Advertisement
Journal of Clinical Oncology  
Search for:
Limit by:
  Browse by Subject or Issue
Home Search or Browse JCO My JCO Subscriptions Customer Service Site Map

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a colleague
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Save to my personal folders
Right arrow Download to citation manager
Right arrowRights & Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Yousef, G. M.
Right arrow Articles by Diamandis, E. P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yousef, G. M.
Right arrow Articles by Diamandis, E. P.
Journal of Clinical Oncology, Vol 21, Issue 16 (August), 2003: 3119-3126
© 2003 American Society for Clinical Oncology

Prognostic Value of the Human Kallikrein Gene 15 Expression in Ovarian Cancer

George M. Yousef, Andreas Scorilas, Dionyssios Katsaros, Stefano Fracchioli, Lisa Iskander, Carla Borgono, Irene A. Rigault de la Longrais, Manuela Puopolo, Marco Massobrio, Eleftherios P. Diamandis

From the Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada; National Center for Scientific Research "Demokritos," Athens, Greece; and Department of Obstetrics and Gynecology, Gynecologic Oncology Unit, University of Turin, and Department of Pathology, S. Anna Hospital, Turin, Italy.

Address reprint requests to Eleftherios P. Diamandis, MD, Mount Sinai Hospital, Department of Pathology and Laboratory Medicine; 600 University Ave, Toronto, Ontario M5G 1X5, Canada; email: ediamandis{at}mtsinai.on.ca.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Purpose: KLK15 is a newly cloned human kallikrein gene. Many kallikreins were found to be differentially expressed in ovarian cancer. Like other kallikreins, KLK15 is regulated by steroid hormones in cancer cell lines. KLK15 is upregulated mainly by androgens and to a lesser extent by progestins. The purpose of this study was to examine the prognostic value of KLK15 in ovarian cancer tissues.

Materials and Methods: We studied KLK15 expression by quantitative reverse transcriptase polymerase chain reaction (RT-PCR) in 168 consecutive patients with epithelial ovarian cancer. Ten patients with benign ovarian tumors were also included in the study. An optimal cutoff point equal to the 50th percentile was defined based on the ability of KLK15 to predict progression-free survival and overall survival of the study population.

Results: KLK15 expression levels were significantly higher in cancerous tissues compared with benign tumors. Kaplan-Meier survival curves showed that KLK15 overexpression is a significant predictor of reduced progression-free survival (PFS; P < .001) and overall survival (OS; P < .009). Univariate and multivariate analyses indicate that KLK15 is an independent prognostic factor for PFS and OS. A weak positive correlation was found between KLK15 expression and serum CA-125 levels.

Conclusion: KLK15 expression, as assessed by quantitative RT-PCR, is an independent marker of unfavorable prognosis for ovarian cancer.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
EPITHELIAL OVARIAN cancer is the most lethal of all gynecologic malignancies. The only validated marker for ovarian cancer management is CA-125, which can be detected in the serum of more than 80% of women with ovarian carcinomas.1 However, CA-125 is robust only in following response to treatment or progression of the disease and not as a diagnostic or prognostic marker.2 Thus, there is an urgent need for additional diagnostic and prognostic markers for this disease.

Several other putative markers have been sought to compensate for the limitations of CA-125, including inhibin3 and prostasin.4 These novel markers may by used in conjunction with CA-125, thereby enhancing the overall diagnostic and prognostic capability.5 A novel approach for finding new tumor markers is the analysis of gene expression profiles in normal and neoplastic ovarian tissues, which has recently identified several candidate molecular markers of epithelial ovarian cancer6; yet, the value of these markers has not been validated.

Kallikreins are a subgroup of the serine protease family of proteolytic enzymes.7 The human kallikrein gene family comprises 15 genes, clustered together in a small region of approximately 400 kb on chromosome 19q13.4.7–9 In the past few years, several groups have shown that many members of the human kallikrein gene family are related to ovarian cancer. Underwood et al10 and Magklara et al11 have shown that KLK8 (also known as neuropsin, TADG14) is differentially expressed in ovarian cancer, KLK7 is upregulated in patients with ovarian cancer,12 and KLK4 and KLK5 are indicators of poor prognosis of ovarian cancer.13–15 More recently, KLK9 has been shown to be a marker of favorable prognosis.16 In addition, two kallikrein proteins, hK6 and hK10, have been shown to be putative serum biomarkers for ovarian cancer diagnosis.17–19

KLK15 (encoding for hK15, a protein also called prostinogen) is the most recently cloned member of the human kallikrein gene family.20,21 It is formed by five coding exons and encodes for a serine protease of a predicted molecular weight of approximately 28 kd. KLK15 shares a high degree of structural similarity with KLK3 (also known as prostate-specific antigen) and other kallikreins. Similar to KLK3, but unlike other trypsin-like serine proteases, KLK15 does not have an aspartate residue in the substrate-binding pocket, suggesting a chymotrypsin-like substrate specificity. We have previously shown preliminarily that KLK15 is upregulated at the mRNA level in prostate cancer.20 A recent report indicated that hK15 can readily activate the precursor of prostate-specific antigen by cleaving an amino terminal peptide bond.21 In addition, we have also shown that KLK15 is under steroid hormone regulation, possibly through the androgen receptor (AR; unpublished data).

Given the aforementioned associations of kallikreins with cancer, their potential applicability as cancer biomarkers,22,23 and the fact that many proteases are known to be mediators of tumor progression, we postulated that KLK15 may also be implicated in ovarian cancer prognosis. This investigation examines this hypothesis.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study Population
In this study we included tumor specimens from 168 consecutive patients undergoing surgical treatment for epithelial ovarian carcinoma at the Department of Gynecology, Gynecological Oncology Unit, University of Turin, Turin, Italy. All tumor specimens were confirmed by histopathologic examination. No patient received any treatment before surgery.

Patient age ranged from 25 to 89 years, with a median age of 59 years. Residual tumor sizes after surgery ranged from 0 to 9 cm, with a median of 2.0 cm. With respect to histologic type, 76 tumors were serous papillary, 28 were endometrioid, 28 were undifferentiated, 17 were mucinous, and 15 were clear cell. We also included 10 benign ovarian tissues from women whose median age was 52 years. Classification of histologic types followed the World Health Organization criteria.24 All patients were staged according to the International Federation of Gynecology and Obstetrics staging system.25 Grading information was available for 162 patients; 54 (33%) had grade 1 or 2, whereas 108 (67%) had grade 3 ovarian carcinoma. Grading was established for each ovarian tumor according to the criteria of Day et al.26 All patients were treated with postoperative platinum-based chemotherapy. The first-line chemotherapy regimens included cisplatin in 95 patients (56%), carboplatin in 50 patients (30%), cyclophosphamide in 69 patients (41%), doxorubicin in 12 patients (7%), epirubicin in 20 patients (12%), paclitaxel in 27 patients (16%), and methotrexate in two patients (1%). Grade 1 and stage I patients received no further treatment. Response to chemotherapy was assessed as follows: complete response was defined as a resolution of all evidence of disease for at least 1 month, and a decrease (lasting at least 1 month) of at least 50% in the diameters of all measurable lesions without the development of new lesions was termed partial response. Stable disease was defined as a decrease of less than 25% in the product of the diameters of all measurable lesions. Progressive disease was defined as an increase of at least 25%. In patients with no clinically measurable disease, response to chemotherapy was assessed by serial measurements of serum CA-125. Responders (partial or complete) experienced a decrease in their CA-125 level by more than 50% after two cycles of chemotherapy.

Investigations were performed in accordance with the Helsinki Declaration and was approved by the Institute of Obstetrics and Gynecology, Turin. Tumor specimens were snap-frozen in liquid nitrogen immediately after surgery. Histologic examination, performed during intrasurgery frozen-section analysis, allowed representative portions of each tumor containing more than 80% of tumor cells to be selected for storage until analysis. Serum CA-125 values before operation were available for 67 patients.

Total RNA Extraction and cDNA Synthesis
Samples were shipped and stored at -80°C. They were then minced with a scalpel on dry ice and transferred immediately to 2-mL polypropylene tubes. They were then homogenized, and total RNA was extracted using Trizol reagent (Gibco BRL, Gaithersburg, MD) according to the manufacturer’s instructions. The concentration and purity of RNA were determined spectrophotometrically. We reverse-transcribed 2 µg of total RNA into first-strand cDNA using the Superscript preamplification system (Gibco BRL). The final volume was 20 µL.

Quantitative Real-Time Polymerase Chain Reaction (PCR) and Continuous Monitoring of PCR Products
On the basis of the published genomic sequence of KLK15 (GenBank [National Institutes of Health, Bethesda, MD] accession no. AF242195), two gene-specific primers were designed (15-F3: 5' TGT GGC TTC TCC TCA CTC TC 3' and 15-R3 5'AGG CTC GTT GTG GGA CAC 3'). These primers spanned more than two exons to avoid contamination by genomic DNA. Real-time monitoring of PCR reaction was performed on the LightCycler system (Roche Molecular Systems, Indianapolis, IN) and the SYBR Green I dye (Roche, Nutley, NJ), which binds preferentially to double-stranded DNA. Fluorescence signals are proportional to the concentration of the product and are measured at the end of each cycle rather than after a fixed number of cycles. The higher the starting quantity of the template, the earlier the threshold cycle, which is defined as the fractional cycle number at which fluorescence passes a fixed threshold above baseline, will be attained.27 For each sample, the amount of KLK15 and an endogenous control (beta actin, a housekeeping gene) were determined using a calibration curve. The amount of KLK15 was then divided by the amount of the endogenous reference, to obtain a normalized KLK15 value.

Standard Curve Construction
The full-length mRNA sequence of the KLK15 gene was amplified by PCR using gene-specific primers, and the PCR product was cloned into a TOPO TA cloning vector (Invitrogen, Carlsbad, CA) according to manufacturer’s instructions. Plasmids were purified using Mini-prep kit (Qiagen Inc, Valencia, CA). Different standard curves for actin and KLK15 were constructed using serial dilutions of the plasmid, as described elsewhere.27 These standards were included in each run. An example is given in Figure 1Go. The reliability of the KLK15 assay was determined by evaluating within- and between-run precision. In all cases, the coefficients of variation were less than 10%.



View larger version (22K):
[in this window]
[in a new window]
  		Fig 1. Quantification of KLK15 gene expression by real-time polymerase chain reaction. (A) A logarithmic plot of fluorescence signal versus cycle number. (B) A representative calibration curve for KLK15 mRNA quantification. Curves were obtained with serially diluted (10-fold) plasmid containing KLK15 cDNA.

 
PCR Amplification
The PCR reaction was carried out on the LightCycler system. For each run, a master mixture was prepared on ice, containing 1 µL of cDNA, 2 µL of LC DNA Master SYBR Green 1 mix, 50 ng of primers, and 1.2 µL of 25 mmol/L MgCl2. The final volume was adjusted to 20 µL with water. After the reaction mixture was loaded into the glass capillary tube, the cycling conditions were carried out as follows: initial denaturation at 94°C for 10 minutes, followed by 45 cycles of denaturation at 94°C for 0 seconds, annealing at 63°C for 5 seconds, and extension at 72°C for 30 seconds. The temperature transition rate was set at 20°C per second. Fluorescent product was measured by a single acquisition mode at 88°C after each cycle. A melting curve was then performed by holding the temperature at 70°C for 30 seconds, followed by a gradual increase in temperature to 98°C at a rate of 0.2°C per second, with the signal acquisition mode set at step. To verify the melting curve results, representative samples of the PCR products were purified and sequenced.

Statistical Analysis
First, an optimal cutoff value was defined by {chi}2 analysis, based on the ability of KLK15 values to predict the progression-free survival (PFS) and overall survival (OS) of the study population. This cutoff (1.0 arbitrary units; 50th percentile) identifies 50% of patients as being KLK15-positive.

Associations between clinicopathologic parameters, such as stage, grade, histotype, and residual tumor, and KLK15 expression were analyzed by the {chi}2 test or the Fisher’s exact test, when appropriate. For survival analysis, two different end points, cancer relapse (either local recurrence or distant metastasis) and death, were used to calculate PFS and OS, respectively. PFS was defined as the time interval between the date of surgery and the date of identification of recurrent or metastatic disease. OS was defined as the time interval between the date of surgery and the date of death.

The Cox univariate and multivariate proportional hazards regression model28 was used to evaluate the hazard ratio (relative risk of relapse or death in the KLK15-positive group). In the multivariate analysis, the models were adjusted for KLK15 expression, clinical stage, histologic grade, residual tumor, and age.

Kaplan-Meier survival curves29 were constructed for KLK15-positive and KLK15-negative patients. For further analysis, patients were divided into two groups either by the tumor grade (grade 1 to 2 v grade 3), tumor stage (stage I/II v stage III/IV), or by the success of debulking (optimal v suboptimal debulking group). In each category, survival rates (DFS and OS) were compared between KLK15-positive and KLK15-negative groups. The differences between the group survival curves were tested for statistical significance by the log-rank test.30


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
KLK15 Expression in Benign and Cancerous Ovarian Tissues
Table 1Go shows the mean and median KLK15 expression levels in benign and malignant ovarian tumors. Expression levels were found to be much higher in cancerous tissues (mean, 328 arbitrary units; median, 1.0 arbitrary units) compared with benign ovarian tumors (mean, 0.077 arbitrary units; median, 0.056 arbitrary units). The distribution of KLK15 expression in ovarian cancer and benign tissues is depicted in Figure 2Go. The differences between medians of the two groups were highly significant (P = .021 by Mann-Whitney U test).


View this table:
[in this window]
[in a new window]
  		Table 1. Descriptive Statistics of KLK15 Expression in Cancer and Benign Tissues
 


View larger version (12K):
[in this window]
[in a new window]
  		Fig 2. Distribution of KLK15 expression levels in cancerous and benign ovarian tissues. Horizontal lines show median values (P = .021 by Mann-Whitney U test).

 
KLK15 Expression in Relation to Other Variables
As shown in Table 2Go, no significant associations were found between KLK15 expression and other clinical variables, except for a weakly significant difference between patients with optimal and suboptimal debulking.


View this table:
[in this window]
[in a new window]
  		Table 2. Relationship Between KLK15 Status and Other Variables in 168 Ovarian Cancer Patients
 
Survival Analysis
Of the 168 patients included in this study, follow-up information was available for 162 patients (median follow-up period, 67 months), among whom 96 (59%) had experienced relapse, and 61 (38%) died.

Kaplan-Meier survival curves demonstrated that patients with KLK15-positive tumors have substantially lower PFS (P < .001) and OS (P = .009; Fig 3Go) compared with those who are KLK15-negative. The strength of the associations between each individual prognostic factor, and PFS or OS are shown in the univariate analysis in Table 3Go. Stage of disease, histologic grade, and residual tumor size showed strong associations with cancer relapse and death (P < .001). KLK15 expression was also found to be a significant predictor of lower PFS and OS (hazard ratios of 2.33 and 1.96, respectively, and P values of < .001 and .012, respectively).



View larger version (14K):
[in this window]
[in a new window]
  		Fig 3. Kaplan-Meier survival curves for (A) progression-free survival (PFS) and (B) overall survival (OS) in patients with KLK15-positive and KLK15-negative ovarian tumors.

 

View this table:
[in this window]
[in a new window]
  		Table 3. Univariate and Multivariate Analysis of KLK15 With Regard to Progression-Free and Overall Survival
 
When all the confounders were included in the Cox model (multivariate analysis, Table 3Go), only residual tumor size and grade, in addition to KLK15, retained their prognostic significance. KLK15 expression showed hazard ratios of 2.27 and 1.79 and P values of less than .001 and .039 for the PFS and OS, respectively. CA-125, as a continuous variable, was found to be an unfavorable prognostic indicator in the Cox univariate analysis for PFS (P = .007) but not for OS (P = .14). When KLK15 was included in the Cox model, CA-125 did not retain its significance for PFS (P = .13 for CA-125 and P = .001 for KLK15) (data not shown).

As shown in Figure 4Go, a weak positive correlation was found between the expression levels of KLK15 levels and presurgical serum CA-125 (rs = 0.37; P = .002).



View larger version (18K):
[in this window]
[in a new window]
  		Fig 4. Correlation between serum CA-125 and tumor levels of KLK15 expression. rs, Spearman correlation coefficient.

 
When Cox proportional hazard regression analysis was applied for subgroups of patients (Table 4Go), KLK15 was found to be a significant predictor of reduced PFS, but not OS, in the subgroups of patients with grade 1 to 2 (hazard ratio, 5.35; P = .004), grade 3 (hazard ratio, 1.89; P = .007), stage I to II (hazard ratio, 7.1; P = .014), and stage III (hazard ratio, 1.93; P = .004). KLK15 retained its prognostic significance after adjusting for other confounders. KLK15 expression retained a highly statistically significant prognostic value for both PFS and OS in patients with optimal debulking, even after adjusting for all other confounders (Table 4Go).


View this table:
[in this window]
[in a new window]
  		Table 4. Cox Proportional Hazards Regression Analysis for Subgroups of Patients
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Our results show that KLK15 is an independent marker of unfavorable prognosis in ovarian cancer. KLK15 is not the only kallikrein that has been found to be differentially regulated in ovarian cancer. We have recently reported that KLK9 is a marker of favorable prognosis.16 In addition, data from other groups and our laboratory indicate that multiple kallikrein genes (KLK4 through KLK10) are differentially expressed in ovarian cancer.11–14,17,31 It will be interesting to simultaneously examine the expression of all these kallikreins in ovarian cancer and to develop multiparametric models of prognosis.

We have recently shown that KLK15 is a hormonally regulated gene.20 KLK15 is upregulated mainly by androgens and to a lesser extent by progestins (our data, submitted for publication). We also provided evidence suggesting that this regulation is possibly mediated through the AR. Appreciable evidence implicates androgens in the pathogenesis of ovarian cancer32 and supports the existence of a physiologic interaction between androgens and the ovarian surface epithelium, as well as the possible role of this interaction in ovarian neoplasia.33 Androgens stimulate growth of rodent ovarian epithelial cells in vivo, leading to benign ovarian neoplasms.34 Furthermore, ovarian cancer patients have higher levels of circulating androgens before their diagnosis than women without cancer.35 Additionally, the majority of ovarian cancers express AR,36,37 and ovarian cancer cell growth is inhibited in vitro by antiandrogens.38 Recent observations show a correlation between AR and susceptibility to ovarian cancer.37 In this study, an optimal cutoff point equal to the 50th percentile was selected, based on the ability of KLK15 to predict PFS and OS. It has been previously pointed out that this approach may overestimate the marker’s prognostic value.39 In this study, however, the prognostic value of KLK15 is further supported by the statistically significant differences between ovarian cancer and benign tissues between patients with optimal versus suboptimal debulking and by the positive correlation between the expression levels of KLK15 and presurgical serum CA-125.

It is now widely accepted that no single biomarker will produce all the necessary information for diagnosis, prognosis, and development of treatment strategies for patients with ovarian cancer. Instead, research is now focusing on generating a panel of ovarian cancer biomarkers. An artificial network approach for combining and interpreting information from a group of biomarkers will enable more accurate diagnosis and prognosis; this method is currently underway and has already produced promising preliminary results.40–42

Our results show a weak positive correlation between KLK15 expression and serum CA-125 levels (Fig 4Go). These results are consistent with previous reports showing that higher CA-125 levels are associated with poor prognosis in ovarian cancer.43 On other hand, although high CA-125 expression levels are associated only with the serous histologic type,43 no significant relationships were found between KLK15 levels and any of the histologic types of ovarian carcinoma (Table 2Go), implicating a possible role of KLK15 in monitoring nonserous ovarian cancer patients, whereas CA-125 is not usually informative. Serum assays for hK15 are required for such application.

In conclusion, we report for the first time that higher KLK15 expression is an indicator of poor prognosis in ovarian cancer. These data would need validation with additional tumor sets. These data add to the growing recent literature suggesting that many other members of the kallikrein gene family have prognostic value in ovarian cancer. It is conceivable that all these enzymes may participate in a common pathway that is activated during ovarian cancer initiation and progression.


   NOTES
 
D.K., S.F., I.A.R., and M.P. are partially supported by the Italian Association for Cancer Research. This work was also supported by a University-Industry grant from the Natural Sciences and Engineering Research Council of Canada and ONCO Therapeutics Inc.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
1. Niloff JM, Klug TL, Schaetzl E, et al: Elevation of serum CA-125 in carcinomas of the fallopian tube, endometrium, and endocervix. Am J Obstet Gynecol 148:1057–1058, 1984[Medline]

2. Meyer T, Rustin GJ: Role of tumour markers in monitoring epithelial ovarian cancer. Br J Cancer 82:1535–1538, 2000[CrossRef][Medline]

3. Lambert-Messerlian GM: Is inhibin a serum marker for ovarian cancer? Eur J Endocrinol 142:331–333, 2000[CrossRef][Medline]

4. Mok SC, Chao J, Skates S, et al: Prostasin, a potential serum marker for ovarian cancer: Identification through microarray technology. J Natl Cancer Inst 93:1458–1464, 2001[Abstract/Free Full Text]

5. Menon U, Jacobs IJ: Recent developments in ovarian cancer screening. Curr Opin Obstet Gynecol 12:39–42, 2000[CrossRef][Medline]

6. Welsh JB, Zarrinkar PP, Sapinoso LM, et al: Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer. Proc Natl Acad Sci USA 98:1176–11781, 2001[Abstract/Free Full Text]

7. Yousef GM, Diamandis EP: The new human tissue kallikrein gene family: Structure, function, and association to disease. Endocr Rev 22:184–204, 2001[Abstract/Free Full Text]

8. Yousef GM, Diamandis EP: Human kallikreins: Common structural features, sequence analysis and evolution. Curr Genomics 4:147–165, 2003[CrossRef]

9. Yousef GM, Chang A, Scorilas A, et al: Genomic organization of the human kallikrein gene family on chromosome 19q13.3–q13.4. Biochem Biophys Res Commun 276:125–133, 2000[CrossRef][Medline]

10. Underwood LJ, Tanimoto H, Wang Y, et al: Cloning of tumor-associated differentially expressed gene-14, a novel serine protease overexpressed by ovarian carcinoma. Cancer Res 59:4435–4439, 1999[Abstract/Free Full Text]

11. Magklara A, Scorilas A, Katsaros D, et al: The human KLK8 (neuropsin/ovasin) gene: Identification of two novel splice variants and its prognostic value in ovarian cancer. Clin Cancer Res 7:806–811, 2001[Abstract/Free Full Text]

12. Tanimoto H, Underwood LJ, Shigemasa K, et al: The stratum corneum chymotryptic enzyme that mediates shedding and desquamation of skin cells is highly overexpressed in ovarian tumor cells. Cancer 86:2074–2082, 1999[CrossRef][Medline]

13. 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 7:2380–2386, 2001[Abstract/Free Full Text]

14. Kim H, Scorilas A, Katsaros D, et al: Human kallikrein gene 5 (KLK5) expression is an indicator of poor prognosis in ovarian cancer. Br J Cancer 84:643–650, 2001[CrossRef][Medline]

15. Dong Y, Kaushal A, Bui L, et al: Human kallikrein 4 (KLK4) is highly expressed in serous ovarian carcinomas. Clin Cancer Res 7:2363–2371, 2001[Abstract/Free Full Text]

16. Yousef GM, Kyriakopoulou LG, Scorilas A, et al: Quantitative expression of the human kallikrein gene 9 (KLK9) in ovarian cancer: A new independent and favorable prognostic marker. Cancer Res 61:7811–7818, 2001[Abstract/Free Full Text]

17. Diamandis EP, Yousef GM, Soosaipillai AR, et al: Human kallikrein 6 (zyme/protease M/neurosin): A new serum biomarker of ovarian carcinoma. Clin Biochem 33:579–583, 2000[CrossRef][Medline]

18. Diamandis EP, Yousef GM, Soosaipillai AR, et al: Immunofluorometric assay of human kallikrein 6 (zyme/protease M/neurosin) and preliminary clinical applications. Clin Biochem 33:369–375, 2000[CrossRef][Medline]

19. Luo L, Bunting P, Scorilas A, et al: Human kallikrein 10: A novel tumor marker for ovarian carcinoma? Clin Chim Acta 306:111–118, 2001[CrossRef][Medline]

20. Yousef GM, Scorilas A, Jung K, et al: Molecular cloning of the human kallikrein 15 gene (KLK15): Up-regulation in prostate cancer. J Biol Chem 276:53–61, 2001[Abstract/Free Full Text]

21. Takayama TK, Carter CA, Deng T: Activation of prostate-specific antigen precursor (pro-PSA) by prostin, a novel human prostatic serine protease identified by degenerate PCR. Biochemistry 40:1679–1687, 2001[CrossRef][Medline]

22. Diamandis EP, Yousef GM, Luo LY, et al: The new human kallikrein gene family: Implications in carcinogenesis. Trends Endocrinol Metab 11:54–60, 2000[CrossRef][Medline]

23. Diamandis EP, Yousef GM: Human tissue kallikrein gene family: A rich source of novel disease biomarkers. Expert Rev Mol Diagn 1:182–190, 2001[CrossRef][Medline]

24. Serov SF, Sorbin LH: Histological Typing of Ovarian Tumors. Geneva, Switzerland, World Health Organization, 1973

25. Pettersson F: Annual Report on the Treatment in Gynecological Cancer. Stockholm, Sweden, International Federation of Gynecology and Obstetrics, 1994

26. Day TG Jr, Gallager HS, Rutledge FN: Epithelial carcinoma of the ovary: Prognostic importance of histologic grade. Natl Cancer Inst Monogr 42:15–21, 1975[Medline]

27. Bieche I, Onody P, Laurendeau I, et al: Real-time reverse transcription-PCR assay for future management of ERBB2-based clinical applications. Clin Chem 45:1148–1156, 1999[Abstract/Free Full Text]

28. Cox DR: Regression models and life tables. J R Stat Soc B 34:187–202, 1972

29. Kaplan EL, Meier P: Nonparametric estimation from incomplete observations. J Am Stat Assoc 53:457–481, 1958[CrossRef]

30. Mantel N: Evaluation of survival data and two new rank order statistics arising in its consideration. Cancer Chemother Rep 50:163–170, 1966[Medline]

31. Luo LY, Katsaros D, Scorilas A, et al: Prognostic value of human kallikrein 10 expression in epithelial ovarian carcinoma. Clin Cancer Res 7:2372–2379, 2001[Abstract/Free Full Text]

32. Risch HA: Hormonal etiology of epithelial ovarian cancer, with a hypothesis concerning the role of androgens and progesterone. J Natl Cancer Inst 90:1774–1786, 1998[Abstract/Free Full Text]

33. Levine DA, Boyd J: The androgen receptor and genetic susceptibility to ovarian cancer: Results from a case series. Cancer Res 61:908–911, 2001[Abstract/Free Full Text]

34. Silva EG, Tornos C, Fritsche HA Jr, et al: The induction of benign epithelial neoplasms of the ovaries of guinea pigs by testosterone stimulation: A potential animal model. Mod Pathol 10:879–883, 1997[Medline]

35. Helzlsouer KJ, Alberg AJ, Gordon GB, et al: Serum gonadotropins and steroid hormones and the development of ovarian cancer. JAMA 274:1926–1930, 1995[Abstract]

36. Chadha S, Rao BR, Slotman BJ, et al: An immunohistochemical evaluation of androgen and progesterone receptors in ovarian tumors. Hum Pathol 24:90–95, 1993[CrossRef][Medline]

37. Kuhnel R, de Graaff J, Rao BR, et al: Androgen receptor predominance in human ovarian carcinoma. J Steroid Biochem 26:393–397, 1987[CrossRef][Medline]

38. Slotman BJ, Rao BR: Response to inhibition of androgen action of human ovarian cancer cells in vitro. Cancer Lett 45:213–220, 1989[CrossRef][Medline]

39. Altman DG, Lausen B, Sauerbrei W, et al: Dangers of using "optimal" cutpoints in the evaluation of prognostic factors. J Natl Cancer Inst 86:829–835, 1994[Free Full Text]

40. Zhang Z, Barnhill SD, Zhang H, et al: Combination of multiple serum markers using an artificial neural network to improve specificity in discriminating malignant from benign pelvic masses. Gynecol Oncol 73:56–61, 1999[CrossRef][Medline]

41. Woolas RP, Xu FJ, Jacobs IJ, et al: Elevation of multiple serum markers in patients with stage I ovarian cancer. J Natl Cancer Inst 85:1748–1751, 1993[Abstract/Free Full Text]

42. Khan J, Wei JS, Ringner M, et al: Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 7:673–679, 2001[CrossRef][Medline]

43. de la Cuesta R, Maestro ML, Solana J, et al: Tissue quantification of CA 125 in epithelial ovarian cancer. Int J Biol Markers 14:106–114, 1999[Medline]

Submitted September 23, 2002; accepted May 21, 2003.




This article has been cited by other articles:


Home page
 Mol Cancer ResHome page
C. A. Borgono, I. P. Michael, and E. P. Diamandis
Human Tissue Kallikreins: Physiologic Roles and Applications in Cancer
Mol. Cancer Res., May 1, 2004; 2(5): 257 - 280.
[Abstract] [Full Text] [PDF]

Home page
 JCOHome page
A. Scorilas, C. A. Borgono, N. Harbeck, J. Dorn, B. Schmalfeldt, M. Schmitt, and E. P. Diamandis
Human Kallikrein 13 Protein in Ovarian Cancer Cytosols: A New Favorable Prognostic Marker
J. Clin. Oncol., February 15, 2004; 22(4): 678 - 685.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a colleague
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Save to my personal folders
Right arrow Download to citation manager
Right arrowRights & Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Yousef, G. M.
Right arrow Articles by Diamandis, E. P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yousef, G. M.
Right arrow Articles by Diamandis, E. P.

About
JCO		 Editorial
Roster		 Advertising
Information		 Librarians &
Institutions		 Rights &
Permissions		 PDA Services

Copyright © 2003 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
Terms and Conditions of Use
  HighWire Press HighWire Press™ assists in the publication of JCO Online