Ph.D., Tel Aviv University, 1990
In silico genomics of cancer; single-cell genomics; inference from noisy biological data; large-scale numerical computing
Cancer is a highly complex genetic disease. A single tumor is an evolving biological system which often contains heterogeneous cell population. Clinical practice only provides us with partial snapshots of this evolution, never its full time course or its full picture at any given time. It is our goal to identify key genetic elements involved in the disease using this incomplete information.
Array-CGH, and, more recently, sequencing experiments reveal patterns of frequent and widespread aberration in cancer genomes. It is plausible that recurrently aberrant loci, are under selection and are therefore enriched in important cancer genes. With this in mind, a novel comprehensive methodology for recurrence analysis was developed and used to analyze multiple-genome data sets for breast, lung, colon and liver cancer. Results of this analysis were adopted by cancer biology laboratories at CSHL to assist functional studies using mouse models and RNAi. In addition, such loci may be valuable as prognostic markers for clinical outcome.
Recent advances in sequencing technology make it possible for us to study cancer at a single-cell level. With access to multiple single-cell genomes assayed from a tumor we are now able to observe and quantify genomic heterogeneity of the disease and to reconstruct, with increasing degree of accuracy, genealogical and evolutionary relationships among cancer cells. A more detailed knowledge of tumor cell population structure will help establish links between tumor heterogeneity and its progression, resistance to treatment and ability to invade.
Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., Muthuswamy, L., Krasnitz, A., McCombie, W.R., Hicks, J., and Wigler, M. 2011. Tumour evolution inferred by single-cell sequencing. Nature 472: 90–94.
Navin, N., Krasnitz, A., Rodgers, L., Cook, K., Meth, J., Kendall, J., Riggs, M., Eberling, Y., Troge, J., Grubor, V., Levy, D., Lundin, P., Månér, S., Zetterberg, A., Hicks, J., and Wigler, M. 2010. Inferring tumor progression from genomic heterogeneity. Genome Res. 20: 68–80.
Xue, W., Krasnitz, A., Lucito, R., Sordella, R., VanAelst, L., Cordon-Cardo, C., Singer, S., Kuehnel, F., Wigler, M., Powers, S., Zender, L., and Lowe, S.W. 2008. DLC1 is a chromosome 8p tumor suppressor whose loss promotes hepatocellular carcinoma. Genes Dev. 22: 1439–1444.
Zender, L., Xue, W., Zuber, J., Semighini, C.P., Krasnitz, A., Ma, B., Zender, P., Kubicka, S., Luk, J.M., Schirmacher, P., McCombie, R.W., Wigler, M., Hicks, J., Hannon, G.J., Powers, S., and Lowe, S.W. 2008 An Oncogenomics-Based In Vivo RNAi Screen Identifies Tumor Suppressors in Liver Cancer. Cell 135: 852–864.
Hicks, J., Krasnitz,A., Lakshmi, B., Navin, N., Riggs, M., Leibu, E., Esposito, D., Alexander, J., Troge, J., Grubor,V., Yoon, S., Wigler, M., Ye, K., Børresen-Dale, A-L., Naume, B., Schlicting, E., Norton, L., Hagerstrom, T., Skoog, L., Auer G., Maner, S., Lundin, P., and Zetterberg, A., 2006. Genome Novel Patterns of Genomic rearrangement and their association with survival in breast cancer. Genome Research 16:1465–1479.