Cyclooxygenase-2 inhibitor blocks the production of West Nile virus-induced neuroinflammatory markers in astrocytes

Inflammatory immune responses triggered initially to clear West Nile virus (WNV) infection later become detrimental and contribute to the pathological processes such as blood–brain barrier (BBB) disruption and neuronal death, thus complicating WNV-associated encephalitis (WNVE). It has been demonstrated previously that WNV infection in astrocytes results in induction of multiple matrix metalloproteinases (MMPs), which mediate BBB disruption. Cyclooxygenase (COX) enzymes and their product, prostaglandin E2 (PGE2), modulate neuroinflammation and regulate the production of multiple inflammatory molecules including MMPs. Therefore, this study determined and characterized the pathophysiological consequences of the expression of COX enzymes in human brain cortical astrocytes (HBCAs) following WNV infection. Whilst COX-1 mRNA expression did not change, WNV infection significantly induced RNA and protein expression of COX-2 in HBCAs. Similarly, PGE2 production was also enhanced significantly in infected HBCAs and was blocked in the presence of the COX-2-specific inhibitor NS-398, thus suggesting that COX-2, and not COX-1, was the source of the increased PGE2. Treatment of infected HBCAs with NS-398 attenuated the expression of MMP-1, -3 and -9 in a dose-dependent manner. Similarly, expression of interleukin-1β, -6 and -8, which were markedly elevated in infected HBCAs, exhibited a significant reduction in their levels in the presence of NS-398. These results provide direct evidence that WNV-induced COX-2/PGE2 is involved in modulating the expression of multiple neuroinflammatory mediators, thereby directly linking COX-2 with WNV disease pathogenesis. The ability of COX-2 inhibitors to modulate WNV-induced COX-2 and PGE2 signalling warrants further investigation in an animal model as a potential approach for clinical management of neuroinflammation associated with WNVE

Evaluation of multiple variate selection methods from a biological perspective: a nutrigenomics case study

Genomics-based technologies produce large amounts of data. To interpret the results and identify the most important variates related to phenotypes of interest, various multivariate regression and variate selection methods are used. Although inspected for statistical performance, the relevance of multivariate models in interpreting biological data sets often remains elusive. We compare various multivariate regression and variate selection methods applied to a nutrigenomics data set in terms of performance, utility and biological interpretability. The studied data set comprised hepatic transcriptome (10,072 predictor variates) and plasma protein concentrations [2 dependent variates: Leptin (LEP) and Tissue inhibitor of metalloproteinase 1 (TIMP-1)] collected during a high-fat diet study in ApoE3Leiden mice. The multivariate regression methods used were: partial least squares “PLS”; a genetic algorithm-based multiple linear regression, “GA-MLR”; two least-angle shrinkage methods, “LASSO” and “ELASTIC NET”; and a variant of PLS that uses covariance-based variate selection, “CovProc.” Two methods of ranking the genes for Gene Set Enrichment Analysis (GSEA) were also investigated: either by their correlation with the protein data or by the stability of the PLS regression coefficients. The regression methods performed similarly, with CovProc and GA performing the best and worst, respectively (R-squared values based on “double cross-validation” predictions of 0.762 and 0.451 for LEP; and 0.701 and 0.482 for TIMP-1). CovProc, LASSO and ELASTIC NET all produced parsimonious regression models and consistently identified small subsets of variates, with high commonality between the methods. Comparison of the gene ranking approaches found a high degree of agreement, with PLS-based ranking finding fewer significant gene sets. We recommend the use of CovProc for variate selection, in tandem with univariate methods, and the use of correlation-based ranking for GSEA-like pathway analysis methods

Functional Characterization of CLPTM1L as a Lung Cancer Risk Candidate Gene in the 5p15.33 Locus

Cleft Lip and Palate Transmembrane Protein 1-Like (CLPTM1L), resides in a region of chromosome 5 for which copy number gain has been found to be the most frequent genetic event in the early stages of non-small cell lung cancer (NSCLC). This locus has been found by multiple genome wide association studies to be associated with lung cancer in both smokers and non-smokers. CLPTM1L has been identified as an overexpressed protein in human ovarian tumor cell lines that are resistant to cisplatin, which is the only insight thus far into the function of CLPTM1L. Here we find CLPTM1L expression to be increased in lung adenocarcinomas compared to matched normal lung tissues and in lung tumor cell lines by mechanisms not exclusive to copy number gain. Upon loss of CLPTM1L accumulation in lung tumor cells, cisplatin and camptothecin induced apoptosis were increased in direct proportion to the level of CLPTM1L knockdown. Bcl-xL accumulation was significantly decreased upon loss of CLPTM1L. Expression of exogenous Bcl-xL abolished sensitization to apoptotic killing with CLPTM1L knockdown. These results demonstrate that CLPTM1L, an overexpressed protein in lung tumor cells, protects from genotoxic stress induced apoptosis through regulation of Bcl-xL. Thus, this study implicates anti-apoptotic CLPTM1L function as a potential mechanism of susceptibility to lung tumorigenesis and resistance to chemotherapy

Increased Levels of Leukocyte-Derived MMP-9 in Patients with Stable Angina Pectoris

Objective: There is a growing interest for matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) in plasma as novel biomarkers in coronary artery disease (CAD). We aimed to identify the sources of MMP-8, MMP-9, TIMP-1 and TIMP-2 among peripheral blood cells and further explore whether gene expression or protein release was altered in patients with stable angina pectoris (SA). Methods: In total, plasma MMP-9 was measured in 44 SA patients and 47 healthy controls. From 10 patients and 10 controls, peripheral blood mononuclear cells (PBMC) and neutrophils were isolated and stimulated ex vivo. MMPs, TIMPs and myeloperoxidase were measured in plasma and supernatants by ELISA. The corresponding gene expression was measured by real-time PCR. Results: Neutrophils were the dominant source of MMP-8 and MMP-9. Upon moderate stimulation with IL-8, the neutrophil release of MMP-9 was higher in the SA patients compared with controls (p,0.05). In PBMC, the TIMP-1 and MMP-9 mRNA expression was higher in SA patients compared with controls, p,0.01 and 0.05, respectively. There were no differences in plasma levels between patients and controls except for TIMP-2, which was lower in patients, p,0.01. Conclusion: Measurements of MMPs and TIMPs in plasma may be of limited use. Despite similar plasma levels in SA patients and controls, the leukocyte-derived MMP-9 and TIMP-1 are significantly altered in patients. The findings indicate that th

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity and Hormone-Related Risk Factors

BACKGROUND: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. RESULTS: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10(-6)). CONCLUSIONS: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility

Clinical parameters affecting survival outcomes in patients with low-grade serous ovarian carcinoma: An international multicentre analysis

Background: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC. Methods: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan–Meier survival curves. Results: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients’ median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage. Conclusion: This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice.publishedVersio

Prognostic gene expression signature for high-grade serous ovarian cancer.

BACKGROUND: Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC. PATIENTS AND METHODS: Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies. RESULTS: Expression levels of 276 genes were associated with OS (false discovery rate \u3c 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P \u3c 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P \u3c 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years. CONCLUSION: The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches

Prognostic gene expression signature for high-grade serous ovarian cancer

BACKGROUND:Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC. PATIENTS AND METHODS:Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies. RESULTS:Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years. CONCLUSION:The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches