Medicine, Oncological Sciences, Pathology
Icahn School of Medicine at Mount Sinai
The past decade has seen breakthroughs in our understanding of how tumors interact with the immune system that have led to transformational cancer therapies. Our work aims to understand the fundamental mechanisms through which the immune system recognizes tumors and to quantify these mechanisms’ impacts on tumor evolution. We believe our integration of perspectives across disciplines will allow us to fully take advantage of recent advances in tumor immunology and immunotherapy.
Benjamin D. Greenbaum, PhD, is an Assistant Professor at the Tisch Cancer Institute in the Departments of Medicine, Oncological Sciences, and Pathology. Dr. Greenbaum is a computational biologist with a PhD in theoretical physics from Columbia University, where he was an undergraduate major in Physics and Philosophy. He trained in the Theoretical Division of Los Alamos National Laboratory and the Simons Center for Systems Biology at the Institute for Advanced Study in Princeton, where he was a Long-Term Member. Dr. Greenbaum utilizes techniques from statistical physics, information theory, and evolutionary biology to better understand the interaction of host tumor RNA with the innate immune system, the role of neoantigens in the evolution of tumors both generally and in response to immunotherapy, and various aspects of virus evolution. As a result of this work he was award a Phillip A. Sharp Award for Innovation in Collaboration from Stand Up to Cancer, where he is a co-leader of a Convergence 2.0 Team studying the interactions between neoantigens and T cells in pancreatic cancer.
Towards Mechanistic Models of Immunotherapy Response
Breakthrough treatments in cancer immunotherapy have greatly improved survival across several cancer types, such as lung cancer and melanoma. However, there is still a need to understand why some patients respond to therapy and others do not. Several clues have emerged suggesting the genome of a tumor and the environment in which it grows contain quantifiable information useful in predicting response to therapy. For instance, tumors arise in part due to mutations in their DNA – a handful of which may cause cells to grow uncontrollably. However, these same mutations also can make a tumor different from the rest of the cells in the body and, as a result, make it a target for the immune system. Our lab and collaborators have developed a new computational approach to predicting who will respond to (immuno)therapy, and recently published its first proof of concept. In doing so, we built a unique interdisciplinary team of quantitative scientists, immunologists, cancer biologists and clinicians.
“The prize will allow us to integrate our understandings of the roles of neoantigens in tumor evolution and responses to immunotherapy with our understanding of how a tumor’s environment shapes its evolution.”
The goal of this proposal is to use our approach as an overarching framework for turning information about the tumor and its environment into improved predictions of response, and create a unique computational platform for rapidly doing so. First, we model the evolutionary dynamics of the tumor under immunotherapy. Second, we incorporate rich information about the tumor’s environment into a modeling framework. In summary, my colleagues and I hope to bring novel mathematical approaches to understanding immunotherapy response so that more patients can be successfully treated.
“Innovation comes from looking across disciplines and seeing relationships between ideas in different fields.”
Benjamin Greenbaum is a Pershing Square Sohn Prize Mark Foundation Fellow. Dr. Greenbaum’s project is funded by The Mark Foundation for Cancer Research in a novel partnership between the two foundations to encourage technological innovation in cancer research. For more information, please refer to the full press release.