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[Cancer Research 63, 2223-2227, May 1, 2003]
© 2003 American Association for Cancer Research


Molecular Biology and Genetics

Parallel Overexpression of Seven Kallikrein Genes in Ovarian Cancer1 ,,2

George M. Yousef, Mary-Ellen Polymeris, George M. Yacoub, Andreas Scorilas, Antoninus Soosaipillai, Cynthia Popalis, Stefano Fracchioli, Dionyssios Katsaros and Eleftherios P. Diamandis3

Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, M5G 1X5 Canada [G. M. Yo., A. So., C. P., E. P. D.]; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada [G. M. Yo., M-E. P., E. P. D.]; Department of Internal Medicine, University of Virginia, Roanoke, VA 24014 [G. M. Ya.]; National Center of Scientific Research "Demokritos," IPC, Athens 153 10, Greece [A. Sc.]; and Department of Obstetrics and Gynecology, Gynecologic Oncology Unit, University of Turin, Turin 10126, Italy [S. F., D. K.]


    ABSTRACT
 Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Recent evidence suggests that many members of the human kallikrein (KLK) gene family are differentially regulated in ovarian cancer and have potential as diagnostic and/or prognostic markers. We used the serial analysis of gene expression and expressed sequence tag databases of the Cancer Genome Anatomy Project to perform in silico analyses of the expression pattern of the 15 human KLK genes in normal and cancerous ovarian tissues and cell lines. We found that seven KLK genes (KLK5, KLK6, KLK7, KLK8, KLK10, KLK11, and KLK14) are up-regulated in ovarian cancer. Probing 2 normal and 10 ovarian cancer serial analysis of gene expression libraries with gene-specific tags for each KLK indicated that whereas no expression was detected in any normal libraries (with the exception of KLK10 and KLK11), these KLKs were found to be expressed with moderate densities (103–408 tags per million) in 40–60% of the ovarian cancer libraries analyzed. These data were verified by screening the expressed sequence tag databases, where 78 of 79 mRNA clones isolated for these genes were from ovarian cancer libraries. X-profiler comparison of the pools of normal and cancerous ovaries identified a significant difference in expression levels for six of the seven KLKs. We experimentally verified the overexpression of six KLK proteins in cancer versus normal or benign tissues with highly sensitive and specific immunofluorometric assays. A statistically significant stepwise increase in protein levels was found among normal, benign, and cancerous ovarian tissues. The expression of five KLKs showed a strong degree of correlation at the protein level, suggesting the existence of a common mechanism or pathway that controls the expression of this group of adjacent genes during ovarian cancer progression.


    INTRODUCTION
 Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The CGAP4 is an international effort implemented by the National Cancer Institute to create a catalogue of the genes associated with cancer and to develop technological tools to support the analysis of the molecular profiles of cancer cells and their normal counterparts (1) . Gene expression data contained in the electronic databases of the CGAP can be used to identify potentially informative marker genes expressed in cancer and to compare cDNA frequencies of genes of interest in normal versus cancer states. The project applies two main approaches, the EST method and the SAGE approach (2) . Various analytical tools have also been developed for data analysis including BLAST, virtual Northern analysis, X-profiler, and digital differential display. These databases have been used successfully in recent years, and results obtained from in silico analysis were experimentally verified in most cases.

Epithelial ovarian cancer continues to be the leading cause of death from gynecological cancers in the United States, accounting for 14,400 deaths/year (3) . Because most patients are asymptomatic until the disease has metastasized, two-thirds are diagnosed in advanced stages, with survival rates of <20%. Currently, the only tumor marker that has a well-defined and validated role in the management of ovarian cancer is CA125 (4) . Serum CA125 has been evaluated for screening for ovarian cancer, differentiation between benign and malignant ovarian masses, and prognosis. This marker does not have a clear place in diagnosis, prognosis, or making treatment decisions, and it lacks specificity (5) . Many potential new serum markers for ovarian cancer have been evaluated, either alone or in combination with CA125, including inhibin, prostasin, OVX1, LASA, CA15.3, and CA72-4 (4) . However, none of them has a clear advantage over CA125 to date. Recently, microarray technology has been used to identify novel potential serum markers for ovarian cancer (6) , and bioinformatic approaches have been successfully used to identify candidate genes for further analysis (7) .

KLKs are a family of 15 genes clustered together on chromosome 19 and belong to the serine protease family of enzymes (8 , 9) . Prostate-specific antigen (PSA, hK3), a member of this family, is the premier tumor marker for prostate cancer (10) . Accumulating evidence suggests a role for KLKs in cancer diagnosis and prognosis (11, 12, 13, 14, 15) .

In this study, we used bioinformatic tools to examine KLK gene expression in normal and cancerous ovarian tissues and cell lines. We found strong evidence that seven KLKs are up-regulated in ovarian cancer. We then experimentally verified the overexpression of six of these KLKs at the protein level in cancer tissues and found a significant correlation between their concentration levels.


    MATERIALS AND METHODS
 Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
VNBs.
The mRNA sequences of the 15 human KLK genes were used to identify unique sequence tags of UniGene clusters for each KLK (for GenBank accession numbers, see Ref. 8 ). Two restriction digestion enzymes (NlaIII and Sau3A) were used as anchoring enzymes. These sequence tags were then used to determine the levels of expression of different KLKs in 2 normal and 10 ovarian cancer libraries (4 from ovarian cancer tissues and 6 from ovarian cancer cell lines). Detailed information for these libraries is available from the web site of the CGAP.5 A list of all libraries used for analysis is submitted as supplementary information.2 Analyses were performed by comparing the proportion of libraries of each type (cancer versus normal) that show expression of each tag, in addition to the average expression densities in these libraries. mRNA sequences from the Human Genome Project were used as reference sequences. If more than one tag of the same gene appears in the same library, we only included the one with the peak level of expression (maximum tpm); the other tags were excluded to avoid inaccurate estimation of expression. Expression levels are displayed as blots with different densities and corrected as tpm to facilitate comparison.

EST Analysis.
The full-length mRNA sequence of each KLK was compared against the human EST databases of the National Center for Biotechnology Information. At the time of the study, these databases included libraries from 9 normal, 3 premalignant, and 17 cancerous tissues. Expression was calculated for each KLK as the number of positive libraries in each tissue type, in addition to the total number of clones detected in each type of library.

X-profiler.
X-profiler analyses of KLK gene expression were performed by comparing normal and cancerous ovarian libraries available in the SAGE databases. Because expression levels of various KLKs might be different from one cell line to another and in different types of ovarian cancer, we compared a pool of normal ovarian libraries (2 normal ovarian epithelial cell lines) against 10 different epithelial ovarian cancer libraries (4 from ovarian cancer tissues and 6 from ovarian cancer cell lines). Ovarian cancer libraries represented different histological types including serous adenocarcinoma and clear cell carcinoma. The X-profiler cutoff value was set at 2-fold difference.

Ovarian Tissue Cytosols.
Human tissue extracts were prepared from 10 histologically confirmed normal ovarian tissues, 10 benign ovarian tumors, and 20 cancerous ovarian tissues. Tissue extraction was as follows: frozen human tissues (0.2 g) were pulverized on dry ice to fine powders. Two ml of extraction buffer [50 mM Tris-HCl buffer (pH 8.0) containing 150 mM NaCl, 5 mM EDTA, and 1% NP40 surfactant] were added to the tissue powders, and the mixture was incubated on ice for 30 min with repeated shaking and vortex mixing every 10 min. Mixtures were centrifuged at 14,000 x g at 4°C for 30 min. The supernatants representing the tissue extracts were collected and stored at -80°C until use. Our procedures have been approved by the Institutional Review Board of Mount Sinai Hospital.

Immunofluorometric Assays.
KLK protein levels were measured by ELISA-type time-resolved immunofluorometric assays developed in our laboratory. These sandwich-type immunoassays use monoclonal and polyclonal antibodies developed against recombinant proteins. All assays were shown to be specific, with no cross-reactivity from other KLKs (12 , 16 , 17) . The protein level of each KLK was normalized according to the total protein content of each sample and expressed as ng KLK/mg total protein.

Statistical Analysis.
Correlation analyses were performed using Spearman correlation coefficient. The analysis of differences between the variables in the three groups was performed with the Kruskal-Wallis test.


    RESULTS
 Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
First, to verify the reliability and sensitivity of the bioinformatic analysis, we compared the in silico pattern of expression of each KLK in normal tissues to the previously published experimental data on tissue KLK expression (8) . Results obtained were concordant with the published data. For example, most EST and SAGE clones for KLK2, KLK3, and KLK4 were found in the prostate, whereas KLK5 was highly expressed in normal breast tissue and skin (data not shown). Also, for those KLKs that show differential expression in ovarian cancer (see below), levels of expression were about the same between normal and cancer tissues for other malignancies, further verifying the accuracy of our results.

Of the 15 KLK genes analyzed in this study, 7 genes (KLK5-8, KLK10, KLK11, and KLK14) were found to be up-regulated in ovarian cancer tissues and cell lines, compared with normal ovary. Probing all ovarian libraries from different sources (cancerous and normal from tissues and cell lines) with KLK5-specific sequences revealed that KLK5 is not detectable in normal ovary as determined by SAGE analysis (Table 1)Citation and EST library screening (Table 2)Citation . These data are consistent with previous experimental reports showing no expression of KLK5 in normal ovary (18) . However, VNB analysis showed that KLK5 is expressed in 5 of 10 ovarian cancer libraries with an average blot density of 177 tpm (Table 1)Citation . These data were further verified by screening the EST databases using the BLAST search engine; KLK5 was expressed in 5 of 17 ovarian cancer EST libraries, whereas 16 KLK5 mRNA clones were isolated, compared with no clones in libraries from normal or premalignant lesions (Table 2)Citation . X-profiler analysis showed a significant difference when comparing KLK5 gene expression between normal and malignant pools of ovarian libraries (Table 3)Citation .


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Table 1 In silico analysis of KLK gene expression in normal and ovarian cancer tissues using the SAGE databases

 

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Table 2 In silico analysis of KLK gene expression in libraries from normal, premalignant, and ovarian cancer tissues as determined by EST database

 

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Table 3 X-profiler analysis of KLK gene expression in normal versus cancerous ovarian tissues and cell lines

 
KLK6 was originally cloned as a gene that is highly expressed in ovarian cancer but not in normal ovaries (19) . This finding was later confirmed by analyzing KLK6 expression patterns in normal tissues by PCR (20) and by immunohistochemistry (21) . In silico analysis in the current study showed that whereas KLK6 was not detectable by VNB in normal ovary, it was detected in 5 of 10 ovarian cancer SAGE libraries with a relatively high blot density (262 tpm; Table 1Citation ). In addition, 21 ovarian cancer EST clones were detected, compared with no clones for normal or premalignant ovarian tissues and cell lines (Table 2)Citation . X-profiler analysis further indicated a significant difference of KLK6 expression (expression factor, 0.953) when comparing normal and malignant pools of ovarian libraries (Table 3)Citation .

KLK8 was also found to be expressed at a fairly decent density (average, 192 tpm) in 6 of 10 ovarian cancer libraries but not in libraries from normal ovaries. Analysis of the EST database also showed no expression in any of the nine normal ovarian libraries screened, whereas five KLK8 EST clones were detected in four ovarian cancer libraries (Table 2)Citation . This was further confirmed by X-profiler analysis (Table 3)Citation . A similar overexpression pattern was observed for KLK10, as shown in Tables 1Citation 2Citation 3Citation .

Weak KLK11 expression was detected by SAGE analysis in normal ovarian libraries. However, expression density was about 20-fold higher in ovarian cancer tissues and cell lines (20 versus 408 tpm for normal and cancer, respectively; Table 1Citation ). In addition, all ESTs detected for this gene were from cancer libraries, not normal libraries (Table 2)Citation . This was also confirmed by X-profiler analysis (Table 3)Citation . Whereas no KLK14 clones were detected in normal SAGE or EST libraries, mRNA tags were found in 6 out of 10 cancer libraries by VNB with an average density of 192 tpm, and 5 EST clones from an ovarian cancer library (Tables 1Citation and 2)Citation .

No other KLKs were found to be differentially expressed in ovarian cancer by these methods. For instance, KLK3 was found to be expressed in 1 of 2 normal ovarian libraries compared with 3 out of 10 ovarian cancer libraries, with an average density of 41 tpm in normal compared with 45 tpm in cancer (data not shown).

Overexpression of KLK Proteins in Ovarian Cancer.
To verify the in silico mRNA overexpression results and to examine whether these mRNA up-regulations reflect enzyme changes at the protein level, we compared protein expression levels of six up-regulated KLKs in normal, benign, and cancerous ovarian tissues (KLK14 could not be examined due to lack of an ELISA assay for this KLK). As shown in Fig. 1Citation and Table 4Citation , there is a stepwise increase in the expression levels of these KLKs among normal, benign, and malignant tissues. These differences were statistically significant by the Kruskal-Wallis test for hK11 (P < 0.001), hK5 (P = 0.048), hK6 (P = 0.044), and hK10 (P = 0.027) but not for hK7 and hK8 (P > 0.05; Fig. 1Citation ). When comparing normal and cancer tissues, the median levels of expression increased between 2-fold (hK5) to ~80-fold (hK11; Table 4Citation ).



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Fig. 1. KLK protein expression in normal (N = 10), benign (N = 10), and cancerous (N = 20) ovarian tissues. KLK levels are expressed in ng/mg total protein. Ps were calculated by Kruskal-Wallis test. For discussion, see Results.

 

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Table 4 Descriptive statistics of protein levels of six KLKs in ovarian tissue extracts

All values are in ng kallikrein/mg total protein.

 
By Spearman correlation, moderate to strong correlations were observed between the expression levels of five of these KLKs (hK5, hK6, hK7, hK8, and hK10), and the results were highly statistically significant (rs = 0.45–0.74 and P < 0.001; Table 5Citation ). hK11 appears to follow a different expression pattern and does not correlate well with any of the other proteins (Table 5)Citation .


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Table 5 Correlations between protein levels of six KLKs in ovarian tissue extractsa

 

    DISCUSSION
 Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Our results show that 7 of the 15 human KLKs are up-regulated in ovarian cancer. The differential expression of certain KLKs in ovarian cancer has been documented previously (11 , 22 , 23) . KLK4 has prognostic value in ovarian cancer patients (13 , 24) , and KLK5 overexpression is an indicator of poor prognosis (25) . We have also shown recently that hK6 (15) , hK10 (26 , 27) , and hK11 (12) are useful serological diagnostic markers for ovarian cancer because their serum levels are higher than normal in >50% of ovarian cancer patients. KLK6 was reported to be overexpressed in ovarian cancer, and it has been suggested to play a role in cancer invasion (19 , 28) . KLK7 and KLK8 were also reported to be overexpressed in ovarian cancer patients compared with normal subjects (14 , 28 , 29) . Also, KLK9 was shown to have prognostic value in ovarian cancer (30) .

It has been reported previously that four of the most centromeric KLKs (KLK2, KLK3, KLK4, and KLK15) are differentially expressed in prostate cancer and are androgen-regulated (8 , 31) . Here we provide strong evidence that many members of the telomeric cluster of adjacent KLKs (KLK5-14) are overexpressed in ovarian cancer. This points out the possibility for the presence of a locus control region or another common regulatory mechanism for these KLKs. Because many of these genes are regulated by steroid hormones, especially estrogens (8) , it will be interesting to investigate whether their up-regulation in cancer is a result of a hormonal derangement.

We used two independent databases (EST and SAGE) to generate our results. We calculated the proportion of positive libraries from each tissue type, in addition to the density of expression. We did not attempt to quantify KLK gene expression from the EST databases because many EST libraries are normalized or subtracted, which could bias the results. It is further emphasized that in silico analysis data should always be experimentally confirmed. Possible sources of bias include sequence errors, presence of mutations associated with certain malignancies, unequal presentation of cDNAs in different libraries, and expression of splice variants in certain malignancies.

Lercher et al. (32) , during global analysis of >11,000 genes in 14 different tissues, selected a cutoff value for gene expression as being low (<=37 tpm) and intermediate or high (>=134 tpm). If this cutoff is applied to our data, we could conclude that whereas KLK gene expression is absent or low in normal ovarian tissues, medium to high levels of expression of 6 of the 15 KLKs are seen in ovarian cancer.

Dong et al. (13) and Obiezu et al. (24) previously reported higher levels of expression of KLK4 in ovarian cancer compared with normal ovarian tissues. In this study, no detectable expression of KLK4 was found in any normal or cancerous tissue, as determined by SAGE or EST analysis. This might reflect the fact that KLK4 is expressed in the ovaries at very low amounts, so that the mRNA is not detectable, except by using a highly sensitive technique such as reverse transcription-PCR.

Our current results, indicating KLK overexpression at the protein level in ovarian cancer, are in accord with previous observations of serum levels of a few of these KLKs in ovarian cancer. We have previously shown that serum levels of hK6 (15) , hK10 (27) , and hK11 (12) are elevated in ovarian cancer patients. Similar data have been generated for hK5, hK7, and hK8.6

Several hypotheses can be proposed regarding the possible involvement of KLKs in ovarian cancer. Being serine proteases, they could be implicated in tumor progression through extracellular matrix degradation. Previous studies have shown that serine protease overexpression is associated with unfavorable clinical prognosis of various forms of cancer (33) . Ovarian cancer is a "hormonal" malignancy. KLKs, being under steroid hormone regulation (8) , may represent downstream targets through which hormones affect the initiation or progression of ovarian cancer. The statistically significant positive correlations between expression levels five of six of these KLKs (Table 5)Citation and the parallel overexpression, as well as data presented elsewhere (22) , are supportive of an emerging idea that a number of these enzymes are part of a cascade enzymatic pathway. Direct evidence is currently lacking.

In conclusion, here we provide strong evidence suggesting that seven KLKs are up-regulated in ovarian cancer. These data were confirmed by examining several databases, in addition to protein analysis of KLKs in tissue cytosols. Further experimentation is necessary to establish the usefulness of these KLKs for diagnosis, prognosis, and treatment of ovarian cancer.


    FOOTNOTES
 
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.

1 Supported by grants from the National Cancer Institute of Canada, the United States National Cancer Institute, and the Early Detection Research Network of the United States National Cancer Institute. Back

2 Supplementary data for this article are available at Cancer Research Online (cancerres.aacrjournals.org). Back

3 To whom requests for reprints should be addressed, at Mount Sinai Hospital, Department of Pathology and Laboratory Medicine, 600 University Avenue, Toronto, Ontario M5G 1X5, Canada. Phone: (416) 586-8443; Fax: (416) 586-8628; E-mail: ediamandis{at}mtsinai.on.ca Back

4 The abbreviations used are: CGAP, Cancer Genome Anatomy Project; SAGE, serial analysis of gene expression; EST, expressed sequence tag; VNB, virtual Northern blot; tpm, tags per million; KLK, kallikrein; hK, human kallikrein protein. Back

5 http://www.ncbi.nlm.nih.gov/ncicgap/. Back

6 E. P. Diamandis and G. M. Yousef, unpublished observations. Back

Received 9/30/02. Accepted 3/ 5/03.


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 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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A. Psyrri, P. Kountourakis, A. Scorilas, S. Markakis, R. Camp, D. Kowalski, E. P. Diamandis, and M. A. Dimopoulos
Human tissue kallikrein 7, a novel biomarker for advanced ovarian carcinoma using a novel in situ quantitative method of protein expression
Ann. Onc., July 1, 2008; 19(7): 1271 - 1277.
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Clin. Cancer Res.Home page
C. Planque, L. Li, Y. Zheng, A. Soosaipillai, K. Reckamp, D. Chia, E. P. Diamandis, and L. Goodglick
A Multiparametric Serum Kallikrein Panel for Diagnosis of Non-Small Cell Lung Carcinoma
Clin. Cancer Res., March 1, 2008; 14(5): 1355 - 1362.
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Clin. Cancer Res.Home page
Y. Zheng, D. Katsaros, S. J.C. Shan, I. R. de la Longrais, M. Porpiglia, A. Scorilas, N. W. Kim, R. L. Wolfert, I. Simon, L. Li, et al.
A Multiparametric Panel for Ovarian Cancer Diagnosis, Prognosis, and Response to Chemotherapy
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Clin. Cancer Res.Home page
J. Dorn, M. Schmitt, R. Kates, B. Schmalfeldt, M. Kiechle, A. Scorilas, E. P. Diamandis, and N. Harbeck
Primary Tumor Levels of Human Tissue Kallikreins Affect Surgical Success and Survival in Ovarian Cancer Patients
Clin. Cancer Res., March 15, 2007; 13(6): 1742 - 1748.
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Clin. Chem.Home page
S. J. C. Shan, A. Scorilas, D. Katsaros, I. Rigault de la Longrais, M. Massobrio, and E. P. Diamandis
Unfavorable Prognostic Value of Human Kallikrein 7 Quantified by ELISA in Ovarian Cancer Cytosols
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J. Biol. Chem.Home page
I. P. Michael, G. Pampalakis, S. D. Mikolajczyk, J. Malm, G. Sotiropoulou, and E. P. Diamandis
Human Tissue Kallikrein 5 Is a Member of a Proteolytic Cascade Pathway Involved in Seminal Clot Liquefaction and Potentially in Prostate Cancer Progression
J. Biol. Chem., May 5, 2006; 281(18): 12743 - 12750.
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Clin. Cancer Res.Home page
C. A. Borgono, T. Kishi, A. Scorilas, N. Harbeck, J. Dorn, B. Schmalfeldt, M. Schmitt, and E. P. Diamandis
Human Kallikrein 8 Protein Is a Favorable Prognostic Marker in Ovarian Cancer
Clin. Cancer Res., March 1, 2006; 12(5): 1487 - 1493.
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Clin. Chem.Home page
I. P. Michael, L. Kurlender, N. Memari, G. M. Yousef, D. Du, L. Grass, C. Stephan, K. Jung, and E. P. Diamandis
Intron Retention: A Common Splicing Event within the Human Kallikrein Gene Family
Clin. Chem., March 1, 2005; 51(3): 506 - 515.
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Clin. Cancer Res.Home page
E. P. Diamandis and D.-E. van der Merwe
Plasma Protein Profiling by Mass Spectrometry for Cancer Diagnosis: Opportunities and Limitations
Clin. Cancer Res., February 1, 2005; 11(3): 963 - 965.
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Cancer Res.Home page
L. E. Graves, E. V. Ariztia, J. R. Navari, H. J. Matzel, M. S. Stack, and D. A. Fishman
Proinvasive Properties of Ovarian Cancer Ascites-Derived Membrane Vesicles
Cancer Res., October 1, 2004; 64(19): 7045 - 7049.
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Z. Zhang, R. C. Bast Jr., Y. Yu, J. Li, L. J. Sokoll, A. J. Rai, J. M. Rosenzweig, B. Cameron, Y. Y. Wang, X.-Y. Meng, et al.
Three Biomarkers Identified from Serum Proteomic Analysis for the Detection of Early Stage Ovarian Cancer
Cancer Res., August 15, 2004; 64(16): 5882 - 5890.
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E. P. Diamandis
How Are We Going to Discover New Cancer Biomarkers? A Proteomic Approach for Bladder Cancer
Clin. Chem., May 1, 2004; 50(5): 793 - 795.
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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]


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Mol. Cell. ProteomicsHome page
E. P. Diamandis
Mass Spectrometry as a Diagnostic and a Cancer Biomarker Discovery Tool: Opportunities and Potential Limitations
Mol. Cell. Proteomics, April 1, 2004; 3(4): 367 - 378.
[Abstract] [Full Text] [PDF]


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Proc. Natl. Acad. Sci. USAHome page
K. R. Kozak, M. W. Amneus, S. M. Pusey, F. Su, M. N. Luong, S. A. Luong, S. T. Reddy, and R. Farias-Eisner
Identification of biomarkers for ovarian cancer using strong anion-exchange ProteinChips: Potential use in diagnosis and prognosis
PNAS, October 14, 2003; 100(21): 12343 - 12348.
[Abstract] [Full Text] [PDF]


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