850 research outputs found

    Chemical models important in understanding the ways in which chromate can damage DNA.

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    Chromate is an established human carcinogen. There have been many studies of the reactivity of chromate aimed at improving understanding of chromate toxicity. In the present paper a number of conclusions of these studies are reviewed and considered in the light of new results obtained in our laboratories. A number of hypotheses are considered; it is concluded, however, that it is impossible to reconcile the generation of strand breaks by chromate during its reduction by glutathione with any simple mechanism involving the generation of DNA lesions by free hydroxyl radicals. Kinetic, spin-trapping, and competition kinetic studies, based on a strand-breaking assay, are reported in support of this conclusion

    Dasatinib, a Src inhibitor, sensitizes liver metastatic colorectal carcinoma to oxaliplatin in tumors with high levels of phospho-Src.

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    Despite the development of new antineoplastic agents for the treatment of colorectal cancer (CRC), oxaliplatin and fluoropyrimidines remain the most commonly employed drugs for the treatment of both early and advanced disease. Intrinsic or acquired resistance is, however, an important limitation to pharmacological therapy, and the development of chemosensitization strategies constitute a major goal with important clinical implications. In the present work, we determined that high levels of activated Src kinase, measured as phospho-Src at the Tyr419 residue in CRC cell lines, can promote colorectal carcinoma cell resistance to oxaliplatin, but not to 5-fluorouracil (5FU), and that inhibition of this protein restores sensitivity to oxaliplatin. Similar results were observed with in vivo patient-derived xenograft (PDX) models that were orthotopically grown in murine livers. In PDX tumor lines derived from human CRC liver metastasis, dasatinib, a Src inhibitor, increases sensitivity to oxaliplatin only in tumors with high p-Src. However, dasatinib did not modify sensitivity to 5FU in any of the models. Our data suggest that chemoresistance induced by p-Src is specific to oxaliplatin, and that p-Src levels can be used to identify patients who may benefit from this combination therapy. These results are relevant for clinicians as they identify a novel biomarker of drug resistance that is suitable to pharmacological manipulation.HUVR-IBiS Biobanco del Sistema Sanitario Público de Andalucía y ISCIII-Red de Biobancos [PT13/0010/0056].FEDER from Regional Development European Funds (European Union), Ministerio de Economía y Competitividad, Plan Nacional de I+D+I 2008-2011, Plan Estatal de I+D+i 2013-2016, ISCIII [Fis: PI12/00137, PI13/02295, PI15/00045, RTICC: RD12/0036/0028].Consejería de Ciencia e Innovación [CTS-1848] y Consejería de Salud de la Junta de Andalucía [PI-0306-2012, PI-0096-2014]

    Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses.

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    Multi-omics datasets can provide molecular insights beyond the sum of individual omics. Various tools have been recently developed to integrate such datasets, but there are limited strategies to systematically extract mechanistic hypotheses from them. Here, we present COSMOS (Causal Oriented Search of Multi-Omics Space), a method that integrates phosphoproteomics, transcriptomics, and metabolomics datasets. COSMOS combines extensive prior knowledge of signaling, metabolic, and gene regulatory networks with computational methods to estimate activities of transcription factors and kinases as well as network-level causal reasoning. COSMOS provides mechanistic hypotheses for experimental observations across multi-omics datasets. We applied COSMOS to a dataset comprising transcriptomics, phosphoproteomics, and metabolomics data from healthy and cancerous tissue from eleven clear cell renal cell carcinoma (ccRCC) patients. COSMOS was able to capture relevant crosstalks within and between multiple omics layers, such as known ccRCC drug targets. We expect that our freely available method will be broadly useful to extract mechanistic insights from multi-omics studies

    Cellular expression, trafficking, and function of two isoforms of human ULBP5/RAET1G

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    Background: The activating immunoreceptor NKG2D is expressed on Natural Killer (NK) cells and subsets of T cells. NKG2D contributes to anti-tumour and anti-viral immune responses in vitro and in vivo. The ligands for NKG2D in humans are diverse proteins of the MIC and ULBP/RAET families that are upregulated on the surface of virally infected cells and tumours. Two splicing variants of ULBP5/RAET1G have been cloned previously, but not extensively characterised. Methodology/Principal Findings: We pursue a number of approaches to characterise the expression, trafficking, and function of the two isoforms of ULBP5/RAET1G. We show that both transcripts are frequently expressed in cell lines derived from epithelial cancers, and in primary breast cancers. The full-length transcript, RAET1G1, is predicted to encode a molecule with transmembrane and cytoplasmic domains that are unique amongst NKG2D ligands. Using specific anti-RAET1G1 antiserum to stain tissue microarrays we show that RAET1G1 expression is highly restricted in normal tissues. RAET1G1 was expressed at a low level in normal gastrointestinal epithelial cells in a similar pattern to MICA. Both RAET1G1 and MICA showed increased expression in the gut of patients with celiac disease. In contrast to healthy tissues the RAET1G1 antiserum stained a wide variety or different primary tumour sections. Both endogenously expressed and transfected RAET1G1 was mainly found inside the cell, with a minority of the protein reaching the cell surface. Conversely the truncated splicing variant of RAET1G2 was shown to encode a soluble molecule that could be secreted from cells. Secreted RAET1G2 was shown to downregulate NKG2D receptor expression on NK cells and hence may represent a novel tumour immune evasion strategy. Conclusions/Significance: We demonstrate that the expression patterns of ULBP5RAET1G are very similar to the well-characterised NKG2D ligand, MICA. However the two isoforms of ULBP5/RAET1G have very different cellular localisations that are likely to reflect unique functionality

    µ-Calpain Conversion of Antiapoptotic Bfl-1 (BCL2A1) into a Prodeath Factor Reveals Two Distinct alpha-Helices Inducing Mitochondria-Mediated Apoptosis

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    Anti-apoptotic Bfl-1 and pro-apoptotic Bax, two members of the Bcl-2 family sharing a similar structural fold, are classically viewed as antagonist regulators of apoptosis. However, both proteins were reported to be death inducers following cleavage by the cysteine protease µ-calpain. Here we demonstrate that calpain-mediated cleavage of full-length Bfl-1 induces the release of C-terminal membrane active α-helices that are responsible for its conversion into a pro-apoptotic factor. A careful comparison of the different membrane-active regions present in the Bfl-1 truncated fragments with homologous domains of Bax show that helix α5, but not α6, of Bfl-1 induces cell death and cytochrome c release from purified mitochondria through a Bax/Bak-dependent mechanism. In contrast, both helices α5 and α6 of Bax permeabilize mitochondria regardless of the presence of Bax or Bak. Moreover, we provide evidence that the α9 helix of Bfl-1 promotes cytochrome c release and apoptosis through a unique membrane-destabilizing action whereas Bax-α9 does not display such activities. Hence, despite a common 3D-structure, C-terminal toxic domains present on Bfl-1 and Bax function in a dissimilar manner to permeabilize mitochondria and induce apoptosis. These findings provide insights for designing therapeutic approaches that could exploit the cleavage of endogenous Bcl-2 family proteins or the use of Bfl-1/Bax-derived peptides to promote tumor cell clearance

    Laminin-332 alters connexin profile, dye coupling and intercellular Ca(2+ )waves in ciliated tracheal epithelial cells

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    BACKGROUND: Tracheal epithelial cells are anchored to a dynamic basement membrane that contains a variety of extracellular matrix proteins including collagens and laminins. During development, wound repair and disease of the airway epithelium, significant changes in extracellular matrix proteins may directly affect cell migration, differentiation and events mediated by intercellular communication. We hypothesized that alterations in cell matrix, specifically type I collagen and laminin α3β3γ2 (LM-332) proteins within the matrix, directly affect intercellular communication in ciliated rabbit tracheal epithelial cells (RTEC). METHODS: Functional coupling of RTEC was monitored by microinjection of the negatively charged fluorescent dyes, Lucifer Yellow and Alexa 350, into ciliated RTEC grown on either a LM-332/collagen or collagen matrix. Coupling of physiologically significant molecules was evaluated by the mechanism and extent of propagated intercellular Ca(2+ )waves. Expression of connexin (Cx) mRNA and proteins were assayed by reverse transcriptase – polymerase chain reaction and immunocytochemistry, respectively. RESULTS: When compared to RTEC grown on collagen alone, RTEC grown on LM-332/collagen displayed a significant increase in dye transfer. Although mechanical stimulation of RTEC grown on either LM-332/collagen or collagen alone resulted in intercellular Ca(2+ )waves, the mechanism of transfer was dependent on matrix: RTEC grown on LM-332/collagen propagated Ca(2+)waves via extracellular purinergic signaling whereas RTEC grown on collagen used gap junctions. Comparison of RTEC grown on collagen or LM-332/collagen matrices revealed a reorganization of Cx26, Cx43 and Cx46 proteins. CONCLUSION: Alterations in airway basement membrane proteins such as LM-332 can induce connexin reorganizations and result in altered cellular communication mechanisms that could contribute to airway tissue function

    Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

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    Signaling pathways play a key role in complex diseases such as cancer, for which the development of novel therapies is a difficult, expensive and laborious task. Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process. In particular, network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics. However, their use is currently hampered by limitations in our knowledge of the underlying biochemistry, as well as in the experimental and computational technologies used for calibrating the models. Thus, the results from such models need to be carefully interpreted and used in order to avoid biased predictions. Here we present a procedure that deals with this uncertainty by using experimental data to build an ensemble of dynamic models. The method incorporates steps to reduce overfitting and maximize predictive capability. We find that by combining the outputs of individual models in an ensemble it is possible to obtain a more robust prediction. We report results obtained with this method, which we call SELDOM (enSEmbLe of Dynamic lOgic-based Models), showing that it improves the predictions previously reported for several challenging problems.JRB and DH acknowledge funding from the EU FP7 project NICHE (ITN Grant number 289384). JRB acknowledges funding from the Spanish MINECO project SYNBIOFACTORY (grant number DPI2014-55276-C5-2-R). AFV acknowledges funding from the Galician government (Xunta de Galiza) through the I2C postdoctoral fellowship ED481B2014/133-0. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio
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