Profiling the emergence of phenotypic heterogeneity in breast cancer organoids

Cell-to-cell heterogeneity in biological systems has been broadly studied in unicellular organisms and mammals.

Furthermore, non-genetic, in addition to genetic heterogeneity has been recently proposed to support tumour growth and to induce resistance to cancer therapy.

However, the molecular events on a spatial and temporal level that lead to the emergence of tumour heterogeneity are largely unknown.

To address this question, I will study breast cancer, which shows the highest cancer incidence in women and is characterised by extensive intra- and inter-patient heterogeneity in cellular and molecular phenotypes.

As model system, I select 3D organoid cultures, which are gaining popularity in cancer research due to their ability to reconstruct tumour-like molecular features and to recapitulate treatment response.

Here, I propose experimental and computational time-course analyses of breast cancer organoids to understand molecular and spatial determinants that underlie the emergence of heterogeneity in cancer cell phenotypes.

On the experimental side, I will use imaging mass cytometry and perturbation experiments to capture and validate spatio-temporal changes in cellular phenotypes, interactions and signalling networks.

Statistical modelling will quantify dynamic changes in phenotypic heterogeneity over the time-course of organoid growth.

Finally, I will predict the emergence of intra-organoid heterogeneity across multiple organoid lines, which allows me to derive targeted treatment strategies.In sum, the proposed work will disentangle and perturb the spatio-temporal emergence of phenotypic intra-tumour heterogeneity, which is characteristic of breast cancer tissues.