Hatice U. Osmanbeyoglu, M.S, Ph.D

  • Assistant Professor
  • Department of Biomedical Informatics

Education & Training

  • PostDoc.,Memorial Sloan Kettering Cancer Center-2018
  • Ph.D., University of Pittsburgh School of Medicine-2012
  • MS., University of Pittsbugh-Bioengineering-2009
  • MS., Carnegie Mellon University-Electrical and Computer Engineering-2006
  • BS., Northeastern University, Computer Engineering-2004

Research Interest Summary

We develop data-driven computational approaches to understand disease mechanisms in order to assist in the development of personalizing anticancer treatments.

Research Categories

Research Interests

Primary focus of our group is developing integrative statistical and machine learning approaches for extracting therapeutic insight from highly heterogenous omic datasets, clinical and drug response data for the purpose of precision medicine. Our projects are in the areas of cancer genomics, epigenetics of drug response, and immunotherapy and are executed through multi-disciplinary collaborations. We have a particular interest in developing statistical methods for single cell multi-omics integration.

Fundamental questions motivate research in our group: 

·   Why do some patients respond to treatment, while others not?

·   Why are some treatments effective initially, but fail over time?

·   How do cancer cells acquire the ability to spread from one part of the body to another?

Representative Publications

Hmeljak J, Sanchez-Vega F, Hoadley KA, Shig J, Stewart C, Heiman D, Tarpey P, Danilova L, Drill E, Gibb E, Bowlby R, Kanchi R, Osmanbeyoglu HU,…, The Cancer Genome Atlas Network,…, Robinson B*, Campbell P*, Ladanyi M* (2018) Integrative molecular characterization of malignant pleural mesothelioma. Cancer Discovery, 8(12): 1548-1565.

Luo C, Osmanbeyoglu HU, Do MH, Bivona MR, Toure A, Kang D, Xie Y, Leslie CS, Li M (2017) Ets transcription factor GABP controls T cell homeostasis and immunity. Nature Communications 8,1062.

Iyer A, Osmanbeyoglu HU, Leslie CS (2017) Computational methods to dissect gene regulatory networks in cancer. Current Opinion in Systems Biology, 2:115-122.

Nargund AM, Pham CG, Dong Y, Wang PI, Osmanbeyoglu HU, Xie Y, Aras O, Han S, Oyama T, Takeda S, Ray CE, Dong Z, Berge M, Hakimi AA, Monetta S, Lekaye CL, Koutcher JA, Leslie CS, Creighton CJ, Weinhold N, Lee W, Tickoo SK, Wang Z, Cheng EH, Hsieh JJ (2017) The SWI/SNF Protein PBMR1 Restrains VHL Loss-Driven Clear Cell Kidney Cancer, Cell Reports 18, 2893-2906.

Toska E, Osmanbeyoglu HU*, Castel P*, Chan C, Dickler M, Hendrickson RC, Scaltriti M, Leslie CS, Armstrong SA, Baselga J (2017) PI3K pathway regulates ER-dependent transcription in breast cancer through the epigenetic regulator KMT2D, Science, 355 (6331), 1324-1330.

Osmanbeyoglu HU, Toska E, Chan C, Baselga J, Leslie CS (2017) Pan-cancer modeling predicts the context-specific impact of somatic mutations on transcriptional programs. Nature Communications 8, 14249.

Feng Y, Veeken J, Shugay M, Putintseva EV, Osmanbeyoglu HU, Dikiy S, Hoyos BE, Moltedo B, Hemmers S, Treuting P, Leslie CS, Chudakov M, Rudensky AY (2015) A mechanism for expansion of regulatory T-cell repertoire and its role in self-tolerance. Nature, 528(7580):132-136.

Osmanbeyoglu HU, Pelossof R, Bromberg JF, Leslie CS (2014) Linking signaling pathways to transcriptional response in breast cancer. Genome Res., 24(11):1869-80.

Osmanbeyoglu HU, Lu KN, Oesterreich S, Day RS, Benos PV, Coronnello C, Lu X (2013) Estrogen represses gene expression through reconfiguring chromatin structures. Nucleic acids research 41(17):8061-71.

Osmanbeyoglu HU, Hartmaier RJ, Oesterreich S, Lu X (2012) Improving ChIP-seq peak-calling for functional co-regulator binding by integrating multiple sources of biological information. BMC Genomics 13 Suppl 1: S1.

Full List of Publications