Epidemiology & Biostatistics
The Benjamin Greenbaum Lab
Research
A main goal in the Greenbaum lab is to quantify how the immune system is activated and how it impacts tumor evolution. A particular focus in the lab is the role of repetitive elements in the genome, which mimic viral features and, just like viruses, evolve to escape immune surveillance. Dr. Greenbaum developed the first models to quantify this ‘viral mimicry’, molecular patterns reminiscent of pathogens that can activate the innate immune system (Greenbaum et al. PNAS 2014; Solovyov et al. Cell Reports 2018). These data recently contributed to a phase II clinical trial of 3TC, a reverse transcriptase inhibitor that prevented the activation of retrotransposons in patients with metastatic colorectal cancer and showed clinical benefits in 9 of 32 patients (Rajurkar et al. Cancer Discovery 2022). Viral mimics play an underappreciated role in tumor evolution and Dr. Greenbaum’s work reveals new vulnerabilities to be exploited. Within the last few years Dr. Greenbaum’s group and his collaborators also created models to predict the role of neoantigens in tumor evolution, and they established the concept of ‘neoantigen quality’ to assess the likelihood that a neoantigen will induce an immune response (Luksza et al. Nature, 2022). Models that contributed to motivating a recent phase I clinical trial (Rojas et al. Nature 2023). His team discovered an immune tradeoff in cancer evolution: oncogenic mutations with lower fitness present poorly to the immune system, while mutations with high fitness generate potent neoantigens (Hoyos et al. Nature 2022). The goal of Immuno-Oncology is to act as a bridge between Computational Oncology and other investigators and clinicians in immuno-oncology at MSK, with the ultimate aim to use the power of the immune system to fight cancer.
Research Projects
People
Benjamin Greenbaum, PhD
- The Greenbaum lab utilizes techniques from statistical physics, information theory, and evolutionary biology to better understand the role of self/non-self discrimination in tumor evolution, model response to immunotherapies, and quantify drivers of virus and cancer evolution.
- PhD in theoretical physics, Columbia University
- [email protected]
- Email Address
Members
Graduate Research Assistant
Senior Research Scientist
Graduate Student
GSK Graduate Student
Graduate Student
Bioinformatics Software Engineer II
Senior Computational Biologist
Bioinformatics Technician
Postdoctoral Research Scholar
Research Fellow
Graduate Student- Tri-I Program
Computational Biologist II
Senior Research Scientist
Senior Research Scientist
Postdoctoral Research Scholar
Graduate Research Assistant
Graduate Research Assistant
Lab Alumni
Computational Biologist I
Senior Computational Biologist II
Lab Affiliations
Achievements
- Invited Professor, Statistical Physics, École Normale Supérieure (2022)
- The Mark Foundation for Cancer Research ASPIRE Award (2021)
- Pancreatic Cancer Collective Phillip A. Sharp Challenge Award (2021)
- Pershing Square Foundation COVID-19 Award (2020)
- NextGen Innovator, HemOnc Today (2019)
Read more
- Pershing Square Sohn Prize for Young Investigators in Cancer Research (2018)
- Mark Foundation Investigator Award (2018)
- Phillip A. Sharp Award for Innovation in Collaboration, Stand Up to Cancer (2016)
