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  • 1
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    A G protein mutant that inhibits thrombin and purinergic receptor activation of phospholipase A2 (1990)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 1990-08-10
    Description: The stimulation of phospholipase A2 by thrombin and type 2 (P2)-purinergic receptor agonists in Chinese hamster ovary cells is mediated by the G protein Gi. To delineate alpha chain regulatory regions responsible for control of phospholipase A2, chimeric cDNAs were constructed in which different lengths of the alpha subunit of Gs (alpha s) were replaced with the corresponding sequence of the Gi alpha subunit (alpha i2). When a carboxyl-terminal chimera alpha s-i(38), which has the last 38 amino acids of alpha s substituted with the last 36 residues of alpha i2, was expressed in Chinese hamster ovary cells, the receptor-stimulated phospholipase A2 activity was inhibited, although the chimera could still activate adenylyl cyclase. Thus, alpha s-i(38) is an active alpha s, but also a dominant negative alpha i molecule, indicating that the last 36 amino acids of alpha i2 are a critical domain for G protein regulation of phospholipase A2 activity.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Gupta, S K -- Diez, E -- Heasley, L E -- Osawa, S -- Johnson, G L -- DK37871/DK/NIDDK NIH HHS/ -- GM30324/GM/NIGMS NIH HHS/ -- New York, N.Y. -- Science. 1990 Aug 10;249(4969):662-6.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Division of Basic Sciences, National Jewish Center for Immunology and Respiratory Medicine, Denver, CO 80206.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/2166341" target="_blank"〉PubMed〈/a〉
    Keywords: Adenosine Triphosphate/pharmacology ; Animals ; Arachidonic Acid ; Arachidonic Acids/metabolism ; Cell Line ; Chlorides/pharmacology ; Enzyme Activation ; GTP-Binding Proteins/*genetics/metabolism ; Inositol Phosphates/metabolism ; Kinetics ; Lithium/pharmacology ; Lithium Chloride ; Macromolecular Substances ; *Mutation ; Phospholipases/*metabolism ; Phospholipases A/*metabolism ; Phospholipases A2 ; Receptors, Purinergic/drug effects/*physiology ; Restriction Mapping ; Thrombin/antagonists & inhibitors/*pharmacology ; Transfection
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Mitogen-activated protein kinase activation resulting from selective oncogene expression in NIH 3T3 and rat 1a cells. (1992)
    National Academy of Sciences
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    Publication Date: 1992-08-15
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 3
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    Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data (2015)
    Oxford University Press
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    Publication Date: 2015-11-21
    Description: Motivation: Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. Results: We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. Availability and implementation: KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/ . Contact: aikchoon.tan@ucdenver.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 4
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    Bioinformatics-driven discovery of rational combination for overcoming EGFR-mutant lung cancer resistance to EGFR therapy (2014)
    Oxford University Press
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    Publication Date: 2014-08-27
    Description: Motivation: Non–small-cell lung cancer (NSCLC) is the leading cause of cancer death in the United States. Targeted tyrosine kinase inhibitors (TKIs) directed against the epidermal growth factor receptor (EGFR) have been widely and successfully used in treating NSCLC patients with activating EGFR mutations. Unfortunately, the duration of response is short-lived, and all patients eventually relapse by acquiring resistance mechanisms. Result: We performed an integrative systems biology approach to determine essential kinases that drive EGFR-TKI resistance in cancer cell lines. We used a series of bioinformatics methods to analyze and integrate the functional genetics screen and RNA-seq data to identify a set of kinases that are critical in survival and proliferation in these TKI-resistant lines. By connecting the essential kinases to compounds using a novel kinase connectivity map (K-Map), we identified and validated bosutinib as an effective compound that could inhibit proliferation and induce apoptosis in TKI-resistant lines. A rational combination of bosutinib and gefitinib showed additive and synergistic effects in cancer cell lines resistant to EGFR TKI alone. Conclusions: We have demonstrated a bioinformatics-driven discovery roadmap for drug repurposing and development in overcoming resistance in EGFR-mutant NSCLC, which could be generalized to other cancer types in the era of personalized medicine. Availability and implementation: K-Map can be accessible at: http://tanlab.ucdenver.edu/kMap . Contact: aikchoon.tan@ucdenver.edu or finiganj@njhealth.org Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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