Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks

Anthony G. Uren; Jaap Kool; Konstantin Matentzoglu; Jeroen de Ridder; Jenny Mattison; Miranda Van Uitert; Wendy Lagcher; Daoud Sie; Ellen Tanger; Tony Cox; Marcel J T Reinders; Tim J. Hubbard; Jane Rogers; Jos Jonkers; Lodewyk F A Wessels; David J. Adams; Maarten van Lohuizen; Anton Berns

doi:10.1016/j.cell.2008.03.021

Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks

Anthony G. Uren, Jaap Kool, Konstantin Matentzoglu, Jeroen de Ridder, Jenny Mattison, Miranda Van Uitert, Wendy Lagcher, Daoud Sie, Ellen Tanger, Tony Cox, Marcel J T Reinders, Tim J. Hubbard, Jane Rogers, Jos Jonkers, Lodewyk F A Wessels, David J. Adams, Maarten van Lohuizen, Anton Berns

Research output: Contribution to journal › Article › Academic › peer-review

129 Citations (Scopus)

Abstract

p53 and p19^ARF are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19^ARF deficiency, we identified 10,806 retroviral insertion sites, implicating over 300 loci in tumorigenesis. This dataset reveals 20 genes that are specifically mutated in either p19^ARF-deficient, p53-deficient or wild-type mice (including Flt3, mmu-mir-106a-363, Smg6, and Ccnd3), as well as networks of significant collaborative and mutually exclusive interactions between cancer genes. Furthermore, we found candidate tumor suppressor genes, as well as distinct clusters of insertions within genes like Flt3 and Notch1 that induce mutants with different spectra of genetic interactions. Cross species comparative analysis with aCGH data of human cancer cell lines revealed known and candidate oncogenes (Mmp13, Slamf6, and Rreb1) and tumor suppressors (Wwox and Arfrp2). This dataset should prove to be a rich resource for the study of genetic interactions that underlie tumorigenesis.

Original language	English
Pages (from-to)	727-741
Number of pages	15
Journal	Cell
Volume	133
Issue number	4
DOIs	https://doi.org/10.1016/j.cell.2008.03.021
Publication status	Published - 16 May 2008
Externally published	Yes

Keywords

HUMDISEASE
SIGNALING
SYSBIO

Access to Document

10.1016/j.cell.2008.03.021

Cite this

Uren, A. G., Kool, J., Matentzoglu, K., de Ridder, J., Mattison, J., Van Uitert, M., Lagcher, W., Sie, D., Tanger, E., Cox, T., Reinders, M. J. T., Hubbard, T. J., Rogers, J., Jonkers, J., Wessels, L. F. A., Adams, D. J., van Lohuizen, M., & Berns, A. (2008). Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks. Cell, 133(4), 727-741. https://doi.org/10.1016/j.cell.2008.03.021

@article{55485f11d71843c8b09e90eca52aa1a8,

title = "Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks",

abstract = "p53 and p19ARF are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19ARF deficiency, we identified 10,806 retroviral insertion sites, implicating over 300 loci in tumorigenesis. This dataset reveals 20 genes that are specifically mutated in either p19ARF-deficient, p53-deficient or wild-type mice (including Flt3, mmu-mir-106a-363, Smg6, and Ccnd3), as well as networks of significant collaborative and mutually exclusive interactions between cancer genes. Furthermore, we found candidate tumor suppressor genes, as well as distinct clusters of insertions within genes like Flt3 and Notch1 that induce mutants with different spectra of genetic interactions. Cross species comparative analysis with aCGH data of human cancer cell lines revealed known and candidate oncogenes (Mmp13, Slamf6, and Rreb1) and tumor suppressors (Wwox and Arfrp2). This dataset should prove to be a rich resource for the study of genetic interactions that underlie tumorigenesis.",

keywords = "HUMDISEASE, SIGNALING, SYSBIO",

author = "Uren, {Anthony G.} and Jaap Kool and Konstantin Matentzoglu and {de Ridder}, Jeroen and Jenny Mattison and {Van Uitert}, Miranda and Wendy Lagcher and Daoud Sie and Ellen Tanger and Tony Cox and Reinders, {Marcel J T} and Hubbard, {Tim J.} and Jane Rogers and Jos Jonkers and Wessels, {Lodewyk F A} and Adams, {David J.} and {van Lohuizen}, Maarten and Anton Berns",

year = "2008",

month = may,

day = "16",

doi = "10.1016/j.cell.2008.03.021",

language = "English",

volume = "133",

pages = "727--741",

number = "4",

}

Uren, AG, Kool, J, Matentzoglu, K, de Ridder, J, Mattison, J, Van Uitert, M, Lagcher, W, Sie, D, Tanger, E, Cox, T, Reinders, MJT, Hubbard, TJ, Rogers, J, Jonkers, J, Wessels, LFA, Adams, DJ, van Lohuizen, M & Berns, A 2008, 'Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks', Cell, vol. 133, no. 4, pp. 727-741. https://doi.org/10.1016/j.cell.2008.03.021

TY - JOUR

T1 - Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks

AU - Uren, Anthony G.

AU - Kool, Jaap

AU - Matentzoglu, Konstantin

AU - de Ridder, Jeroen

AU - Mattison, Jenny

AU - Van Uitert, Miranda

AU - Lagcher, Wendy

AU - Sie, Daoud

AU - Tanger, Ellen

AU - Cox, Tony

AU - Reinders, Marcel J T

AU - Hubbard, Tim J.

AU - Rogers, Jane

AU - Jonkers, Jos

AU - Wessels, Lodewyk F A

AU - Adams, David J.

AU - van Lohuizen, Maarten

AU - Berns, Anton

PY - 2008/5/16

Y1 - 2008/5/16

N2 - p53 and p19ARF are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19ARF deficiency, we identified 10,806 retroviral insertion sites, implicating over 300 loci in tumorigenesis. This dataset reveals 20 genes that are specifically mutated in either p19ARF-deficient, p53-deficient or wild-type mice (including Flt3, mmu-mir-106a-363, Smg6, and Ccnd3), as well as networks of significant collaborative and mutually exclusive interactions between cancer genes. Furthermore, we found candidate tumor suppressor genes, as well as distinct clusters of insertions within genes like Flt3 and Notch1 that induce mutants with different spectra of genetic interactions. Cross species comparative analysis with aCGH data of human cancer cell lines revealed known and candidate oncogenes (Mmp13, Slamf6, and Rreb1) and tumor suppressors (Wwox and Arfrp2). This dataset should prove to be a rich resource for the study of genetic interactions that underlie tumorigenesis.

AB - p53 and p19ARF are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19ARF deficiency, we identified 10,806 retroviral insertion sites, implicating over 300 loci in tumorigenesis. This dataset reveals 20 genes that are specifically mutated in either p19ARF-deficient, p53-deficient or wild-type mice (including Flt3, mmu-mir-106a-363, Smg6, and Ccnd3), as well as networks of significant collaborative and mutually exclusive interactions between cancer genes. Furthermore, we found candidate tumor suppressor genes, as well as distinct clusters of insertions within genes like Flt3 and Notch1 that induce mutants with different spectra of genetic interactions. Cross species comparative analysis with aCGH data of human cancer cell lines revealed known and candidate oncogenes (Mmp13, Slamf6, and Rreb1) and tumor suppressors (Wwox and Arfrp2). This dataset should prove to be a rich resource for the study of genetic interactions that underlie tumorigenesis.

KW - HUMDISEASE

KW - SIGNALING

KW - SYSBIO

UR - http://www.scopus.com/inward/record.url?scp=43149084575&partnerID=8YFLogxK

U2 - 10.1016/j.cell.2008.03.021

DO - 10.1016/j.cell.2008.03.021

M3 - Article

C2 - 18485879

AN - SCOPUS:43149084575

SN - 0092-8674

VL - 133

SP - 727

EP - 741

JO - Cell

JF - Cell

IS - 4

ER -

Large-Scale Mutagenesis in p19ARF- and p53-Deficient Mice Identifies Cancer Genes and Their Collaborative Networks

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this