Neutrophil Granulocytes in Ovarian Cancer - Induction of Epithelial-To- Mesenchymal-Transition and Tumor Cell Migration

Background: Ovarian cancer (OvCa) is a highly aggressive malignoma with a tumor-promoting microenvironment. Infiltration of polymorphonuclear neutrophils (PMN) is frequently seen, raising the question of their impact on tumor development. In that context, effects of PMN on human ovarian cancer cells were assessed. Methods: Human epithelial ovarian cancer cells were incubated with human PMN, lysate of PMN, or neutrophil elastase. Morphological alterations were observed by time-lapse video-microscopy, and the underlying molecular mechanism was analyzed by flow cytometry and Western blotting. Functional alternations were assessed by an in vitro wound healing assay. In parallel, a large cohort of n=334 primary OvCa tissue samples of various histological subtypes was histologically evaluated. Results: Co-cultivation of cancer cells with either PMN or PMN lysate causes a change of the polygonal epithelial phenotype of the cells towards a spindle shaped morphology, causing a cribriform cell growth. The PMN-induced alteration could be attributed to elastase, a major protease of PMN. Elastase-induced shape change was most likely due to the degradation of membranous E-cadherin, which results in loss of cell contacts and polarity. Moreover, in response to elastase, epithelial cytokeratins were downmodulated, in parallel with a nuclear translocation of β-catenin. These PMN-elastase induced alterations of cells are compatible with an epithelial-to-mesenchymal transition (EMT) of the cancer cells. Following EMT, the cells displayed a more migratory phenotype. In human biopsies, neutrophil infiltration was seen in 72% of the cases. PMN infiltrates were detected preferentially in areas with low E-cadherin expression. Conclusion: PMN in the microenvironment of OvCa can alter tumor cells towards a mesenchymal and migratory phenotype

Dynamics of the intratumoral immune response during progression of high-grade serous ovarian cancer

PURPOSE: Tumor-infiltrating lymphocytes (TILs) have an established impact on the prognosis of high-grade serous ovarian carcinoma (HGSOC), however, their role in recurrent ovarian cancer is largely unknown. We therefore systematically investigated TIL densities and MHC class I and II (MHC1, 2) expression in the progression of HGSOC. EXPERIMENTAL DESIGN: CD3+, CD4+, CD8+ TILs and MHC1, 2 expression were evaluated by immunohistochemistry on tissue microarrays in 113 paired primary and recurrent HGSOC. TILs were quantified by image analysis. All patients had been included to the EU-funded OCTIPS FP7 project. RESULTS: CD3+, CD4+, CD8+ TILs and MHC1 and MHC2 expression showed significant correlations between primary and recurrent tumor levels (Spearman rho 0.427, 0.533, 0.361, 0.456, 0.526 respectively; P<.0001 each). Paired testing revealed higher CD4+ densities and MHC1 expression in recurrent tumors (Wilcoxon P=.034 and P=.018). There was also a shift towards higher CD3+ TILs levels in recurrent carcinomas when analyzing platinum-sensitive tumors only (Wilcoxon P=.026) and in pairs with recurrent tumor tissue from first relapse only (Wilcoxon P=.031). High MHC2 expression was the only parameter to be significantly linked to prolonged progression-free survival after first relapse (PFS2, log-rank P=.012). CONCLUSIONS: This is the first study that analyzed the development of TILs density and MHC expression in paired primary and recurrent HGSOC. The level of the antitumoral immune response in recurrent tumors was clearly dependent on the one in the primary tumor. Our data contribute to the understanding of temporal heterogeneity of HGSOC immune microenvironment and have implications for selection of samples for biomarker testing in the setting of immune-targeting therapeutics

Neutrophil gelatinase-associated lipocalin (NGAL) predicts response to neoadjuvant chemotherapy and clinical outcome in primary human breast cancer

In our previous work we showed that NGAL, a protein involved in the regulation of proliferation and differentiation, is overexpressed in human breast cancer (BC) and predicts poor prognosis. In neoadjuvant chemotherapy (NACT) pathological complete response (pCR) is a predictor for outcome. The aim of this study was to evaluate NGAL as a predictor of response to NACT and to validate NGAL as a prognostic factor for clinical outcome in patients with primary BC. Immunohistochemistry was performed on tissue microarrays from 652 core biopsies from BC patients, who underwent NACT in the GeparTrio trial. NGAL expression and intensity was evaluated separately. NGAL was detected in 42.2% of the breast carcinomas in the cytoplasm. NGAL expression correlated with negative hormone receptor (HR) status, but not with other baseline parameters. NGAL expression did not correlate with pCR in the full population, however, NGAL expression and staining intensity were significantly associated with higher pCR rates in patients with positive HR status. In addition, strong NGAL expression correlated with higher pCR rates in node negative patients, patients with histological grade 1 or 2 tumors and a tumor size <40 mm. In univariate survival analysis, positive NGAL expression and strong staining intensity correlated with decreased disease-free survival (DFS) in the entire cohort and different subgroups, including HR positive patients. Similar correlations were found for intense staining and decreased overall survival (OS). In multivariate analysis, NGAL expression remained an independent prognostic factor for DFS. The results show that in low-risk subgroups, NGAL was found to be a predictive marker for pCR after NACT. Furthermore, NGAL could be validated as an independent prognostic factor for decreased DFS in primary human BC

Discovery and Validation of Novel Biomarkers for Detection of Epithelial Ovarian Cancer

Detection of epithelial ovarian cancer (EOC) poses a critical medical challenge. However, novel biomarkers for diagnosis remain to be discovered. Therefore, innovative approaches are of the utmost importance for patient outcome. Here, we present a concept for blood-based biomarker discovery, investigating both epithelial and specifically stromal compartments, which have been neglected in search for novel candidates. We queried gene expression profiles of EOC including microdissected epithelium and adjacent stroma from benign and malignant tumours. Genes significantly differentially expressed within either the epithelial or the stromal compartments were retrieved. The expression of genes whose products are secreted yet absent in the blood of healthy donors were validated in tissue and blood from patients with pelvic mass by NanoString analysis. Results were confirmed by the comprehensive gene expression database, CSIOVDB (Ovarian cancer database of Cancer Science Institute Singapore). The top 25% of candidate genes were explored for their biomarker potential, and twelve were able to discriminate between benign and malignant tumours on transcript levels (p < 0.05). Among them T-cell differentiation protein myelin and lymphocyte (MAL), aurora kinase A (AURKA), stroma-derived candidates versican (VCAN), and syndecan-3 (SDC), which performed significantly better than the recently reported biomarker fibroblast growth factor 18 (FGF18) to discern malignant from benign conditions. Furthermore, elevated MAL and AURKA expression levels correlated significantly with a poor prognosis. We identified promising novel candidates and found the stroma of EOC to be a suitable compartment for biomarker discovery

High-grade ovarian serous carcinoma patients exhibit profound alterations in lipid metabolism

Ovarian cancer is a very severe type of disease with poor prognosis. Treatment of ovarian cancer is challenging because of the lack of tests for early detection and effective therapeutic targets. Thus, new biomarkers are needed for both diagnostics and better understanding of the cellular processes of the disease. Small molecules, consisting of metabolites or lipids, have shown emerging potential for ovarian cancer diagnostics. Here we performed comprehensive lipidomic profiling of serum and tumor tissue samples from high-grade serous ovarian cancer patients to find lipids that were altered due to cancer and also associated with progression of the disease. Ovarian cancer patients exhibited an overall reduction of most lipid classes in their serum as compared to a control group. Despite the overall reduction, there were also specific lipids showing elevation, and especially alterations in ceramide and triacylglycerol lipid species were dependent on their fatty acyl side chain composition. Several lipids showed progressive alterations in patients with more advanced disease and poorer overall survival, and outperformed CA-125 as prognostic markers. The abundance of many serum lipids correlated with their abundance in tumor tissue samples. Furthermore, we found a negative correlation of serum lipids with 3-hydroxybutyric acid, suggesting an association between decreased lipid levels and fatty acid oxidation. In conclusion, here we present a comprehensive analysis of lipid metabolism alterations in ovarian cancer patients, with clinical implications.Peer reviewe

Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging

With regard to relapse and survival, early-stage high-grade serous ovarian (HGSOC) patients comprise a heterogeneous group and there is no clear consensus on first-line treatment. Currently, no prognostic markers are available for risk assessment by standard targeted immunohistochemistry and novel approaches are urgently required. Here, we applied MALDI-imaging mass spectrometry (MALDI-IMS), a new method to identify distinct mass profiles including protein signatures on paraffin-embedded tissue sections. In search of prognostic biomarker candidates, we compared proteomic profiles of primary tumor sections from early-stage HGSOC patients with either recurrent (RD) or non-recurrent disease (N = 4; each group) as a proof of concept study. In total, MALDI-IMS analysis resulted in 7537 spectra from the malignant tumor areas. Using receiver operating characteristic (ROC) analysis, 151 peptides were able to discriminate between patients with RD and non-RD (AUC > 0.6 or 0.7). These results confirm that in using IMS, we could identify new candidates to predict clinical outcome and treatment extent for patients with early-stage HGSOC

Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy

Introduction: Reliable predictive and prognostic markers for routine diagnostic purposes are needed for breast cancer patients treated with neoadjuvant chemotherapy. We evaluated protein biomarkers in a cohort of 116 participants of the GeparDuo study on anthracycline/taxane-based neoadjuvant chemotherapy for operable breast cancer to test for associations with pathological complete response (pCR) and disease-free survival (DFS). Particularly, we evaluated if interactions between hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression might lead to a different clinical behavior of HR+/HER2+ coexpressing and HR+/HER2- tumors and whether subgroups of triple negative tumors might be identified by the help of Ki67 labeling index, cytokeratin 5/6 (CK5/6), as well as cyclooxygenase-2 (COX-2), and Y-box binding protein 1 (YB-1) expression. Methods: Expression analysis was performed using immunohistochemistry and silver-enhanced in situ hybridization on tissue microarrays (TMAs) of pretherapeutic core biopsies. Results: pCR rates were significantly different between the biology-based tumor types (P = 0.044) with HR+/HER2+ and HR-/HER2- tumors having higher pCR rates than HR+/HER2-tumors. Ki67 labeling index, confirmed as significant predictor of pCR in the whole cohort (P = 0.001), identified HR-/HER- (triple negative) carcinomas with a higher chance for a pCR (P = 0.006). Biology-based tumor type (P = 0.046 for HR+/HER2+vs. HR+/HER2-), Ki67 labeling index (P = 0.028), and treatment arm (P = 0.036) were independent predictors of pCR in a multivariate model. DFS was different in the biology-based tumor types (P < 0.0001) with HR+/HER2- and HR+/HER2+ tumors having the best prognosis and HR-/HER2+ tumors showing the worst outcome. Biology-based tumor type was an independent prognostic factor for DFS in multivariate analysis (P < 0.001). Conclusions: Our data demonstrate that a biology-based breast cancer classification using estrogen receptor (ER), progesterone receptor (PgR), and HER2 bears independent predictive and prognostic potential. The HR+/HER2+ coexpressing carcinomas emerged as a group of tumors with a good response rate to neoadjuvant chemotherapy and a favorable prognosis. HR+/HER2- tumors had a good prognosis irrespective of a pCR, whereas patients with HR-/HER- and HR-/HER+ tumors, especially if they had not achieved a pCR, had an unfavorable prognosis and are in need of additional treatment options. Trial registration ClinicalTrials.gov identifier: NCT0079337