Previous reports have implicated an induction of genes in IFN/STAT1 (Interferon/STAT1) signaling in radiation resistant and prosurvival tumor phenotypes in a number of cancer cell lines, and we have hypothesized that upregulation of these genes may be predictive of poor survival outcome and/or treatment response in Glioblastoma Multiforme (GBM) patients. We have developed a list of 8 genes related to IFN/STAT1 that we hypothesize to be predictive of poor survival in GBM patients. Our working hypothesis that over-expression of this gene signature predicts poor survival outcome in GBM patients was confirmed, and in addition, it was demonstrated that the survival model was highly subtype-dependent, with strong dependence in the Proneural subtype and no detected dependence in the Classical and Mesenchymal subtypes. We developed a specific multi-gene survival model for the Proneural subtype in the TCGA (the Cancer Genome Atlas) discovery set which we have validated in the TCGA validation set. In addition, we have performed network analysis in the form of Bayesian Network discovery and Ingenuity Pathway Analysis to further dissect the underlying biology of this gene signature in the etiology of GBM. We theorize that the strong predictive value of the IFN/STAT1 gene signature in the Proneural subtype may be due to chemotherapy and/or radiation resistance induced through prolonged constitutive signaling of these genes during the course of the illness. The results of this study have implications both for better prediction models for survival outcome in GBM and for improved understanding of the underlying subtype-specific molecular mechanisms for GBM tumor progression and treatment response.
Purpose This study assessed whether Myristoylated Alanine Rich C-Kinase Substrate (MARCKS) can regulate glioblastoma (GBM) growth, radiation sensitivity and clinical outcome. Experimental Design MARCKS protein levels were analyzed in five GBM explant cell lines and eight patient-derived xenograft tumors by immunoblot, and these levels were correlated to proliferation rates and intracranial growth rates, respectively. Manipulation of MARCKS protein levels was assessed by lentiviral-mediated shRNA knockdown in the U251 cell line and MARCKS over-expression in the U87 cell line. The effect of manipulation of MARCKS on proliferation, radiation sensitivity and senescence was assessed. MARCKS gene expression was correlated with survival outcomes in the Repository of Molecular Brain Neoplasia Data (REMBRANDT) Database and The Cancer Genome Atlas (TCGA). Results MARCKS protein expression was inversely correlated with GBM proliferation and intracranial xenograft growth rates. Genetic silencing of MARCKS promoted GBM proliferation and radiation resistance, while MARCKS overexpression greatly reduced GBM growth potential and induced senescence. We found MARCKS gene expression to be directly correlated with survival in both the REMBRANDT and TCGA databases. Specifically, patients with high MARCKS expressing tumors of the Proneural molecular subtype had significantly increased survival rates. This effect was most pronounced in tumors with unmethylated O6-methylguanine DNA methyltransferase (MGMT) promoters, a traditionally poor prognostic factor. Conclusions MARCKS levels impact GBM growth and radiation sensitivity. High MARCKS expressing GBM tumors are associated with improved survival, particularly with unmethylated MGMT promoters. These findings suggest the use of MARCKS as a novel target and biomarker for prognosis in the Proneural subtype of GBM.
Summary Background Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear. Methods We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts. Findings The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14–1·83) and the presence of either LPA SNP (1·88, 1·40–2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81–1·11 and either LPA SNP 1·10, 0·92–1·31) or cardiovascular mortality (0·99, 0·81–1·2 and 1·13, 0·90–1·40, respectively) or in the validation studies. Interpretation In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established. Funding Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny.
In normotensive dogs, oscillometric measurements of MAP and SAP agreed more closely with direct arterial pressure measurements than oscillometric estimates of DAP. Oscillometric measurement of MAP was accurate during both normotension and hypertension in dogs.
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