Katarzyna Lisowska

Oncolytic viruses have emerged as novel promising therapeutic agents for some hard-to-cure cancers. In the present study, we examined different types of ovarian cancer cell lines to determine the permissiveness of myxoma virus constructs and assessed the metabolic changes associated with viral infection. The Kuramochi, OAW42, and OVP10 cell lines were found to be permissive for the viral constructs, while the OVPA8 line was resistant to this treatment. Nuclear magnetic resonance (NMR) spectra of the cellular extracts and intact cells were acquired using a Bruker Avance III 400 MHz spectrometer. The decreased phosphocholine and succinate, as well as the increased glutamine and uridine nucleotides/uridine diphosphate nucleotide sugars are the common metabolic abnormalities detected in the NMR spectra of aqueous extracts obtained from all virus-sensitive cell lines tested 24 h after infection. The decrease in phosphocholine, increased phosphatidylcholine, and uridine nucleotides/uridine diphosphate nucleotide sugars were also evident in the NMR spectra of intact cells. There was no association between infection and increased lactate levels. Such metabolic changes were not observed for non-permissive OVPA8 cells. We conclude that changes in the metabolome could find use in attempts at ovarian cancer therapy based on these oncolytics, as well as in testing combined approaches exploring such changes.

Ovarian cancer (OC) is usually diagnosed late due to its nonspecific symptoms and lack of reliable tools for early diagnostics and screening. OC studies concentrate on the search for new biomarkers and therapeutic targets. This study aimed to validate the MFAP5 gene, and its encoded protein, as a potential prognostic biomarker. In our previous study, we found that patients with high-grade serous OC who had higher MFAP5 mRNA levels had shorter survival, as compared with those with lower levels. Here, we used the Kaplan-Meier Plotter and CSIOVDB online tools to analyze possible associations of MFAP5 expression with survival and other clinico-pathological features. In these analyses, higher MFAP5 mRNA expression was observed in the more advanced FIGO stages and high-grade tumors, and was significantly associated with shorter overall and progression-free survival. Next, we analyzed the expression of the MFAP5 protein by immunohistochemistry (IHC) in 108 OC samples and tissue arrays. Stronger MFAP5 expression was associated with stronger desmoplastic reaction and serous vs. non-serous histology. We found no significant correlation between IHC results and survival, although there was a trend toward shorter survival in patients with the highest IHC scores. We searched for co-expressed genes/proteins using cBioPortal and analyzed potential MFAP5 interaction networks with the STRING tool. MFAP5 was shown to interact with many extracellular matrix proteins, and was connected to the Notch signaling pathway. Therefore, although not suitable as a prognostic biomarker for evaluation with a simple diagnostic tool like IHC, MFAP5 is worth further studies as a possible therapeutic target.

FGFR signalling is one of the most prominent pathways involved in cell growth and development as well as cancer progression. FGFR1 amplification occurs in approximately 20% of all squamous cell lung carcinomas (SCC), a predominant subtype of non-small cell lung carcinoma (NSCLC), indicating FGFR as a potential target for the new anti-cancer treatment. However, acquired resistance to this type of therapies remains a serious clinical challenge. Here, we investigated the NSCLC cell lines response and potential mechanism of acquired resistance to novel selective FGFR inhibitor CPL304110. We found that despite significant genomic differences between CPL304110-sensitive cell lines, their resistant variants were characterised by upregulated p38 expression/phosphorylation, as well as enhanced expression of genes involved in MAPK signalling. We revealed that p38 inhibition restored sensitivity to CPL304110 in these cells. Moreover, the overexpression of this kinase in parental cells led to impaired response to FGFR inhibition, thus confirming that p38 MAPK is a driver of resistance to a novel FGFR inhibitor. Taken together, our results provide an insight into the potential direction for NSCLC targeted therapy.

In our previous microarray study we identified two subgroups of high-grade serous ovarian cancers with distinct gene expression and survival. Among differentially expressed genes was an Integrin beta-like 1 (ITGBL1), coding for a poorly characterized protein comprised of ten EGF-like repeats. Here, we have analyzed the influence of ITGBL1 on the phenotype of ovarian cancer (OC) cells. We analyzed expression of four putative ITGBL1 mRNA isoforms in five OC cell lines. OAW42 and SKOV3, having the lowest level of any ITGBL1 mRNA, were chosen to produce ITGBL1-overexpressing variants. In these cells, abundant ITGBL1 mRNA expression could be detected by RT-PCR. Immunodetection was successful only in the culture media, suggesting that ITGBL1 is efficiently secreted. We found that ITGBL1 overexpression affected cellular adhesion, migration and invasiveness, while it had no effect on proliferation rate and the cell cycle. ITGBL1-overexpressing cells were significantly more resistant to cisplatin and paclitaxel, major drugs used in OC treatment. Global gene expression analysis revealed that signaling pathways affected by ITGBL1 overexpression were mostly those related to extracellular matrix organization and function, integrin signaling, focal adhesion, cellular communication and motility; these results were consistent with the findings of our functional studies. Overall, our results indicate that higher expression of ITGBL1 in OC is associated with features that may worsen clinical course of the disease.

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.

Nowadays, targeted therapy plays a growing role in oncological treatment. In ovarian cancer, particularly promising results are achieved with poly (ADP-ribose) polymerase (PARP) inhibitors. Recent clinical trials have shown that PARP inhibitors can result in significantly longer progression-free survival. These results encourage the search for other targeted therapies and bring hope that ovarian cancer can soon become a manageable chronic disease. The main problem in ovarian cancer research is the heterogeneity of this disease. Recent studies have shown that different histological types of ovarian cancer can originate from distinct tissues. According to the recent knowledge, “ovarian cancer” is an artificial term for distinct invasive malignancies localised within the pelvis. Genetic and immunophenotype analyses have shown that high-grade serous ovarian cancer, the most frequent histological type and the one with the worst prognosis, originates mainly from fallopian tube epithelium, while endometrioid and clear-cell cancers originate from the endometrium. For these reasons, in basic and preclinical studies on ovarian cancer, one has to carefully choose a well-defined model system, corresponding to the histological type of interest. In this article, we discuss ovarian cancer cell lines most frequently used in in vitro studies. Our aim is to indicate the advantages and disadvantages of different models, encompassing primary and established cell cultures, two- and three-dimensional models, etc. In particular, we would like to alert researchers to the fact that the most popular cell lines SKOV3 and A2780 do not represent a suitable model for studies on high-grade serous ovarian cancer. Nowadays, targeted therapy plays a growing role in oncological treatment. In ovarian cancer, particularly promising results are achieved with poly (ADP-ribose) polymerase (PARP) inhibitors. Recent clinical trials have shown that PARP inhibitors can result in significantly longer progression-free survival. These results encourage the search for other targeted therapies and bring hope that ovarian cancer can soon become a manageable chronic disease. The main problem in ovarian cancer research is the heterogeneity of this disease. Recent studies have shown that different histological types of ovarian cancer can originate from distinct tissues. According to the recent knowledge, “ovarian cancer” is an artificial term for distinct invasive malignancies localised within the pelvis. Genetic and immunophenotype analyses have shown that high-grade serous ovarian cancer, the most frequent histological type and the one with the worst prognosis, originates mainly from fallopian tube epithelium, while endometrioid and clear-cell cancers originate from the endometrium. For these reasons, in basic and preclinical studies on ovarian cancer, one has to carefully choose a well-defined model system, corresponding to the histological type of interest. In this article, we discuss ovarian cancer cell lines most frequently used in in vitro studies. Our aim is to indicate the advantages and disadvantages of different models, encompassing primary and established cell cultures, two- and three-dimensional models, etc. In particular, we would like to alert researchers to the fact that the most popular cell lines SKOV3 and A2780 do not represent a suitable model for studies on high-grade serous ovarian cancer.

An understanding of the molecular pathogenesis and heterogeneity of ovarian cancer holds promise for the development of early detection strategies and novel, efficient therapies. In this review, we discuss the advantages and limitations of animal models available for basic and preclinical studies. The fruit fly model is suitable mainly for basic research on cellular migration, invasiveness, adhesion, and the epithelial-to-mesenchymal transition. Higher-animal models allow to recapitulate the architecture and microenvironment of the tumor. We discuss a syngeneic mice model and the patient derived xenograft model (PDX), both useful for preclinical studies. Conditional knock-in and knock-out methodology allows to manipulate selected genes at a given time and in a certain tissue. Such models have built our knowledge about tumor-initiating genetic events and cell-of-origin of ovarian cancers; it has been shown that high-grade serous ovarian cancer may be initiated in both the ovarian surface and tubal epithelium. It is postulated that clawed frog models could be developed, enabling studies on tumor immunity and anticancer immune response. In laying hen, ovarian cancer develops spontaneously, which provides the opportunity to study the genetic, biochemical, and environmental risk factors, as well as tumor initiation, progression, and histological origin; this model can also be used for drug testing. The chick embryo chorioallantoic membrane is another attractive model and allows the study of drug response.

High-grade serous ovarian carcinoma (HGSOC) is the most frequent histological type of ovarian cancer and the one with worst prognosis. Unfortunately, the majority of established ovarian cancer cell lines which are used in the research have unclear histological origin and probably do not represent HGSOC. Thus, new and reliable models of HGSOC are needed. Ascitic fluid from a patient with recurrent HGSOC was used to establish a stable cancer cell line. Cells were characterized by cytogenetic karyotyping and short tandem repeat (STR) profiling. New generation sequencing was applied to test for hot-spot mutations in 50 cancer-associated genes and fluorescence in situ hybridization (FISH) analysis was used to check for TP53 status. Cells were analyzed for expression of several marker genes/proteins by reverse-transcription polymerase chain reaction (RT-PCR), fluorescence-activated cell sorting (FACS), and immunocytochemistry (ICC). Functional tests were performed to compare OVPA8 cells with five commercially available and frequently used ovarian cancer cell lines: SKOV3, A2780, OVCAR3, ES2, and OAW42. Our newly-established OVPA8 cell line shows morphologic and genetic features consistent with HGSOC, such as epithelial morphology, multiple chromosomal aberrations, TP53 mutation, BRCA1 mutation, and loss of one copy of BRCA2. The OVPA8 line has a stable STR profile. Cells are positive for EpCAM, CK19, and CD44; they have relatively low plating efficiency/ability to form spheroids, a low migration rate, and intermediate invasiveness in matrigel, as compared to other ovarian cancer lines. OVPA8 is sensitive to paclitaxel and resistant to cisplatin. We also tested two FGFR inhibitors; OVPA8 cells were resistant to AZD4547 (AstraZeneca, London, UK), but sensitive to the new inhibitor CPL304-110-01 (Celon Pharma, Łomianki/Kiełpin, Poland). We have established and characterized a novel cell line, OVPA8, which can be a valuable preclinical model for studies on high-grade serous ovarian cancer.

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.

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.