13 resultados para Survival Analysis

em Indian Institute of Science - Bangalore - Índia


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Object. Insulin-like growth factor binding proteins (IGEBPs) have been implicated in the pathogenesis of glioma. In a previous study the authors demonstrated that IGFBP-3 is a novel glioblastoma biomarker associated with poor survival. Since signal transducer and activator of transcription 1 (STAT-1) has been shown to be regulated by IGFBP-3 during chondrogenesis and is a prosurvival and radioresistant molecule in different tumors, the aim in the present study was to explore the functional significance of IGFBP-3 in malignant glioma cells, to determine if STAT-1 is indeed regulated by IGFBP-3, and to study the potential of STAT-1 as a biomarker in glioblastoma. Methods. The functional significance of IGFBP-3 was investigated using the short hairpin (sh)RNA gene knockdown approach on U251MG cells. STAT-1 regulation by IGFBP-3 was tested on U251MG and U87MG cells by shRNA gene knockdown and exogenous treatment with recombinant IGFBP-3 protein. Subsequently, the expression of STAT-1 was analyzed with real-time reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC) in glioblastoma and control brain tissues. Survival analyses were done on a uniformly treated prospective cohort of adults with newly diagnosed glioblastoma (136 patients) using Kaplan-Meier and Cox regression models. Results. IGFBP-3 knockdown significantly impaired proliferation, motility, migration, and invasive capacity of U251MG cells in vitro (p < 0.005). Exogenous overexpression of IGFBP-3 in U251MG and U87MG cells demonstrated STAT-1 regulation. The mean transcript levels (by real-time RT-PCR) and the mean labeling index of STAT-1 (by IHC) were significantly higher in glioblastoma than in control brain tissues (p = 0.0239 and p < 0.001, respectively). Multivariate survival analysis revealed that STAT-1 protein expression (HR 1.015, p = 0.033, 95% CI 1.001-1.029) along with patient age (HR 1.025, p = 0.005, 95% CI 1.008-1.042) were significant predictors of shorter survival in patients with glioblastoma. Conclusions. IGFBP-3 influences tumor cell proliferation, migration, and invasion and regulates STAT-1 expression in malignant glioma cells. STAT-1 is overexpressed in human glioblastoma tissues and emerges as a novel prognostic biomarker.

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Overexpression of the epidermal growth factor receptor family genes, which include ErbB-1, 2, 3 and 4, has been implicated in a number of cancers. We have studied the extent of ErbB-2 overexpression among Indian women with sporadic breast cancer. Methods: Immmunohistochemistry and genomic polymerase chain reaction (PCR) were used to study the ErbB2 overexpression. ErbB2 status was correlated with other clinico-pathological parameters, including patient survival. Results: ErbB-2 overexpression was detected in 43.2% (159/368) of the cases by immunohistochemistry. For a sub-set of patients (n = 55) for whom total DNA was available, ErbB-2 gene amplification was detected in 25.5% (14/55) of the cases by genomic PCR. While the ErbB2 overexpression was significantly higher in patients with lymphnode (χ2 = 12.06, P≤ 0.001), larger tumor size (χ2 = 8.22, P = 0.042) and ductal carcinoma (χ2 = 15.42, P ≤ 0.001), it was lower in patients with disease-free survival (χ2 = 22.13, P ≤ 0.001). Survival analysis on a sub-set of patients for whom survival data were available (n = 179) revealed that ErbB-2 status (χ2 =25.94, P ≤ 0.001), lymphnode status (χ2 = 12.68, P ≤ 0.001), distant metastasis (χ2 = 19.49, P ≤ 0.001) and stage of the disease (χ2 = 28.04, P ≤0.001) were markers of poor prognosis. Conclusions: ErbB-2 overexpression was significantly greater compared with the Western literature, but comparable to other Indian studies. Significant correlation was found between ErbB-2 status and lymphnode status, tumor size and ductal carcinoma. ErbB-2 status, lymph node status, distant metastasis and stage of the disease were found to be prognostic indicators.

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Although LH is essential for survival and function of the corpus luteum (CL) in higher primates, luteolysis occurs during nonfertile cycles without a discernible decrease in circulating LH levels. Using genome-wide expression analysis, several experiments were performed to examine the processes of luteolysis and rescue of luteal function in monkeys. Induced luteolysis with GnRH receptor antagonist (Cetrorelix) resulted in differential regulation of 3949 genes, whereas replacement with exogenous LH (Cetrorelix plus LH) led to regulation of 4434 genes (1563 down-regulation and 2871 up-regulation). A model system for prostaglandin (PG) F-2 alpha-induced luteolysis in the monkey was standardized and demonstrated that PGF(2 alpha) regulated expression of 2290 genes in the CL. Analysis of the LH-regulated luteal transcriptome revealed that 120 genes were regulated in an antagonistic fashion by PGF(2 alpha). Based on the microarray data, 25 genes were selected for validation by real-time RT-PCR analysis, and expression of these genes was also examined in the CL throughout the luteal phase and from monkeys treated with human chorionic gonadotropin (hCG) to mimic early pregnancy. The results indicated changes in expression of genes favorable to PGF(2 alpha) action during the late to very late luteal phase, and expressions of many of these genes were regulated in an opposite manner by exogenous hCG treatment. Collectively, the findings suggest that curtailment of expression of downstream LH-target genes possibly through PGF(2 alpha) action on the CL is among the mechanisms underlying cross talk between the luteotropic and luteolytic signaling pathways that result in the cessation of luteal function, but hCG is likely to abrogate the PGF(2 alpha)-responsive gene expression changes resulting in luteal rescue crucial for the maintenance of early pregnancy. (Endocrinology 150: 1473-1484, 2009)

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Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

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We derive a very general expression of the survival probability and the first passage time distribution for a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space, which is valid irrespective of the statistical nature of the dynamics. The expression, together with the Jensen's inequality, naturally leads to a lower bound to the actual survival probability and an approximate first passage time distribution. These are expressed in terms of the position-position, velocity-velocity, and position-velocity variances. Knowledge of these variances enables one to compute a lower bound to the survival probability and consequently the first passage distribution function. As examples, we compute these for a Gaussian Markovian process and, in the case of non-Markovian process, with an exponentially decaying friction kernel and also with a power law friction kernel. Our analysis shows that the survival probability decays exponentially at the long time irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant.

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The properties of the generalized survival probability, that is, the probability of not crossing an arbitrary location R during relaxation, have been investigated experimentally (via scanning tunneling microscope observations) and numerically. The results confirm that the generalized survival probability decays exponentially with a time constant tau(s)(R). The distance dependence of the time constant is shown to be tau(s)(R)=tau(s0)exp[-R/w(T)], where w(2)(T) is the material-dependent mean-squared width of the step fluctuations. The result reveals the dependence on the physical parameters of the system inherent in the prior prediction of the time constant scaling with R/L-alpha, with L the system size and alpha the roughness exponent. The survival behavior is also analyzed using a contrasting concept, the generalized inside survival S-in(t,R), which involves fluctuations to an arbitrary location R further from the average. Numerical simulations of the inside survival probability also show an exponential time dependence, and the extracted time constant empirically shows (R/w)(lambda) behavior, with lambda varying over 0.6 to 0.8 as the sampling conditions are changed. The experimental data show similar behavior, and can be well fit with lambda=1.0 for T=300 K, and 0.5 analysis indicates that the scaling effect due to the true correlation time is relevant in the parameter space of the experimental observations.

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We report numerical and analytic results for the spatial survival probability for fluctuating one-dimensional interfaces with Edwards-Wilkinson or Kardar-Parisi-Zhang dynamics in the steady state. Our numerical results are obtained from analysis of steady-state profiles generated by integrating a spatially discretized form of the Edwards-Wilkinson equation to long times. We show that the survival probability exhibits scaling behavior in its dependence on the system size and the "sampling interval" used in the measurement for both "steady-state" and "finite" initial conditions. Analytic results for the scaling functions are obtained from a path-integral treatment of a formulation of the problem in terms of one-dimensional Brownian motion. A "deterministic approximation" is used to obtain closed-form expressions for survival probabilities from the formally exact analytic treatment. The resulting approximate analytic results provide a fairly good description of the numerical data.

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Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

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Topoisomerases are an important class of enzymes for regulating the DNA transaction processes. Mycobacterium tuberculosis (Mtb) is one of the most formidable pathogens also posing serious challenges for therapeutic interventions. The organism contains only one type IA topoisomerase (Rv3646c), offering an opportunity to test its potential as a candidate drug target. To validate the essentiality of M.tuberculosis topoisomerase I (TopoI(Mt)) for bacterial growth and survival, we have generated a conditionally regulated strain of topoI in Mtb. The conditional knockdown mutant exhibited delayed growth on agar plate. In liquid culture, the growth was drastically impaired when TopoI expression was suppressed. Additionally, novobiocin and isoniazid showed enhanced inhibitory potential against the conditional mutant. Analysis of the nucleoid revealed its altered architecture upon TopoI depletion. These studies establish the essentiality of TopoI for the M.tuberculosis growth and open up new avenues for targeting the enzyme.

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In cells, N-10-formyltetrahydrofolate (N-10-fTHF) is required for formylation of eubacterial/organellar initiator tRNA and purine nucleotide biosynthesis. Biosynthesis of N-10-fTHF is catalyzed by 5,10-methylene-tetrahydrofolate dehydrogenase/cyclohydrolase (FolD) and/or 10-formyltetrahydrofolate synthetase (Fhs). All eubacteria possess FolD, but some possess both FolD and Fhs. However, the reasons for possessing Fhs in addition to FolD have remained unclear. We used Escherichia coli, which naturally lacks fhs, as our model. We show that in E. coli, the essential function of folD could be replaced by Clostridium perfringens fhs when it was provided on a medium-copy-number plasmid or integrated as a single-copy gene in the chromosome. The fhs-supported folD deletion (Delta folD) strains grow well in a complex medium. However, these strains require purines and glycine as supplements for growth in M9 minimal medium. The in vivo levels of N-10-fTHF in the Delta folD strain (supported by plasmid-borne fhs) were limiting despite the high capacity of the available Fhs to synthesize N-10-fTHF in vitro. Auxotrophy for purines could be alleviated by supplementing formate to the medium, and that for glycine was alleviated by engineering THF import into the cells. The Delta folD strain (harboring fhs on the chromosome) showed a high NADP(+)-to-NADPH ratio and hypersensitivity to trimethoprim. The presence of fhs in E. coli was disadvantageous for its aerobic growth. However, under hypoxia, E. coli strains harboring fhs outcompeted those lacking it. The computational analysis revealed a predominant natural occurrence of fhs in anaerobic and facultative anaerobic bacteria.

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The bacterial second messengers (p)ppGpp and bis-(3'-5')-cyclic dimeric GMP (c-di-GMP) regulate important functions, such as transcription, virulence, biofilm formation, and quorum sensing. In mycobacteria, they regulate long-term survival during starvation, pathogenicity, and dormancy. Recently, a Pseudomonas aeruginosa strain lacking (p) ppGpp was shown to be sensitive to multiple classes of antibiotics and defective in biofilm formation. We were interested to find out whether Mycobacterium smegmatis strains lacking the gene for either (p)ppGpp synthesis (Delta rel(Msm)) or c-di-GMP synthesis (Delta dcpA) would display similar phenotypes. We used phenotype microarray technology to compare the growth of the wild-type and the knockout strains in the presence of several antibiotics. Surprisingly, the Delta rel(Msm) and Delta dcpA strains showed enhanced survival in the presence of many antibiotics, but they were defective in biofilm formation. These strains also displayed altered surface properties, like impaired sliding motility, rough colony morphology, and increased aggregation in liquid cultures. Biofilm formation and surface properties are associated with the presence of glycopeptidolipids (GPLs) in the cell walls of M. smegmatis. Thin-layer chromatography analysis of various cell wall fractions revealed that the levels of GPLs and polar lipids were reduced in the knockout strains. As a result, the cell walls of the knockout strains were significantly more hydrophobic than those of the wild type and the complemented strains. We hypothesize that reduced levels of GPLs and polar lipids may contribute to the antibiotic resistance shown by the knockout strains. Altogether, our data suggest that (p)ppGpp and c-di-GMP may be involved in the metabolism of glycopeptidolipids and polar lipids in M. smegmatis.

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Mycobacterium tuberculosis employs various strategies to modulate host immune responses to facilitate its persistence in macrophages. The M. tuberculosis cell wall contains numerous glycoproteins with unknown roles in pathogenesis. Here, by using Concanavalin A and LC-MS analysis, we identified a novel mannosylated glycoprotein phosphoribosyltransferase, encoded by Rv3242c from M. tuberculosis cell walls. Homology modeling, bioinformatic analyses, and an assay of phosphoribosyltransferase activity in Mycobacterium smegmatis expressing recombinant Rv3242c (MsmRv3242c) confirmed the mass spectrometry data. Using Mycobacterium marinum-zebrafish and the surrogate MsmRv3242c infection models, we proved that phosphoribosyltransferase is involved in mycobacterial virulence. Histological and infection assays showed that the M. marinum mimG mutant, an Rv3242c orthologue in a pathogenic M. marinum strain, was strongly attenuated in adult zebrafish and also survived less in macrophages. In contrast, infection with wild type and the complemented Delta mimG: Rv3242c M. marinum strains showed prominent pathological features, such as severe emaciation, skin lesions, hemorrhaging, and more zebrafish death. Similarly, recombinant Msm Rv3242c bacteria showed increased invasion in non-phagocytic epithelial cells and longer intracellular survival in macrophages as compared with wild type and vector control M. smegmatis strains. Further mechanistic studies revealed that the Rv3242c- and mimG-mediated enhancement of intramacrophagic survival was due to inhibition of autophagy, reactive oxygen species, and reduced activities of superoxide dismutase and catalase enzymes. Infection with MsmRv3242c also activated the MAPK pathway, NF-kappa B, and inflammatory cytokines. In summary, we show that a novel mycobacterial mannosylated phosphoribosyltransferase acts as a virulence and immunomodulatory factor, suggesting that it may constitute a novel target for antimycobacterial drugs.

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Medicinal plants are considered as one of the ideal sources for cancer therapy due to their bioactive contents and low toxicity to humans. Vernonia genus is one of the common medicinal plants, which has wide spread usage in food and medicine. However, there are limited studies to explore its anticancer properties. In the current study, we have used Vernonia condensata, to explore its anticancer activity using various approaches. Here, we show that extract prepared from Vernonia condensata (VCE) exhibits cytotoxic properties against various cancer cells in a dose- and time-dependent manner. Interestingly, when treated with VCE, there was no significant cytotoxicity in peripheral blood mononuclear cells (PBMCs). Flow cytometry analysis revealed that although VCE induced cell death, arrest was not observed. VCE treatment led to disruption of mitochondrial membrane potential in a concentration dependent manner resulting in activation of apoptosis culminating in cell death. Immunoblotting studies revealed that VCE activated intrinsic pathway of apoptosis. More importantly, VCE treatment resulted in tumor regression leading to significant enhancement in life span in treated mice, without showing any detectable side effects. Therefore, for the first time our study reveals the potential of extract from Vernonia condensata to be used as an anticancer agent.