166 research outputs found

    No hormonal chemoprevention in breast cancer

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    A Study of the PDGF Signaling Pathway with PRISM

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    In this paper, we apply the probabilistic model checker PRISM to the analysis of a biological system -- the Platelet-Derived Growth Factor (PDGF) signaling pathway, demonstrating in detail how this pathway can be analyzed in PRISM. We show that quantitative verification can yield a better understanding of the PDGF signaling pathway.Comment: In Proceedings CompMod 2011, arXiv:1109.104

    Differential modulatory effects of GSK-3β and HDM2 on sorafenib-induced AIF nuclear translocation (programmed necrosis) in melanoma

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    <p>Abstract</p> <p>Background</p> <p>GSK-3β phosphorylates numerous substrates that govern cell survival. It phosphorylates p53, for example, and induces its nuclear export, HDM2-dependent ubiquitination, and proteasomal degradation. GSK-3β can either enhance or inhibit programmed cell death, depending on the nature of the pro-apoptotic stimulus. We previously showed that the multikinase inhibitor sorafenib activated GSK-3β and that this activation attenuated the cytotoxic effects of the drug in various BRAF-mutant melanoma cell lines. In this report, we describe the results of studies exploring the effects of GSK-3β on the cytotoxicity and antitumor activity of sorafenib combined with the HDM2 antagonist MI-319.</p> <p>Results</p> <p>MI-319 alone increased p53 levels and p53-dependent gene expression in melanoma cells but did not induce programmed cell death. Its cytotoxicity, however, was augmented in some melanoma cell lines by the addition of sorafenib. In responsive cell lines, the MI-319/sorafenib combination induced the disappearance of p53 from the nucleus, the down modulation of Bcl-2 and Bcl-x<sub>L</sub>, the translocation of p53 to the mitochondria and that of AIF to the nuclei. These events were all GSK-3β-dependent in that they were blocked with a GSK-3β shRNA and facilitated in otherwise unresponsive melanoma cell lines by the introduction of a constitutively active form of the kinase (GSK-3β-S9A). These modulatory effects of GSK-3β on the activities of the sorafenib/MI-319 combination were the exact reverse of its effects on the activities of sorafenib alone, which induced the down modulation of Bcl-2 and Bcl-x<sub>L </sub>and the nuclear translocation of AIF only in cells in which GSK-3β activity was either down modulated or constitutively low. In A375 xenografts, the antitumor effects of sorafenib and MI-319 were additive and associated with the down modulation of Bcl-2 and Bcl-x<sub>L</sub>, the nuclear translocation of AIF, and increased suppression of tumor angiogenesis.</p> <p>Conclusions</p> <p>Our data demonstrate a complex partnership between GSK-3β and HDM2 in the regulation of p53 function in the nucleus and mitochondria. The data suggest that the ability of sorafenib to activate GSK-3β and alter the intracellular distribution of p53 may be exploitable as an adjunct to agents that prevent the HDM2-dependent degradation of p53 in the treatment of melanoma.</p

    Stabilisation of β-Catenin Downstream of T Cell Receptor Signalling

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    The role of TCF/β-catenin signalling in T cell development is well established, but important roles in mature T cells have only recently come to light.Here we have investigated the signalling pathways that are involved in the regulation of β-catenin in primary human T cells. We demonstrate that β-catenin expression is upregulated rapidly after T cell receptor (TCR) stimulation and that this involves protein stabilisation rather than an increase in mRNA levels. Similar to events in Wnt signalling, the increase in β-catenin coincides with an inhibition of GSK3, the kinase that is required for β-catenin degradation. β-catenin stabilisation in T cells can also be induced by the activation of PKC with phorbol esters and is blocked by inhibitors of phosphatidylinositol 3-kinase (PI3K) and phospholipase C (PKC). Upon TCR signalling, β-catenin accumulates in the nucleus and, parallel to this, the ratio of TCF1 isoforms is shifted in favour of the longer β-catenin binding isoforms. However, phosphorylated β-catenin, which is believed to be inactive, can also be detected and the expression of Wnt target genes Axin2 and dickkopf is down regulated.These data show that in mature human T cells, TCR signalling via PI3K and PKC can result in the stabilisation of β-catenin, allowing β-catenin to migrate to the nucleus. They further highlight important differences between β-catenin activities in TCR and Wnt signalling

    Rho GTPase Cdc42 Is a Direct Interacting Partner of Adenomatous Polyposis Coli Protein and Can Alter Its Cellular Localization

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    Adenomatous Polyposis Coli (APC) is a tumor suppressor gene product involved in colon cancer. APC is a large multidomain molecule of 2843 amino acid residues and connects cell-cell adhesion, the F-actin/microtubule cytoskeleton and the nucleus. Here we show that Cdc42 interacts directly with the first three armadillo repeats of APC by yeast two-hybrid screens. We confirm the Cdc42-APC interaction using pulldown assays in vitro and FRET assays in vivo. Interestingly, Cdc42 interacts with APC at leading edge sites where F-actin is enriched. In contrast, Cdc42 interacts with the truncated mutant APC1–1638 in cellular puncta associated with the golgi-lysozome pathway in transfected CHO cells. In HCT116 and SW480 cells, Cdc42 induces the relocalization of endogenous APC and the mutant APC1–1338 to the plasma membrane and cellular puncta, respectively. Taken together, these data indicate that the Cdc42-APC interaction induces localization of both APC and mutant APC and may thus play a direct role in the functions of these proteins

    Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines

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    <p>Abstract</p> <p>Background</p> <p>Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.</p> <p>Results</p> <p>43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (<it>CFTR</it>, <it>ROBO1</it>, <it>PTPRD</it>, <it>BTBD12</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD</it>, <it>LPHN2</it>, <it>GRIK1</it>, <it>ZNF607</it>). SNPs in <it>GRIK1</it>, <it>DCT</it>, <it>SGCD </it>and <it>CFTR </it>were predicted to be intronic enhancers, altering gene expression, while SNPs in <it>ZNF607 </it>and <it>BTBD12 </it>cause conservative missense mutations. mRNA expression analysis supported these findings as <it>GRIK1</it>, <it>DCT</it>, <it>SNTG1</it>, <it>SGCD </it>and <it>CFTR </it>showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in <it>GRIK1, SGCD, ROBO1, LPHN2</it>, and <it>PTPRD </it>were more strongly associated with response than their individual SNPs.</p> <p>Conclusions</p> <p>Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.</p

    Histopathological growth patterns as biomarker for adjuvant systemic chemotherapy in patients with resected colorectal liver metastases

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    Adjuvant systemic chemotherapy (CTx) is widely administered in patients with colorectal liver metastases (CRLM). Histopathological growth patterns (HGPs) are an independent prognostic factor for survival after complete resection. This study evaluates whether HGPs can predict the efectiveness of adjuvant CTx in patients with resected CRLM. Two main types of HGPs can be distinguished; the desmoplastic type and the non-desmoplastic type. Uni- and multivariable analyses for overall survival (OS) and disease-free survival (DFS) were performed, in both patients treated with and without preoperative chemotherapy. A total of 1236 patients from two tertiary centers (Memorial Sloan Kettering Cancer Center, New York, USA; Erasmus MC Cancer Institute, Rotterdam, The Netherlands) were included (period 2000–2016). A total of 656 patients (53.1%) patients received preoperative chemotherapy. Adjuvant CTx was only associated with a superior OS in non-desmoplastic patients that had not been pretreated (adjusted hazard ratio (HR) 0.52, 95% confdence interval (CI) 0.37–0.73, p<0.001), and not in desmoplastic patients (adjusted HR 1.78, 95% CI 0.75–4.21, p=0.19). In pretreated patients no signifcant efect of adjuvant CTx was observed, neither in the desmoplastic group (adjusted HR 0.83, 95% CI 0.49–1.42, p=0.50) nor in the non-desmoplastic group (adjusted HR 0.96, 95% CI 0.71–1.29, p=0.79). Similar results were found for DFS, with a superior DFS in non-desmoplastic patients treated with adjuvant CTx (HR 0.71, 95% CI 0.55–0.93, p<0.001) that were not pretreated. Adjuvant CTx seems to improve OS and DFS after resection of non-desmoplastic CRLM. However, this efect was only observed in patients that were not treated with chemotherap
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