BackgroundSince a substantial percentage of ovarian cancers express gonadotropin receptors and are responsive to the relatively high concentrations of pituitary gonadotropins during the postmenopausal years, it has been suggested that receptor activation may contribute to the etiology and/or progression of the neoplasm. The goal of the present study was to develop a cell model to determine the impact of luteinizing hormone (LH) receptor (LHR) expression and LH-mediated LHR activation on gene expression and thus obtain insights into the mechanism of gonadotropin action on ovarian surface epithelial (OSE) carcinoma cells.MethodsThe human ovarian cancer cell line, SKOV-3, was stably transfected to express functional LHR and incubated with LH for various periods of time (0-20 hours). Transcriptomic profiling was performed on these cells to identify LHR expression/activation-dependent changes in gene expression levels and pathways by microarray and qRT-PCR analyses.ResultsThrough comparative analysis on the LHR-transfected SKOV-3 cells exposed to LH, we observed the differential expression of 1,783 genes in response to LH treatment, among which five significant families were enriched, including those of growth factors, translation regulators, transporters, G-protein coupled receptors, and ligand-dependent nuclear receptors. The most highly induced early and intermediate responses were found to occupy a network impacting transcriptional regulation, cell growth, apoptosis, and multiple signaling transductions, giving indications of LH-induced apoptosis and cell growth inhibition through the significant changes in, for example, tumor necrosis factor, Jun and many others, supportive of the observed cell growth reduction in in vitro assays. However, other observations, e.g. the substantial up-regulation of the genes encoding the endothelin-1 subtype A receptor, stromal cell-derived factor 1, and insulin-like growth factor II, all of which are potential therapeutic targets, may reflect a positive mediation of ovarian cancer growth.ConclusionOverall, the present study elucidates the extensive transcriptomic changes of ovarian cancer cells in response to LH receptor activation, which provides a comprehensive and objective assessment for determining new cancer therapies and potential serum markers, of which over 100 are suggested.

Advantages to using DOACs render them an attractive alternative to conventional therapy in PE treatment that may simplify acute and long-term treatment paradigms, improve patient outcomes, and increase patient compliance. However, questions remain pertaining to the use of DOACs in PE patients with high-risk features and in cancer patients and fragile populations. Clinical studies are under way to address many of these issues.

BackgroundMicroRNAs have been widely-studied with regard to their aberrant expression and high correlation with tumorigenesis and progression in various solid tumors. With the major goal of assessing gonadotropin (luteinizing hormone, LH) contributions to LH receptor (LHR)-positive ovarian cancer cells, we have conducted a genome-wide transcriptomic analysis on human epithelial ovarian cancer cells to identify the microRNA-associated cellular response to LH-mediated activation of LHR.MethodsHuman ovarian cancer cells (SKOV3) were chosen as negative control (LHR−) and stably transfected to express functional LHR (LHR+), followed by incubation with LH (0–20 h). At different times of LH-mediated activation of LHR the cancer cells were analyzed by a high-density Ovarian Cancer Disease-Specific-Array (DSA, ALMAC™), which profiled ∼100,000 transcripts with ∼400 non-coding microRNAs.FindingsIn total, 65 microRNAs were identified to exhibit differential expression in either LHR expressing SKOV3 cells or LH-treated cells, a few of which have been found in the genomic fragile regions that are associated with abnormal deletion or amplification in cancer, such as miR-21, miR-101-1, miR-210 and miR-301a. By incorporating the dramatic expression changes observed in mRNAs, strong microRNA/mRNA regulatory pairs were predicted through statistical analyses coupled with collective computational prediction. The role of each microRNA was then determined through a functional analysis based on the highly-confident microRNA/mRNA pairs.ConclusionThe overall impact on the transcriptome-level expression indicates that LH may regulate apoptosis and cell growth of LHR+ SKOV3 cells, particularly by reducing cancer cell proliferation, with some microRNAs involved in regulatory roles.

Background Current risk assessment models (RAMs) for prediction of venous thromboembolism (VTE) risk in the outpatient cancer population have shown poor predictive value in many of the most common cancers. The Comparison of Methods for Thromboembolic Risk Assessment with Clinical Perceptions and AwareneSS in Real Life Patients‐Cancer Associated Thrombosis (COMPASS‐CAT) RAM was derived in this patient population and predicted patients at high risk for VTE even after initiation of chemotherapy. We sought to externally validate this RAM. Materials and Methods Patients aged ≥18 years who presented to a tertiary care center between January 1, 2014, and December 31, 2016, with invasive breast, ovarian, lung, or colorectal cancers were included. The COMPASS‐CAT RAM was applied using our health system's tumor registry and variables that were identified by International Statistical Classification of Diseases and Related Health Problems‐9 and ‐10 codes of the electronic health record and independent chart review. The primary endpoint at 6‐month study follow‐up was documented VTE. Results A total of 3,814 patients were included. Documented VTE at 6‐month follow‐up occurred in 5.85% of patients. Patients stratified into low/intermediate‐ and high‐risk groups had VTE rates of 2.27% and 6.31%, respectively. The sensitivity, specificity, and negative and positive predictive value of the RAM were 95%, 12%, 97.73%, and 6.31%, respectively. Diagnostic accuracy via receiver operating characteristic curve was calculated at 0.62 of the area under the curve. Conclusion In this large retrospective external validation study of the COMPASS‐CAT RAM for VTE in patients with cancer undergoing active treatment, model discrimination was moderate and calibration was poor. The model had good negative predictive value. Further prospective validation studies—especially within 6 months of cancer diagnosis—are needed before the model can be implemented into routine clinical practice for primary thromboprophylaxis of high‐VTE‐risk patients with cancer with solid tumors. Implications for Practice This study provides further guidance for researchers and clinicians in determining clinical and laboratory risk factors associated with development of venous thromboembolism among the ambulatory population of patients being treated for lung, breast, colorectal, or ovarian cancer. It validates the COMPASS‐CAT risk model that was developed in this cancer population and suggests that further prospective validation of the model, with more focus on patients within 6 months of their index cancer diagnosis, would likely enhance the accuracy and usefulness of this model as a clinical prediction tool.