Speaker
Description
Cancer spheroids capture the hallmark intratumoral heterogeneity of solid tumours, including phenotypic diversity and spatially distinct gene expression patterns, making them invaluable tools for studying therapeutic resistance. Differential receptor expression across tumour subpopulations remains a major challenge in cancer therapy, yet most computational models treat receptor proteins as a uniform, population-wide property, overlooking the functional consequences of mixed receptor populations within a single tumour. Here, we present a multi-scale agent-based model of a two-dimensional cross-section of a cancer spheroid, implemented in the Chaste framework, that resolves heterozygous Epidermal Growth Factor Receptor (EGFR) expression at the single-cell level. By coupling hypoxia-inducible factor (HIF)-driven transforming growth factor-α (TGF-α) autocrine and paracrine signalling, we show that the ratio of wild-type to mutated EGFR governs emergent spheroid phenotypes - proliferation in normoxic zones, quiescence under hypoxia, and necrosis under anoxia. We envision our modelling framework will provide a foundation for designing therapeutic strategies by accounting for the heterozygous receptor landscapes observed in clinical tumour samples.
