16 resultados para Biology, Molecular|Biology, Neuroscience|Biology, Cell|Chemistry, Biochemistry


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Background: There is an urgent need to identify molecular signatures in small cell lung cancer (SCLC) that may select patients who are likely to respond to molecularly targeted therapies. In this study, we investigate the feasibility of undertaking focused molecular analyses on routine diagnostic biopsies in patients with SCLC.

Methods: A series of histopathologically confirmed formalin-fixed, paraffin-embedded SCLC specimens were analysed for epidermal growth factor receptors (EGFR), KRAS, NRAS and BRAF mutations, ALK gene rearrangements and MET amplification. EGFR and KRAS mutation testing was evaluated using real time polymerase chain reaction (RT-PCR cobas®), BRAF and NRAS mutations using multiplex PCR and capillary electrophoresis-single strand conformation analysis, and ALK and MET aberrations with fluorescent in situ hybridization. All genetic aberrations detected were validated independently.

Results: A total of 105 patients diagnosed with SCLC between July 1990 and September 2006 were included. 60 (57 %) patients had suitable tumour tissue for molecular testing. 25 patients were successfully evaluated for all six pre-defined molecular aberrations. Eleven patients failed all molecular analysis. No mutations in EGFR, KRAS and NRAS were detected, and no ALK gene rearrangements or MET gene amplifications were identified. A V600E substitution in BRAF was detected in a Caucasian male smoker diagnosed with SCLC with squamoid and glandular features.

Conclusion: The paucity of patients with sufficient tumour tissue, quality of DNA extracted and low frequency of aberrations detected indicate that alternative molecular characterisation approaches are necessary, such as the use of circulating plasma DNA in patients with SCLC.

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Hairy cell leukaemia variant (HCL-variant) and splenic marginal zone lymphoma (SMZL) are disorders with overlapping features. We investigated the prognostic impact in these disorders of clinical and molecular features including IGH VDJ rearrangements, IGHV gene usage and TP 53 mutations. Clinical and laboratory data were collected before therapy from 35 HCL-variant and 68 SMZL cases. End-points were the need for treatment and overall survival. 97% of HCL-variant and 77% of SMZL cases required treatment (P = 0·009). Survival at 5 years was significantly worse in HCL-variant [57% (95% confidence interval 38-73%)] compared with SMZL [84% (71-91%); Hazard Ratio 2·25 (1·20-4·25), P = 0·01]. In HCL-variant, adverse prognostic factors for survival were older age (P = 0·04), anaemia (P = 0·01) and TP 53 mutations (P = 0·02). In SMZL, splenomegaly, anaemia and IGHV genes with >98% homology to the germline predicted the need for treatment; older age, anaemia and IGHV unmutated genes (100% homology) predicted shorter survival. IGHV gene usage had no impact on clinical outcome in either disease. The combination of unfavourable factors allowed patients to be stratified into risk groups with significant differences in survival. Although HCL-variant and SMZL share some features, they have different outcomes, influenced by clinical and biological factors.

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Our previous studies have shown that overexpression of beta1,4-galactosyltransferase1 (beta1,4GT1) leads to increased apoptosis induced by cycloheximide (CHX) in SMMC-7721 human hepatocarcinoma cells. However, the role of beta1,4GT1 in apoptosis remains unclear. Here we demonstrated that cell surface beta1,4GT1 inhibited the autophosphorylation of epidermal growth factor receptor (EGFR) especially at Try 1068. The phosphorylation of protein kinase B (PKB/Akt) and extracellular signal-regulated protein kinase1/2 (ERK1/2), which are downstream molecules of EGFR, were also reduced in cell surface beta1,4GT1-overexpressing cells. Furthermore, the translocations of Bad and Bax that are regulated by PKB/Akt and ERK1/2 were also increased in these cells. As a result, the release of cytochrome c from mitochondria to cytosol was increased and caspase-3 was activated. In contrast, RNAi-mediated knockdown of beta1,4GT1 increased the autophosphorylation of EGFR. These results demonstrated that cell surface beta1,4GT1 may negatively regulate cell survival possibly through inhibiting and modulating EGFR signaling pathway.

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Much research over the past two decades has focussed on understanding the complex interactions of nitric oxide (NO()) in both physiological and pathological processes. As with many other aspects of NO() biology, its precise role in tumour pathophysiology has been the cause of intense debate and we now know that it participates in numerous signalling pathways that are crucial to the malignant character of cancer. The available experimental evidence highlights contrasting pro- and anti-tumour effects of NO() expression, which appear to be reconciled by consideration of the concentrations involved. This review addresses the complexities of the role of NO() in cancer, whilst evaluating various experimental approaches to NO()-based cancer therapies, including both inhibition of nitric oxide synthases, and overexpression of NO() using donor drugs or nitric oxide synthase gene transfer. The evidence provided strongly supports a role for manipulation of tumour NO() either as a stand-alone therapy or in combination with conventional treatments to achieve a significant therapeutic gain.

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Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure. which encourages further research towards a higher-dimensional analysis of Pareto fronts. (C) 2010 Elsevier Ltd. All rights reserved.

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We present results from three-dimensional protein folding simulations in the HP-model on ten benchmark problems. The simulations are executed by a simulated annealing-based algorithm with a time-dependent cooling schedule. The neighbourhood relation is determined by the pull-move set. The results provide experimental evidence that the maximum depth D of local minima of the underlying energy landscape can be upper bounded by D < n(2/3). The local search procedure employs the stopping criterion (In/delta)(D/gamma) where m is an estimation of the average number of neighbouring conformations, gamma relates to the mean of non-zero differences of the objective function for neighbouring conformations, and 1-delta is the confidence that a minimum conformation has been found. The bound complies with the results obtained for the ten benchmark problems. (c) 2008 Elsevier Ltd. All rights reserved.

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We present experimental results on benchmark problems in 3D cubic lattice structures with the Miyazawa-Jernigan energy function for two local search procedures that utilise the pull-move set: (i) population-based local search (PLS) that traverses the energy landscape with greedy steps towards (potential) local minima followed by upward steps up to a certain level of the objective function; (ii) simulated annealing with a logarithmic cooling schedule (LSA). The parameter settings for PLS are derived from short LSA-runs executed in pre-processing and the procedure utilises tabu lists generated for each member of the population. In terms of the total number of energy function evaluations both methods perform equally well, however. PLS has the potential of being parallelised with an expected speed-up in the region of the population size. Furthermore, both methods require a significant smaller number of function evaluations when compared to Monte Carlo simulations with kink-jump moves. (C) 2009 Elsevier Ltd. All rights reserved.

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In this paper we define the structural information content of graphs as their corresponding graph entropy. This definition is based on local vertex functionals obtained by calculating-spheres via the algorithm of Dijkstra. We prove that the graph entropy and, hence, the local vertex functionals can be computed with polynomial time complexity enabling the application of our measure for large graphs. In this paper we present numerical results for the graph entropy of chemical graphs and discuss resulting properties. (C) 2007 Elsevier Ltd. All rights reserved.