Cancers arise when normal cells accumulate mutations that drive uncontrollable proliferation. Tumour cells can harbour thousands of these mutations, but only a fraction of them cause cancer. We use insertional mutagenesis screens as a tool to identify genes that are deregulated and mutated in cancer and investigate how they cooperate to drive tumour development.

When a mouse is infected with slow transforming retroviruses, the virus repeatedly integrates into the host cell’s DNA creating insertion mutations, some of which activate protooncogenes or inactivate tumour suppressor genes. Using multiplex PCR in combination with high throughput sequencing platforms, the insertion profile of hundreds of tumours can be determined simultaneously. In recent screens we have identified 20,000 insertion mutations from 1,000 lymphomas in mice and by pooling these data we identified hundreds of loci that contribute to lymphoma development.

Cancer Genomics

Left: As retroviral insertion mutations accumulate, a subset of normal hematopoietic cells will proliferate uncontrollably and eventually give rise to lymphomas bearing multiple mutations. Right: Counting which mutations occur most frequently across a panel of tumour genomes distinguishes mutations that contribute to lymphoma development from bystander mutations.

These screens confirm the oncogenicity of mutations previously found in human tumours and serve as a starting point to search for novel mutations in humans.
They can also identify combinations of mutations that cooperate in tumour development or alternatively identify mutation pairs that are never found together in the same tumour. Such genetic interactions can be used to place oncogenes and tumour suppressors into pathways that suggest an interdependent or redundant role in cancer.

We categorize and prioritize which mutations to study further using informatics approaches that integrate the mutation profile of our mouse tumours with other tumour derived genome wide datasets from humans and mice. Our ultimate goal is to develop mouse models that examine which of these mutated genes encode useful targets for the development of novel cancer therapeutics.

Cancer Genomics

Figure 2 – Contingency table tests demonstrate a significant selection for comutation of Notch1 and Ikzf1, confirming previous observations that these genes are frequently comutated in human T Acute lymphoblastic leukemia. Conversely Myc and Mycn are found mutated together less frequently than expected by chance, consistent with their structural and functional equivalence.

Cancer Genomics

Figure 3 – Interactions between the 20 most significant common insertion sites from our previous MuLV screens visualized as a network. Lines represent all interactions with a p-value > 0.01. Solid lines represent concomitant mutations whereas dashed lines represent mutual exclusivity.

Selected Publications

Kool, J., Uren, A. G., Martins, C. P., Sie, D., de Ridder, J., Turner, G., van Uitert, M., Matentzoglu, K., Lagcher, W., Krimpenfort, P., Gadiot, J., Pritchard, C., Lenz, J., Lund, A. H., Jonkers, J., Rogers, J., Adams, D. J., Wessels, L., Berns, A., & van Lohuizen, M. (2010). Insertional mutagenesis in mice deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 reveals cancer gene interactions and correlations with tumor phenotypes. Cancer Research, 70(2), 520–531.

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., Hubbard, T. J., Rogers, J., Jonkers, J., Wessels, L., Adams, D. J., van Lohuizen, M., & Berns, A. (2008). Large-scale mutagenesis in p19(ARF)- and p53-deficient mice identifies cancer genes and their collaborative networks. Cell, 133(4), 727–741.

de Ridder, J., Uren, A., Kool, J., Reinders, M., & Wessels, L. (2006). Detecting statistically significant common insertion sites in retroviral insertional mutagenesis screens. PLoS Computational Biology, 2(12), e166+.

Uren, A. G., Wong, L., Pakusch, M., Fowler, K. J., Burrows, F. J., Vaux, D. L., & Choo, K. H. (2000b). Survivin and the inner centromere protein INCENP show similar cell-cycle localization and gene knockout phenotype. Current Biology : CB, 10(21), 1319–1328.

Uren, A. G., O’Rourke, K., Aravind, L., Pisabarro, Seshagiri, S., Koonin, E. V., & Dixit, V. M. (2000a). Identification of paracaspases and metacaspases. Molecular Cell, 6(4), 961–967.

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