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A Multiparametric Serum Kallikrein Panel for Diagnosis of Non–Small Cell Lung Carcinoma

Authors' Affiliations: ¹ Department of Laboratory Medicine and Pathobiology, University of Toronto and ² Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada; ³ Fred Hutchinson Cancer Research Center, Seattle, Washington; ⁴ Divisions of Hematology and Medical Oncology, City of Hope Comprehensive Cancer Center and Beckman Research Institute, Duarte, California; and ⁵ Department of Pathology and Laboratory Medicine, Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California

Requests for reprints: Lee Goodglick, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, 10833 Le Conte Avenue, Box 951732, CHS, Los Angeles, CA 90095-1747. Phone: 310-825-9134; Fax: 310-267-2104; E-mail: lgoodglick{at}mednet.ucla.edu.

	Abstract

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Purpose: Human tissue kallikreins are a family of 15 secreted serine proteases. We have previously shown that the expression of several tissue kallikreins is significantly altered at the transcriptional level in lung cancer. Here, we examined the clinical value of 11 members of the tissue kallikrein family as potential biomarkers for lung cancer diagnosis.

Experimental Design: Serum specimens from 51 patients with non–small cell lung cancer (NSCLC) and from 50 healthy volunteers were collected. Samples were analyzed for 11 kallikreins (KLK1, KLK4-8, and KLK10-14) by specific ELISA. Data were statistically compared and receiver operating characteristic curves were constructed for each kallikrein and for various combinations.

Results: Compared with sera from normal subjects, sera of patients with NSCLC had lower levels of KLK5, KLK7, KLK8, KLK10, and KLK12, and higher levels of KLK11, KLK13, and KLK14. Expression of KLK11 and KLK12 was positively correlated with stage. With the exception of KLK5, expression of kallikreins was independent of smoking status and gender. KLK11, KLK12, KLK13, and KLK14 were associated with higher risk of NSCLC as determined by univariate analysis and confirmed by multivariate analysis. The receiver operating characteristic curve of KLK4, KLK8, KLK10, KLK11, KLK12, KLK13, and KLK14 combined exhibited an area under the curve of 0.90 (95% confidence interval, 0.87-0.97).

Conclusions: We propose a multiparametric panel of kallikrein markers for lung cancer diagnosis with relatively good accuracy. This model requires validation with a larger series and may be further improved by addition of other biomarkers.

To supplement advances in surgical treatment, many studies have focused on the development of diagnostic methods, including new serum tumor markers. Thus far, a number of such biomarkers have been reported for NSCLC, including SCC antigen, carcinoembryonic antigen, neuron-specific enolase, cytokeratin 19 fragment (CYFRA 21-1), cancer antigen 125 (CA-125), and tissue polypeptide antigen. However, the expression of these antigens does not seem to be sufficiently sensitive and specific to be reliable for the diagnosis of the majority of lung malignancies.

Proteases may represent good diagnostic/prognostic biomarkers, as they are involved in cancer progression (3). Human tissue kallikreins are a family of 15 highly conserved serine proteases (KLK1-KLK15) encoded by the largest contiguous cluster of protease genes in the human genome. Due to their protease activity and expression in many tissues and cell types, kallikreins have been implicated in a wide range of physiologic functions, ranging from regulation of cell growth to tissue remodeling and skin desquamation. Kallikreins may also be directly or indirectly involved in cancer pathogenesis by promoting angiogenesis and degradation of extracellular matrix proteins (4). Accumulating evidence indicates that many members of the kallikrein family are differentially expressed in cancer, primarily in hormone-related malignancies, at the mRNA and protein levels. Furthermore, many members of the kallikrein family have been reported to be promising diagnostic/prognostic biomarkers for several cancer types, including breast, prostate, ovarian, and testicular carcinomas. In addition to prostate-specific antigen, a prostate cancer biomarker, several kallikrein proteins, including KLK6 and KLK10, represent promising serum-based markers for diagnosis and prognosis of ovarian cancer (4). Likewise, KLK3, KLK5, and KLK14 have been proposed as serum markers for diagnosis and prognosis of breast carcinomas (4).

Little is known about the role of kallikreins in lung cancer. Thus far, most of the information related to kallikrein expression in the lung was obtained by microarray analysis and real-time reverse transcription-PCR. For instance, microarray profiling of human lung adenocarcinoma showed that KLK11 is uniquely overexpressed in a subgroup (cluster C2) of neuroendocrine tumors with less favorable outcome (5). Another microarray-based study indicated that KLK5 and KLK10 are overexpressed in the squamous cell lung carcinoma subtype (6). In addition, using quantitative real-time reverse transcription-PCR, we previously reported a significant correlation between KLK5 overexpression and the SCC histotype, as well as a decrease of KLK7 expression in lung adenocarcinoma, compared with adjacent nonmalignant lung tissues (7). Similarly, we identified only one transcript of KLK10 in lung tissues using reverse transcription-PCR, whereas KLK11 expressed at least four alternative transcripts. Subsequently, using multivariate analysis, we found a correlation between KLK10 overexpression in tumor and the SCC histotype. A similar expression pattern was also observed for these two genes in lung tissue, suggesting coregulation of KLK10 and KLK11 expression in this organ (8). Furthermore, expression of KLK5, KLK6, KLK7, KLK10, KLK11, KLK12, KLK13, and KLK14 in the epithelium of the upper and lower respiratory tract (nose, paranasal sinuses, larynx, trachea, bronchial tree) and in their submucosal glands has been reported immunohistochemically (9). In contrast, no staining was detected in the alveolar epithelium of the lung parenchyma. Interestingly, kallikreins were expressed in varying degree only in non–small cell carcinoma and not in neuroendocrine small-cell carcinoma (9).

As there is a critical need to discover novel biomarkers for lung cancer, the aim of this study was to evaluate whether human tissue kallikreins, alone or in combination, can be potential diagnostic biomarkers in serum from patients with NSCLC.

	Materials and Methods

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Clinical samples. One hundred and one subjects, including 51 cases diagnosed with NSCLC and 50 normal healthy donors were enrolled in this study. Samples were collected at the University of California at Los Angeles Medical Center between October 2004 and March 2006, in accordance with the University of California at Los Angeles Institutional Review Board and patient written informed consent. Peripheral blood was collected from patients at least 4 weeks after receiving prior therapy for patients with advanced disease. In patients who had previously undergone surgical resection, blood was collected after recurrence at least 1 year following surgery. Plasma was collected in EDTA-containing vacutainer tubes. Samples were centrifuged at 3,000 rpm for 15 min within 1 h of collection, separated, and stored in aliquots at –80°C. Staging was determined by the American Joint Committee on Cancer Guidelines. Distributions of patients by demographic and clinical characteristics are presented in Table 1 .

Statistical methods. The relationships between biomarkers and tumor and patient characteristics were examined with the nonparametric Kruskal-Wallis test. Spearman's rank correlation coefficient was used to assess the correlations among biomarkers. Logistic regression was done to calculate the odds ratio (OR) to define the relation between biomarkers and cancer status. ORs were calculated on log-transformed biomarkers and were represented with their 95% confidence interval (95% CI) and two-sided P values.

To evaluate the markers for disease screening and diagnosis, the classification accuracy needs to be assessed. Here, we used receiver operating characteristic (ROC) curve, the most commonly used summary of classification accuracy. The ROC curve is a plot of the true positive fraction versus the false positive fraction for the set of rules that classify a subject as "test-positive," that is, if the marker value exceeds a threshold value, where threshold varies over all possible values. It quantifies how well a marker discriminates between diseased and nondiseased individuals.

To explore the potential that a marker panel can lead to improved performance, we did the ROC analysis first on individual markers and then in combination. We considered an algorithm that renders a single composite score using the linear predictor, fitted from a binary regression model. This algorithm has been justified to be optimal under the linearity assumption (11). A stepwise regression procedure was used to select markers in the panel, sometimes along with clinical variables.

Because an independent validation series was not available for this study, the predictive accuracy of composite scores was evaluated based on resampling of the original data. Specifically, we randomly split the data into a learning set and a test set. The learning set included two thirds of the observations, and the test set one third of the observations. Using the learning set, we first did model selection from which the final selected model gave rise to the linear combination rule. We then calculated two ROC curves for the linear score, one using data from the learning set and the other from the training set. The vertical differences between the two ROC curves gave the overestimation of the sensitivities at given specificities. The whole procedure was repeated 200 times and these differences were averaged to yield an estimate of the expected overestimation. We present both the original ROC curves and the ROC curves that are corrected for overestimation.

All analyses were done using SAS 9.1 (SAS Institute, Inc.) and Splus 7.0 (Insightful Corp.).

	Results

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Distribution of biomarkers. To determine the clinical utility of the kallikrein family as potential biomarkers in NSCLC, the expression profile of several members of the family was examined by ELISA assays previously developed and validated. The differential expression of KLK1, KLK4-8, and KLK10-14 (after logarithmic transformation of values) was determined by Kruskal-Wallis testing. As shown in Table 2 , the distributions of biomarkers between cases and controls were significantly different at the 0.05 level for KLK5, KLK7-8, and KLK10-14. More precisely, KLK5, KLK7, KLK8, KLK10, and KLK12 exhibited a reduced expression level, whereas KLK11, KLK13, and KLK14 were overexpressed in lung cancer patients, compared with samples taken from healthy individuals (Fig. 1 ). Among different members of the kallikrein family, KLK13 was of particular interest as it was detected in almost 26% of cancers, as opposed to only 4% of normal individuals.

View larger version (21K): [in this window] [in a new window] [Download PPT slide]   Fig. 1. Scatter plots of individual kallikrein levels (µg/L) in the sera of healthy volunteers (normal) and patients with NSCLC (lung cancer). Horizontal lines, median values. P values were determined by the Wilcoxon rank sum test.

To assess correlations among markers of the kallikrein family, Spearman's rank correlation coefficients were calculated (Supplementary Table S3). Several kallikreins were statistically correlated with each other. For instance, KLK7 seemed to be moderately correlated to KLK8, KLK10, KLK12, and KLK13 (Spearman's rank correlations ranged from 0.25 to 0.47, P < 0.05). By contrast, KLK1 and KLK4 expressions were not statistically correlated with any of the other members of the family.

Association of biomarkers with lung cancer risk. Logistic regression models were used to examine a possible association between kallikrein biomarkers and lung cancer risk (Table 3 ). Based on univariate analysis, higher values of KLK11 (OR, 2.28; P = 0.004), KLK13 (OR, 2.03; P = 0.009), and KLK14 (OR, 2.00; P = 0.007) were associated with higher risk of NSCLC. Among kallikreins down-regulated in serum of patients with lung cancer, lower values of KLK8 (OR, 0.53; P = 0.024) and KLK12 (OR, 0.44; P = 0.006) were also correlated with higher risk of lung cancer. As expected, smoking history, but not gender, was found to be strongly associated with lung cancer risk (OR, 4.13; P = 0.001).

Diagnostic accuracy of biomarkers. The clinical usefulness of kallikreins in distinguishing NSCLC from noncancer was confirmed using ROC curve analysis (Fig. 2 ). When different candidates were considered individually, most of them, for example, KLK5, KLK7-10, or KLK12-14, had a moderate discriminatory capacity for classifying patients into cancer and noncancer groups, with an area under the curve (AUC) ranging from 0.61 to 0.70 (Table 2; Fig. 2). KLK11 showed the highest AUC (0.70; 95% CI, 0.58-0.82) in differentiating between cases and controls. We further investigated if panels of markers could improve the diagnostic accuracy. We used a stepwise model selection procedure that took all the baseline markers into consideration. Using the linear predictors from the final model, we found that combining a few of these markers improved the classification capacity. Indeed, a panel of markers, including KLK4, KLK8, KLK10, KLK11, KLK12, KLK13, and KLK14, yielded an AUC of 0.90 (95%CI, 0.87-0.97; Fig. 3 ). After correcting for potential overfitting, the adjusted AUC was still at 0.80. After taking into account the clinical variables, including gender and smoking, along with KLK8, KLK11, KLK12, KLK13, and KLK14 markers, the AUC of the ROC curve was 0.92 (95% CI, 0.85-0.98; Fig. 3), with a corrected AUC of 0.82. Smoking and gender alone had an AUC of 0.67. These data suggest that a panel of tissue kallikrein biomarkers, along with clinical variables, may represent a powerful diagnostic modality for lung cancer.

View larger version (16K): [in this window] [in a new window] [Download PPT slide]   Fig. 2. ROC curve analysis of KLK5, KLK7, KLK8, KLK10, KLK11, KLK12, KLK13, and KLK14 in differentiating NSCLC cases and controls. The AUC is given in each panel.

View larger version (15K): [in this window] [in a new window] [Download PPT slide]   Fig. 3. ROC curve analysis of combined kallikreins in differentiating NSCLC cases and controls. Black and red lines, uncorrected and corrected AUC value for potential overfitting, respectively. Shaded area, 95% CI. Additional clinical variables of smoking status and gender are included in the right panel. The AUC for smoking and gender alone is also shown (AUC 0.67).

	Discussion

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In a previous study, we found that KLK11 is represented by at least four alternative transcripts in lung tissues. Among them, one was identical to the brain type KLK11 mRNA (24) in noncancerous and cancerous lung tissues. On the other hand, a longer coding splice variant, containing an additional exon in the 5' untranslated region, was only detected in cancerous lung tissues (8). Given that the majority of the putative proteins encoded by splice variants are predicted to be secreted (25, 26), the above-mentioned cancer-specific KLK11 variant may be useful as a biomarker.

Of the different kallikreins measured, we found that KLK4 and KLK13 were expressed at very low levels in most of the serum samples of this study. Indeed, KLK4 and KLK13 proteins were above the detection limit (0.1 and 0.05 µg/L, respectively) in only 15% of controls and 30% of cases for KLK4, and in 4% of controls and 26% of cases for KLK13. It is known that serine protease inhibitors, such as ₂-macroglobulin, can form complexes with certain serum kallikreins, including KLK2, KLK3, KLK4, KLK5, and KLK13 (27–31). Binding of KLK4 and KLK13 with serum proteinase inhibitors may lead to complexes that are not recognized by ELISA, as shown for prostate-specific antigen (32). Alternatively, these kallikreins may be expressed/secreted at low levels. For instance, KLK4/KLK4 was found to be expressed in ovarian cancer tissues using reverse transcription-PCR, Southern blot, and immunoblotting (33–35). However, a recent study indicated that the concentration of KLK4 was very low in ovarian cancer effusions, suggesting that KLK4 could be expressed in ovarian cancer cells but not secreted to the extracellular medium (36). The most recent data on kallikrein expression in normal lung tissue indicate that KLK7, KLK10, KLK11, and KLK12 are most prominently expressed (10).

Tissue kallikreins are an emerging family on the cancer proteolysis scene. They may exert their function at various stages of cancer initiation and/or progression (4, 37, 38). In our study, we observed that KLK10 was down-regulated in sera of patients with NSCLC. In our study, we also highlighted a significant decrease of KLK8 in sera of patients with NSCLC. More recently, it was reported that KLK8 cleaved fibronectin, thereby suppressing tumor cell invasion and conferred a favorable outcome in early-stage NSCLC (39).

Several other kallikreins, such as KLK11, KLK13, and KLK14, show an increase in serum of patients with NSCLC. These kallikreins may be involved in the promotion of cancer cell growth, angiogenesis, and invasion. For example, several studies reported the cleavage of insulin-like growth factor binding proteins in vitro by kallikreins, including insulin-like growth factor binding protein 3 processing by KLK11 in estrogen receptor–positive breast cancer cells (40) and insulin-like growth factor binding proteins 2 and 3 by KLK14 (22). Reciprocally, the bioavailability of insulin-like growth factor binding protein ligands (i.e., insulin-like growth factors) is increased, which in turn stimulates cancer cell growth. Furthermore, via degradation of extracellular matrix components (e.g., collagens I-III, fibronectin) and proteins of basement membranes (e.g., laminin, collagen IV), KLK13 and KLK14 may also contribute to tumor cell invasion and metastasis (22, 29). KLK14 was also found to cleave vitronectin in vitro, which in turn may decrease integrin-mediated and urokinase receptor–mediated cell adhesion, facilitating tumor cell detachment (22).

Thus far, kallikreins have mainly been described as individual potential biomarkers. Combination of multiple members and/or other tumor markers could further improve their utility. For instance, although KLK3/prostate-specific antigen is clinically used as the main prostatic biomarker, serum KLK2 and KLK11 have been shown to function as complementary biomarkers (19, 41–43). Similarly, combined serum KLK6 and KLK10 can increase the diagnostic sensitivity of CA-125 in patients with early stage (I/II) ovarian cancer (4). It has recently been shown that a combination of eight kallikreins (KLK5-8, KLK10, KLK11, KLK13, and KLK14) in effusion samples can achieve areas under the ROC curve of 0.994 and 0.961 in separating ovarian cancer from benign and other cancer groups, respectively (36). In lung cancer, biomarker panels have already been investigated. Molina et al. (44) did a prospective, multicenter study to determine the clinical utility of five well-known tumor markers (carcinoembryonic antigen, CA-125, SCC antigen, CYFRA 21-1, and neuron-specific enolase) in relation to clinical and pathologic variables used in NSCLC. Using a panel of three markers (CYFRA 21-1, CA-125, and carcinoembryonic antigen), they found high sensitivity for NSCLC (87% for locoregional and 93% for advanced disease).

Here, we report for the first time that a panel of kallikreins may be useful for diagnosis of NSCLC. Seven kallikreins (KLK4, KLK8, and KLK10-14) achieved an AUC of 0.90 between lung cancer cases and controls, which was higher than the AUC of any single kallikrein (ranging from 0.57 for KLK4 to 0.70 for KLK11). Because our cohort is relatively small, further studies will be necessary to validate our findings.

	Acknowledgments

 
We thank Julie Chao (Medical University of South Carolina, Charleston, SC) for providing us with the immunoassay for KLK1.

	Footnotes

 
Grant support: Natural Sciences and Engineering Research Council of Canada (E.P. Diamandis), and Early Detection Research Network National Cancer Institute CA-86366 (L. Goodglick, E.P. Diamandis, and D. Chia) and the Specialized Programs of Research Excellence in Lung Cancer grant P50-CA90388, National Cancer Institute (L. Goodglick and K. Reckamp).

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

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

Received 9/ 5/07; revised 12/12/07; accepted 12/13/07.

	References

Top Abstract Materials and Methods Results Discussion References

 

1. Brambilla E. [Classification of broncho-pulmonary cancers (WHO 1999)]. Rev Mal Respir 2002;19:455–66.[Medline]
2. Etzioni R, Urban N, Ramsey S, et al. The case for early detection. Nat Rev Cancer 2003;3:243–52.[CrossRef][Medline]
3. Duffy MJ. Do proteases play a role in cancer invasion and metastasis? Eur J Cancer Clin Oncol 1987;23:583–9.[CrossRef][Medline]
4. Borgono CA, Diamandis EP. The emerging roles of human tissue kallikreins in cancer. Nat Rev Cancer 2004;4:876–90.[CrossRef][Medline]
5. Bhattacharjee A, Richards WG, Staunton J, et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci U S A 2001;98:13790–5. Epub 2001 Nov 13.[Abstract/Free Full Text]
6. Garber ME, Troyanskaya OG, Schluens K, et al. Diversity of gene expression in adenocarcinoma of the lung. Proc Natl Acad Sci U S A 2001;98:13784–9.[Abstract/Free Full Text]
7. Planque C, de Monte M, Guyetant S, et al. KLK5 and KLK7, two members of the human tissue kallikrein family, are differentially expressed in lung cancer. Biochem Biophys Res Commun 2005;329:1260–6.[CrossRef][Medline]
8. Planque C, Ainciburu M, Heuze-Vourc'h N, Regina S, de Monte M, Courty Y. Expression of the human kallikrein genes 10 (KLK10) and 11 (KLK11) in cancerous and non-cancerous lung tissues. Biol Chem 2006;387:783–8.[CrossRef][Medline]
9. Petraki CD, Papanastasiou PA, Karavana VN, Diamandis EP. Cellular distribution of human tissue kallikreins: immunohistochemical localization. Biol Chem 2006;387:653–63.[CrossRef][Medline]
10. Shaw JL, Diamandis EP. Distribution of 15 human kallikreins in tissues and biological fluids. Clin Chem 2007;53:1423–32.[Abstract/Free Full Text]
11. McIntosh MW, Pepe MS. Combining several screening tests: optimality of the risk score. Biometrics 2002;58:657–64.[CrossRef][Medline]
12. Yu H, Diamandis EP, Levesque M, et al. Prostate specific antigen in breast cancer, benign breast disease and normal breast tissue. Breast Cancer Res Treat 1996;40:171–8.[CrossRef][Medline]
13. Liu XL, Wazer DE, Watanabe K, Band V. Identification of a novel serine protease-like gene, the expression of which is down-regulated during breast cancer progression. Cancer Res 1996;56:3371–9.[Abstract/Free Full Text]
14. Yousef GM, Magklara A, Diamandis EP. KLK12 is a novel serine protease and a new member of the human kallikrein gene family—differential expression in breast cancer [in process citation]. Genomics 2000;69:331–41.[CrossRef][Medline]
15. Petraki CD, Gregorakis AK, Papanastasiou PA, Karavana VN, Luo LY, Diamandis EP. Immunohistochemical localization of human kallikreins 6, 10 and 13 in benign and malignant prostatic tissues. Prostate Cancer Prostatic Dis 2003;6:223–7.[CrossRef][Medline]
16. Yousef GM, Scorilas A, Chang A, et al. Down-regulation of the human kallikrein gene 5 (KLK5) in prostate cancer tissues. Prostate 2002;51:126–32.[CrossRef][Medline]
17. Yousef GM, Obiezu CV, Jung K, Stephan C, Scorilas A, Diamandis EP. Differential expression of Kallikrein gene 5 in cancerous and normal testicular tissues. Urology 2002;60:714–8.[CrossRef][Medline]
18. Luo LY, Rajpert-De Meyts ER, Jung K, Diamandis EP. Expression of the normal epithelial cell-specific 1 (NES1; KLK10) candidate tumour suppressor gene in normal and malignant testicular tissue. Br J Cancer 2001;85:220–4.[CrossRef][Medline]
19. Diamandis EP, Okui A, Mitsui S, et al. Human kallikrein 11: a new biomarker of prostate and ovarian carcinoma. Cancer Res 2002;62:295–300.[Abstract/Free Full Text]
20. Borgono CA, Grass L, Soosaipillai A, et al. Human kallikrein 14: a new potential biomarker for ovarian and breast cancer. Cancer Res 2003;63:9032–41.[Abstract/Free Full Text]
21. Yousef GM, Polymeris ME, Yacoub GM, et al. Parallel overexpression of seven kallikrein genes in ovarian cancer. Cancer Res 2003;63:2223–7.[Abstract/Free Full Text]
22. Borgono CA, Michael IP, Shaw JL, et al. Expression and functional characterization of the cancer-related serine protease, human tissue kallikrein 14. J Biol Chem 2007;282:2405–22.[Abstract/Free Full Text]
23. Sasaki H, Kawano O, Endo K, et al. Decreased kallikrein 11 messenger RNA expression in lung cancer. Clin Lung Cancer 2006;8:45–8.[Medline]
24. Mitsui S, Yamada T, Okui A, Kominami K, Uemura H, Yamaguchi N. A novel isoform of a kallikrein-like protease, TLSP/hippostasin (PRSS20), is expressed in the human brain and prostate. Biochem Biophys Res Commun 2000;272:205–11.[CrossRef][Medline]
25. Kurlender L, Borgono C, Michael IP, et al. A survey of alternative transcripts of human tissue kallikrein genes. Biochim Biophys Acta 2005;1755:1–14.[Medline]
26. Tan OL, Whitbread AK, Clements JA, Dong Y. Kallikrein-related peptidase (KLK) family mRNA variants and protein isoforms in hormone-related cancers: do they have a function? Biol Chem 2006;387:697–705.[CrossRef][Medline]
27. Christensson A, Laurell CB, Lilja H. Enzymatic activity of prostate-specific antigen and its reactions with extracellular serine proteinase inhibitors. Eur J Biochem 1990;194:755–63.[Medline]
28. Yousef GM, Kapadia C, Polymeris ME, et al. The human kallikrein protein 5 (hK5) is enzymatically active, glycosylated and forms complexes with two protease inhibitors in ovarian cancer fluids. Biochim Biophys Acta 2003;1628:88–96.[Medline]
29. Kapadia C, Yousef GM, Mellati AA, Magklara A, Wasney GA, Diamandis EP. Complex formation between human kallikrein 13 and serum protease inhibitors. Clin Chim Acta 2004;339:157–67.[CrossRef][Medline]
30. Mikolajczyk SD, Millar LS, Kumar A, Saedi MS. Human glandular kallikrein, hK2, shows arginine-restricted specificity and forms complexes with plasma protease inhibitors. Prostate 1998;34:44–50.[CrossRef][Medline]
31. Obiezu CV, Shan SJ, Soosaipillai A, et al. Human kallikrein 4: quantitative study in tissues and evidence for its secretion into biological fluids. Clin Chem 2005;51:1432–42.[Abstract/Free Full Text]
32. Leinonen J, Zhang WM, Stenman UH. Complex formation between PSA isoenzymes and protease inhibitors. J Urol 1996;155:1099–103.[CrossRef][Medline]
33. Dong Y, Kaushal A, Bui L, et al. Human kallikrein 4 (KLK4) is highly expressed in serous ovarian carcinomas. Clin Cancer Res 2001;7:2363–71.[Abstract/Free Full Text]
34. Obiezu CV, Scorilas A, Katsaros D, et al. Higher human kallikrein gene 4 (KLK4) expression indicates poor prognosis of ovarian cancer patients. Clin Cancer Res 2001;7:2380–6.[Abstract/Free Full Text]
35. Davidson B, Xi Z, Klokk TI, et al. Kallikrein 4 expression is up-regulated in epithelial ovarian carcinoma cells in effusions. Am J Clin Pathol 2005;123:360–8.[CrossRef][Medline]
36. Shih Ie M, Salani R, Fiegl M, et al. Ovarian cancer specific kallikrein profile in effusions. Gynecol Oncol 2007;105:501–7.[CrossRef][Medline]
37. Emami N, Diamandis EP. Human tissue kallikreins: a road under construction. Clin Chim Acta 2007;381:78–84.[CrossRef][Medline]
38. Paliouras M, Borgono C, Diamandis EP. Human tissue kallikreins: the cancer biomarker family. Cancer Lett 2007;249:61–79.[CrossRef][Medline]
39. Sher YP, Chou CC, Chou RH, et al. Human kallikrein 8 protease confers a favorable clinical outcome in non-small cell lung cancer by suppressing tumor cell invasiveness. Cancer Res 2006;66:11763–70.[Abstract/Free Full Text]
40. Sano A, Sangai T, Maeda H, Nakamura M, Hasebe T, Ochiai A. Kallikrein 11 expressed in human breast cancer cells releases insulin-like growth factor through degradation of IGFBP-3. Int J Oncol 2007;30:1493–8.[Medline]
41. Stenman UH. New ultrasensitive assays facilitate studies on the role of human glandular kallikrein (hK2) as a marker for prostatic disease. Clin Chem 1999;45:753–4.[Free Full Text]
42. Nakamura T, Scorilas A, Stephan C, Jung K, Soosaipillai AR, Diamandis EP. The usefulness of serum human kallikrein 11 for discriminating between prostate cancer and benign prostatic hyperplasia. Cancer Res 2003;63:6543–6.[Abstract/Free Full Text]
43. Stephan C, Meyer HA, Cammann H, Nakamura T, Diamandis EP, Jung K. Improved prostate cancer detection with a human kallikrein 11 and percentage free PSA-based artificial neural network. Biol Chem 2006;387:801–5.[CrossRef][Medline]
44. Molina R, Filella X, Auge JM, et al. Tumor markers (CEA, CA 125, CYFRA 21–1, SCC and NSE) in patients with non-small cell lung cancer as an aid in histological diagnosis and prognosis. Comparison with the main clinical and pathological prognostic factors. Tumour Biol 2003;24:209–18.[CrossRef][Medline]

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