We develop wetlab and computational multi-omic single cell approaches to decode tumor heterogeneity and plasticity
Decoding Tumor Heterogeneity and Plasticity to Provide Translational Solutions for Hard-to-Treat Heterogeneous Cancers
Tumors are complex and heterogeneous systems, which challenge their classification and treatment. The Silverbush lab decodes tumor heterogeneity and plasticity to understand how cancer cells transform to become more aggressive or evade treatment. We particularly examine hard-to-treat cancers with high heterogeneity, focusing on the notorious kings of heterogeneity and aggressiveness: brain cancers.
To achieve this goal, we develop and implement wetlab and computational multi-omic single-cell tools.
These tools enable us, for the first time, to simultaneously measure DNA methylation, point mutations, and transcriptional activity in the same single cells. We then use these tools to study patient samples, often treated with innovative clinical trials, and build solutions to understand whom the treatment can help, how to improve it, and what the optimal time window is for administering it.
To tackle these complex goals, we build an interdisciplinary team, welcoming MDs, biologists, immunologists, computational biologists, and pure computer scientists focusing on ML and AI. The lab encompasses wet lab and computational components, managing complex algorithmic and wet lab challenges, translational applications, and working closely with clinicians.
Meet our Team
Joining the Cancer Biology department at UPenn was an easy decision for Dana. Here, she built a collaborative and interdisciplinary team focusing on cutting-edge technologies, pivotal research on tumor heterogeneity, and its impact on resistance mechanisms in glioma clinical trials. She believes that having a versatile skill set and engaging with experts from different disciplines makes the team sharper and enables sustainable contributions to the world of medicine and cancer research. Dana works with the group to develop wet lab and computational solutions to decipher tumor heterogeneity and plasticity, particularly in the context of targeted and immunotherapy[…]
Dana Silverbush
Assistant Professor