Katie Maurer

This study identifies ASXL1 truncating mutations as a driver of leukemic resistance to T cell attack and proposes EZH2 inhibition as a therapeutic strategy to overcome this resistance.

The paper analyzes single-cell data from bone marrow samples to identify immune cell interactions that predict response to adoptive cellular therapy in myeloid leukemia.

DIISCO infers dynamic intercellular interactions from time-series single-cell data using a Bayesian framework, showing its ability to capture time-dependent communication patterns in simulated and CAR-T cell data.