Literature DB >> 15037740

A global suppressor motif for p53 cancer mutants.

Timothy E Baroni1, Ting Wang, Hua Qian, Lawrence R Dearth, Lan N Truong, Jue Zeng, Alec E Denes, Stephanie W Chen, Rainer K Brachmann.   

Abstract

The transcription factor and tumor suppressor protein p53 is frequently inactivated in human cancers. In many cases, p53 gene mutations result in high levels of inactive, full-length p53 protein with one amino acid change in the core domain that recognizes p53 DNA-binding sites. The ability to endow function to mutated p53 proteins would dramatically improve cancer therapy, because it would reactivate a central apoptotic pathway. By using genetic strategies and p53 assays in yeast and mammalian cells, we identified a global suppressor motif involving codons 235, 239, and 240. These intragenic suppressor mutations, either alone or in combination, restored function to 16 of 30 of the most common p53 cancer mutants tested. The 235-239-240 suppressor motif establishes that manipulation of a small region of the core domain is sufficient to activate a large number of p53 cancer mutants. Understanding the structural basis of the rescue mechanism will allow the pursuit of small compounds able to achieve a similar stabilization of p53 cancer mutants.

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Year:  2004        PMID: 15037740      PMCID: PMC387351          DOI: 10.1073/pnas.0401162101

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  31 in total

1.  Mechanism of rescue of common p53 cancer mutations by second-site suppressor mutations.

Authors:  P V Nikolova; K B Wong; B DeDecker; J Henckel; A R Fersht
Journal:  EMBO J       Date:  2000-02-01       Impact factor: 11.598

2.  Pharmacological rescue of mutant p53 conformation and function.

Authors:  B A Foster; H A Coffey; M J Morin; F Rastinejad
Journal:  Science       Date:  1999-12-24       Impact factor: 47.728

Review 3.  p53: death star.

Authors:  K H Vousden
Journal:  Cell       Date:  2000-11-22       Impact factor: 41.582

4.  Surfing the p53 network.

Authors:  B Vogelstein; D Lane; A J Levine
Journal:  Nature       Date:  2000-11-16       Impact factor: 49.962

5.  Wild-type p53 transactivates the KILLER/DR5 gene through an intronic sequence-specific DNA-binding site.

Authors:  R Takimoto; W S El-Deiry
Journal:  Oncogene       Date:  2000-03-30       Impact factor: 9.867

6.  Quantitative analysis of residual folding and DNA binding in mutant p53 core domain: definition of mutant states for rescue in cancer therapy.

Authors:  A N Bullock; J Henckel; A R Fersht
Journal:  Oncogene       Date:  2000-03-02       Impact factor: 9.867

Review 7.  The p53 pathway.

Authors:  C Prives; P A Hall
Journal:  J Pathol       Date:  1999-01       Impact factor: 7.996

8.  Amifostine (WR2721) restores transcriptional activity of specific p53 mutant proteins in a yeast functional assay.

Authors:  D Maurici; P Monti; P Campomenosi; S North; T Frebourg; G Fronza; P Hainaut
Journal:  Oncogene       Date:  2001-06-14       Impact factor: 9.867

9.  Novel human p53 mutations that are toxic to yeast can enhance transactivation of specific promoters and reactivate tumor p53 mutants.

Authors:  A Inga; M A Resnick
Journal:  Oncogene       Date:  2001-06-07       Impact factor: 9.867

10.  Restoration of the tumor suppressor function to mutant p53 by a low-molecular-weight compound.

Authors:  Vladimir J N Bykov; Natalia Issaeva; Alexandre Shilov; Monica Hultcrantz; Elena Pugacheva; Peter Chumakov; Jan Bergman; Klas G Wiman; Galina Selivanova
Journal:  Nat Med       Date:  2002-03       Impact factor: 53.440

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  37 in total

1.  Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.

Authors:  Samuel A Danziger; S Joshua Swamidass; Jue Zeng; Lawrence R Dearth; Qiang Lu; Jonathan H Chen; Jianlin Cheng; Vinh P Hoang; Hiroto Saigo; Ray Luo; Pierre Baldi; Rainer K Brachmann; Richard H Lathrop
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2006 Apr-Jun       Impact factor: 3.710

Review 2.  Genetic constraints on protein evolution.

Authors:  Manel Camps; Asael Herman; Ern Loh; Lawrence A Loeb
Journal:  Crit Rev Biochem Mol Biol       Date:  2007 Sep-Oct       Impact factor: 8.250

3.  Choosing where to look next in a mutation sequence space: Active Learning of informative p53 cancer rescue mutants.

Authors:  Samuel A Danziger; Jue Zeng; Ying Wang; Rainer K Brachmann; Richard H Lathrop
Journal:  Bioinformatics       Date:  2007-07-01       Impact factor: 6.937

4.  Analysis of p53-RNA interactions in cultured human cells.

Authors:  Kasandra J-L Riley; L James Maher
Journal:  Biochem Biophys Res Commun       Date:  2007-09-10       Impact factor: 3.575

5.  The mutational status of p53 can influence its recognition by human T-cells.

Authors:  Katerina Shamalov; Shlomo N Levy; Miryam Horovitz-Fried; Cyrille J Cohen
Journal:  Oncoimmunology       Date:  2017-01-31       Impact factor: 8.110

6.  p53 regulates FAK expression in human tumor cells.

Authors:  Vita M Golubovskaya; Richard Finch; Frederick Kweh; Nicole A Massoll; Martha Campbell-Thompson; Margaret R Wallace; William G Cance
Journal:  Mol Carcinog       Date:  2008-05       Impact factor: 4.784

7.  A novel p53 mutant found in iatrogenic urothelial cancers is dysfunctional and can be rescued by a second-site global suppressor mutation.

Authors:  Adam F Odell; Luke R Odell; Jon M Askham; Hiba Alogheli; Sreenivasan Ponnambalam; Monica Hollstein
Journal:  J Biol Chem       Date:  2013-04-23       Impact factor: 5.157

8.  Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.

Authors:  Vadim Y Bichutskiy; Richard Colman; Rainer K Brachmann; Richard H Lathrop
Journal:  Cancer Inform       Date:  2007-02-20

9.  All-codon scanning identifies p53 cancer rescue mutations.

Authors:  Roberta Baronio; Samuel A Danziger; Linda V Hall; Kirsty Salmon; G Wesley Hatfield; Richard H Lathrop; Peter Kaiser
Journal:  Nucleic Acids Res       Date:  2010-06-25       Impact factor: 16.971

10.  Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning.

Authors:  Samuel A Danziger; Roberta Baronio; Lydia Ho; Linda Hall; Kirsty Salmon; G Wesley Hatfield; Peter Kaiser; Richard H Lathrop
Journal:  PLoS Comput Biol       Date:  2008-09-04       Impact factor: 4.475

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