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Frauenklinik Und Poliklinik Der Technischen Universität München Klinikum Rechts Der Isar (Direktorin: Univ.-Prof

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Frauenklinik Und Poliklinik Der Technischen Universität München Klinikum Rechts Der Isar (Direktorin: Univ.-Prof Frauenklinik und Poliklinik der Technischen Universität München Klinikum rechts der Isar (Direktorin: Univ.-Prof. Dr. M. B. Kiechle) Human tissue kallikreins, uPA and PAI-1 as prognostic markers in ovarian carcinoma Julia Dorn Vollständiger Abdruck der von der Fakultät für Medizin der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Medizin genehmigten Dissertation Vorsitzendes: Univ.-Prof. Dr. D. Neumeier Prüfer der Dissertation: 1. Univ.-Prof. Dr. M. Schmitt 2. Univ.-Prof. Dr. B. Schmalfeldt 2. Univ.-Prof. Dr. F. Fendt Die Dissertation wurde am 28.06.2006 bei der Technischen Universität München eingereicht und durch die Fakultät für Medizin am 13.12.2006 angenommen. Meiner Familie Julia Dorn: Human tissue kallikreins, uPA and PAI-1 as prognostic markers in ovarian carcinoma; page 1 1. INTRODUCTION .................................................................................................................3 1.1 Ovarian cancer, prognostic and predictive factors..................................................3 1.2 Tumor biological markers in ovarian cancer ............................................................6 1.2.1 CA125 ....................................................................................................................6 1.2.2 Serine proteases ....................................................................................................7 1.2.3 Urokinase-type plasminogen activator system.......................................................8 1.2.4 Tissue kallikrein family .........................................................................................10 2. AIM OF THE STUDY.........................................................................................................21 3. MATERIALS AND METHODS ..........................................................................................22 3.1 Patients.......................................................................................................................22 3.2 Tissue collection and extraction..............................................................................22 3.3 ELISA (Enzyme-linked immunosorbent assay)-analysis.......................................22 3.4 Statistical methods....................................................................................................25 4. RESULTS..........................................................................................................................28 4.1 Patient cohort ............................................................................................................28 4.2 Antigen levels of the proteolytic factors in primary tumor extracts of ovarian cancer patients FIGO I-IV .....................................................................................30 4.3 Stratification of antigen levels of the proteolytic factors in primary tumor extracts of ovarian cancer patients by nuclear grading ...................................33 4.4 Association of clinical parameters within the patient collective ..........................34 4.5 Assessment of correlation between proteolytic factors uPA, PAI-1, and tissue kallikreins hK5, hK6, h7, hK8, hK10, hK11, hK13 ..............................................36 4.6 Cox uni- and multivariate proportional hazard regression analysis of clinical, histomorphological, and proteolytic factors´ influence on overall (OS) and progression-free survival (PFS) ..........................................................................39 4.7 Antigen levels in primary tumors compared with omentum metastases – impact on survival.............................................................................................................45 4.8 Validation of previously described optimized cut-offs ..........................................52 5. DISCUSSION ....................................................................................................................53 5.1 Distribution and correlation .....................................................................................54 5.2 Outcome prediction...................................................................................................55 5.3 Predictors of optimal tumor debulking ...................................................................56 5.4 Impact of antigen content in primary tumor and omentum metastasis ...............58 Julia Dorn: Human tissue kallikreins, uPA and PAI-1 as prognostic markers in ovarian carcinoma; page 2 5.5 Optimized cutoffs proteolytic factors......................................................................59 5.6 Conclusions and outlook..........................................................................................59 6. ABSTRACT.......................................................................................................................61 7. APPENDIX ........................................................................................................................63 7.1 TNM and FIGO staging system for ovarian cancer ................................................63 7.2 Classification of nuclear grading of ovarian tumors .............................................63 7.3 Official and alternative kallikrein gene and protein names ...................................64 7.4 Abbreviations.............................................................................................................65 7.5 References .................................................................................................................66 7.6 Publication list ...........................................................................................................87 7.7 Acknowledgment.......................................................................................................89 Julia Dorn: Human tissue kallikreins, uPA and PAI-1 as prognostic markers in ovarian carcinoma; page 3 1. Introduction 1.1 Ovarian cancer, prognostic and predictive factors Every year, almost 7,500 women are newly diagnosed with ovarian cancer in Germany and as a result up to 6,000 of these patients die of the malignant disease per year. Epithelial ovarian carcinoma (ovarian cancer) is the third most common neoplasm of the female reproductive tract, but the leading cause of death from a gynecological malignancy (73; 187). Early ovarian cancer detection could potentially decrease mortality, still, the tumor commonly shows no obvious, often only unspecific, signs or symptoms such as general abdominal discomfort or pain, bowel irregularity, loss of appetite, weight gain or loss or persisting fatigue until late in its development (175). Moreover, current ovarian cancer screening methods are limited as sensitivity and specificity of such methods are not high enough. Given the low prevalence of epithelial ovarian cancer (40 per 100,000 women > 50 years) (205), a clinically acceptable positive predictive value of 10 % could only be acquainted with a specificity of >99 % and a sensitivity of > 67 % (73). Therefore, one goal is to tailor the therapeutic regimen for each of the patients afflicted with ovarian cancer based on the tumor´s unique molecular signature by finding reliable prognostic and/or predictive factors so that the patients that are at risk can be directed to clinical trials or more effective ways of treatment. Established clinical prognostic factors in ovarian carcinoma are: • Staging of the disease at time of diagnosis • Retroperitoneal nodal status • Residual tumor mass after primary surgery • Histomorphology and cellular differentiation (nuclear grading) of the tumor • Ascitic fluid volume • Clinical circumstances such as age, anemia, and performance status According to the guidelines of the International Federation of Gynecology and Obstetrics, FIGO (see Appendix), staging of the disease at time of diagnosis represents the major prognostic factor in ovarian cancer (23). FIGO stage I patients have a 5-year survival of 80- 90 % compared to only 15-20 % for women with advanced disease stage III or IV. Unfortunately, 65 % of all patients are diagnosed in advanced FIGO stage III or IV (193). Appropriate intra-operative staging is vitally important for effective post-operative therapy decision-making. According to recommendations of the German national treatment guidelines (AGO, Arbeitsgemeinschaft gynäkologischer Onkologen), a staging laparotomy should be executed by longitudinal abdominal section with bilateral adnectomy, hysterectomy, infragastric omentectomy, radical paraaortic and pelvic lymphadenectomy, and appendectomy. Furthermore, multiple cytological washings and random biopsies of the Julia Dorn: Human tissue kallikreins, uPA and PAI-1 as prognostic markers in ovarian carcinoma; page 4 peritoneum, the diaphragm, and of suspect regions is required (158; 164). Assessment of the nodal status, i.e. lymphogenic metastasis of the iliac, sacral, paraaortal, and inguinal area is of prognostic value. To assess the nodal status adequately, at least 10 lymph nodes have to be removed and analyzed histologically (50). A systematic removal of all pelvic and paraaortal lymph nodes does not prove to be of therapeutic use, but nevertheless, a radical pelvic and paraaortal lymphadenectomy is recommended if intraabdominal tumor-free status can be achieved, as nodal status is often positive in advanced ovarian carcinoma (120). Radical surgery and platinum-based chemotherapy are cornerstones for treatment of ovarian carcinoma. As the amount of postoperative residual
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