Mathematical Biology Seminar: Josh Scurll

Diffuse Large B-Cell Lymphoma (DLBCL), a non-Hodgkin lymphoma, is the most common blood cancer and comprises more than two subtypes. The Activated B-Cell like (ABC) subtype has inferior survival rates, and is typically characterized by constitutive signalling that resembles B-cell activation following antigen engagement. However, there is significant heterogeneity observed clinically within the ABC subtype of DLBCL, with various mutations able to give rise to this oncogenic signalling. When present within an individual patient’s tumour, this kind of heterogeneity can lead to drug resistance due to evolutionary selection for cells with mutations that confer drug resistance. Optimized personalized therapies should therefore account for any underlying intratumour heterogeneity to prevent or delay the onset of drug resistance. In this work-in-progress talk, I will present our work towards developing a pipeline using mass cytometry -- a technique that enables the measurement of over 30 proteins simultaneously in single cells -- and computational analysis to study proteomic heterogeneity, especially at the level of intracellular signalling, in DLBCL samples. Since the ‘ground-truth’ cellular populations (clusters in proteomic or mutational feature space) that make up a heterogeneous tumour are not known for real tumours, we have devised novel mass cytometry experiments to simulate a heterogeneous DLBCL sample using cell lines as ‘ground-truth’ populations. This novel data will facilitate the improvement of existing, and development of new, computational algorithms for analysing heterogeneity and signalling in tumours.