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

• Published in: Nature communications Vol. 9; no. 1; pp. 2649 - 14
• Main Authors: Webster, Philip, Dawes, Joanna C, Dewchand, Hamlata, Takacs, Katalin, Iadarola, Barbara, Bolt, Bruce J, Caceres, Juan J, Kaczor, Jakub, Dharmalingam, Gopuraja, Dore, Marian, Game, Laurence, Adejumo, Thomas, Elliott, James, Naresh, Kikkeri, Karimi, Mohammad, Rekopoulou, Katerina, Tan, Ge, Paccanaro, Alberto, Uren, Anthony G
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 09.07.2018; Nature Publishing Group UK; Nature Portfolio
• Subjects: Animal models; Animals; Cancer; Gene loci; Genetic Association Studies; Genetic Loci - genetics; Genetic Predisposition to Disease - genetics; Genome-Wide Association Study; Genomes; HEK293 Cells; High-Throughput Nucleotide Sequencing; Humans; Immunosurveillance; Leukemia; Leukemia Virus, Murine - genetics; Leukemia Virus, Murine - physiology; Lymphoma; Lymphoma - genetics; Major histocompatibility complex; Mice, Inbred BALB C; Mice, Inbred C57BL; Mice, Transgenic; Mutagenesis, Insertional; Mutation; Negative selection; Phenotypes; Tumors; Viruses
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-018-05069-9

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 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 resource http://mulv.lms.mrc.ac.uk allows customized queries of the entire dataset.