Computational metabolic modelling of Richter's transformation using integrated single-cell transcriptomic data

Richter’s transformation (RT) is a serious complication of chronic lymphocytic leukaemia (CLL), characterised by treatment resistance and poor prognosis. Here, we performed computational metabolic modelling using genome-scale metabolic models (GEMs) constructed from our integrated single-cell transcriptomic dataset of RT. We also conducted dynamical system modelling using ordinary differential equations (ODEs) parameterised with kinetic information from previous studies of RT metabolism and enzyme activity. Collectively, our findings provide insights into metabolic interactions between tumour and tumour microenvironment cells, highlighting potential roles of cancer metabolism and immunometabolism in RT.