Ph.D., Tel Aviv University, 1990
firstname.lastname@example.org | (516) 367-6863 (p)
Many types of cancer display bewildering intra-tumor heterogeneity on a cellular and molecular level, with aggressive malignant cell populations found alongside normal tissue and infiltrating immune cells. I am developing mathematical and statistical tools to disentangle tumor cell population structure, enabling an earlier and more accurate diagnosis of the disease and better-informed clinical decisions.
Alexander Krasnitz and colleagues develop mathematical and statistical tools to investigate population structure of cells comprising a malignant tumor and to reconstruct evolutionary processes leading up to that structure. These tools are designed to make optimal use of emerging molecular technologies, chief among them high-throughput genomic profiling of multiple individual cells harvested from a tumor. By analyzing these profiles, Krasnitz derives novel molecular measures of malignancy, such as the number of aggressive clones in a tumor, the invasive capacity of each clone and the amount of cancer-related genetic alteration sustained by clonal cells. Krasnitz and colleagues collaborate closely with clinical oncologists to explore the utility of such measures for earlier detection of cancer, more accurate patient outcome prediction and risk assessment, and better-informed choice of treatment options.
Alexander, J. and Kendall, J. and McIndoo, J. and Rodgers, L. and Aboukhalil, R. and Levy, D. and Stepansky, A. and Sun, G. and Chobadjiev, L. and Riggs, M. and Cox, H. and Hakker, I. and Nowak, D. G. and Laze, J. and Llukani, E. and Srivastava, A. and Gruschow, S. and Yadav, S. S. and Robinson, B. D. and Atwal, G. and Trotman, L. C. and Lepor, H. and Hicks, J. B. and Wigler, M. and Krasnitz, A. (2018) Utility of single cell genomics in diagnostic evaluation of prostate cancer. Cancer Res, 78(2) pp. 348-358.
Krasnitz, Alexander and Kendall, Jude and Alexander, Joan and Levy, Dan and Wigler, Michael (2017) Early Detection of Cancer in Blood Using Single-Cell Analysis: A Proposal. Trends in Molecular Medicine, 23(7) pp. 594-603.
Krasnitz, A. and Sun, G. and Andrews, P. and Wigler, M. (2013) Target inference from collections of genomic intervals. Proceedings of the National Academy of Sciences of the United States of America, 110(25) pp. E2271-E2278.
Navin, N. E. and Krasnitz, A. and Rodgers, L. and Cook, K. and Meth, J. L. and Kendall, J. T. and Riggs, M. and Eberling, Y. and Troge, J. E. and Grubor, V. and Levy, D. and Lundin, P. and Månér, S. and Zetterberg, A. and Hicks, J. B. and Wigler, M. H. (2010) Inferring tumor progression from genomic heterogeneity. Genome Research, 20(1) pp. 68-80.
Hicks, J. B. and Krasnitz, A. and Lakshmi, B. and Navin, N. E. and Riggs, M. and Leibu, E. and Esposito, D. and Alexander, J. and Troge, J. E. and Grubor, V. and Yoon, S. and Wigler, M. H. and Ye, K. and Borresen-Dale, A. L. and Naume, B. and Schlicting, E. and Norton, L. and Hagerstrom, T. and Skoog, L. and Auer, G. and Månér, S. and Lundin, P. and Zetterberg, A. (2006) Novel patterns of genome rearrangement and their association with survival in breast cancer. Genome Research, 16(12) pp. 1465-79.Additional materials of the author at
CSHL Institutional Repository