Epithelial ovarian cancer is typically diagnosed at an advanced stage. Current state-of-the-art surgery and chemotherapy result in the high incidence of complete remissions; however, the recurrence rate is also high. For most patients, the disease eventually becomes a continuum of symptom-free periods and recurrence episodes. Different targeted treatment approaches and biological drugs, currently under development, bring the promise of turning ovarian cancer into a manageable chronic disease. In this review, we discuss the current standard in the therapy for ovarian cancer, major recent studies on the new variants of conventional therapies, and new therapeutic approaches, recently approved and/or in clinical trials. The latter include anti-angiogenic therapies, polyADP-ribose polymerase (PARP) inhibitors, inhibitors of growth factor signaling, or folate receptor inhibitors, as well as several immunotherapeutic approaches. We also discuss cost-effectiveness of some novel therapies and the issue of better selection of patients for personalized treatment.

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients treatment; however, the results of such studies are poorly reproducible, and critical analyses of these methods are rare. In this study we examined gene expression in 97 ovarian cancer samples. Validation of results by quantitative RT-PCR was performed also on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients prognosis. Histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints (tumor response to chemotherapy, overall survival, disease-free survival, DFS) brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found as important for DFS in the independent group, while in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worth of further testing. Our results confirm that histological tumor type is a strong confounding factor and gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Relatively small and unequal patients groups, may be a reason of poor reproducibility of statistical results, as well as the fact that the patients were treated with different chemotherapies. In addition, clinical endpoints may depend on subtle changes in many alternative molecular pathways, and this may be difficult to demonstrate by the methods applied. Also, arbitrarily performed division of samples may not reflect their true biological diversity

Ovarian cancer is the most frequent cause of deaths from among gynecologic malignancies. Due to its asymptomatic development the disease is frequently diagnosed at an advanced, incurable stages. Although ovarian cancers usually respond well to the first line chemotherapy based on platinum compounds and taxanes, majority of patients develop recurrence and chemo-resistance. Despite many years of studies there is still lack of reliable diagnostic markers as well as other diagnostic methods enabling early detection and suitable for screening. Thus, current studies are aimed on finding new biomarkers with diagnostic, prognostic and predictive potential as well as on the search for the new therapeutic targets. Interestingly, an understanding of ovarian cancer etiology has changed fundamentally within recent years. The classical theory, claiming that ovarian cancers originate from ovarian surface epithelial cells, was undermined. Currently, there is a lot of evidence that majority of serous ovarian cancers have its origin in malignant tubal epithelium, while endometrioid and clear cell ovarian cancers develop most likely from endometriosis. These new findings will have an impact on diagnostic approaches as well as on the prevention options for women with genetic predisposition to ovarian cancer. The new knowledge about an origin of different histological types of ovarian cancer may open new pathways in basic research and clinical studies. In this paper we report current knowledge about ovarian cancer risk factors, we also present the arguments for extraovarian origin of the majority of ovarian cancers and stress the mechanisms of action of new drugs for targeted therapies that show most promising results in the current clinical trials.

Previously, based on a DNA microarray experiment, we identified a 96-gene prognostic signature associated with the shorter survival of ovarian cancer patients. We hypothesized that some differentially expressed protein-coding genes from this signature could potentially serve as prognostic markers. The present study was aimed to validate two proteins, namely fibronectin (FN1) and periostin (POSTN), in the independent set of ovarian cancer samples. Both proteins are mainly known as extracellular matrix proteins with many important functions in physiology. However, there are also indications that they are implicated in cancer, including ovarian cancer. The expression of these proteins was immunohistochemically analyzed in 108 surgical samples of advanced ovarian cancer (majority: high-grade serous) and additionally on tissue arrays representing different stages of the progression of ovarian and fallopian tube epithelial tumors, from normal epithelia, through benign tumors, to adenocarcinomas of different stages. The correlation with clinical, pathological, and molecular features was evaluated. Kaplan–Meier survival analysis and Cox-proportional hazards models were used to estimate the correlation of the expression levels these proteins with survival. We observed that the higher expression of fibronectin in the tumor stroma was highly associated with shorter overall survival (OS) (Kaplan–Meier analysis, log-rank test p = 0.003). Periostin was also associated with shorter OS (p = 0.04). When we analyzed the combined score, calculated by adding together individual scores for stromal fibronectin and periostin expression, Cox regression demonstrated that this joint FN1&POSTN score was an independent prognostic factor for OS (HR = 2.16; 95% CI: 1.02–4.60; p = 0.044). The expression of fibronectin and periostin was also associated with the source of ovarian tumor sample: metastases showed higher expression of these proteins than primary tumor samples (χ² test, p = 0.024 and p = 0.032). Elevated expression of fibronectin and periostin was also more common in fallopian cancers than in ovarian cancers. Our results support some previous observations that fibronectin and periostin have a prognostic significance in ovarian cancer. In addition, we propose the joint FN1&POSTN score as an independent prognostic factor for OS. Based on our results, it may also be speculated that these proteins are related to tumor progression and/or may indicate fallopian–epithelial origin of the tumor.

Purpose Ovarian cancer is typically diagnosed at late stages, and thus, patients’ prognosis is poor. Improvement in treatment outcomes depends, at least partly, on better understanding of ovarian cancer biology and finding new molecular markers and therapeutic targets. Methods An unsupervised method of data analysis, singular value decomposition, was applied to analyze microarray data from 101 ovarian cancer samples; then, selected genes were validated by quantitative PCR. Results We found that the major factor influencing gene expression in ovarian cancer was tumor histological type. The next major source of variability was traced to a set of genes mainly associated with extracellular matrix, cell motility, adhesion, and immunological response. Hierarchical clustering based on the expression of these genes revealed two clusters of ovarian cancers with different molecular profiles and distinct overall survival (OS). Patients with higher expression of these genes had shorter OS than those with lower expression. The two clusters did not derive from high- versus low-grade serous carcinomas and were unrelated to histological (ovarian vs. fallopian) origin. Interestingly, there was considerable overlap between identified prognostic signature and a recently described invasion-associated signature related to stromal desmoplastic reaction. Several genes from this signature were validated by quantitative PCR; two of them—DSPG3 and LOX—were validated both in the initial and independent sets of samples and were significantly associated with OS and disease-free survival. Conclusions We distinguished two molecular subgroups of serous ovarian cancers characterized by distinct OS. Among differentially expressed genes, some may potentially be used as prognostic markers. In our opinion, unsupervised methods of microarray data analysis are more effective than supervised methods in identifying intrinsic, biologically sound sources of variability. Moreover, as histological type of the tumor is the greatest source of variability in ovarian cancer and may interfere with analyses of other features, it seems reasonable to use histologically homogeneous groups of tumors in microarray experiments.