ONCO Subgroup Contributed Talks

Magnus Haughey

Barts Cancer Institute

"Extrachromosomal DNA driven oncogene spatial heterogeneity and evolution in glioblastoma"

Extrachromosomal DNA (ecDNA) oncogene amplification is associated with treatment resistance and shorter survival in cancer. Currently, the spatial dynamics of ecDNA, and their evolutionary impact, are poorly understood. Here, we investigate ecDNA spatial-temporal evolution by integrating computational modeling with samples from 94 treatment-naive human IDH-wildtype glioblastoma patients. Random ecDNA segregation combined with ecDNA-conferred fitness advantages induce predictable spatial ecDNA copy-number patterns which depend on ecDNA oncogenic makeup. EGFR-ecDNAs often reach high copy-number, confer strong fitness advantages and do not co-amplify other oncogenes on the same ecDNA. In contrast, PDGFRA-ecDNAs reach lower copy-number, confer weaker fitness advantages and co-amplify other oncogenes. EGFR structural variants occur exclusively on ecDNA, arise from and are intermixed with wild-type EGFR-ecDNAs. Modeling suggests wild-type and variant EGFR-ecDNAs often accumulate before clonal expansion, even in patients co-amplifying multiple ecDNA species. Early emergence of oncogenic ecDNA under strong positive selection is confirmed in vivo and in vitro in mouse neural stem cells. Our results implicate ecDNA as a driver of gliomagenesis, and suggest a potential time window in which early ecDNA detection may facilitate more effective intervention.

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Luke Heirene

University of Oxford

"Data Driven Mathematical Modelling Highlights the Impact of Bivalency on the Optimum Affinity for Monoclonal Antibody Therapies"

Monoclonal antibody (mAb)-based therapeutics are pivotal in treating a wide range of diseases, including cancer. One key mechanism by which these antibodies exert anti-tumour effects is through antibody-dependent cellular cytotoxicity (ADCC). In ADCC, mAbs bind to specific antigens on tumour cells and Fc receptors on immune effector cells. This trimeric complex triggers these effector cells to kill the tumour. ADCC is influenced by multiple factors, notably the properties of the mAb and its interactions with Fc receptors and target antigens. However, the optimum conditions for ADCC remain unclear. In this study, we investigate how variations in target antigen and mAb properties, particularly antibody valency, modulate ADCC response to identify parameters that maximize its potency. We developed an ordinary differential equation (ODE) model to simulate mAb binding within the immune synapse and quantify trimeric complex formation. To link the number of trimeric complexes to ADCC response, we validated the model using Bayesian inference on ADCC assay data. The results suggest that lower-affinity mAbs enhance ADCC by increasing the number of target cell-bound antibodies. Our validated model indicates that a “steric penalty” is necessary for bivalently target-bound versus monovalently target-bound antibodies. Due to constraints from dual antigen binding, these antibodies experience limited mobility, reducing Fc receptor engagement. After model validation, we explored variations in target expression, binding affinity, and antibody valency on ADCC potency, quantified by EC50. Our key finding is that the optimal binding affinity for maximizing ADCC potency depends on antibody valency. Monovalent antibodies are most potent at high affinity, while bivalent antibodies peak at lower affinities. Furthermore, the magnitude of this effect varies with target expression levels.

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