Literature DB >> 15485892

Identification of a network involved in thapsigargin-induced apoptosis using a library of small interfering RNA expression vectors.

Takashi Futami1, Makoto Miyagishi, Kazunari Taira.   

Abstract

We describe here the construction of a library of small interfering RNA expression vectors targeted to a few hundred apoptosis-related genes and the application of this library to an investigation of thapsigargin (TG)-induced apoptosis. Thapsigargin triggers endoplasmic reticulum stress, with subsequent apoptosis, but the molecular mechanisms underlying this process are incompletely understood. Using our library, we identified three anti-apoptotic genes, namely, NOXA, E2F1, and MAPK1, in addition to already characterized genes in the apoptotic pathway. In contrast to proposals by others, our data revealed (i) that TG-induced apoptosis is associated with Apaf1 in a caspase-3- and caspase-9-independent manner; (ii) that the E2F1-PUMA pathway might be involved; and (iii) that the ERK pathway, via MAP3K8 (mitogen-activated protein kinase kinase 8), is required for the induction by TG of apoptosis. Our study demonstrates clearly that unexpected and novel genes can be identified effectively by our method, and it provides evidence for the efficacy and utility of the comprehensive analysis of signaling networks and pathways using a library of small interfering RNA expression vectors.

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Year:  2004        PMID: 15485892     DOI: 10.1074/jbc.M409948200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  24 in total

1.  Implication of TAp73 in the p53-independent pathway of Puma induction and Puma-dependent apoptosis in primary cortical neurons.

Authors:  Michael Fricker; Sofia Papadia; Giles E Hardingham; Aviva M Tolkovsky
Journal:  J Neurochem       Date:  2010-05-08       Impact factor: 5.372

2.  Role of p53, PUMA, and Bax in wogonin-induced apoptosis in human cancer cells.

Authors:  Dae-Hee Lee; Clifford Kim; Lin Zhang; Yong J Lee
Journal:  Biochem Pharmacol       Date:  2008-02-29       Impact factor: 5.858

3.  The Role of BH3-Only Proteins in Tumor Cell Development, Signaling, and Treatment.

Authors:  Rana Elkholi; Konstantinos V Floros; Jerry E Chipuk
Journal:  Genes Cancer       Date:  2011-05

4.  The essential role of p53-up-regulated modulator of apoptosis (Puma) and its regulation by FoxO3a transcription factor in β-amyloid-induced neuron death.

Authors:  Rumana Akhter; Priyankar Sanphui; Subhas Chandra Biswas
Journal:  J Biol Chem       Date:  2014-02-24       Impact factor: 5.157

5.  Interlaboratory evaluation of a multiplexed high information content in vitro genotoxicity assay.

Authors:  Steven M Bryce; Derek T Bernacki; Jeffrey C Bemis; Richard A Spellman; Maria E Engel; Maik Schuler; Elisabeth Lorge; Pekka T Heikkinen; Ulrike Hemmann; Véronique Thybaud; Sabrina Wilde; Nina Queisser; Andreas Sutter; Andreas Zeller; Melanie Guérard; David Kirkland; Stephen D Dertinger
Journal:  Environ Mol Mutagen       Date:  2017-04       Impact factor: 3.216

6.  MKP-1 antagonizes C/EBPβ activity and lowers the apoptotic threshold after ischemic injury.

Authors:  A Rininger; C Dejesus; A Totten; A Wayland; M W Halterman
Journal:  Cell Death Differ       Date:  2012-04-20       Impact factor: 15.828

7.  Predictions of genotoxic potential, mode of action, molecular targets, and potency via a tiered multiflow® assay data analysis strategy.

Authors:  Stephen D Dertinger; Andrew R Kraynak; Ryan P Wheeldon; Derek T Bernacki; Steven M Bryce; Nikki Hall; Jeffrey C Bemis; Sheila M Galloway; Patricia A Escobar; George E Johnson
Journal:  Environ Mol Mutagen       Date:  2019-02-27       Impact factor: 3.216

8.  γH2AX and p53 responses in TK6 cells discriminate promutagens and nongenotoxicants in the presence of rat liver S9.

Authors:  Derek T Bernacki; Steven M Bryce; Jeffrey C Bemis; David Kirkland; Stephen D Dertinger
Journal:  Environ Mol Mutagen       Date:  2016-07-01       Impact factor: 3.216

Review 9.  PUMA, a potent killer with or without p53.

Authors:  J Yu; L Zhang
Journal:  Oncogene       Date:  2008-12       Impact factor: 9.867

10.  Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.

Authors:  Steven M Bryce; Derek T Bernacki; Jeffrey C Bemis; Stephen D Dertinger
Journal:  Environ Mol Mutagen       Date:  2016-01-13       Impact factor: 3.216

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