The Role of Chemotherapy Plus Immune Checkpoint Inhibitors in Oncogenic-Driven NSCLC: A University of California Lung Cancer Consortium Retrospective Study.

Introduction: There is a paucity of data on immune checkpoint inhibitors (ICIs) plus doublet chemotherapy (C) in patients with advanced lung cancer whose tumor harbors an actionable mutation. We sought to provide insight into the role of this combination in relation to chemotherapy alone in this patient population. Methods: We conducted a retrospective study at the five University of California National Cancer Institute-designated Comprehensive Cancer Centers. The primary end point was progression-free survival (PFS). Secondary end points included overall survival (OS) and significant adverse events. Adverse events in patients who received a tyrosine kinase inhibitor (TKI) post-ICI were also captured. Results: A total of 246 patients were identified, 170 treated with C plus ICI and 76 treated with C alone. Driver alterations included EGFR (54.9%), KRAS (32.9%), ALK (5.3%), HER2/ERBB2 (2.9%), ROS1 (1.2%), MET (1.2%), RET (0.8%), and BRAF non-V600 (0.8%). The overall PFS and OS hazard ratios were not significant at 1.12 (95% confidence interval 0.83-1.51; p = 0.472) and 0.86 (95% confidence interval: 0.60-1.24, p = 0.429), respectively. No significant differences in PFS or OS were observed in the mutational subgroups. Grade 3 or greater adverse events were lower in the C plus ICI group. The multivariate analysis for PFS and OS revealed a performance status (Eastern Cooperative Oncology Group) score of 2, and previous TKI treatment was associated with poorer outcomes with C plus ICI. Conclusions: Our study suggests that patients with oncogenic-driven NSCLC, primarily those with EGFR-driven tumors, treated with a TKI should not subsequently receive C plus ICI. Analysis from prospective clinical trials will provide additional information on the role of ICIs in this group of patients.

Using big data to retrospectively validate the COMPASS-CAT risk assessment model: considerations on methodology.

External validation is a prerequisite in order for a prediction model to be introduced into clinical practice. Nonetheless, methodologically intact external validation studies are a scarce finding. Utilization of big datasets can help overcome several causes of methodological failure. However, transparent reporting is needed to standardize the methods, assess the risk of bias and synthesize multiple validation studies in order to infer model generalizability. We describe the methodological challenges faced when using multiple big datasets to perform the first retrospective external validation study of the Prospective Comparison of Methods for thromboembolic risk assessment with clinical Perceptions and AwareneSS in real life patients-Cancer Associated Thrombosis (COMPASS-CAT) Risk Assessment Model for predicting venous thromboembolism in patients with cancer. The challenges included choosing the starting point, defining time sensitive variables that serve both as risk factors and outcome variables and using non-research oriented databases to form validated definitions from administrative codes. We also present the structured plan we used so as to overcome those obstacles and reduce bias with the target of producing an external validation study that successfully complies with prediction model reporting guidelines.

External Validation of a Venous Thromboembolic Risk Score for Cancer Outpatients with Solid Tumors: The COMPASS-CAT Venous Thromboembolism Risk Assessment Model.

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.

Direct oral anticoagulants in the treatment of pulmonary embolism.

OBJECTIVE: The objective of this review is to examine the management strategies for pulmonary embolism (PE) with an emphasis of the role of direct oral anticoagulants (DOACs). METHODS: PubMed was searched to identify relevant journal articles published through April 2017. Additional references were obtained from articles discovered during the database search. RESULTS: Initial heparinization followed by long-term anticoagulation with vitamin K antagonists has been considered the mainstay for the treatment of PE. However, DOACs now offer comparably effective and potentially safer alternatives for both acute and long-term treatment of PE using a monotherapy approach without the need for initial heparinization for rivaroxaban or apixaban. Advantages to using DOACs include oral availability, rapid onset of action, minimal drug and food interactions, predictable pharmacokinetics, and lack of need for routine monitoring. Limitations of using these agents include a limited availability of assays to quickly and efficiently measure their anticoagulant effects and the lack of widely available reversal agents for the direct oral factor Xa inhibitors; although idarucizumab has recently been approved for the reversal of dabigatran's anticoagulant effects. CONCLUSIONS: 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.

MicroRNA expression and regulation in human ovarian carcinoma cells by luteinizing hormone.

BACKGROUND: MicroRNAs 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. METHODS: Human 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. FINDINGS: In 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. CONCLUSION: The 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.

Regulation of gene expression in ovarian cancer cells by luteinizing hormone receptor expression and activation.

BACKGROUND: Since 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. METHODS: The 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. RESULTS: Through 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. CONCLUSION: Overall, 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.