Towards Predictive Models of Immunotherapy Response


PERSHING SQUARE SOHN PRIZE-MARK FOUNDATION FELLOW, IN PARTNERSHIP WITH THE PERSHING SQUARE SOHN CANCER RESEARCH ALLIANCE (2018-Present)

Dr. Greenbaum is a theoretical physicist who applies tools from the fields of computer science, mathematics, and physics to difficult problems in cancer biology. Immunotherapy has proven to be a groundbreaking strategy for cancer therapy, with incredible success for some patients. In part due to the complex systems involved – interactions between tumor cells, normal cells, immune system cells, and the surrounding environment – it is difficult to predict which patients will benefit from immunotherapy. Dr. Greenbaum’s lab is developing a computational model that takes these complexities into account to more accurately predict response of cancer patients to immunotherapy. Dr. Greenbaum is Program Leader in Computational Immuno-Oncology at Memorial Sloan Kettering Cancer Center.

PUBLISHED RESEARCH

Nogalski MT, Solovyov A, Kulkarni AS, Desai N, Oberstein A, Levine AJ, Ting DT, Shenk T, Greenbaum BD. A tumor-specific endogenous repetitive element is induced by herpesviruses. Nat Commun. 2019.

Perumal D, Imai N, Laganà A, Finnigan J, Melnekoff D, Leshchenko VV, Solovyov A, Madduri D, Chari A, Cho HJ, Dudley JT, Brody JD, Jagannath S, Greenbaum B, Gnjatic S, Bhardwaj N, Parekh S. Mutation-derived Neoantigen-specific T-cell Responses in Multiple Myeloma. Clin Cancer Res. 2020.

Roudko V, Greenbaum B, Bhardwaj N. Computational Prediction and Validation of Tumor-Associated Neoantigens. Front Immunol. 2020.

Maura F, Rustad EH, Yellapantula V, Łuksza M, Hoyos D, Maclachlan KH, Diamond BT, Greenbaum BD, Morgan G, Lesokhin A, Papaemmanuil E, Landgren O. Role of AID in the temporal pattern of acquisition of driver mutations in multiple myeloma. Leukemia. 2020.

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