365 resultados para mast cell tumour


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During growth of antral ovarian follicles granulosa cells first become associated with a novel type of extracellular matrix, focimatrix, and at larger sizes follicles become either subordinate or dominant. To examine this, bovine subordinate (9.0±s.e.m. 0.4 mm; n=16), partially dominant (12.0±0.6 mm; n=18) and fully dominant (15.0±0.4 mm; n=14) follicles were examined by real time RT-PCR analyses of granulosa cells and by immunohistochemistry of focimatrix. Changes in the expression of FSH receptor, LH receptor, cholesterol side-chain cleavage (CYP11A1), 3β-hydroxysteroid dehydrogenase, aromatase (CYP19A1) and inhibin-α and β-B were observed as expected for follicle sizes examined. After adjusting for size differences, only CYP11A1 was significantly different between the groups, and elevated in dominant follicles. Also after adjusting for differences in size there were no significant differences in expression of focimatrix components collagen type IV α-1 (COL4A1), laminin β-2, nidogen 1 (NID1), and perlecan (HSPG2) or the volume density of NID1 and -2 and HSPG2. The volume density of focimatrix components in laminin 111 was significantly elevated in dominant follicles. Adjusting for analysis of more than one follicle per animal and for multiple correlations, CYP11A1 mRNA levels were highly correlated with the focimatrix genes COL4A1, NID1 and -2 and HSPG2. Thus, focimatrix may potentially regulate CYP11A1 expression, and the regulation of both could be important in follicular dominance.

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The CDKN2 gene, encoding the cyclin-dependent kinase inhibitor p16, is a tumour suppressor gene that maps to chromosome band 9p21-p22. The most common mechanism of inactivation of this gene in human cancers is through homozygous deletion; however, in a smaller proportion of tumours and tumour cell lines intragenic mutations occur. In this study we have compiled a database of over 120 published point mutations in the CDKN2 gene from a wide variety of tumour types. A further 50 deletions, insertions, and splice mutations in CDKN2 have also been compiled. Furthermore, we have standardised the numbering of all mutations according to the full-length 156 amino acid form of p16. From this study we are able to define several hot spots, some of which occur at conserved residues within the ankyrin domains of p16. While many of the hotspots are shared by a number of cancers, the relative importance of each position varies, possibly reflecting the role of different carcinogens in the development of certain tumours. As reported previously, the mutational spectrum of CDKN2 in melanomas differs from that of internal malignancies and supports the involvement of UV in melanoma tumorigenesis. Notably, 52% of all substitutions in melanoma-derived samples occurred at just six nucleotide positions. Nonsense mutations comprise a comparatively high proportion of mutations present in the CDKN2 gene, and possible explanations for this are discussed.

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The CDKN2A gene maps to chromosome 9p21-22 and is responsible for melanoma susceptibility in some families. Its product, p16, binds specifically to CDK4 and CDK6 in vitro and in vivo, inhibiting their kinase activity. CDKN2A is homozygously deleted or mutated in a large proportion of tumor cell lines and some primary tumors, including melanomas. The aim of this study was to investigate the involvement of CDKN2A and elucidate the mechanisms of p16 inactivation in a panel of 60 cell lines derived from sporadic melanomas. Twenty-six (43%) of the melanoma lines were homozygously deleted for CDKN2A, and an additional 15 (25%) lines carried missense, nonsense, or frameshift mutations. All but one of the latter group were shown by microsatellite analysis to be hemizygous for the region of 9p surrounding CDKN2A. p16 was detected by Western blotting in only five of the cell lines carrying mutations. Immunoprecipitation of p16 in these lines, followed by Western blotting to detect the coprecipitation of CDK4 and CDK6, revealed that p16 was functionally compromised in all cell lines but the one that carried a heterozygous CDKN2A mutation. In the remaining 19 lines that carried wild-type CDKN2A alleles, Western blot analysis and immunoprecipitation indicated that 11 cell lines expressed a wild-type protein. Northern blotting was performed on the remaining eight cell lines and revealed that one cell line carried an aberrantly sized RNA transcript, and two other cell lines failed to express RNA. The promoter was found to be methylated in five cell lines that expressed CDKN2A transcript but not p16. Presumably, the message seen by Northern blotting in these cell lines is the result of cross-hybridization of the total cDNA probe with the exon 1beta transcript. Microsatellite analysis revealed that the majority of these cell lines were hemi/homozygous for the region surrounding CDKN2A, indicating that the wild-type allele had been lost. In the 11 cell lines that expressed functional p16, microsatellite analysis revealed loss of heterozygosity at the markers immediately surrounding CDKN2A in five cases, and the previously characterized R24C mutation of CDK4 was identified in one of the remaining 6 lines. These data indicate that 55 of 60 (92%) melanoma cell lines demonstrated some aberration of CDKN2A or CDK4, thus suggesting that this pathway is a primary genetic target in melanoma development.

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Mutations in exon 3 of the CTNNB1 gene encoding beta-catenin have been reported in colorectal cancer cell lines and tumours. Although one study reported mutations or deletions affecting beta-catenin in 20% of melanoma cell lines, subsequent reports detected a much lower frequency of aberrations in uncultured melanomas. To determine whether this difference in mutation frequency reflected an in vitro culturing artefact, exon 3 of CTNNB1 was screened in a panel of 62 melanoma cell lines. In addition, reverse transcription-polymerase chain reaction (RT-PCR) was performed to detect intragenic deletions affecting exon 3. One out of 62 (1.6%) cell lines was found to carry a mutation, indicating that aberration of the Wnt-1/wingless pathway through activation of beta-catenin is a rare event, even in melanoma cell lines.

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p53 is the central member of a critical tumor suppressor pathway in virtually all tumor types, where it is silenced mainly by missense mutations. In melanoma, p53 predominantly remains wild type, thus its role has been neglected. To study the effect of p53 on melanocyte function and melanomagenesis, we crossed the 'high-p53'Mdm4+/- mouse to the well-established TP-ras0/+ murine melanoma progression model. After treatment with the carcinogen dimethylbenzanthracene (DMBA), TP-ras0/+ mice on the Mdm4+/- background developed fewer tumors with a delay in the age of onset of melanomas compared to TP-ras0/+ mice. Furthermore, we observed a dramatic decrease in tumor growth, lack of metastasis with increased survival of TP-ras0/+: Mdm4+/- mice. Thus, p53 effectively prevented the conversion of small benign tumors to malignant and metastatic melanoma. p53 activation in cultured primary melanocyte and melanoma cell lines using Nutlin-3, a specific Mdm2 antagonist, supported these findings. Moreover, global gene expression and network analysis of Nutlin-3-treated primary human melanocytes indicated that cell cycle regulation through the p21WAF1/CIP1 signaling network may be the key anti-melanomagenic activity of p53.

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Stochastic models for competing clonotypes of T cells by multivariate, continuous-time, discrete state, Markov processes have been proposed in the literature by Stirk, Molina-París and van den Berg (2008). A stochastic modelling framework is important because of rare events associated with small populations of some critical cell types. Usually, computational methods for these problems employ a trajectory-based approach, based on Monte Carlo simulation. This is partly because the complementary, probability density function (PDF) approaches can be expensive but here we describe some efficient PDF approaches by directly solving the governing equations, known as the Master Equation. These computations are made very efficient through an approximation of the state space by the Finite State Projection and through the use of Krylov subspace methods when evolving the matrix exponential. These computational methods allow us to explore the evolution of the PDFs associated with these stochastic models, and bimodal distributions arise in some parameter regimes. Time-dependent propensities naturally arise in immunological processes due to, for example, age-dependent effects. Incorporating time-dependent propensities into the framework of the Master Equation significantly complicates the corresponding computational methods but here we describe an efficient approach via Magnus formulas. Although this contribution focuses on the example of competing clonotypes, the general principles are relevant to multivariate Markov processes and provide fundamental techniques for computational immunology.

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One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.

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Endocytosis is the process by which cells internalise molecules including nutrient proteins from the extracellular media. In one form, macropinocytosis, the membrane at the cell surface ruffles and folds over to give rise to an internalised vesicle. Negatively charged phospholipids within the membrane called phosphoinositides then undergo a series of transformations that are critical for the correct trafficking of the vesicle within the cell, and which are often pirated by pathogens such as Salmonella. Advanced fluorescent video microscopy imaging now allows the detailed observation and quantification of these events in live cells over time. Here we use these observations as a basis for building differential equation models of the transformations. An initial investigation of these interactions was modelled with reaction rates proportional to the sum of the concentrations of the individual constituents. A first order linear system for the concentrations results. The structure of the system enables analytical expressions to be obtained and the problem becomes one of determining the reaction rates which generate the observed data plots. We present results with reaction rates which capture the general behaviour of the reactions so that we now have a complete mathematical model of phosphoinositide transformations that fits the experimental observations. Some excellent fits are obtained with modulated exponential functions; however, these are not solutions of the linear system. The question arises as to how the model may be modified to obtain a system whose solution provides a more accurate fit.