This project focuses on characterizing the dynamic processes that drive acute leukemia cell evolution, including phenotypic drift and lineage switching, by integrating multimodal single-cell data with additional topological and kinetic measures (e.g., RNA velocity).
The heterogeneity and dynamic behavior of leukemic blasts present significant challenges for minimal residual disease (MRD) monitoring and the assessment of treatment responses. Current single-cell methodologies provide only static snapshots of leukemic cells at specific time points; however, computational approaches can infer the underlying dynamics from these static views. This project focuses on characterizing the dynamic processes that drive acute leukemia cell evolution, including phenotypic drift and lineage switching, by integrating multimodal single-cell data with additional topological and kinetic measures (e.g., RNA velocity). The project employs advanced computational and mathematical methods—including computational topology, stochastic modeling, and deep learning—to dissect the state transitions and fate-determining processes of leukemic cells. A core objective is to develop a computational framework capable of integrating diverse data modalities and analyzing the associated mathematical structures. These techniques will identify therapy-resistant cell subsets and link MRD findings to their developmental context.
The analytical framework will be applied to MRD samples from leukemia patients exhibiting phenotypic changes, lineage switching, or delayed therapeutic responses. The research is expected to provide a detailed understanding of the mechanisms driving phenotypic transitions in residual leukemic blasts and to identify key features of drug-resistant leukemic clones. Additionally, it will deliver a broadly applicable computational framework for high-dimensional single-cell data analysis, specifically designed to study MRD dynamics and the complex interplay of cells within their tissue environment.
Host:
Charles University, Prague, Czech Republic
Supervisors:
Jan Trka and Dr. Jan Stuchly