New treatments are urgently required that are based on greater insight into the biological processes that enable cancer cells to evade treatment and regenerate tumours. To this end, we need new technologies that can temporally resolve and integrate phenotypic and cell ancestry information. In the lab, we are building a new molecular recorder tailored to paediatric cancers to record lineage relationships, developmental cell state plasticity dynamics and trancriptomic landscape information at single-cell resolution to understand how cancer cells can chameleon to alternative phenotypes/cell states to avoid treatment, regrow and relapse. Distinct cell states (i.e., chameleonic colours continuing with the analogy) are marked with fluorescent colours, which can be seen in live microscopy approaches to have a direct observation of the dynamics, time, and types of plastic behaviours at a population and single-cell level.

Using the evolutionary insight of plasticity and phenotypic dynamics, and how this interplays with other hereditable sources of evolution (DNA/TME) we aim to design new adaptive treatment strategies for paediatric cancer patients that are at high risk of relapsing and/or becoming treatment refractory. 

We are using our innovative molecular tools and an integrative approach of single-cell molecular technologies to identify non-genetic molecular determinants of plasticity-driven evolution and their potential as candidate biomarkers in paediatric cancer patients to identify, predict and monitor relapsed/ refractory disease when this occurs in the absence of genetic changes. 

We aim to adapt cutting-edge technologies to identify drugs which modulate chameleon-like changes or kill cells in specific phenotypes (colours). Altogether, we aim to improve our predictions and monitoring of relapse/refractory disease to help guide the clinical implementation of innovative and intelligently designed therapeutic approaches incorporating our improved understanding of cancer evolution.

We aim to adapt to paediatric cancer patients our established preclinical pipeline for patient-derived tumour ex vivo and in vivo drug testing. (see our latest publication here: Modelling drug responses and evolutionary dynamics using triple negative breast cancer patient-derived xenografts. A Shea, Y Eyal-Lubling, D Guerrero-Romero, et al. Bruna A. bioRxiv, 2023)

We will integrate this approach with the other projects in the lab to guide the clinical implementation of innovative and intelligently designed therapeutic approaches incorporating our improved understanding of cancer evolution.