Tackling mutational heterogeneity in DLBCL through mathematical modelling

Diffuse large B cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma, accounting for nearly 40% of diagnosed non-Hodgkin lymphomas. DLBCL is clinically is further classified, based on putative cell-of-origin, into activated B cell-like (ABC) and germinal centre B cell-like (GCB) subtypes, each with distinct gene expression profiles and clinical outcomes. However, a recent genetic and molecular study of patient samples reveals substantial heterogeneity beyond these classifications. Despite an increasing understanding of the signalling dysregulation leading to DLBCL, standard combination therapy (R-CHOP) has remained unchanged for more than a decade. However, roughly 40% of patients treated with R-CHOP develop a recurring or progressive disease that is usually fatal. The substantial heterogeneity likely leads to our standard treatment failing for many. Thus we leverage this mutational characterisation to recreate, using a mathematical model, genetic events seen in distinct patient samples to determine B cell fates given each genetic alteration. In particular, we are interested in modelling the mutational heterogeneity to create `virtual DLBCL patients' and use this model as a tool to identify molecular targets and biomarkers that cluster patients based on their optimal target for therapy.