Literature DB >> 32484602

Transcriptional profiling reveals a subset of human breast tumors that retain wt TP53 but display mutant p53-associated features.

Gal Benor1, Garold Fuks1, Suet-Feung Chin2, Oscar M Rueda2, Saptaparna Mukherjee3, Sharathchandra Arandkar3,4, Yael Aylon3, Carlos Caldas2, Eytan Domany1, Moshe Oren3.   

Abstract

TP53 gene mutations are very common in human cancer. While such mutations abrogate the tumor suppressive activities of the wild-type (wt) p53 protein, some of them also endow the mutant (mut) protein with oncogenic gain of function (GOF), facilitating cancer progression. Yet, p53 may acquire altered functionality even without being mutated; in particular, experiments with cultured cells revealed that wtp53 can be rewired to adopt mut-like features in response to growth factors or cancer-mimicking genetic manipulations. To assess whether such rewiring also occurs in human tumors, we interrogated gene expression profiles and pathway deregulation patterns in the METABRIC breast cancer (BC) dataset as a function of TP53 gene mutation status. Harnessing the power of machine learning, we optimized a gene expression classifier for ER+Her2- patients that distinguishes tumors carrying TP53 mutations from those retaining wt TP53. Interestingly, a small subset of wt TP53 tumors displayed gene expression and pathway deregulation patterns markedly similar to those of TP53-mutated tumors. Moreover, similar to TP53-mutated tumors, these 'pseudomutant' cases displayed a signature for enhanced proliferation and had worse prognosis than typical wtp53 tumors. Notably, these tumors revealed upregulation of genes which, in BC cell lines, were reported to be positively regulated by p53 GOF mutants. Thus, such tumors may benefit from mut p53-associated activities without having to accrue TP53 mutations.
© 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

Entities:  

Keywords:  METABRIC; breast cancer; machine learning; p53 gain of function; pseudomutant p53

Mesh:

Substances:

Year:  2020        PMID: 32484602      PMCID: PMC7400784          DOI: 10.1002/1878-0261.12736

Source DB:  PubMed          Journal:  Mol Oncol        ISSN: 1574-7891            Impact factor:   6.603


  29 in total

1.  Outcome signature genes in breast cancer: is there a unique set?

Authors:  Liat Ein-Dor; Itai Kela; Gad Getz; David Givol; Eytan Domany
Journal:  Bioinformatics       Date:  2004-08-12       Impact factor: 6.937

2.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.

Authors:  T Sørlie; C M Perou; R Tibshirani; T Aas; S Geisler; H Johnsen; T Hastie; M B Eisen; M van de Rijn; S S Jeffrey; T Thorsen; H Quist; J C Matese; P O Brown; D Botstein; P E Lønning; A L Børresen-Dale
Journal:  Proc Natl Acad Sci U S A       Date:  2001-09-11       Impact factor: 11.205

3.  Flexibility: the key to p53 function?

Authors:  J Milner
Journal:  Trends Biochem Sci       Date:  1995-02       Impact factor: 13.807

4.  Pathway-based personalized analysis of breast cancer expression data.

Authors:  Anna Livshits; Anna Git; Garold Fuks; Carlos Caldas; Eytan Domany
Journal:  Mol Oncol       Date:  2015-04-29       Impact factor: 6.603

5.  IARC Database of p53 gene mutations in human tumors and cell lines: updated compilation, revised formats and new visualisation tools.

Authors:  P Hainaut; T Hernandez; A Robinson; P Rodriguez-Tome; T Flores; M Hollstein; C C Harris; R Montesano
Journal:  Nucleic Acids Res       Date:  1998-01-01       Impact factor: 16.971

Review 6.  When mutants gain new powers: news from the mutant p53 field.

Authors:  Ran Brosh; Varda Rotter
Journal:  Nat Rev Cancer       Date:  2009-08-20       Impact factor: 60.716

7.  Breast cancer statistics, 2017, racial disparity in mortality by state.

Authors:  Carol E DeSantis; Jiemin Ma; Ann Goding Sauer; Lisa A Newman; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2017-10-03       Impact factor: 508.702

8.  Conformational change of p53 protein in growth factor-stimulated human myelogenous leukemia cells.

Authors:  W Zhang; A B Deisseroth
Journal:  Leuk Lymphoma       Date:  1994-07

9.  Global analysis of p53-regulated transcription identifies its direct targets and unexpected regulatory mechanisms.

Authors:  Mary Ann Allen; Zdenek Andrysik; Veronica L Dengler; Hestia S Mellert; Anna Guarnieri; Justin A Freeman; Kelly D Sullivan; Matthew D Galbraith; Xin Luo; W Lee Kraus; Robin D Dowell; Joaquin M Espinosa
Journal:  Elife       Date:  2014-05-27       Impact factor: 8.140

10.  Down-regulation of LATS kinases alters p53 to promote cell migration.

Authors:  Noa Furth; Noa Bossel Ben-Moshe; Yair Pozniak; Ziv Porat; Tamar Geiger; Eytan Domany; Yael Aylon; Moshe Oren
Journal:  Genes Dev       Date:  2015-11-15       Impact factor: 11.361

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  3 in total

Review 1.  Mutant p53 in cell-cell interactions.

Authors:  Steven Pilley; Tristan A Rodriguez; Karen H Vousden
Journal:  Genes Dev       Date:  2021-04-01       Impact factor: 11.361

2.  A p53 transcriptional signature in primary and metastatic cancers derived using machine learning.

Authors:  Faeze Keshavarz-Rahaghi; Erin Pleasance; Tyler Kolisnik; Steven J M Jones
Journal:  Front Genet       Date:  2022-08-29       Impact factor: 4.772

Review 3.  Regulation of p53 and Cancer Signaling by Heat Shock Protein 40/J-Domain Protein Family Members.

Authors:  Atsushi Kaida; Tomoo Iwakuma
Journal:  Int J Mol Sci       Date:  2021-12-16       Impact factor: 5.923

  3 in total

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