first column over a protein A–Sepharose column preloaded with a polyclonal rabbit anti-uPAR antibody (23) to adsorb the remaining uPAR. The depleted serum contained 7.7% of the initial amounts of uPAR(I-III) measured by TR-FIA 1 and only 4.4% of the initial amounts of uPAR(I-III) + uPAR(II-III) measured by TR-FIA 2. Depletion of uPAR(I) reduced the TR-FIA 3 signal to 14% of that obtained before immunodepletion. We then added purified uPAR(I-III) and uPAR(I) to this depleted serum at concentrations of 0.016–10 µg/L [0.5–325 pmol/L uPAR(I-III) and 1.5–961 pmol/L uPAR(I)]. The limit of quantification was defined as the lowest concentration at which the CV did not exceed 20%.

We assessed the analytical specificities (i.e., immunologic cross-reactivities) of the assays by measuring the concentrations of the uPAR variants in the different assays before and after uPAR depletion of serum. Intra- and interassay precision was determined by measuring 10 or 26 replicates of the serum pool in the 3 TR-FIAs. Because the amount of uPAR(I) in the 1:10-diluted serum pool was close to the limit of quantification, we determined the interassay precision of TR-FIA 3 by adding 480 pmol/L uPAR(I) to serum. All samples were diluted 1:10 in assay buffer before analysis. We determined the recoveries of calibrators added at concentrations of 0.041–8 µg/L [3.9–769 pmol/L uPAR(I) or 1.3–260 pmol/L uPAR(I-III)] in a serum pool diluted (10% by volume) in assay buffer. The recoveries were calculated from the slopes of the lines representing the uPAR(I-III) or uPAR(I) signals as a function of concentration, and 100% recovery was defined as the slope in assay buffer.

We calculated uPAR(II-III) by subtracting the moles of uPAR(I-III) measured in TR-FIA 1 from those of uPAR(I-III) and uPAR(II-III) measured in TR-FIA 2.

tPSA and fPSA.
To detect tPSA and fPSA, we used the commercial version of a previously reported dual-label assay (DELFIA® ProStatusTM PSA Free/Total Kit; PerkinElmer Life Sciences) that measures tPSA and fPSA on an equimolar basis. Detection limits were 0.04 µg/L for fPSA (CV = 3.7% at 0.44 µg/L and 18% at 0.10 µg/L) and 0.05 µg/L for tPSA (CV = 5.0% at 2.32 µg/L and 14% at 0.34 µg/L).

samples
We collected 390 consecutive serum samples from patients referred to the Department of Urology at the University Clinic (UKE) Hamburg, Germany, during 1999–2001. Of these, 367 patients were evaluated for the presence of PCa because of increased tPSA concentrations, suspicious digital rectal examination (DRE), or both. These patients were evaluated by systematic (at least sextant) biopsy of the prostate, which was performed with transrectal ultrasound guidance. Biopsies were taken from the apex, mid region, and base of the left and right peripheral zones. An additional 23 serum samples were taken from patients undergoing transurethral or open surgery for symptomatic BPH in whom pathology work-up of the specimen revealed no evidence of cancer. The median (range) ages were 63 (43–76) years for cancer patients and 64 (47–85) years for noncancer patients. All sera were drawn before any prostatic manipulation. Patients who received 5{alpha}-reductase inhibitors for symptomatic relief of BPH were excluded. The collected blood was processed to serum by centrifugation within 2 h; the serum samples were frozen within 6 h, stored at –80 °C, and thawed only immediately before analysis.

statistical analyses
Descriptive statistics for the measured concentrations of tPSA, fPSA, uPAR(I-III), uPAR(I-III) + uPAR(II-III), and uPAR(I) and the calculated %fPSA and uPAR(II-III) are given as the median (range). Correlation coefficients between these measurements were estimated by rank statistics (Spearman).

Tests for location between the 2 groups of patients were performed with the Mann–Whitney test, with the results obtained by the U-statistic normalized by the total number of combinations (i.e., an estimate of the probability that a randomly selected cancer patient has a higher concentration than a randomly selected non-cancer patient) denoted P(x>y) and its P value.

Results for the total cohort of 390 patients (224 cancer patients and 166 noncancer patients) were analyzed in a blind, randomly organized manner. In addition, a subgroup analysis of those patients with tPSA between 2 and 10 µg/L was subsequently performed.

The probability of cancer for multivariate data was estimated by logistic regression analysis. All entered covariates were log-transformed. Results are presented by the odds ratio (95% confidence interval). Regression diagnostics were evaluated by conventional techniques, and cross-validation was performed (24). Significantly correlated covariates (r > 0.7) were not entered simultaneously into the multivariate model.

ROC curves were generated, and the areas under the curves (AUCs) were calculated. Finally, we calculated the specificities for fixed sensitivities of 85%, 90%, and 95% for each covariate and the multivariate result, using a reduced-bias estimate for the predicted probability of an event. Similar estimates of the sensitivity for fixed specificities were calculated. The differences in sensitivity and specificity between models at selected cutpoints were evaluated by McNemar test. In addition, the false-positive (defined as the proportion of incorrectly classified cancers compared with the predicted number of cancers) and false-negative (defined as the proportion of incorrectly classified noncancers compared with the predicted number of noncancers) rates were estimated.

P <0.5 was considered significant. All calculations were done with SAS software (Ver. 9.1; SAS Institute).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
validation of tr-fia assays
The limits of quantification (CV <20%) for uPAR(I-III) were 1.6 pmol/L in TR-FIA 1 and 2.0 pmol/L in TR-FIA 2. For uPAR(I) in TR-FIA 3, the limit of quantification was 1.9 pmol/L. The loss of linearity (defined as a deviation >20%) for TR-FIA 1, TR-FIA 2, and TR-FIA 3 occurred at 1.6, 2.8, and 3.8 pmol/L, respectively.

Intraassay imprecision (CV; Table 1 ) was <20% in all cases except for TR-FIA 3 in serum diluted 1:10, in which the uPAR(I) concentration was at the limit of quantification. We nonetheless used this dilution routinely because only limited sample volumes were available. Interassay imprecision results are given in Table 1 .


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  		Table 1. Intra- and interassay precision of uPAR immunoassays, based on measurements in 10% serum (in assay buffer).

The recoveries in TR-FIA 2 and TR-FIA 3 were 89% and 99%, respectively. The recovery of uPAR(I-III) in 10% serum (in buffer) measured by TR-FIA 1 was only 75%. This may reflect that the serum pool contains uPA or another uPAR ligand that binds uPAR and thus prevents full recovery of the added uPAR(I-III).

findings in entire cohort
For the entire cohort of 390 patients, median (range) tPSA was 6.99 (0.27–87.1) µg/L. The median tPSA concentrations were 7.82 µg/L in patients with histologically confirmed PCa (n = 224) vs 5.58 µg/L in patients with no evidence of PCa (n = 166). The concentrations of uPAR(I-III) and uPAR(I-III) + uPAR(II-III) in all 390 samples were above the limits of quantification for the TR-FIA 1 and TR-FIA 2 assays, whereas in 6 of the 390 samples, the uPAR(I) concentrations were below the limit of quantification for TR-FIA 3. Descriptive statistics for all measurements and the results of the Mann–Whitney test for location, including the statistical measure for discrimination P(x>y), are shown in Table 2A .


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  		Table 2. Descriptive statistics for PCa vs noncancer.

uPAR(I-III) and uPAR(I-III) + uPAR(II-III) were highly correlated, whereas all uPAR measurements were weakly correlated with tPSA, fPSA, and %fPSA (Table 3 ). The Spearman correlation coefficients for patients, stratified by cancer/noncancer, showed similar results in each stratum (data not shown).


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  		Table 3. Rank correlation coefficients and P values, all patients (n = 390).

Multivariate analysis (Table 4A ) of the above measurements included tPSA, %fPSA, uPAR(I-III), and uPAR(I), but uPAR(I-III)+uPAR(II-III) was not included because it was highly correlated with uPAR(I-III). Including age in the multivariate model did not alter the results (P = 0.19, dichotomized by the median). uPAR(I-III) was not significant in the univariate model, whereas it was significant in the multivariate model including uPAR(I), suggesting an interrelationship between these covariates. The regression coefficients for uPAR(I) and uPAR(I-III) were similar in magnitude. The negative character of uPAR(I-III) implies that the model could be formulated as the ratio of uPAR(I) to uPAR(I-III). The {chi}2 value for model 2 was 69.06 (compared with 69.52 for model 1), suggesting that the ratio of uPAR(I) to uPAR(I-III) adequately describes the data illustrated in Table 4A .


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  		Table 4. Logistic regression analysis (multivariate analysis) to predict cancer on biopsy.

patients with tPSA between 2 and 10 µG/L
Among 255 men with moderately increased tPSA (between 2 and 10 µg/L), median tPSA concentrations were 6.31 µg/L in 139 patients with PCa vs 5.14 µg/L in 116 patients with no evidence of malignancy. The results of multivariate analysis in this subgroup are shown in Table 4BUp , where the ratio uPAR(I)/uPAR(I-III) is included (tPSA is not a statistically significant prognostic variable in the model).

roc analysis
To assess the accuracy of the multivariate models incorporating different combinations of variables, we calculated AUCs for the ROC curves (Fig. 1 ). For the entire set of patients, the AUC of tPSA alone was 0.65 [95% confidence interval (CI), 0.60–0.70]. For a model combining tPSA and %fPSA, the AUC was 0.75 (0.70–0.80), which further increased to 0.78 (0.74–0.82) for the combination of tPSA, %fPSA, and the ratio uPAR(I)/uPAR(I-III). This further increase was statistically highly significant (P <0.001).


Figure 1
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  		Figure 1. ROC analysis and AUC (95% CI) calculated for PSA forms for the entire cohort (A) and for men with tPSA between 2 and 10 µg/L (B).

(A), ROC curves for tPSA, tPSA + %fPSA, and tPSA + %fPSA + uPAR(I)/uPAR(I-III) for the entire study cohort (n = 390). (B), ROC curves for %fPSA and %fPSA + uPAR(I)/uPAR(I-III) for men with tPSA between 2 and 10 µg/L (n = 255).

In the entire tPSA range, specificities for tPSA were 15%, 24%, and 32% at sensitivities of 95%, 90%, and 85%, respectively. From this baseline, specificity increased by 10% to 19% when we used the calculated combinations of tPSA, fPSA, and the tested uPAR forms (Table 5A ). The widths of the 95% CIs for the shown sensitivities ranged from 9% to 13% and from 10% to 15% for the specificities. For 90% sensitivity, the false-positive rate was 41% for tPSA, which decreased to 32% in the multivariate model. Similarly, the false-negative rate decreased from 46% to 24%.


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  		Table 5. ROC analysis: Specificities and sensitivities in discriminating prostate cancer vs noncancer.2

For patients with tPSA of 2–10 µg/L (Fig. 1BUp ), the AUCs for %fPSA and for the combination of %fPSA with the ratio uPAR(I)/uPAR(I-III) were 0.68 (95% CI, 0.62–0.79) and 0.73 (0.67–0.79) (P <0.001). In this group, specificities for %fPSA were 10%, 19%, and 36% at sensitivities of 95%, 90%, and 85%, respectively. Specificity increased up to 41% when we used the calculated combinations of %fPSA and the tested uPAR forms (Table 5BUp ). The widths of the 95% CIs for the shown sensitivities ranged from 8% to 13% and from 10% to 15% for the specificities. For 90% sensitivity, the false-positive rate was 43% for %fPSA, which decreased to 41% for the multivariate model, whereas the false-negative rate was decreased from 39% to 31%. The tests for differences in sensitivities and specificities at the chosen cutpoints are descriptive and should not be interpreted as confirmative tests. This can also be seen in Fig. 1Up , in which differences are even greater in the middle range. Moreover, false-positive and -negative rates are dependent on the study population and would differ in a population with another cancer prevalence.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
The results of this study indicate that uPAR forms can improve discrimination of PCa from nonmalignant sources of increased PSA and that tPSA and fPSA correlate only weakly with the concentrations of uPAR forms (Table 3Up ). Thus, uPAR forms are largely independent analytical variables, conceivably offering clinical information that is different from and additive to that contributed by fPSA and tPSA. Various mechanisms have been proposed for the release of soluble forms of uPAR in the serum, including cleavage at the lipid anchor by phospholipases and proteases to release full-length and cleaved receptor, cleavage and release of domain I by uPA or other proteases, or a combination of these events. Furthermore, it is possible that the amounts of uPAR(I) and uPAR(II-III) in the circulation may be directly related to the extent of uPA-catalyzed plasminogen activation and thus may be stronger diagnostic/prognostic markers than the total amount of uPAR. Increased concentrations of uPA in sera from PCa patients may be a confounding factor in measurements of uPAR because the increased amount of uPA observed in men with PCa (21)(25) may cause uPAR(I-III) concentrations to be underestimated in sera collected from these men. Among the measured 390 samples, all were above the limits of quantification for the TR-FIA 1 and TR-FIA 2 assays, and only 6 were below the experimentally determined limit of quantification for TR-FIA 3. Analysis of the diagnostic utility of the combination of uPAR forms with PSA forms can be accomplished by logistic regression analysis. Logistic regression analyses using combinations of variables frequently provide better discrimination than simple algorithms, e.g., ratios calculated from the individual measurements from each patient. Logistic regression analysis is instrumental in providing the basis for various risk analysis systems that support medical decision-making.

The optimal cutoff concentration depends on whether high sensitivity or high specificity is preferred in detecting PCa. In this consecutive cohort of referral patients, men were either symptomatic for BPH or had been recommended for prostate biopsy because of previous findings of increased tPSA and/or abnormal DRE results. ROC analyses revealed significant clinical information from 2 of the 3 uPAR immunoassays, which measure uPAR(I-III) and uPAR(I).

The discriminative power of the uPAR forms as individual analytes is not as powerful as that of tPSA or %fPSA. In the unrestricted PSA group and in both groups, tPSA and %fPSA, respectively, discriminated highly significantly between biopsy outcomes. In contrast, only the directly measured uPAR(I) and the calculated uPAR(I)/uPAR(I-III) were significant discriminators. These improvements were achieved not only in relation to tPSA alone, but also in relation to the more recently introduced use of %fPSA.

The most clinically relevant application of uPAR measurements, as evidenced in our study, is the tPSA range <10 µg/L. In this clinical scenario, the use of an algorithm that combines fPSA with uPAR would increase the AUC from 67% to 73%. It is in this tPSA range that the need for additional biomarkers is greatest because of the favorable outcome when PCa is detected early on the one hand, and the relatively high number of patients without cancer who might be spared an invasive, potentially harmful, and costly prostate biopsy on the other hand.


   Acknowledgments
 
We gratefully acknowledge the excellent technical assistance of Ruth Petersson and Marjo Westerdahl. This work was supported by European Union Contracts QLK4-CT-1999-51464, QLK3-CT-2002-02136, and LSHC-CT-2003-503297; the Danish Cancer Society; the Aase and Einar Danielsens Fund; the Deutsche Forschungsgemeinschaft (Gz Ha3168 1/1); National Cancer Institute Contract P50-CA92629–SPORE Pilot Project 7; Department of Defense Contract W81XWH-05-1-0124; the Swedish Cancer Society (Project 3555), European Union 6th Framework Contract LSHC-CT-2004-503011 (P-Mark), and Fundación Federico SA. A suPAR patent application has been filed on behalf of Drs. Timo Piironen, Alexander Haese, Hartwig Huland, Nils Brünner, Keld Danø, Gunilla Høyer-Hansen, and Hans Lilja.


   Footnotes
 
1 Nonstandard abbreviations: PSA, prostate-specific antigen; PCa, prostate cancer; fPSA, free prostate-specific antigen; BPH, benign prostatic hyperplasia; tPSA, total PSA; %fPSA, ratio of free total PSA; uPA, urokinase plasminogen activator; (s)uPAR, (soluble) urokinase plasminogen activator receptor; DRE, digital rectal examination; AUC, area under the curve; and 95% CI, 95% confidence interval.

2 Current affiliation: Schering Oy, Turku, Finland.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Danø K, Behrendt N, Høyer-Hansen G, Johnsen M, Lund LR, Ploug M, et al. Plasminogen activation and cancer. Thromb Haemost 2005;93:676-681.[ISI][Medline] [Order article via Infotrieve]
  2. Almholt K, Lund LR, Rygaard J, Nielsen BS, Danø K, Rømer J, et al. Reduced metastasis of transgenic mammary cancer in urokinase-deficient mice. Int J Cancer 2005;113:525-532.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  3. Ploug M. Structure-function relationships in the interaction between the urokinase-type plasminogen activator and its receptor. Curr Pharm Des 2003;9:1499-1528.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  4. Llinas P, Le Du MH, Gardsvoll H, Danø K, Ploug M, Gilquin B, et al. Crystal structure of the human urokinase plasminogen activator receptor bound to an antagonist peptide. EMBO J 2005;24:1655-1663.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  5. Høyer-Hansen G, Rønne E, Solberg H, Behrendt N, Ploug M, Lund LR, et al. Urokinase plasminogen activator cleaves its cell surface receptor releasing the ligand-binding domain. J Biol Chem 1992;267:18224-18229.[Abstract/Free Full Text]
  6. Wilhelm OG, Wilhelm S, Escott GM, Lutz V, Magdolen V, Schmitt M, et al. Cellular glycosylphosphatidylinositol-specific phospholipase D regulates urokinase receptor shedding and cell surface expression. J Cell Physiol 1999;180:225-235.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  7. Beaufort N, Leduc D, Rousselle JC, Magdolen V, Luther T, Namane A, et al. Proteolytic regulation of the urokinase receptor/CD87 on monocytic cells by neutrophil elastase and cathepsin G. J Immunol 2004;172:540-549.[Abstract/Free Full Text]
  8. Usher PA, Thomsen OF, Iversen P, Johnsen M, Brünner N, Høyer-Hansen G, et al. Expression of urokinase plasminogen activator, its receptor and type-1 inhibitor in malignant and benign prostate tissue. Int J Cancer 2005;113:870-880.[CrossRef][Medline] [Order article via Infotrieve]
  9. Solberg H, Rømer J, Brünner N, Holm A, Sidenius N, Danø K, et al. A cleaved form of the receptor for urokinase-type plasminogen activator in invasive transplanted human and murine tumors. Int J Cancer 1994;58:877-881.[ISI][Medline] [Order article via Infotrieve]
  10. Piironen T, Laursen B, Pass J, List K, Gårdsvoll H, Ploug M, et al. Specific immunoassays for detection of intact and cleaved forms of the urokinase receptor. Clin Chem 2004;50:2059-2068.[Abstract/Free Full Text]
  11. Pappot H, Høyer-Hansen G, Rønne E, Hansen HH, Brünner N, Danø K, et al. Elevated plasma levels of urokinase plasminogen activator receptor in non-small cell lung cancer patients. Eur J Cancer 1997;33:867-872.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  12. Stephens RW, Pedersen AN, Nielsen HJ, Hamers MJ, Høyer-Hansen G, Rønne E, et al. ELISA determination of soluble urokinase receptor in blood from healthy donors and cancer patients. Clin Chem 1997;43:1868-1876.[Abstract/Free Full Text]
  13. Wahlberg K, Høyer-Hansen G, Casslen B. Soluble receptor for urokinase plasminogen activator in both full-length and a cleaved form is present in high concentration in cystic fluid from ovarian cancer. Cancer Res 1998;58:3294-3298.[Abstract/Free Full Text]
  14. Mustjoki S, Sidenius N, Sier CF, Blasi F, Elonen E, Alitalo R, et al. Soluble urokinase receptor levels correlate with number of circulating tumor cells in acute myeloid leukemia and decrease rapidly during chemotherapy. Cancer Res 2000;60:7126-7132.[Abstract/Free Full Text]
  15. Pedersen H, Brünner N, Francis D, Osterlind K, Rønne E, Hansen HH, et al. Prognostic impact of urokinase, urokinase receptor, and type 1 plasminogen activator inhibitor in squamous and large cell lung cancer tissue. Cancer Res 1994;54:4671-4675.[Abstract/Free Full Text]
  16. Ganesh S, Sier CF, Heerding MM, Griffioen G, Lamers CB, Verspaget HW. Urokinase receptor and colorectal cancer survival. Lancet 1994;344:401-402.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  17. Grøndahl-Hansen J, Peters HA, van Putten WL, Look MP, Pappot H, Rønne E, et al. Prognostic significance of the receptor for urokinase plasminogen activator in breast cancer. Clin Cancer Res 1995;1:1079-1087.[Abstract]
  18. Almasi CE, Høyer-Hansen G, Christensen IJ, Danø K, Pappot H. Prognostic impact of liberated domain I of the urokinase plasminogen activator receptor in squamous cell lung cancer tissue. Lung Cancer 2005;48:349-355.[Medline] [Order article via Infotrieve]
  19. Stephens RW, Nielsen HJ, Christensen IJ, Thorlacius-Ussing O, Sorensen S, Danø K, et al. Plasma urokinase receptor levels in patients with colorectal cancer: relationship to prognosis. J Natl Cancer Inst 1999;91:869-874.[Abstract/Free Full Text]
  20. Riisbro R, Christensen IJ, Piironen T, Greenall M, Larsen B, Stephens RW, et al. Prognostic significance of soluble urokinase plasminogen activator receptor in serum and cytosol of tumor tissue from patients with primary breast cancer. Clin Cancer Res 2002;8:1132-1141.[Abstract/Free Full Text]
  21. Miyake H, Hara I, Yamanaka K, Gohji K, Arakawa S, Kamidono S. Elevation of serum levels of urokinase-type plasminogen activator and its receptor is associated with disease progression and prognosis in patients with prostate cancer. Prostate 1999;39:123-129.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  22. McCabe NP, Angwafo FF, 3rd, Zaher A, Selman SH, Kouinche A, Jankun J. Expression of soluble urokinase plasminogen activator receptor may be related to outcome in prostate cancer patients. Oncol Rep 2000;7:879-882.[Medline] [Order article via Infotrieve]
  23. Rønne E, Høyer-Hansen G, Brünner N, Pedersen H, Rank F, Osborne CK, et al. Urokinase receptor in breast cancer tissue extracts. Enzyme-linked immuno-sorbent assay with a combination of mono- and polyclonal antibodies. Breast Cancer Res Treat 1995;33:199-207.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  24. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361-387.[CrossRef][ISI][Medline] [Order article via Infotrieve]
  25. Wun TC, Schleuning WD, Reich E. Isolation and characterization of urokinase from human plasma. J Biol Chem 1982;257:3276-3283.[Abstract/Free Full Text]



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