Search

Background: Ovarian cancer has a poor prognosis due to advanced stage at presentation and either intrinsic or acquired resistance to classic cytotoxic drugs such as platinum and taxoids. Recent large clinical trials with different combinations and sequences of classic cytotoxic drugs indicate that further significant improvement in prognosis by this type of drugs is not to be expected. Currently a large number of drugs, targeting dysregulated molecular pathways in cancer cells have been developed and are introduced in the clinic. A major challenge is to identify those patients who will benefit from drugs targeting these specific dysregulated pathways.The aims of our study were (1) to develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, (2) to assess the association of pathways and transcription factors with overall survival, and (3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers.Methods and Findings: According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using approximately 35,000 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available dataset of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent dataset to assess the similarities with results from our own dataset. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 versus 41 mo, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that composed the overall survival profile were also able to discriminate between the two risk groups in the independent dataset. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival, of which 16 and 12, respectively, were confirmed in the independent dataset.Conclusions: Our study provides new clues to genes, pathways, and transcription factors that contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies. [ABSTRACT FROM AUTHOR]

Purpose A relationship between mean heart dose (MHD) and acute coronary event (ACE) rate was reported in a study of patients with breast cancer (BC). The main objective of our cohort study was to validate this relationship and investigate if other dose-distribution parameters are better predictors for ACEs than MHD. Patients and Methods The cohort consisted of 910 consecutive female patients with BC treated with radiotherapy (RT) after breast-conserving surgery. The primary end point was cumulative incidence of ACEs within 9 years of follow-up. Both MHD and various dose-distribution parameters of the cardiac substructures were collected from three-dimensional computed tomography planning data. Results The median MHD was 2.37 Gy (range, 0.51 to 15.25 Gy). The median follow-up time was 7.6 years (range, 0.1 to 10.1 years), during which 30 patients experienced an ACE. The cumulative incidence of ACE increased by 16.5% per Gy (95% CI, 0.6 to 35.0; P = .042). Analysis showed that the volume of the left ventricle receiving 5 Gy (LV-V5) was the most important prognostic dose-volume parameter. The most optimal multivariable normal tissue complication probability model for ACEs consisted of LV-V5, age, and weighted ACE risk score per patient (c-statistic, 0.83; 95% CI, 0.75 to 0.91). Conclusion A significant dose-effect relationship was found for ACEs within 9 years after RT. Using MHD, the relative increase per Gy was similar to that reported in the previous study. In addition, LV-V5 seemed to be a better predictor for ACEs than MHD. This study confirms the importance of reducing exposure of the heart to radiation to avoid excess risk of ACEs after radiotherapy for BC.

Background and Purpose: To develop a multivariable prediction model for the risk of grade⩾2 fibrosis in the boost area after breast conserving surgery (BCS) followed by three-dimensional conformal radiotherapy (RT) with a simultaneous integrated photon boost (3D-CRT-SIB), five years after RT., Material and Methods: This prospective cohort study included 1,030 patients treated with RT for breast cancer (stage 0-III), after BCS. Data regarding physician-rated fibrosis and dose-volume parameters were available in 546 patients. A multivariable logistic regression model for grade⩾2 fibrosis was generated., Results: At 5years, grade⩾2 fibrosis was observed in 13.4% of the patients. The multivariable analysis resulted in a prediction model for grade⩾2 fibrosis in the boost area including three independent variables: patient age, breast volume receiving⩾55Gy (V55 CTV breast) and the maximum radiation dose in the breast (D max )., Conclusions: A multivariable prediction model was developed including age, V55 CTV breast and D max for grade⩾2 fibrosis in the boost area after breast cancer RT using a 3D-CRT-SIB technique. This model can be used to estimate the risk of fibrosis and to optimize dose distributions aiming at reducing this risk., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Ovarian cancer ranks the most lethal among gynecologic neoplasms in women. To develop potential biomarkers for diagnosis, we have identified five novel genes (CYP39A1, GTF2A1, FOXD4L4, EBP, and HAAO) that are hypermethylated in ovarian tumors, compared with the non-malignant normal ovarian surface epithelia, using the quantitative methylation-specific polymerase chain reactions. Interestingly enough, multivariate Cox regression analysis has identified hypermethylation of CYP39A1 correlated with an increase rate of relapsing (P=0.032, hazard ratio >1). Concordant hypermethylation in at least three loci was observed in 50 out of 55 (91%) of ovarian tumors examined. The test sensitivity and specificity were assessed to be 96 and 67% for CYP39A1; 95 and 88% for GTF2A1; 93 and 67% for FOXD4L4; 81 and 67% for EBP; 89 and 82% for HAAO, respectively. Our data have identified, for the first time, GTF2A1 alone, or GTF2A1 plus HAAO are excellent candidate biomarkers for detecting this disease. Moreover, the known functions of these gene products further implicate dysregulated transcriptional control, cholesterol metabolism, or synthesis of quinolinic acids, may play important roles in attributing to ovarian neoplasm. Molecular therapies, by reversing the aberrant epigenomes using inhibitory agents or by abrogating the upstream signaling pathways that convey the epigenomic perturbations, may be developed into promising treatment regimens.

Background: P53, EGFR and HER-2/neu are the most frequently studied molecular biological parameters in epithelial ovarian cancer, but their prognostic impact is still unequivocal. We performed a meta-analysis to more precisely estimate their prognostic significance., Methods: Published studies that investigated the association between p53, EGFR and HER-2/neu status and survival were identified. Meta-analysis was performed using a DerSimonian-Laird model. Publication bias was investigated using funnel plots and sources of heterogeneity were identified using meta-regression analysis., Results: A total of 62 studies were included for p53, 15 for EGFR and 20 for HER-2/neu. P53, EGFR and HER-2/neu status had a modest effect on overall survival (pooled HR 1.47, 95% CI 1.33-1.61 for p53; HR 1.65, 95% CI 1.25-2.19 for EGFR and HR 1.67, 95% CI 1.34-2.08 for HER-2/neu). Meta-regression analysis for p53 showed that FIGO stage distribution influenced study outcome. For EGFR and HER-2/neu, considerable publication bias was present., Conclusions: Although p53, EGFR and HER-2/neu status modestly influences survival, these markers are, by themselves, unlikely to be useful as prognostic markers in clinical practice. Our study highlights the need for well-defined, prospective clinical trials and more complete reporting of results of prognostic factor studies.

Ovarian cancer is the most frequent cause of death from gynaecological cancer in the Western world. Current prognostic factors do not allow reliable prediction of response to chemotherapy and survival for individual ovarian cancer patients. Epidermal growth factor receptor (EGFR) and HER-2/neu are frequently expressed in ovarian cancer but their prognostic value remains unclear. In this study, we investigated the expression and prognostic value of EGFR, EGFR variant III (EGFRvIII), HER-2/neu and important downstream signalling components in a large series of epithelial ovarian cancer patients. Immunohistochemical staining of EGFR, pEGFR, EGFRvIII, Her-2/neu, PTEN (phosphatase and tensin homologue deleted on chromosome 10), total and phosphorylated AKT (pAKT) and phosphorylated ERK (pERK) was performed in 232 primary tumours using the tissue microarray platform and related to clinicopathological characteristics and survival. In addition, EGFRvIII expression was determined in 45 tumours by RT-PCR. Our results show that negative PTEN immunostaining was associated with stage I/II disease (P=0.006), non-serous tumour type (P=0.042) and in multivariate analysis with a longer progression-free survival (P=0.015). Negative PTEN staining also predicted improved progression-free survival in patients with grade III or undifferentiated serous carcinomas (P=0.011). Positive pAKT staining was associated with advanced-stage disease (P=0.006). Other proteins were expressed only at low levels, and were not associated with any clinicopathological parameter or survival. None of the tumours were positive for EGFRvIII. In conclusion, our results indicate that tumours showing negative PTEN staining could represent a subgroup of ovarian carcinomas with a relatively favourable prognosis.

Three amino-acid loop extension (TALE) homeobox proteins MEIS and PBX are cofactors for HOX-class homeobox proteins, which control growth and differentiation during embryogenesis and homeostasis. We showed that MEIS and PBX expression are related to cisplatin resistance in ovarian cancer cell lines. Therefore, MEIS1, MEIS2 and PBX expression were investigated immunohistochemically in a tissue microarray (N=232) of ovarian cancers and ovarian surface epithelium (N=15). Results were related to clinicopathologic characteristics and survival. All cancers expressed MEIS1, MEIS2 and PBX in nucleus and cytoplasm. MEIS1 and 2 only stained nuclear in surface epithelium. Nuclear MEIS2 was negatively related to stage, grade and overall survival in univariate analyses. Additionally, MEIS and PBX RNA expression in ovarian surface epithelium and other normal tissues and ovarian cancer versus other tumour types using public array data sets were studied. In ovarian cancer, MEIS1 is highly expressed compared to other cancer types. In conclusion, MEIS and PBX are extensively expressed in ovarian carcinomas and may play a role in ovarian carcinogenesis.

Ovarian cancer is a heterogeneous disease with respect to histopathology, molecular biology, and clinical outcome. In advanced stages, surgery and chemotherapy result in an approximately 25% overall 5-year survival rate, pointing to a strong need to identify subgroups of patients that may benefit from targeted innovative molecular therapy. This review summarizes: (a) microarray research identifying gene-expression profiles in ovarian cancer; (b) the methodological flaws in the available microarray studies; and (c) applications of pathway analysis to define new molecular subgroups. Microarray technology now permits the analysis of expression levels of thousands of genes. So far seven studies have aimed to identify a genetic profile that can predict survival/clinical outcome and/or response to platinum-based therapy. To date, the clinical evidence of prognostic microarray studies has only reached the level of small retrospective studies, and there are other issues that may explain the nonreproducibility among the reported prognostic profiles, such as overfitting, technical platform differences, and accuracy of measurements. We consider pathway analysis a promising new strategy. The accumulation of small differential expressions within a meaningful molecular regulatory network might lead to a critical threshold level, resulting in ovarian cancer. Microarray technologies have already provided valuable expression data for classifying ovarian cancer and the first clues about which molecular changes in ovarian cancer could be exploited in new treatment strategies. Further improvements in technology as well as in study design, combined with pathway analysis, will allow us to detect even more subtle tumor expression differences among subgroups of ovarian cancer patients. Disclosure of potential conflicts of interest is found at the end of this article.

Purpose: To evaluate if serum cytokine levels could be used as diagnostic or prognostic markers in ovarian cancer., Experimental Design: A cytokine bead array was done to simultaneously analyze 14 cytokines in the sera of 187 ovarian cancer patients with complete clinicopathologic data and follow-up, 45 patients with benign ovarian tumors, and 50 healthy controls. Serum levels of the well-known serum tumor marker CA-125 were routinely measured in all patients., Results: Serum levels of CA-125, interleukin 6 (IL-6), IL-7, and IL-10 were elevated in ovarian cancer patients compared with patients with benign ovarian tumors. Analyzing the cytokines in combination with CA-125 showed that a combination of IL-7 and CA-125 serum levels could accurately predict 69% of the ovarian cancer patients, without falsely classifying patients with benign pelvic mass. The cytokines IL-6, IL-7, IL-8, IL-10, monocyte chemotactic protein-1 (MCP-1), and IP-10 and CA-125 were associated with disease-free and overall survival in univariate analysis. In multivariate analysis, IL-7 and IP-10 were independent predictors of overall survival, although after inclusion of the clinicopathologic parameters, only stage and residual disease remained as independent predictors of survival., Conclusions: IL-7 levels were found to be strongly associated with ovarian cancer and could be used in combination with CA-125 to distinguish between malignant and benign ovarian tumors.

Background: Factor analysis (FA) has been widely applied in microarray studies as a data-reduction-tool without any a-priori assumption regarding associations between observed data and latent structure (Exploratory Factor Analysis).A disadvantage is that the representation of data in a reduced set of dimensions can be difficult to interpret, as biological contrasts do not necessarily coincide with single dimensions. However, FA can also be applied as an instrument to confirm what is expected on the basis of pre-established hypotheses (Confirmatory Factor Analysis, CFA). We show that with a hypothesis incorporated in a balanced (orthogonal) design, including 'SelfSelf' hybridizations, dye swaps and independent replications, FA can be used to identify the latent factors underlying the correlation structure among the observed two-color microarray data. An orthogonal design will reflect the principal components associated with each experimental factor. We applied CFA to a microarray study performed to investigate cisplatin resistance in four ovarian cancer cell lines, which only differ in their degree of cisplatin resistance., Results: Two latent factors, coinciding with principal components, representing the differences in cisplatin resistance between the four ovarian cancer cell lines were easily identified. From these two factors 315 genes associated with cisplatin resistance were selected, 199 genes from the first factor (False Discovery Rate (FDR): 19%) and 152 (FDR: 24%) from the second factor, while both gene sets shared 36. The differential expression of 16 genes was validated with reverse transcription-polymerase chain reaction., Conclusion: Our results show that FA is an efficient method to analyze two-color microarray data provided that there is a pre-defined hypothesis reflected in an orthogonal design.

The prognostic impact of p53 immunostaining in a large series of tumours from epithelial ovarian cancer patients in a two-centre study was analysed. The study population (n=476) comprised of a retrospective series of 188 patients (Dutch cohort) and a prospective series of 288 patients (Scottish cohort) enrolled in clinical trials. P53 expression was determined by immunohistochemistry on tissue microarrays. Association with progression-free survival (PFS) and overall survival (OS) was analysed by univariate and multivariate Cox regression analysis. Aberrant p53 overexpression was significantly associated with PFS in the Dutch and Scottish cohorts (P=0.001 and 0.038, respectively), but not with OS in univariate analysis. In multivariate analysis, when the two groups were combined and account taken of clinical factors and country of origin of the cohort, p53 expression was not an independent prognostic predictor of PFS or OS. In this well-powered study with minimal methodological variability, p53 immunostaining is not an independent prognostic marker of clinical outcome in epithelial ovarian cancer. The data demonstrate the importance of methodological standardisation, particularly defining patient characteristics and survival end-point data, if biomarker data from multicentre studies are to be combined.

In ovarian cancer the ceiling seems to be reached with chemotherapeutic drugs. Therefore a paradigm shift is needed. Instead of treating all patients according to standard guidelines, individualized molecular targeted treatment should be aimed for. This means that molecular profiles of the distinct ovarian cancer subtypes should be established. Until recently, most studies trying to identify molecular targets were single-marker studies. The prognostic role of key components of apoptotic and prosurvival pathways such as p53, EGFR, and HER2 has been extensively studied because resistance to chemotherapy is often caused by failure of tumor cells to go into apoptosis. However, it is more than likely that different ovarian cancer subtypes with extensive molecular heterogeneity exist. Therefore, exploration of the potential of specific tumor-targeted therapy, based on expression of a prognostic tumor profile, may be of interest. Recently, new profiling techniques, such as DNA and protein microarrays, have enabled high-throughput screening of tumors. In this review an overview of the current status of prognostic marker and molecular targeting research in ovarian cancer, including microarray studies, is presented.

A 42-year-old woman developed jaundice due to acute hepatitis several weeks after ingestion of a herbal preparation containing greater celandine (Chelidonium majus) and curcuma root, which had been prescribed by an alternative therapist due to a skin complaint. After the medication had been withdrawn, clinical recovery was rapid and the hepatic functions returned to normal within 2 months. The hepatitis was ascribed to the known hepatotoxic effects of C. majus. In view of the increasing popularity of herbal remedies, greater awareness of side effects, such as hepatotoxicity, is needed. Quite a number of herbal preparations carry the risk of liver damage. The supposed clinical effectiveness of herbal remedies does not seem to always outweigh the potential risks. In the event of non-clarified liver function disturbances the ingestion of supposedly harmless, but potentially hepatotoxic, herbal products should be considered.

We have isolated 462 bp of sequence termed ovarian-specific promoter 1 (OSP-1) that is part of a retrovirus-like element specifically expressed in the rat ovary. We have evaluated the ability of OSP-1 to activate gene expression in normal and neoplastic cell lines derived from the ovaries of rats and women. We have found that there was marked specificity in the ability of OSP-1 to drive reporter gene expression in an ovarian epithelial cell lineage manner. The expression of herpes simplex virus thymidine kinase (HSV-TK) under OSP-1 control was sufficiently ovarian cancer cell line specific to render ganciclovir approximately 50-fold more toxic in the A2780 human ovarian cancer cell line compared with clones of the HCT-116 and HT-29 colon cancer cell lines. Furthermore, ganciclovir had marked antitumor efficacy in vivo in severe combined immunodeficient mice bearing A2780OSP-1-HSV-TK as a s.c. xenograft. We suggest that these data support the use of OSP-1 as a tool to provide specificity to the gene therapy of ovarian cancer and to drive ovarian-specific oncogene expression for the creation of transgenic mouse models of ovarian cancer.