Project description
Delineating tumour heterogeneity using organoids
Accumulating evidence suggests that cellular heterogeneity supports tumour growth and induces resistance to therapy. However, we lack fundamental information on its spatiotemporal emergence. To address this issue, the EU-funded SpatialOrganoids project will undertake experimental and computational analyses of breast cancer 3D organoid cultures over time. By capturing spatiotemporal changes in cellular phenotypes, scientists will identify molecular and spatial determinants of breast cancer heterogeneity. Given the high incidence of breast cancer in women and the extensive intra- and inter-patient heterogeneity, the project's results will contribute to the development of new targeted treatment strategies.
Objective
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.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
8006 Zurich
Switzerland