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Background Mutated and non-mutated genes interact to drive cancer growth and metastasis. While research has focused on understanding the impact of mutated genes on cancer biology, understanding non-mutated genes that are essential to tumor development could lead to new therapeutic strategies. The recent advent of high-throughput whole genome sequencing being applied to many different samples has made it possible to calculate if genes are significantly non-mutated in a specific cancer patient cohort. Methods We carried out random mutagenesis simulations of the human genome approximating the regions sequenced in the publicly available Cancer Growth Atlas Project for ovarian cancer (TCGA-OV). Simulated mutations were compared to the observed mutations in the TCGA-OV cohort and genes with the largest deviations from simulation were identified. Pathway analysis was performed on the non-mutated genes to better understand their biological function. We then compared gene expression, methylation and copy number distributions of non-mutated and mutated genes in cell lines and patient data from the TCGA-OV project. To directly test if non-mutated genes can affect cell proliferation, we carried out proof-of-concept RNAi silencing experiments of a panel of nine selected non-mutated genes in three ovarian cancer cell lines and one primary ovarian epithelial cell line. Results We identified a set of genes that were mutated less than expected (non-mutated genes) and mutated more than expected (mutated genes). Pathway analysis revealed that non-mutated genes interact in cancer associated pathways. We found that non-mutated genes are expressed significantly more than mutated genes while also having lower methylation and higher copy number states indicating that they could be functionally important. RNAi silencing of the panel of non-mutated genes resulted in a greater significant reduction of cell viability in the cancer cell lines than in the non-cancer cell line. Finally, as a test case, silencing ANKLE2, a significantly non-mutated gene, affected the morphology, reduced migration, and increased the chemotherapeutic response of SKOV3 cells. Conclusion We show that we can identify significantly non-mutated genes in a large ovarian cancer cohort that are well-expressed in patient and cell line data and whose RNAi-induced silencing reduces viability in three ovarian cancer cell lines. Targeting non-mutated genes that are important for tumor growth and metastasis is a promising approach to expand cancer therapeutic options.

In spite of the growing importance of endothelial protein C receptor/active protein C (EPCR/aPC) in tumor biology, their impact on immunological homeostasis remains largely unexplored. The objective of this study was to assess whether soluble plasma endothelial protein C receptor (sEPCR), which is a regulator of circulating aPC, is involved in innate immune response in cancer patients. In the Ovcar-3 ovarian cancer line, the role of aPC in secretion of cytokines was analyzed. In parallel, in 33 patients, with a diagnosis of ovarian epithelial cancer, sEPCR was quantified, blood immune cell phenotypes were determined by flow cytometry and plasma cytokines were evaluated using a protein array. Spearman's rank correlation coefficients (r) and coefficient significance was determined by a statistical hypothesis test (α=0.05). Our results show that i) aPC induced the secretion of several cytokines in Ovcar-3 cells; ii) 61% of patients exhibited a concentration of plasma sEPCR well above the baseline (normal plasma level, 100 ± 28 ng/ml); iii) comparing immune cell phenotypes in patients having a normal level of sEPCR with those having a high level of sEPCR, it was found that sEPCR levels were correlated with high intensity of cells expressing CD45ra, CD3, CD8, CD25 and low intensity of cells expressing CD56 (NK cells), CD294 (TH2 cells), IL-2, IL-10, IL-17a (TH17 cells), IL-21 (TH21 cells) and CD29 markers (r ≥ 0.60); and iv) high levels of sEPCR correlate with high levels of plasma bioactive proteins such as insulin-like growth factor-2 (IGFII), IL-13rα, macrophage inflammatory protein (MIP1α) and matrix metalloproteinase-7 (MMP-7) that have already been proposed as biomarkers for ovarian cancer and particularly those with poor prognosis. In conclusion, sEPCR produced by ovarian cancer cells, by modulating circulating aPC, influences the secretory behavior of tumor cells (cytokines and interleukins). Consequently, sEPCR in turn acts on the innate immune response by decreasing effector cells such as natural killer and T helper cells (TH2, TH17 and TH21).

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies.

Coagulation disorders often accompany cancer onset and evolution, which, if not properly managed, could have grave consequences. Endothelial protein C is an important regulator of homeostasis and acts through its high affinity binding to its transmembrane receptor (EPCR). Soluble (sEPCR) which results from the proteolytic cleavage of the membrane bound form can trap activated endothelial protein C and deprive it of its anti-coagulant function. In this study, the expression of EPCR and its soluble form (sEPCR) released into plasma as a result of proteolytic cleavage were investigated in ovarian, breast, lung and colorectal cancer biopsies, as well as in ascitic cell clusters and peritoneal fluid from ovarian cancer samples. In parallel, breast, ovarian, lung and colorectal cancer cell lines were investigated for the expression of EPCR. The integrity of the EPCR gene sequence as well gene haplotypes were ascertained in the established cancer cell lines in order to understand their eventual regulatory functions. The results from the present study indicate that in cancer patients, the levels of sEPCR are significantly higher than the normal range compared to healthy volunteers. The increase in the levels of sEPCR parallels the increase in CA125, showing a close correlation. Therefore, the detection of sEPCR in cancer and during the post-treatment period could be taken into account as an additional marker that could re-inforce the one obtained using CA125 alone as a marker of cancer cell mass.

Background The early peritoneal invasion of epithelial ovarian cancer (EOC) by tumoral aggregates presents in ascites is a major concern. The role of the microenvironment seems to be important in this process but the lack of adequate models to study cellular interactions between cancer cells and stromal cells does not allow to uncover the molecular pathways involved. Our goal was to study the interactions between ovarian cancer cells (OCC) and mesenchymal stem cells (MSC) using a 3D model. Methods We used millimetric pieces of amniochorionic membrane - referred to as amniotic membrane scaffold (AMS) - to create 3D peritoneal nodules mimicking EOC early invasion. We were able to measure the distribution and the depth of infiltration using confocal microsopy. We extracted MSC from the amniochorionic membrane using the markers CD34-, CD45-, CD73+, CD90+, CD105+ and CD29+ at the Fluorescence Activated Cell Sorting (FACS) analysis. We used transwell and wound healing tests to test OCC migration and invasion in vitro. Results Here we show that OCC tumors were located in regions rich in MSC (70%). The tumors infiltrated deeper within AMS in regions rich in MSC (p Conclusions The use of tridimensional models using AMS could be a useful tool to decipher early molecular events in ovarian cancer metastasis. Cytokine inhibitors interrupting the cross-talk between OCCs and MSCs such as IL6 should be investigated as a new therapeutic approach in ovarian cancer.