Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates. / Webster, Philip; Dawes, Joanna; Dewchand, Hamlata; Takacs, Katalin; Iadarola, Barbara; Bolt, Bruce; Caceres Silva, Juan; Kaczor, Jakub; Dharmalingam, Gopuraja; Dore, Marian; Game, Laurence; Adejumo, Thomas; Elliott, James; Naresh, Kikkeri; Karimi, Mohammad; Rekopoulou, Katerina; Tan, Ge; Paccanaro, Alberto; Uren, Anthony.

In: Nature Communications, Vol. 9, 2649, 09.07.2018, p. 1-14.

Research output: Contribution to journalArticlepeer-review

Published

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Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates. / Webster, Philip; Dawes, Joanna; Dewchand, Hamlata; Takacs, Katalin; Iadarola, Barbara; Bolt, Bruce; Caceres Silva, Juan; Kaczor, Jakub; Dharmalingam, Gopuraja; Dore, Marian; Game, Laurence; Adejumo, Thomas; Elliott, James; Naresh, Kikkeri; Karimi, Mohammad; Rekopoulou, Katerina; Tan, Ge; Paccanaro, Alberto; Uren, Anthony.

In: Nature Communications, Vol. 9, 2649, 09.07.2018, p. 1-14.

Research output: Contribution to journalArticlepeer-review

Harvard

Webster, P, Dawes, J, Dewchand, H, Takacs, K, Iadarola, B, Bolt, B, Caceres Silva, J, Kaczor, J, Dharmalingam, G, Dore, M, Game, L, Adejumo, T, Elliott, J, Naresh, K, Karimi, M, Rekopoulou, K, Tan, G, Paccanaro, A & Uren, A 2018, 'Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates', Nature Communications, vol. 9, 2649, pp. 1-14. https://doi.org/10.1038/s41467-018-05069-9

APA

Webster, P., Dawes, J., Dewchand, H., Takacs, K., Iadarola, B., Bolt, B., Caceres Silva, J., Kaczor, J., Dharmalingam, G., Dore, M., Game, L., Adejumo, T., Elliott, J., Naresh, K., Karimi, M., Rekopoulou, K., Tan, G., Paccanaro, A., & Uren, A. (2018). Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates. Nature Communications, 9, 1-14. [2649]. https://doi.org/10.1038/s41467-018-05069-9

Vancouver

Webster P, Dawes J, Dewchand H, Takacs K, Iadarola B, Bolt B et al. Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates. Nature Communications. 2018 Jul 9;9:1-14. 2649. https://doi.org/10.1038/s41467-018-05069-9

Author

Webster, Philip ; Dawes, Joanna ; Dewchand, Hamlata ; Takacs, Katalin ; Iadarola, Barbara ; Bolt, Bruce ; Caceres Silva, Juan ; Kaczor, Jakub ; Dharmalingam, Gopuraja ; Dore, Marian ; Game, Laurence ; Adejumo, Thomas ; Elliott, James ; Naresh, Kikkeri ; Karimi, Mohammad ; Rekopoulou, Katerina ; Tan, Ge ; Paccanaro, Alberto ; Uren, Anthony. / Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates. In: Nature Communications. 2018 ; Vol. 9. pp. 1-14.

BibTeX

@article{684997b2a0664a23916901cd98c1b21b,
title = "Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates",
abstract = "Determining whether recurrent but rare cancer mutations are bona fide driver mutations remains a bottleneck in cancer research. Here we present the most comprehensive analysis of retrovirus driven lymphomagenesis produced to date, sequencing 700,000 mutations from >500 malignancies collected at time points throughout tumor development. This scale of data allows novel, novel statistical approaches for identifying driver mutations and yields a high-resolution, genome wide map of the selective forces surrounding cancer gene loci. We also demonstrate negative selection of mutations that may be deleterious to tumor development indicating novel avenues for therapy. Screening two BCL2 transgenic models confirms known drivers of human B-cell non- Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features also gives robust identification of known cancer genes independently of local variance in mutation density. An online resource http://mulv.lms.mrc.ac.uk allows customized queries of the entire dataset.",
author = "Philip Webster and Joanna Dawes and Hamlata Dewchand and Katalin Takacs and Barbara Iadarola and Bruce Bolt and {Caceres Silva}, Juan and Jakub Kaczor and Gopuraja Dharmalingam and Marian Dore and Laurence Game and Thomas Adejumo and James Elliott and Kikkeri Naresh and Mohammad Karimi and Katerina Rekopoulou and Ge Tan and Alberto Paccanaro and Anthony Uren",
year = "2018",
month = jul,
day = "9",
doi = "10.1038/s41467-018-05069-9",
language = "English",
volume = "9",
pages = "1--14",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",

}

RIS

TY - JOUR

T1 - Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates

AU - Webster, Philip

AU - Dawes, Joanna

AU - Dewchand, Hamlata

AU - Takacs, Katalin

AU - Iadarola, Barbara

AU - Bolt, Bruce

AU - Caceres Silva, Juan

AU - Kaczor, Jakub

AU - Dharmalingam, Gopuraja

AU - Dore, Marian

AU - Game, Laurence

AU - Adejumo, Thomas

AU - Elliott, James

AU - Naresh, Kikkeri

AU - Karimi, Mohammad

AU - Rekopoulou, Katerina

AU - Tan, Ge

AU - Paccanaro, Alberto

AU - Uren, Anthony

PY - 2018/7/9

Y1 - 2018/7/9

N2 - Determining whether recurrent but rare cancer mutations are bona fide driver mutations remains a bottleneck in cancer research. Here we present the most comprehensive analysis of retrovirus driven lymphomagenesis produced to date, sequencing 700,000 mutations from >500 malignancies collected at time points throughout tumor development. This scale of data allows novel, novel statistical approaches for identifying driver mutations and yields a high-resolution, genome wide map of the selective forces surrounding cancer gene loci. We also demonstrate negative selection of mutations that may be deleterious to tumor development indicating novel avenues for therapy. Screening two BCL2 transgenic models confirms known drivers of human B-cell non- Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features also gives robust identification of known cancer genes independently of local variance in mutation density. An online resource http://mulv.lms.mrc.ac.uk allows customized queries of the entire dataset.

AB - Determining whether recurrent but rare cancer mutations are bona fide driver mutations remains a bottleneck in cancer research. Here we present the most comprehensive analysis of retrovirus driven lymphomagenesis produced to date, sequencing 700,000 mutations from >500 malignancies collected at time points throughout tumor development. This scale of data allows novel, novel statistical approaches for identifying driver mutations and yields a high-resolution, genome wide map of the selective forces surrounding cancer gene loci. We also demonstrate negative selection of mutations that may be deleterious to tumor development indicating novel avenues for therapy. Screening two BCL2 transgenic models confirms known drivers of human B-cell non- Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features also gives robust identification of known cancer genes independently of local variance in mutation density. An online resource http://mulv.lms.mrc.ac.uk allows customized queries of the entire dataset.

U2 - 10.1038/s41467-018-05069-9

DO - 10.1038/s41467-018-05069-9

M3 - Article

VL - 9

SP - 1

EP - 14

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

M1 - 2649

ER -