Many theories have been proposed describing the single-cell dynamics of chemotherapy response and expansion of resistant clones. These usually require selection of a pre-existing stem cell population, a low frequency somatic mutation or the de novo acquisition of new mutations. In contrast to these predominantly genetic mechanisms, we have now utilised mathematical modelling and longitudinal single-cell imaging to demonstrate that the survival and propagation of single cancer cells can arise merely through the inherently noisy process of gene expression, which is amplified by the non-linear behaviour of apoptotic signalling pathways.
High-risk neuroblastoma is an aggressive, highly chemoresistant childhood tumour. We previously demonstrated that in silico, patient-specific modelling of apoptotic signalling can stratify neuroblastoma patient cohorts and provide robust biomarkers of patient survival (Fey, 2015, Science Signaling). We now show that application of this patient-focused model to single-cell populations also predicts the presence of this innately chemoresistant cell population, which cannot activate sufficient drug-induced signalling to reach an in-built apoptotic threshold.
Using a JNK activity biosensor with longitudinal high-content imaging, we have now confirmed that this stochastic population of chemoresistant cells exist prior to treatment, and that a memory of this resistant state is maintained through epigenetic remodelling following exposure to chemotherapy. We further demonstrate with both cell line and PDX models of drug resistance that priming neuroblastoma cells with a histone deacetylase inhibitor, followed by combination therapy with BH3-mimetics, can overcome this resistance. However, due to resistance generated by epigenetic remodelling, this approach is only effective for primary, not relapsed tumours.