Regulation of Fas-Mediated Apoptosis by N-ras in Melanoma

Oncogenic ras has been shown to downregulate Fas receptor expression and increase Fas ligand expression and thus contribute to resistance to Fas-mediated cell death in several cell types. The effects of ras on Fas-mediated apoptosis have not been studied in melanoma. We studied the effects of activated N-ras by measuring Fas, Fas ligand, and FLIP expression as well as susceptibility to Fas-ligand-induced cell death in transfectants of WM35, a radial growth phase human melanoma cell line. Based on quantitative polymerase chain reaction and fluorescence-activated cell sorter analysis, we found that the ras transfectants expressed less Fas mRNA and surface Fas receptor. Cr51 release cytotoxicity assays demonstrated less susceptibility to Fas-mediated apoptosis in ras transfectants, correlating with the Fas mRNA and protein expression results. Ras inhibition with the specific inhibitor FTI-277 showed that downregulation of Fas in the ras transfectants could be reversed. This correlates with cytotoxicity experiments showing that ras inhibition increases susceptibility to Fas-mediated apoptosis. The control transfectants expressed FLIP but ras did not affect FLIP expression. The control and ras transfectants did not express Fas ligand as demonstrated by reverse transcriptase polymerase chain reaction and fluorescence-activated cell sorter analysis. Cytotoxicity assays further confirmed that these melanoma ras transfectants do not express functional Fas ligand. These results suggest that ras contributes to tumor progression by decreasing susceptibility to Fas-mediated cell death at least in part through downregulation of Fas receptor at the transcriptional level

Measurement of cathode luminescence efficiency of phosphors for micro-channel plate based x-ray framing cameras

Abstract not provide

Matrix Metalloproteinase-9 (MMP-9) polymorphisms in patients with cutaneous malignant melanoma

BACKGROUND: Cutaneous Malignant Melanoma causes over 75% of skin cancer-related deaths, and it is clear that many factors may contribute to the outcome. Matrix Metalloproteinases (MMPs) play an important role in the degradation and remodeling of the extracellular matrix and basement membrane that, in turn, modulate cell division, migration and angiogenesis. Some polymorphisms are known to influence gene expression, protein activity, stability, and interactions, and they were shown to be associated with certain tumor phenotypes and cancer risk. METHODS: We tested seven polymorphisms within the MMP-9 gene in 1002 patients with melanoma in order to evaluate germline genetic variants and their association with progression and known risk factors of melanoma. The polymorphisms were selected based on previously published reports and their known or potential functional relevance using in-silico methods. Germline DNA was then genotyped using pyrosequencing, melting temperature profiles, heteroduplex analysis, and fragment size analysis. RESULTS: We found that reference alleles were present in higher frequency in patients who tend to sunburn, have family history of melanoma, higher melanoma stage, intransit metastasis and desmoplastic melanomas among others. However, after adjustment for age, sex, phenotypic index, moles, and freckles only Q279R, P574R and R668Q had significant associations with intransit metastasis, propensity to tan/sunburn and primary melanoma site. CONCLUSION: This study does not provide strong evidence for further investigation into the role of the MMP-9 SNPs in melanoma progression

Does Kin Recognition and Sib-Mating Avoidance Limit the Risk of Genetic Incompatibility in a Parasitic Wasp?

Background: When some combinations of maternal and paternal alleles have a detrimental effect on offspring fitness, females should be able to choose mates on the basis of their genetic compatibility. In numerous Hymenoptera, the sex of an individual depends of the allelic combination at a specific locus (single-locus Complementary Sex Determination), and in most of these species individuals that are homozygous at this sexual locus develop into diploid males with zero fitness. Methods and Findings: In this paper, we tested the hypothesis of genetic incompatibility avoidance by investigating sibmating avoidance in the solitary wasp parasitoid, Venturia canescens. In the context of mate choice we show, for the first time in a non-social hymenopteran species, that females can avoid mating with their brothers through kin recognition. In ‘‘no-choice’ ’ tests, the probability a female will mate with an unrelated male is twice as high as the chance of her mating with her brothers. In contrast, in choice tests in small test arenas, no kin discrimination effect was observed. Further experiments with male extracts demonstrate that chemical cues emanating from related males influence the acceptance rate of unrelated males. Conclusions: Our results are compatible with the genetic incompatibility hypothesis. They suggest that the female wasps recognize sibs on the basis of a chemical signature carried or emitted by males possibly using a ‘‘self-referent phenotyp

Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>A reverse engineering of gene regulatory network with large number of genes and limited number of experimental data points is a computationally challenging task. In particular, reverse engineering using linear systems is an underdetermined and ill conditioned problem, i.e. the amount of microarray data is limited and the solution is very sensitive to noise in the data. Therefore, the reverse engineering of gene regulatory networks with large number of genes and limited number of data points requires rigorous optimization algorithm.</p> <p>Results</p> <p>This study presents a novel algorithm for reverse engineering with linear systems. The proposed algorithm is a combination of the orthogonal least squares, second order derivative for network pruning, and Bayesian model comparison. In this study, the entire network is decomposed into a set of small networks that are defined as unit networks. The algorithm provides each unit network with P(D|H_i), which is used as confidence level. The unit network with higher P(D|H_i) has a higher confidence such that the unit network is correctly elucidated. Thus, the proposed algorithm is able to locate true positive interactions using P(D|H_i), which is a unique property of the proposed algorithm.</p> <p>The algorithm is evaluated with synthetic and <it>Saccharomyces cerevisiae </it>expression data using the dynamic Bayesian network. With synthetic data, it is shown that the performance of the algorithm depends on the number of genes, noise level, and the number of data points. With Yeast expression data, it is shown that there is remarkable number of known physical or genetic events among all interactions elucidated by the proposed algorithm.</p> <p>The performance of the algorithm is compared with Sparse Bayesian Learning algorithm using both synthetic and <it>Saccharomyces cerevisiae </it>expression data sets. The comparison experiments show that the algorithm produces sparser solutions with less false positives than Sparse Bayesian Learning algorithm.</p> <p>Conclusion</p> <p>From our evaluation experiments, we draw the conclusion as follows: 1) Simulation results show that the algorithm can be used to elucidate gene regulatory networks using limited number of experimental data points. 2) Simulation results also show that the algorithm is able to handle the problem with noisy data. 3) The experiment with Yeast expression data shows that the proposed algorithm reliably elucidates known physical or genetic events. 4) The comparison experiments show that the algorithm more efficiently performs than Sparse Bayesian Learning algorithm with noisy and limited number of data.</p