Ovarian carcinoma has the highest mortality rate among gynaecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300-gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p = 0.0087). In a second validation step, the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p = 0.0063). In multivariate analysis, the OPI was independent of the post-operative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8-23.5, p = 0.0049) and 1.9 (Duke cohort, CI 1.2-3.0, p = 0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimized assessment of the prognosis of platinum-taxol-treated ovarian cancer. As traditional treatment options are limited, this analysis may be able to optimize clinical management and to identify those patients who would be candidates for new therapeutic strategies.

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Neuroendocrine breast carcinomas are rare but may represent either metastatic or primary lesions. So far, clinical and preoperative histopathological examinations do not distinguish properly between a primary or metastatic breast tumor. Due to any possible consequences following an appropriate treatment, markers which may be helpful for such a distinguishment are needed. We addressed this study in order to evaluate the immunohistochemical expression of GCDFP-15 and mammaglobin in a subset of pure neuroendocrine breast carcinomas (n = 9) and compared the expression profile with a cohort of non-mammary neuroendocrine tumors (n = 99). We observed in our study that solid neuroendocrine breast carcinomas are characterized by the expression of estrogen and progesterone receptors as well as GCDFP-15 and/or mammaglobin. GCDFP-15 was expressed in 6 out of 9 cases, mammaglobin was positive in 4 out of 9 tumors. In contrast, neuroendocrine tumors of the non-mammary cohort expressed neither GCDFP-15 nor mammaglobin. We conclude that mammaglobin and GCDFP-15 as markers of epithelial breast origin may work as a new and reliable diagnostic tool to distinguish primary endocrine tumors of the breast from a metastatic neuroendocrine disease. This is of utmost importance, especially for surgical management.

The insulin-like growth factor-II mRNA-binding protein IMP3 plays an important role in embryogenesis and recent reports suggest an involvement in tumorigenesis. Although IMP3 expression has been well studied in mouse and human fetal and adult gonads, its role in ovarian cancer is unknown. We investigated the expression of IMP3 at protein and mRNA levels in a cohort of primary ovarian carcinomas and in 11 ovarian cancer cell lines. Western blot analysis revealed an expression of IMP3 in all ovarian cancer cell lines and immunohistochemistry demonstrated a positive cytoplasmic staining in 32 of 68 carcinomas (47%). In contrast, epithelium of borderline tumors, as well as, benign ovarian lesions and normal ovaries exhibited only weak or no IMP3 expression. In univariate Kaplan-Meier analysis, IMP3 protein expression was significantly associated with better overall survival (P=0.048). To confirm these findings, we further determined IMP3 mRNA expression in 43 ovarian cancer specimens by real time quantitative reverse transcription-polymerase chain reaction. A significant correlation between protein and mRNA levels (r=0.414, P=0.006), as well as a correlation of IMP3 mRNA expression with patient overall survival (P=0.044), was observed. Our results demonstrate that IMP3 is expressed in a subpopulation of ovarian cancer and a marker of good prognosis.