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

Philip Webster; Joanna C. Dawes; Hamlata Dewchand; Katalin Takacs; Barbara Iadarola; Bruce J. Bolt; Juan J. Caceres; Jakub Kaczor; Gopuraja Dharmalingam; Marian Dore; Laurence Game; Thomas Adejumo; James Elliott; Kikkeri Naresh; Mohammad Karimi; Katerina Rekopoulou; Ge Tan; Alberto Paccanaro; Anthony G. Uren

doi:10.1038/s41467-018-05069-9

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

Philip Webster, Joanna C. Dawes, Hamlata Dewchand, Katalin Takacs, Barbara Iadarola, Bruce J. Bolt, Juan J. Caceres, Jakub Kaczor, Gopuraja Dharmalingam, Marian Dore, Laurence Game, Thomas Adejumo, James Elliott, Kikkeri Naresh, Mohammad Karimi, Katerina Rekopoulou, Ge Tan, Alberto Paccanaro, Anthony G. Uren^*

^*Corresponding author for this work

School of Biomedical Sciences

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

Abstract

AbstractDetermining 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 murine leukemia virus-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 statistical approaches for identifying selected 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 of two BCL2 transgenic models confirmed known drivers of human non-Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features independently of local variance in mutation density also provides support for weakly evidenced cancer genes. An online resourcehttp://mulvdb.orgallows customized queries of the entire dataset.

Original language	English
Number of pages	0
Journal	Nature Communications
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41467-018-05069-9
Publication status	E-pub ahead of print - 9 Jul 2018

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Webster, P., Dawes, J. C., Dewchand, H., Takacs, K., Iadarola, B., Bolt, B. J., Caceres, J. 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. G. (2018). Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates. Nature Communications, 9(1). Advance online publication. https://doi.org/10.1038/s41467-018-05069-9

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title = "Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates",

abstract = "AbstractDetermining 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 murine leukemia virus-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 statistical approaches for identifying selected 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 of two BCL2 transgenic models confirmed known drivers of human non-Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features independently of local variance in mutation density also provides support for weakly evidenced cancer genes. An online resourcehttp://mulvdb.orgallows customized queries of the entire dataset.",

author = "Philip Webster and Dawes, {Joanna C.} and Hamlata Dewchand and Katalin Takacs and Barbara Iadarola and Bolt, {Bruce J.} and Caceres, {Juan J.} 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 Uren, {Anthony G.}",

year = "2018",

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doi = "10.1038/s41467-018-05069-9",

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Webster, P, Dawes, JC, Dewchand, H, Takacs, K, Iadarola, B, Bolt, BJ, Caceres, JJ, Kaczor, J, Dharmalingam, G, Dore, M, Game, L, Adejumo, T, Elliott, J, Naresh, K, Karimi, M, Rekopoulou, K, Tan, G, Paccanaro, A & Uren, AG 2018, 'Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates', Nature Communications, vol. 9, no. 1. https://doi.org/10.1038/s41467-018-05069-9

TY - JOUR

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

AU - Webster, Philip

AU - Dawes, Joanna C.

AU - Dewchand, Hamlata

AU - Takacs, Katalin

AU - Iadarola, Barbara

AU - Bolt, Bruce J.

AU - Caceres, Juan J.

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 G.

PY - 2018/7/9

Y1 - 2018/7/9

N2 - AbstractDetermining 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 murine leukemia virus-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 statistical approaches for identifying selected 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 of two BCL2 transgenic models confirmed known drivers of human non-Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features independently of local variance in mutation density also provides support for weakly evidenced cancer genes. An online resourcehttp://mulvdb.orgallows customized queries of the entire dataset.

AB - AbstractDetermining 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 murine leukemia virus-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 statistical approaches for identifying selected 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 of two BCL2 transgenic models confirmed known drivers of human non-Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features independently of local variance in mutation density also provides support for weakly evidenced cancer genes. An online resourcehttp://mulvdb.orgallows customized queries of the entire dataset.

U2 - 10.1038/s41467-018-05069-9

DO - 10.1038/s41467-018-05069-9

M3 - Article

SN - 2041-1723

VL - 9

JO - Nature Communications

JF - Nature Communications

IS - 1

ER -

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

Abstract

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