120 research outputs found

    Nuclear Entry of Activated MAPK Is Restricted in Primary Ovarian and Mammary Epithelial Cells

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    The MAPK/ERK1/2 serine kinases are primary mediators of the Ras mitogenic signaling pathway. Phosphorylation by MEK activates MAPK/ERK in the cytoplasm, and phospho-ERK is thought to enter the nucleus readily to modulate transcription.Here, however, we observe that in primary cultures of breast and ovarian epithelial cells, phosphorylation and activation of ERK1/2 are disassociated from nuclear translocalization and transcription of downstream targets, such as c-Fos, suggesting that nuclear translocation is limited in primary cells. Accordingly, in import assays in vitro, primary cells showed a lower import activity for ERK1/2 than cancer cells, in which activated MAPK readily translocated into the nucleus and activated c-Fos expression. Primary cells express lower levels of nuclear pore complex proteins and the nuclear transport factors, importin B1 and importin 7, which may explain the limiting ERK1/2 import found in primary cells. Additionally, reduction in expression of nucleoporin 153 by siRNA targeting reduced ERK1/2 nuclear activity in cancer cells.ERK1/2 activation is dissociated from nuclear entry, which is a rate limiting step in primary cells and in vivo, and the restriction of nuclear entry is disrupted in transformed cells by the increased expression of nuclear pores and/or nuclear transport factors

    Spatio-temporal Models of Lymphangiogenesis in Wound Healing

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    Several studies suggest that one possible cause of impaired wound healing is failed or insufficient lymphangiogenesis, that is the formation of new lymphatic capillaries. Although many mathematical models have been developed to describe the formation of blood capillaries (angiogenesis), very few have been proposed for the regeneration of the lymphatic network. Lymphangiogenesis is a markedly different process from angiogenesis, occurring at different times and in response to different chemical stimuli. Two main hypotheses have been proposed: 1) lymphatic capillaries sprout from existing interrupted ones at the edge of the wound in analogy to the blood angiogenesis case; 2) lymphatic endothelial cells first pool in the wound region following the lymph flow and then, once sufficiently populated, start to form a network. Here we present two PDE models describing lymphangiogenesis according to these two different hypotheses. Further, we include the effect of advection due to interstitial flow and lymph flow coming from open capillaries. The variables represent different cell densities and growth factor concentrations, and where possible the parameters are estimated from biological data. The models are then solved numerically and the results are compared with the available biological literature.Comment: 29 pages, 9 Figures, 6 Tables (39 figure files in total

    An Intermittent Live Cell Imaging Screen for siRNA Enhancers and Suppressors of a Kinesin-5 Inhibitor

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    Kinesin-5 (also known as Eg5, KSP and Kif11) is required for assembly of a bipolar mitotic spindle. Small molecule inhibitors of Kinesin-5, developed as potential anti-cancer drugs, arrest cell in mitosis and promote apoptosis of cancer cells. We performed a genome-wide siRNA screen for enhancers and suppressors of a Kinesin-5 inhibitor in human cells to elucidate cellular responses, and thus identify factors that might predict drug sensitivity in cancers. Because the drug's actions play out over several days, we developed an intermittent imaging screen. Live HeLa cells expressing GFP-tagged histone H2B were imaged at 0, 24 and 48 hours after drug addition, and images were analyzed using open-source software that incorporates machine learning. This screen effectively identified siRNAs that caused increased mitotic arrest at low drug concentrations (enhancers), and vice versa (suppressors), and we report siRNAs that caused both effects. We then classified the effect of siRNAs for 15 genes where 3 or 4 out of 4 siRNA oligos tested were suppressors as assessed by time lapse imaging, and by testing for suppression of mitotic arrest in taxol and nocodazole. This identified 4 phenotypic classes of drug suppressors, which included known and novel genes. Our methodology should be applicable to other screens, and the suppressor and enhancer genes we identified may open new lines of research into mitosis and checkpoint biology

    Autocrine Activation of the MET Receptor Tyrosine Kinase in Acute Myeloid Leukemia

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    Although the treatment of acute myeloid leukemia (AML) has improved significantly, more than half of all patients develop disease that is refractory to intensive chemotherapy. Functional genomics approaches offer a means to discover specific molecules mediating aberrant growth and survival of cancer cells. Thus, using a loss-of-function RNA interference genomic screen, we identified aberrant expression of the hepatocyte growth factor (HGF) as a critical factor in AML pathogenesis. We found HGF expression leading to autocrine activation of its receptor tyrosine kinase, MET, in nearly half of the AML cell lines and clinical samples studied. Genetic depletion of HGF or MET potently inhibited the growth and survival of HGF-expressing AML cells. However, leukemic cells treated with the specific MET kinase inhibitor crizotinib developed resistance due to compensatory upregulation of HGF expression, leading to restoration of MET signaling. In cases of AML where MET is coactivated with other tyrosine kinases, such as fibroblast growth factor receptor 1 (FGFR1), concomitant inhibition of FGFR1 and MET blocked compensatory HGF upregulation, resulting in sustained logarithmic cell kill both in vitro and in xenograft models in vivo. Our results demonstrate widespread dependence of AML cells on autocrine activation of MET, as well as the importance of compensatory upregulation of HGF expression in maintaining leukemogenic signaling by this receptor. We anticipate that these findings will lead to the design of additional strategies to block adaptive cellular responses that drive compensatory ligand expression as an essential component of the targeted inhibition of oncogenic receptors in human cancers

    Successful Inhibition of Tumor Development by Specific Class-3 Semaphorins Is Associated with Expression of Appropriate Semaphorin Receptors by Tumor Cells

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    The class-3 semaphorins (sema3s) include seven family members. Six of them bind to neuropilin-1 (np1) or neuropilin-2 (np2) receptors or to both, while the seventh, sema3E, binds to the plexin-D1 receptor. Sema3B and sema3F were previously characterized as tumor suppressors and as inhibitors of tumor angiogenesis. To determine if additional class-3 semaphorins such as sema3A, sema3D, sema3E and sema3G possess anti-angiogenic and anti-tumorigenic properties, we expressed the recombinant full length semaphorins in four different tumorigenic cell lines expressing different combinations of class-3 semaphorin receptors. We show for the first time that sema3A, sema3D, sema3E and sema3G can function as potent anti-tumorigenic agents. All the semaphorins we examined were also able to reduce the concentration of tumor associated blood vessels although the potencies of the anti-angiogenic effects varied depending on the tumor cell type. Surprisingly, there was little correlation between the ability to inhibit tumor angiogenesis and their anti-tumorigenic activity. None of the semaphorins inhibited the adhesion of the tumor cells to plastic or fibronectin nor did they modulate the proliferation of tumor cells cultured in cell culture dishes. However, various semaphorins were able to inhibit the formation of soft agar colonies from tumor cells expressing appropriate semaphorin receptors, although in this case too the inhibitory effect was not always correlated with the anti-tumorigenic effect. In contrast, the anti-tumorigenic effect of each of the semaphorins correlated very well with tumor cell expression of specific signal transducing receptors for particular semaphorins. This correlation was not broken even in cases in which the tumor cells expressed significant concentrations of endogenous semaphorins. Our results suggest that combinations of different class-3 semaphorins may be more effective than single semaphorins in cases in which tumor cells express more than one type of semaphorin receptors

    Functional genomic analysis of drug sensitivity pathways to guide adjuvant strategies in breast cancer

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    The widespread introduction of high throughput RNA interference screening technology has revealed tumour drug sensitivity pathways to common cytotoxics such as paclitaxel, doxorubicin and 5-fluorouracil, targeted agents such as trastuzumab and inhibitors of AKT and Poly(ADP-ribose) polymerase (PARP) as well as endocrine therapies such as tamoxifen. Given the limited power of microarray signatures to predict therapeutic response in associative studies of small clinical trial cohorts, the use of functional genomic data combined with expression or sequence analysis of genes and microRNAs implicated in drug response in human tumours may provide a more robust method to guide adjuvant treatment strategies in breast cancer that are transferable across different expression platforms and patient cohorts

    Discovering cancer genes by integrating network and functional properties

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    <p>Abstract</p> <p>Background</p> <p>Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes.</p> <p>Methods</p> <p>Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1.</p> <p>Results</p> <p>Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs) with the inclusion of the topological features from the PPI network, protein domain compositions and GO annotations. We then applied the trained SVM classifier to human genes to prioritize putative cancer genes. siRNA knock-down of several SVM predicted cancer genes displayed greatly reduced cell viability in human colon cancer cell line DLD-1.</p> <p>Conclusion</p> <p>Topological features of PPI networks, protein domain compositions and GO annotations are good predictors of cancer genes. The SVM classifier integrates multiple features and as such is useful for prioritizing candidate cancer genes for experimental validations.</p
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