144 resultados para Signature


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The use of high linear energy transfer radiations in the form of carbon ions in heavy ion beam lines or alpha particles in new radionuclide treatments has increased substantially over the past decade and will continue to do so due to the favourable dose distributions they can offer versus conventional therapies. Previously it has been shown that exposure to heavy ions induces pan-nuclear phosphorylation of several DNA repair proteins such as H2AX and ATM in vitro. Here we describe similar effects of alpha particles on ex vivo irradiated primary human peripheral blood lymphocytes. Following alpha particle irradiation pan-nuclear phosphorylation of H2AX and ATM, but not DNA-PK and 53BP1, was observed throughout the nucleus. Inhibition of ATM, but not DNA-PK, resulted in the loss of pan-nuclear phosphorylation of H2AX in alpha particle irradiated lymphocytes. Pan-nuclear gamma-H2AX signal was rapidly lost over 24h at a much greater rate than foci loss. Surprisingly, pan-nuclear gamma-H2AX intensity was not dependent on the number of alpha particle induced double strand breaks, rather the number of alpha particles which had traversed the cell nucleus. This distinct fluence dependent damage signature of particle radiation is important in both the fields of radioprotection and clinical oncology in determining radionuclide biological dosimetry and may be indicative of patient response to new radionuclide cancer therapies.

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BACKGROUND: Aberrant DNA methylation has been implicated as a key survival mechanism in cancer, whereby promoter hypermethylation silences genes essential for many cellular processes including apoptosis. Limited data is available on the methylation profile of apoptotic genes in prostate cancer (CaP). The aim of this study was to profile methylation of apoptotic-related genes in CaP using denaturing high performance liquid chromatography (DHPLC).

METHODS: Based on an in silico selection process, 13 genes were screened for methylation in CaP cell lines using DHPLC. Quantitative methylation specific PCR was employed to determine methylation levels in prostate tissue specimens (n = 135), representing tumor, histologically benign prostate, high-grade prostatic intraepithelial neoplasia and benign prostatic hyperplasia. Gene expression was measured by QRT-PCR in cell lines and tissue specimens.

RESULTS: The promoters of BIK, BNIP3, cFLIP, TMS1, DCR1, DCR2, and CDKN2A appeared fully or partially methylated in a number of malignant cell lines. This is the first report of aberrant methylation of BIK, BNIP3, and cFLIP in CaP. Quantitative methylation analysis in prostate tissues identified 5 genes (BNIP3, CDKN2A, DCR1, DCR2 and TMS1) which were frequently methylated in tumors but were unmethylated in 100% of benign tissues. Furthermore, 69% of tumors were methylated in at least one of the five-gene panel. In the case of all genes, except BNIP3, promoter hypermethylation was associated with concurrent downregulation of gene expression.

CONCLUSION: Future examination of this "CaP apoptotic methylation signature" in a larger cohort of patients is justified to further evaluate its value as a diagnostic and prognostic marker.

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Nuclear factor kappa B (NF-kappaB) activation has been proposed as a cardinal feature of tumourigenesis, although the precise mechanism, frequency, relevance, and extent of NF-kappaB activation in lymphomas remain to be fully elucidated. In this study, expression profiling and tissue microarray studies of 209 and 323 non-Hodgkin's lymphomas (NHLs) respectively, including the most frequent sub-types of NHL, were employed to generate a hypothesis concerning the most common NF-kappaB targets in NHL. These analyses showed that NF-kappaB activation is a common phenomenon in NHL, resulting in the expression of distinct sets of NF-kappaB target genes, depending on the cell context. BCL2 and BIRC5/Survivin were identified as key NF-kappaB targets and their expression distinguished small and aggressive B-cell lymphomas, respectively. Interestingly, in the vast majority of B-cell lymphomas, the expression of these markers was mutually exclusive. A set of genes was identified whose expression correlates either with BIRC5/Survivin or with BCL2. BIRC5/Survivin expression, in contrast to BCL2, was associated with a signature of cell proliferation (overexpression of cell cycle control, DNA repair, and polymerase genes), which may contribute to the aggressive phenotype and poor prognosis of these lymphomas. Strikingly, mantle cell lymphoma and chronic lymphocytic leukaemia expressed highly elevated levels of BCL2 protein and mRNA, higher than that observed in reactive mantle zone cells or even in follicular lymphomas, where BCL2 expression is deregulated through the t(14;18) translocation. In parallel with this observation, BIRC5/Survivin expression was higher in Burkitt's lymphoma and diffuse large B-cell lymphoma than in non-tumoural germinal centre cells. In vitro studies confirmed that NF-kappaB activation contributes to the expression of both markers. In cell lines representing aggressive lymphomas, NF-kappaB inhibition resulted in a decrease in BIRC5/Survivin expression. Meanwhile, in chronic lymphocytic leukaemia (CLL)-derived lymphocytes, NF-kappaB inhibition resulted in a marked decrease in BCL2 expression.

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Mycosis fungoides (MF) is the most frequent type of cutaneous T-cell lymphoma, whose diagnosis and study is hampered by its morphologic similarity to inflammatory dermatoses (ID) and the low proportion of tumoral cells, which often account for only 5% to 10% of the total tissue cells. cDNA microarray studies using the CNIO OncoChip of 29 MF and 11 ID cases revealed a signature of 27 genes implicated in the tumorigenesis of MF, including tumor necrosis factor receptor (TNFR)-dependent apoptosis regulators, STAT4, CD40L, and other oncogenes and apoptosis inhibitors. Subsequently a 6-gene prediction model was constructed that is capable of distinguishing MF and ID cases with unprecedented accuracy. This model correctly predicted the class of 97% of cases in a blind test validation using 24 MF patients with low clinical stages. Unsupervised hierarchic clustering has revealed 2 major subclasses of MF, one of which tends to include more aggressive-type MF cases including tumoral MF forms. Furthermore, signatures associated with abnormal immunophenotype (11 genes) and tumor stage disease (5 genes) were identified.

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Promoter hypermethylation is central in deregulating gene expression in cancer. Identification of novel methylation targets in specific cancers provides a basis for their use as biomarkers of disease occurrence and progression. We developed an in silico strategy to globally identify potential targets of promoter hypermethylation in prostate cancer by screening for 5' CpG islands in 631 genes that were reported as downregulated in prostate cancer. A virtual archive of 338 potential targets of methylation was produced. One candidate, IGFBP3, was selected for investigation, along with glutathione-S-transferase pi (GSTP1), a well-known methylation target in prostate cancer. Methylation of IGFBP3 was detected by quantitative methylation-specific PCR in 49/79 primary prostate adenocarcinoma and 7/14 adjacent preinvasive high-grade prostatic intraepithelial neoplasia, but in only 5/37 benign prostatic hyperplasia (P < 0.0001) and in 0/39 histologically normal adjacent prostate tissue, which implies that methylation of IGFBP3 may be involved in the early stages of prostate cancer development. Hypermethylation of IGFBP3 was only detected in samples that also demonstrated methylation of GSTP1 and was also correlated with Gleason score > or =7 (P=0.01), indicating that it has potential as a prognostic marker. In addition, pharmacological demethylation induced strong expression of IGFBP3 in LNCaP prostate cancer cells. Our concept of a methylation candidate gene bank was successful in identifying a novel target of frequent hypermethylation in early-stage prostate cancer. Evaluation of further relevant genes could contribute towards a methylation signature of this disease.

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It is now well established that cancer cells exhibit a number of genetic defects in the machinery that governs programmed cell death and that sabotage of apoptosis is one of the principal factors aiding in the evolution of the carcinogenic phenotype. A number of studies have implicated aberrant DNA methylation as a key survival mechanism in cancer, whereby promoter hypermethylation silences genes essential for many processes including apoptosis. To date, studies on the methylation profile of apoptotic genes have largely focused on cancers of the breast, colon and stomach, with only limited data available on prostate cancer. Here we discuss the major developments in the field of DNA methylation and its role in the regulation of aberrant apoptosis in prostate cancer. The most significant advances have involved the discovery of apoptotic gene targets of methylation, including XAF1, (fragile histidine triad (FHIT ), cellular retinol binding protein 1 (CRBP1), decoy receptor 1(DCR1), decoy receptor 2 (DCR2 ), target of methylation-induced silenceing 1 (TMS1), TNF receptor superfamily, member 6 (FAS), Reprimo (RPRM) and GLI pathogenesis-related 1 (GLIPR1). These genes are reported to be hypermethylated in prostate cancer and some offer potential as diagnostic and prognostic markers. We also introduce the concept of an 'apoptotic methylation signature' for prostate cancer and evaluate its potential in a diagnostic, prognostic and therapeutic setting.

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With over 50 billion downloads and more than 1.3 million apps in Google’s official market, Android has continued to gain popularity amongst smartphone users worldwide. At the same time there has been a rise in malware targeting the platform, with more recent strains employing highly sophisticated detection avoidance techniques. As traditional signature based methods become less potent in detecting unknown malware, alternatives are needed for timely zero-day discovery. Thus this paper proposes an approach that utilizes ensemble learning for Android malware detection. It combines advantages of static analysis with the efficiency and performance of ensemble machine learning to improve Android malware detection accuracy. The machine learning models are built using a large repository of malware samples and benign apps from a leading antivirus vendor. Experimental results and analysis presented shows that the proposed method which uses a large feature space to leverage the power of ensemble learning is capable of 97.3 % to 99% detection accuracy with very low false positive rates.

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Methane-derived authigenic carbonate (MDAC) mound features at the Codling Fault Zone (CFZ), located in shallow waters (50-120m) of the western Irish Sea were investigated and provide a comparison to deep sea MDAC settings. Carbonates consisted of aragonite as the major mineral phase, with δ13C depletion to -50‰ and δ18O enrichment to~2‰. These isotope signatures, together with the co-precipitation of framboidal pyrite confirm that anaerobic oxidation of methane (AOM) is an important process mediating methane release to the water column and the atmosphere in this region. 18O-enrichment could be a result of MDAC precipitation with seawater in colder than present day conditions, or precipitation with 18O-enriched water transported from deep petroleum sources. The 13C depletion of bulk carbonate and sampled gas (-70‰) suggests a biogenic source, but significant mixing of thermogenic gas and depletion of the original isotope signature cannot be ruled out. Active seepage was recorded from one mound and together with extensive areas of reduced sediment, confirms that seepage is ongoing. The mounds appear to be composed of stacked pavements that are largely covered by sand and extensively eroded. The CFZ mounds are colonized by abundant Sabellaria polychaetes and possible Nemertesia hydroids, which benefit indirectly from available hard substrate. In contrast to deep sea MDAC settings where seep-related macrofauna are commonly reported, seep-specialist fauna appear to be lacking at the CFZ. In addition, unlike MDAC in deep waters where organic carbon input from photosynthesis is limited, lipid biomarkers and isotope signatures related to marine planktonic production (e.g. sterols, alkanols) were most abundant. Evidence for microbes involved in AOM was limited from samples taken; possibly due to this dilution effect from organic matter derived from the photic zone, and will require further investigation. 

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One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

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Castrate-resistant prostate cancer (CRPC) is poorly characterized and heterogeneous and while the androgen receptor (AR) is of singular importance, other factors such as c-Myc and the E2F family also play a role in later stage disease. HES6 is a transcription co-factor associated with stem cell characteristics in neural tissue. Here we show that HES6 is up-regulated in aggressive human prostate cancer and drives castration-resistant tumour growth in the absence of ligand binding by enhancing the transcriptional activity of the AR, which is preferentially directed to a regulatory network enriched for transcription factors such as E2F1. In the clinical setting, we have uncovered a HES6-associated signature that predicts poor outcome in prostate cancer, which can be pharmacologically targeted by inhibition of PLK1 with restoration of sensitivity to castration. We have therefore shown for the first time the critical role of HES6 in the development of CRPC and identified its potential in patient-specific therapeutic strategies.

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BACKGROUND: Prostate cancer (PCa) is the most common cancer in men. PCa is strongly age associated; low death rates in surveillance cohorts call into question the widespread use of surgery, which leads to overtreatment and a reduction in quality of life. There is a great need to increase the understanding of tumor characteristics in the context of disease progression.

OBJECTIVE: To perform the first multigenome investigation of PCa through analysis of both autosomal and mitochondrial DNA, and to integrate exome sequencing data, and RNA sequencing and copy-number alteration (CNA) data to investigate how various different tumor characteristics, commonly analyzed separately, are interconnected.

DESIGN, SETTING, AND PARTICIPANTS: Exome sequencing was applied to 64 tumor samples from 55 PCa patients with varying stage and grade. Integrated analysis was performed on a core set of 50 tumors from which exome sequencing, CNA, and RNA sequencing data were available.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Genes, mutated at a significantly higher rate relative to a genomic background, were identified. In addition, mitochondrial and autosomal mutation rates were correlated to CNAs and proliferation, assessed as a cell cycle gene expression signature.

RESULTS AND LIMITATIONS: Genes not previously reported to be significantly mutated in PCa, such as cell division cycle 27 homolog (Saccharomyces cerevisiae) (CDC27), myeloid/lymphoid or mixed-lineage leukemia 3 (MLL3), lysine (K)-specific demethylase 6A (KDM6A), and kinesin family member 5A (KIF5A) were identified. The mutation rate in the mitochondrial genome was 55 times higher than that of the autosomes. Multilevel analysis demonstrated a tight correlation between high reactive-oxygen exposure, chromosomal damage, high proliferation, and in parallel, a transition from multiclonal indolent primary PCa to monoclonal aggressive disease. As we only performed targeted sequence analysis; copy-number neutral rearrangements recently described for PCa were not accounted for.

CONCLUSIONS: The mitochondrial genome displays an elevated mutation rate compared to the autosomal chromosomes. By integrated analysis, we demonstrated that different tumor characteristics are interconnected, providing an increased understanding of PCa etiology.

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The androgen receptor (AR) regulates prostate cell growth in man, and prostate cancer is the commonest cancer in men in the UK. We present a comprehensive analysis of AR binding sites in human prostate cancer tissues, including castrate-resistant prostate cancer (CRPC). We identified thousands of AR binding sites in CRPC tissue, most of which were not identified in PC cell lines. Many adjacent genes showed AR regulation in xenografts but not in cultured LNCaPs, demonstrating an in-vivo-restricted set of AR-regulated genes. Functional studies support a model of altered signaling in vivo that directs AR binding. We identified a 16 gene signature that outperformed a larger in-vitro-derived signature in clinical data sets, showing the importance of persistent AR signaling in CRPC.

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Breast cancer is a heterogeneous disease and several distinct subtypes exist based on differential gene expression patterns. Molecular apocrine tumours were recently identified as an additional subgroup, characterised as oestrogen receptor negative and androgen receptor positive (ER- AR+), but with an expression profile resembling ER+ luminal breast cancer. One possible explanation for the apparent incongruity is that ER gene expression programmes could be recapitulated by AR. Using a cell line model of ER- AR+ molecular apocrine tumours (termed MDA-MB-453 cells), we map global AR binding events and find a binding profile that is similar to ER binding in breast cancer cells. We find that AR binding is a near-perfect subset of FoxA1 binding regions, a level of concordance never previously seen with a nuclear receptor. AR functionality is dependent on FoxA1, since silencing of FoxA1 inhibits AR binding, expression of the majority of the molecular apocrine gene signature and growth cell growth. These findings show that AR binds and regulates ER cis-regulatory elements in molecular apocrine tumours, resulting in a transcriptional programme reminiscent of ER-mediated transcription in luminal breast cancers.

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Conducting atomic force microscopy images of bulk semiconducting BaTiO3 surfaces show clear stripe domain contrast. High local conductance correlates with strong out-of-plane polarization (mapped independently using piezoresponse force microscopy), and current- voltage characteristics are consistent with dipole-induced alterations in Schottky barriers at the metallic tip-ferroelectric interface. Indeed, analyzing current-voltage data in terms of established Schottky barrier models allows relative variations in the surface polarization, and hence the local domain structure, to be determined. Fitting also reveals the signature of surface-related depolarizing fields concentrated near domain walls. Domain information obtained from mapping local conductance appears to be more surface-sensitive than that from piezoresponse force microscopy. In the right materials systems, local current mapping could therefore represent a useful complementary technique for evaluating polarization and local electric fields with nanoscale resolution.

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Diverse land use activities can elevate risk of microbiological contamination entering stream headwaters. Spatially distributed water quality monitoring carried out across a 17km(2) agricultural catchment aimed to characterize microbiological contamination reaching surface water and investigate whether winter agricultural land use restrictions proved effective in addressing water quality degradation. Combined flow and concentration data revealed no significant difference in fecal indicator organism (FIO) fluxes in base flow samples collected during the open and prohibited periods for spreading organic fertilizer, while relative concentrations of Escherichia coli, fecal streptococci and sulfite reducing bacteria indicated consistently fresh fecal pollution reached aquatic receptors during both periods. Microbial source tracking, employing Bacteroides 16S rRNA gene markers, demonstrated a dominance of bovine fecal waste in river water samples upstream of a wastewater treatment plant discharge during open periods. This contrasted with responses during prohibited periods where human-derived signatures dominated. Differences in microbiological signature, when viewed with hydrological data, suggested that increasing groundwater levels restricted vertical infiltration of effluent from on-site wastewater treatment systems and diverted it to drains and surface water. Study results reflect seasonality of contaminant inputs, while suggesting winter land use restrictions can be effective in limiting impacts of agricultural wastes to base flow water quality.